American Psychological Association 5th Edition
Cost-Effectiveness of Home- and Community-Based Programs in the United States: Review of the Current Literature Prepared for the Claude Pepper Center, Florida State University Prepared by Jung Kwak, PhD, MSWHelen Bader School of Social Welfare, University of Wisconsin-MilwaukeeDecember 24, 2013The current draft of this report was prepared under contract to the Clause Pepper Center at the Florida State University (Contract # PO 0824623). The purpose of this report is to provide a comprehensive review of the current literature on the cost-effectiveness of various home- and community-based programs for frail, older adults in the United States. ABSTRACTObjectives. To examine the effectiveness of home- and community-based services (HCBS) in terms of its effects on mental and physical health, and quality of life outcomes, acute services utilization, and cost. Data sources. Bibliography databases PubMeD andPsycINFO; grey literature in the form of program evaluation reports and reports from Web sites of relevant state and federal agencies and research and advocacy organizations; citation searches of articles; and hand searches. Review methods. Included in the review were three review articles and reports that were published in English between 2000 and 2013, and in the United States. The literature search focused on studies that met all of the following conditions: (1) study older adults aged 60 or older, (2) use experimental, quasiexperimental, or survey design, and (3) evaluate one of the key dimensions of effectiveness of HCBS (access, health outcome, cost). To capture studies most relevant to the report I limited studies by date (2000 to 2013), language (English), and geographical location (United States). Results. The literature search identified and included four review articles/reports, 18 peer-reviewed articles, and two comprehensive state evaluations of HCBS programs in Wisconsin and Florida. Overall, the majority of the studies consistently reported the positive association between HCBS and reduced nursing home admission rates. However, the effects of HCBS on beneficiary outcomes and cost were mixed. There were several methodological limitations and variability in study design that were present in the most of the studies which made it difficult to draw any definitive conclusions about HCBS effect on beneficiary outcomes and cost. Mainly, these limitations include lack of rigorous design such as use of randomized controlled trial (RCT), limited number of longitudinal studies, lack of controlling for a comprehensive set of confounding variables at state, local, and individual levels, and a relative short follow-up time frame.INTRODUCTIONHome- and community-based alternatives to institutional care such as nursing home remain an important priority for many state Medicaid programs. Home- and community-based services (HCBS) refer to services provided in an array of noninstitutional settings, including recipients’ homes; community group living arrangements such as congregate housing, adult foster care, residential care (RC) and assisted living facilities; and community settings such as adult day care and adult day health ADDIN EN.CITE <EndNote><Cite><Author>Wysocki</Author><Year>2012</Year><RecNum>75</RecNum><DisplayText>(Wysocki et al., 2012)</DisplayText><record><rec-number>75</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">75</key></foreign-keys><ref-type name="Book">6</ref-type><contributors><authors><author>Wysocki, A.</author><author>Butler, M.</author><author>Kane, R. L.</author><author>Kane, R. A.</author><author>Shippee, T.</author><author>Sainfort, F.</author></authors></contributors><titles><title>Long-Term Care for Older Adults: A Review of Home and Community-Based Services Versus Institutional Care</title></titles><dates><year>2012</year><pub-dates><date>Nov</date></pub-dates></dates><pub-location>Rockville MD</pub-location><accession-num>23256217</accession-num><urls></urls><language>eng</language></record></Cite></EndNote>(Wysocki et al., 2012). A recent analysis of participant and expenditure data of Medicaid HCBS programs by Ng and colleagues (2012) showed that in 2009, there were 3.25 million individuals served through HCBS programs. This number, over 3 million individuals, is significantly higher than 1.4 million individuals who are receiving their long-term care (LTC) in nursing home. Although the majority of Medicaid long-term services and supports (LTSS) expenditure is still on institutional care ADDIN EN.CITE <EndNote><Cite><Author>Wysocki</Author><Year>2012</Year><RecNum>75</RecNum><DisplayText>(Wysocki et al., 2012)</DisplayText><record><rec-number>75</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">75</key></foreign-keys><ref-type name="Report">27</ref-type><contributors><authors><author>Wysocki, A.</author><author>Butler, M.</author><author>Kane, R. L.</author><author>Kane, R. A.</author><author>Shippee, T.</author><author>Sainfort, F.</author></authors></contributors><titles><title>Long-Term Care for Older Adults: A Review of Home and Community-Based Services Versus Institutional Care</title><secondary-title>Effective Health Care Program: Comparative Effectiveness Review</secondary-title></titles><volume>81</volume><dates><year>2012</year><pub-dates><date>Nov</date></pub-dates></dates><pub-location>Rockville, MD</pub-location><publisher>Agency for Healthcare Research and Quality</publisher><accession-num>23256217</accession-num><urls></urls><language>eng</language></record></Cite></EndNote>(Wysocki et al., 2012), the national percentage of Medicaid spending on HCBS has more than doubled from 20% in 1995 to 45% in 2010 ADDIN EN.CITE <EndNote><Cite><Author>Ng</Author><Year>2012</Year><RecNum>108</RecNum><DisplayText>(Ng, Harrington, Musumeci, & Reaves, 2012)</DisplayText><record><rec-number>108</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">108</key></foreign-keys><ref-type name="Report">27</ref-type><contributors><authors><author>Ng, T.</author><author>Harrington, C.</author><author>Musumeci, M.</author><author>Reaves, E.</author></authors></contributors><titles><title>Medicaid Home and Community-Based Services Program: 2009 Data Update</title></titles><dates><year>2012</year></dates><publisher>Kaiser Commission on Medicaid and the Uninsured </publisher><urls><related-urls><url>;(Ng, Harrington, Musumeci, & Reaves, 2012). In 2009, HCBS expenditures accounted for 36% of LTC expenditures for older adults and people with physical disabilities ADDIN EN.CITE <EndNote><Cite><Author>Wysocki</Author><Year>2012</Year><RecNum>75</RecNum><DisplayText>(Wysocki et al., 2012)</DisplayText><record><rec-number>75</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">75</key></foreign-keys><ref-type name="Report">27</ref-type><contributors><authors><author>Wysocki, A.</author><author>Butler, M.</author><author>Kane, R. L.</author><author>Kane, R. A.</author><author>Shippee, T.</author><author>Sainfort, F.</author></authors></contributors><titles><title>Long-Term Care for Older Adults: A Review of Home and Community-Based Services Versus Institutional Care</title><secondary-title>Effective Health Care Program: Comparative Effectiveness Review</secondary-title></titles><volume>81</volume><dates><year>2012</year><pub-dates><date>Nov</date></pub-dates></dates><pub-location>Rockville, MD</pub-location><publisher>Agency for Healthcare Research and Quality</publisher><accession-num>23256217</accession-num><urls></urls><language>eng</language></record></Cite></EndNote>(Wysocki et al., 2012). There was also an 11% rate increase in total Medicaid HCBS spending from 2008 to 2009, with the average per person annual spending on Medicaid HCBS of 15,371 dollars (although there was considerable variation across states and programs).The growth of HCBS in the last two decades are in part due to overwhelming preferences to stay in community settings and avoid nursing home placement as long as possible, and the substantially less cost of providing long-term care per person via HCBS options than nursing home care. In addition, the Affordable Care Act (ACA) incentivizes states to enhance HCBS initiatives by increasing federal policy options and financial support for HCBS and, by expanding Medicaid eligibility as well as by allowing for waiver consolidation and state HCBS program expansion. As the ACA continues to be implemented across states, it will become even more important for states to monitor and evaluate its current HCBS programs, options for expanding HCBS, and their impact on access and impact on care quality and cost ADDIN EN.CITE <EndNote><Cite><Author>Ng</Author><Year>2012</Year><RecNum>108</RecNum><DisplayText>(Ng et al., 2012)</DisplayText><record><rec-number>108</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">108</key></foreign-keys><ref-type name="Report">27</ref-type><contributors><authors><author>Ng, T.</author><author>Harrington, C.</author><author>Musumeci, M.</author><author>Reaves, E.</author></authors></contributors><titles><title>Medicaid Home and Community-Based Services Program: 2009 Data Update</title></titles><dates><year>2012</year></dates><publisher>Kaiser Commission on Medicaid and the Uninsured </publisher><urls><related-urls><url>;(Ng et al., 2012). The main purpose of this report is to inform practice, policy and research by synthesizing the current research on the effect of HCBS on health and quality of life outcomes and cost. In evaluating the state of science on the effectiveness of HCBS, it is important to acknowledge at least two main challenges in such effort. One major challenge is that there are substantial variations across different HCBS programs in various states in terms of availability and coverage of HCBS, eligibility criteria, and financing and administrative structure. For instance, although all states have some type of restrictive policies to control for the growth of HCBS, there are variations in what type of restrictions are in place across states. In 2011, all states reported using cost controls in HCBS such as restrictive financial (26% of waiver programs using more restrictive criteria for HCBS than for institutional care) and functional (10 waivers with more restrictive criteria for HCBS than for institutional care) eligibility standards, enrollment limits, and waiting lists. These variations of waiver programs make it difficult to compare effectiveness across programs. The other challenge is various methodologies used in the evaluation studies, especially the absence of randomized experimental designs with representative samples of users and programs from multiple states in more recent studies, and use of valid and comparable measures for covariates and outcomes. Hence, recent reviews of HCBS programs have not been able to draw definitive conclusions regarding the cost-effectiveness of HCBS, see reviews on HCBS by Grabowski (2006a) and Wysocki and colleagues (2012). . Scope and Key QuestionsPopulation and OutcomesThe target population for this report was older adults aged 60 or older with LTC support needs. The review of the literature focused on studies that evaluated one or more of the following aspects of HCBS: access/utilization, mental and/or physical health outcomes, or cost. Key QuestionsKey questions that guided the literature review included: (1) does HCBS lead to better outcomes in physical and mental health than nursing home care?; (2) does HCBS reduce avoidable short-term or long-term institutionalization (e.g., hospitalization, short-term rehabilitations); and (3) does HCBS reduce overall Medicaid LTC cost? MethodsLiterature Review Search StrategyAs the literature review process began for this report, three comprehensive literature reviews on similar topics were located. These three comprehensive literature reviews published on key issues regarding HCBS guided the literature search and selection of published journal articles and reports reviewed in depth for this report. Grabowski ADDIN EN.CITE <EndNote><Cite><Author>Grabowski</Author><Year>2006</Year><RecNum>147</RecNum><DisplayText>(Grabowski, 2006b)</DisplayText><record><rec-number>147</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">147</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Grabowski, D. C.</author></authors></contributors><titles><title>The cost-effectiveness of noninstitutional long-term care services: Review and synthesis of the most recent evidence</title><secondary-title>Medical Care Research and Review</secondary-title></titles><periodical><full-title>Medical care research and review</full-title></periodical><pages>3-28</pages><volume>63</volume><number>1</number><dates><year>2006</year></dates><isbn>1077-5587</isbn><urls></urls></record></Cite></EndNote>(Grabowski, 2006b) reviewed studies published between 1996 and 2004 regarding HCBS, ADDIN EN.CITE <EndNote><Cite AuthorYear="1"><Author>Weissert</Author><Year>2013</Year><RecNum>73</RecNum><DisplayText>Weissert and Frederick (2013)</DisplayText><record><rec-number>73</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">73</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Weissert, W. G.</author><author>Frederick, L.</author></authors></contributors><auth-address>Department of Political Science, Faculty Associate, Pepper Institute on Aging and Public Policy, Director, Masters of Public Health Degree Program, Florida State University, Tallahassee, Florida 32306, USA. wweissert@fsu.edu</auth-address><titles><title>The woodwork effect: estimating it and controlling the damage</title><secondary-title>J Aging Soc Policy</secondary-title><alt-title>Journal of aging & social policy</alt-title></titles><periodical><full-title>J Aging Soc Policy</full-title><abbr-1>Journal of aging & social policy</abbr-1></periodical><alt-periodical><full-title>J Aging Soc Policy</full-title><abbr-1>Journal of aging & social policy</abbr-1></alt-periodical><pages>107-33</pages><volume>25</volume><number>2</number><edition>2013/04/11</edition><dates><year>2013</year></dates><isbn>1545-0821 (Electronic)
0895-9420 (Linking)</isbn><accession-num>23570506</accession-num><urls></urls><electronic-resource-num>10.1080/08959420.2013.766073</electronic-resource-num><remote-database-provider>NLM</remote-database-provider><language>eng</language></record></Cite></EndNote>Weissert and Frederick (2013) reviewed 43 studies of HCBS programs published between 1963 and 2008, and ADDIN EN.CITE <EndNote><Cite AuthorYear="1"><Author>Wysocki</Author><Year>2012</Year><RecNum>75</RecNum><DisplayText>Wysocki et al. (2012)</DisplayText><record><rec-number>75</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">75</key></foreign-keys><ref-type name="Report">27</ref-type><contributors><authors><author>Wysocki, A.</author><author>Butler, M.</author><author>Kane, R. L.</author><author>Kane, R. A.</author><author>Shippee, T.</author><author>Sainfort, F.</author></authors></contributors><titles><title>Long-Term Care for Older Adults: A Review of Home and Community-Based Services Versus Institutional Care</title><secondary-title>Effective Health Care Program: Comparative Effectiveness Review</secondary-title></titles><volume>81</volume><dates><year>2012</year><pub-dates><date>Nov</date></pub-dates></dates><pub-location>Rockville, MD</pub-location><publisher>Agency for Healthcare Research and Quality</publisher><accession-num>23256217</accession-num><urls></urls><language>eng</language></record></Cite></EndNote>Wysocki et al. (2012) identified 42 studies (37 peer reviewed, 5 grey literature) published between 1995 and March 2012. Between these three reviews, there was considerable amount of overlap in terms of studies and evaluations reviewed. Because of such overlap, the current report focused on the two groups of the literature: (1) studies/evaluations that were reviewed by these three reviews that specifically addressed the effect of HCBS on cost or beneficiary outcomes; and (2) studies/evaluations that were not included in these reviews that were published between 2000 and 2013.To identify additional studies (other than those identified in the three aforementioned reviews), I used several strategies to identify potentially relevant studies from published and grey literature sources. I searched the bibliographic databases PubMed and PsycINFO for RCTs and observational studies of HBCS published from 2000 to 2013. I supplemented bibliographic database searches with searches of relevant articles identified from review articles and by hand searching. To identify additional reports, I searched grey literature sources including Web sites of relevant Federal and State agencies (such as the Centers for Medicare & Medicaid Services and the Administration on Aging), research organizations (such as the Lewin Group and Public Policy Institute of AARP), and foundations (such as the Kaiser Commission on Medicaid and the Uninsured). Study SelectionThe literature search focused on studies that met all of the following conditions: (1) studied older adults aged 60 or older, (2) used experimental, quasi-experimental, or observational design, and (3) evaluated one of the key dimensions of effectiveness of HCBS (access, health outcome, cost). To capture studies most relevant to the report I limited studies by date (2000 to 2013), language (English), and geographical location (United States). ResultsResults of Literature Searches - Reviews/Articles/Reports Included for ReviewThe literature search identified and included four review articles/reports PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5HcmFib3dza2k8L0F1dGhvcj48WWVhcj4yMDA2PC9ZZWFy
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ADDIN EN.CITE.DATA (Fox-Grage & Walls, 2013; Grabowski, 2006b; Weissert & Frederick, 2013; Wysocki et al., 2012). Also included are 17 peer-reviewed articles PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5IYWhuPC9BdXRob3I+PFllYXI+MjAxMTwvWWVhcj48UmVj
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ADDIN EN.CITE.DATA (Eiken, Burwell, & Sredl, 2013; Hahn, Thomas, Hyer, Andel, & Meng, 2011; Kane et al., 2013; Kaye, LaPlante, & Harrington, 2009; Kitchener, Ng, Miller, & Harrington, 2006; Konetzka, Karon, & Potter, 2012; Marek et al., 2005; N. A. Miller, 2011; G. Mitchell, Salmon, Polivka, & Soberon-Ferrer, 2006; S. L. Mitchell, Morris, Park, & Fries, 2004; Muramatsu, Hoyem, Yin, & Campbell, 2008; Muramatsu et al., 2007; Muramatsu, Yin, & Hedeker, 2010; Shapiro, Loh, & Mitchell, 2011; Shireman & Rigler, 2004; Thomas, 2013; Wieland, Boland, Baskins, & Kinosian, 2010). Lastly, two comprehensive state evaluations of HCBS programs in Wisconsin and Florida that were not included in the AARP report (Fox-Grage, 2013) are reviewed in this report (APS Healthcare, 2005; OPPAGA, 2010). Key Questions in Evaluation of HCBS Two primary questions concerning effectiveness of the HCBS that were the focus of the current literature included: (1) moral hazard issue, otherwise known as ‘“woodwork effect”’; and (2) cost-effectiveness vs. cost analysis. Woodwork effect or woodwork problem means that once the HCBS programs become more available and accessible, many people who are currently eligible for the HCBS programs but have not signed up for the programs, may come “out of the woodwork” and sign up to receive these benefits. Such increase in the number of beneficiaries who are actually receiving services may drive up the cost. This issue of woodwork effect addressed in the literature is addressed in the context of cost analysis. The majority of studies and evaluation reports however evaluated the effect of HCBS on only cost or beneficiary outcomes alone, but not both. Hence, the current literature review is organized by three domains that were most commonly addressed by individual studies/reports: effect of HCBS on beneficiary health/functional outcomes, nursing home admission, and cost. A detailed summary of the findings from the literature review on the three domains, and the summary of methodological limitations are described in the following sections. Summary of Recent Literature Review on HCBS ADDIN EN.CITE <EndNote><Cite AuthorYear="1"><Author>Grabowski</Author><Year>2006</Year><RecNum>90</RecNum><DisplayText>Grabowski (2006a)</DisplayText><record><rec-number>90</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">90</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Grabowski, D. C.</author></authors></contributors><auth-address>Harvard Medical School, USA.</auth-address><titles><title>The cost-effectiveness of noninstitutional long-term care services: review and synthesis of the most recent evidence</title><secondary-title>Med Care Res Rev</secondary-title><alt-title>Medical care research and review : MCRR</alt-title></titles><periodical><full-title>Med Care Res Rev</full-title><abbr-1>Medical care research and review : MCRR</abbr-1></periodical><alt-periodical><full-title>Med Care Res Rev</full-title><abbr-1>Medical care research and review : MCRR</abbr-1></alt-periodical><pages>3-28</pages><volume>63</volume><number>1</number><edition>2006/05/12</edition><keywords><keyword>Community Health Services/ economics</keyword><keyword>Cost-Benefit Analysis</keyword><keyword>Dementia/therapy</keyword><keyword>Evidence-Based Medicine</keyword><keyword>Home Care Services/ economics</keyword><keyword>Humans</keyword><keyword>Long-Term Care</keyword><keyword>United States</keyword></keywords><dates><year>2006</year><pub-dates><date>Feb</date></pub-dates></dates><isbn>1077-5587 (Print)
1077-5587 (Linking)</isbn><accession-num>16686071</accession-num><urls></urls><remote-database-provider>NLM</remote-database-provider><language>eng</language></record></Cite></EndNote>Grabowski (2006a) reviewed empirical research published between 1996 and 2004 that examined cost-effectiveness of four models of noninstitutional long-term care: Medicaid HCBS waivers, consumer-directed care, capitated long-term care, and case management for persons suffering from dementia. ADDIN EN.CITE <EndNote><Cite AuthorYear="1"><Author>Weissert</Author><Year>2013</Year><RecNum>73</RecNum><DisplayText>Weissert and Frederick (2013)</DisplayText><record><rec-number>73</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">73</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Weissert, W. G.</author><author>Frederick, L.</author></authors></contributors><auth-address>Department of Political Science, Faculty Associate, Pepper Institute on Aging and Public Policy, Director, Masters of Public Health Degree Program, Florida State University, Tallahassee, Florida 32306, USA. wweissert@fsu.edu</auth-address><titles><title>The woodwork effect: estimating it and controlling the damage</title><secondary-title>J Aging Soc Policy</secondary-title><alt-title>Journal of aging & social policy</alt-title></titles><periodical><full-title>J Aging Soc Policy</full-title><abbr-1>Journal of aging & social policy</abbr-1></periodical><alt-periodical><full-title>J Aging Soc Policy</full-title><abbr-1>Journal of aging & social policy</abbr-1></alt-periodical><pages>107-33</pages><volume>25</volume><number>2</number><edition>2013/04/11</edition><dates><year>2013</year></dates><isbn>1545-0821 (Electronic)
0895-9420 (Linking)</isbn><accession-num>23570506</accession-num><urls></urls><electronic-resource-num>10.1080/08959420.2013.766073</electronic-resource-num><remote-database-provider>NLM</remote-database-provider><language>eng</language></record></Cite></EndNote>Weissert and Frederick (2013) reviewed 43 studies of HCBS programs published between 1963 and 2008. They compared between the treatment (i.e., those receiving HCBS) and control group (those not receiving HCBS) regarding admission rates and length of stay in nursing home and hospital, and inpatient and outpatient saving, and cost of HCBS per capita. ADDIN EN.CITE <EndNote><Cite AuthorYear="1"><Author>Wysocki</Author><Year>2012</Year><RecNum>75</RecNum><DisplayText>Wysocki et al. (2012)</DisplayText><record><rec-number>75</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">75</key></foreign-keys><ref-type name="Report">27</ref-type><contributors><authors><author>Wysocki, A.</author><author>Butler, M.</author><author>Kane, R. L.</author><author>Kane, R. A.</author><author>Shippee, T.</author><author>Sainfort, F.</author></authors></contributors><titles><title>Long-Term Care for Older Adults: A Review of Home and Community-Based Services Versus Institutional Care</title><secondary-title>Effective Health Care Program: Comparative Effectiveness Review</secondary-title></titles><volume>81</volume><dates><year>2012</year><pub-dates><date>Nov</date></pub-dates></dates><pub-location>Rockville, MD</pub-location><publisher>Agency for Healthcare Research and Quality</publisher><accession-num>23256217</accession-num><urls></urls><language>eng</language></record></Cite></EndNote>Wysocki et al. (2012) reviewed RCTs and observational studies that directly compared LTC for older adults served through HCBS and in NHs and published between 1995-March 2012. They identified 42 relevant studies (37 peer reviewed, 5 grey literature). AARP conducted a review of the grey literature that consisted of a total of 38 studies including state-specific public studies, evaluations, and fiscal analyses published between 2005 and 2012 ADDIN EN.CITE <EndNote><Cite><Author>Fox-Grage</Author><Year>2013</Year><RecNum>117</RecNum><DisplayText>(Fox-Grage & Walls, 2013)</DisplayText><record><rec-number>117</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">117</key></foreign-keys><ref-type name="Report">27</ref-type><contributors><authors><author>Fox-Grage, W. </author><author>Walls, J.</author></authors></contributors><titles><title>State Studies Find Home and Community-Based Services to Be Cost-Effective</title><secondary-title>Spotlight </secondary-title></titles><dates><year>2013</year></dates><pub-location>Washington, DC</pub-location><publisher>Public Policy Institute, AARP</publisher><urls></urls></record></Cite></EndNote>(Fox-Grage & Walls, 2013). In his review of the earlier literature on HCBS, ADDIN EN.CITE <EndNote><Cite AuthorYear="1"><Author>Grabowski</Author><Year>2006</Year><RecNum>90</RecNum><DisplayText>Grabowski (2006a)</DisplayText><record><rec-number>90</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">90</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Grabowski, D. C.</author></authors></contributors><auth-address>Harvard Medical School, USA.</auth-address><titles><title>The cost-effectiveness of noninstitutional long-term care services: review and synthesis of the most recent evidence</title><secondary-title>Med Care Res Rev</secondary-title><alt-title>Medical care research and review : MCRR</alt-title></titles><periodical><full-title>Med Care Res Rev</full-title><abbr-1>Medical care research and review : MCRR</abbr-1></periodical><alt-periodical><full-title>Med Care Res Rev</full-title><abbr-1>Medical care research and review : MCRR</abbr-1></alt-periodical><pages>3-28</pages><volume>63</volume><number>1</number><edition>2006/05/12</edition><keywords><keyword>Community Health Services/ economics</keyword><keyword>Cost-Benefit Analysis</keyword><keyword>Dementia/therapy</keyword><keyword>Evidence-Based Medicine</keyword><keyword>Home Care Services/ economics</keyword><keyword>Humans</keyword><keyword>Long-Term Care</keyword><keyword>United States</keyword></keywords><dates><year>2006</year><pub-dates><date>Feb</date></pub-dates></dates><isbn>1077-5587 (Print)
1077-5587 (Linking)</isbn><accession-num>16686071</accession-num><urls></urls><remote-database-provider>NLM</remote-database-provider><language>eng</language></record></Cite></EndNote>Grabowski (2006a) concluded that while quality of care and access to services were found to either improve or remain stable across capitated HCBS programs, the evaluations have produced mixed evidence regarding reducing program costs. The PACE, Wisconsin Family Care, MSHO, and S/HMO II evaluations found higher program costs, and the ALTCS and the Texas STAR+PLUS evaluations found lower program costs under capitation. In addressing the “woodwork effect” of the HCBS expansion, ADDIN EN.CITE <EndNote><Cite AuthorYear="1"><Author>Weissert</Author><Year>2013</Year><RecNum>73</RecNum><DisplayText>Weissert and Frederick (2013)</DisplayText><record><rec-number>73</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">73</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Weissert, W. G.</author><author>Frederick, L.</author></authors></contributors><auth-address>Department of Political Science, Faculty Associate, Pepper Institute on Aging and Public Policy, Director, Masters of Public Health Degree Program, Florida State University, Tallahassee, Florida 32306, USA. wweissert@fsu.edu</auth-address><titles><title>The woodwork effect: estimating it and controlling the damage</title><secondary-title>J Aging Soc Policy</secondary-title><alt-title>Journal of aging & social policy</alt-title></titles><periodical><full-title>J Aging Soc Policy</full-title><abbr-1>Journal of aging & social policy</abbr-1></periodical><alt-periodical><full-title>J Aging Soc Policy</full-title><abbr-1>Journal of aging & social policy</abbr-1></alt-periodical><pages>107-33</pages><volume>25</volume><number>2</number><edition>2013/04/11</edition><dates><year>2013</year></dates><isbn>1545-0821 (Electronic)
0895-9420 (Linking)</isbn><accession-num>23570506</accession-num><urls></urls><electronic-resource-num>10.1080/08959420.2013.766073</electronic-resource-num><remote-database-provider>NLM</remote-database-provider><language>eng</language></record></Cite></EndNote>Weissert and Frederick (2013) concluded from the current literature that HCBS reduced nursing home use rates on average by only a small percentage, not enough to offset the costs of HCBS. Also, HCBS has limited evidence to support its effect on reducing adverse health outcomes (e.g., ADL, mortality). Similarly, ADDIN EN.CITE <EndNote><Cite AuthorYear="1"><Author>Wysocki</Author><Year>2012</Year><RecNum>75</RecNum><DisplayText>Wysocki et al. (2012)</DisplayText><record><rec-number>75</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">75</key></foreign-keys><ref-type name="Report">27</ref-type><contributors><authors><author>Wysocki, A.</author><author>Butler, M.</author><author>Kane, R. L.</author><author>Kane, R. A.</author><author>Shippee, T.</author><author>Sainfort, F.</author></authors></contributors><titles><title>Long-Term Care for Older Adults: A Review of Home and Community-Based Services Versus Institutional Care</title><secondary-title>Effective Health Care Program: Comparative Effectiveness Review</secondary-title></titles><volume>81</volume><dates><year>2012</year><pub-dates><date>Nov</date></pub-dates></dates><pub-location>Rockville, MD</pub-location><publisher>Agency for Healthcare Research and Quality</publisher><accession-num>23256217</accession-num><urls></urls><language>eng</language></record></Cite></EndNote>Wysocki et al. (2012) concluded that there was low or insufficient evidence for beneficial effects of HCBS on HCBS recipients or assisted living residents compared with nursing home residents over time in terms of physical function, cognition, mental health, and mortality. They further concluded that evidence was also insufficient for cost comparisons. On the contrary, the AARP report ADDIN EN.CITE <EndNote><Cite><Author>Fox-Grage</Author><Year>2013</Year><RecNum>117</RecNum><DisplayText>(Fox-Grage & Walls, 2013)</DisplayText><record><rec-number>117</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">117</key></foreign-keys><ref-type name="Report">27</ref-type><contributors><authors><author>Fox-Grage, W. </author><author>Walls, J.</author></authors></contributors><titles><title>State Studies Find Home and Community-Based Services to Be Cost-Effective</title><secondary-title>Spotlight </secondary-title></titles><dates><year>2013</year></dates><pub-location>Washington, DC</pub-location><publisher>Public Policy Institute, AARP</publisher><urls></urls></record></Cite></EndNote>(Fox-Grage & Walls, 2013) concluded that the studies that evaluated the cost effectiveness of HCBS supported Medicaid “balancing” and other efforts to move more resources toward HCBS rather than institutional care. They also reported that although few studies document absolute cost savings, the studies consistently found much lower per-individual, average costs for HCBS compared with institutional care.Key methodological issues identified included: (1) lack of randomized study design or an appropriate statistical technique such as instrumental variables to address the issue of selection bias or attrition (Grabowski, 2006; Wysocki et al., 2012); (2) limited generalizability of study findings given that each HCBS program evaluation is specific to unique characteristics of each state and there is a great variability across states in terms of their HCBS coverage (Grabowski, 2006); (3) poor measurement of quality and variation in outcome measures and data collection used across studies (Grabowski, 2006; Wysocki et al., 2012); (4) small number of longitudinal studies with sufficient length of time frame to measure changes over time (Grabowski, 2006); (5) weak statistical methods that did not adjust for covariates that may confound observed differences across the treatment and comparison groups (Grabowski, 2006); (6) insufficient description of the settings and services received as well as the study sample composition (Wysocki et al., 2012); (7) lack of examination of recipients’ or caregivers’ experiences of care and how informal care may have affected the type, frequency, or intensity of HCBS and beneficiary outcomes (Wysocki et al., 2012); and (8) lack of distinction between long-standing and new LTC users and following individuals across different providers or settings over time (Wysocki et al., 2012).In sum, two literature reviews on mostly evaluation studies published in peer-reviewed journals (Grabowski, 2006; Wysocki et al., 2012) concluded that there was not sufficient evidence to support positive or negative effects of HCBS on beneficiary outcomes as well as the HCBS’ cost effectiveness due to methodological limitations in past research. Weissert and Frederick (2013) however concluded that the literature supported the woodwork effect hypothesis. They concluded that HCBS reduced nursing home use rates on average by only a small percentage, not enough to offset the costs of HCBS. At the same time, the AARP report concluded that there was strong evidence for lower per-individual, average costs for HCBS compared with institutional care.Summary of Individual Studies on Health/Function/End-of-Life OutcomesSeven studies examined the effects of HCBS on various beneficiary outcomes such as hospitalization admission, health and function, and end-of-life outcomes (APS Healthcare, 2005; Konetzka, Karon, & Potter, 2012; Marek et al., 2005; Mitchell et al., 2004; Muramatsu, Yin, & Hedeker, 2010; Rigler, Perara, Jachna, Chireman, & Eng, 2004; Wieland et al., 2010). Two studies used quasi-experimental design (APS Healthcare, 2005; Marek et al., 2005) while the other studies were secondary data analysis studies. Six studies were longitudinal (APS Healthcare, 2005; Marek et al., 2005; Mitchell et al., 2004; Muramatsu, Yin, & Hedeker, 2010; Rigler et al., 2004; Wieland et al., 2010). Two studies examined the effects of HCBS at the national level (Konetzka et al., 2012; Muramatsu et al., 2010) while the rest of the studies looked at programs in specific states. Marek et al (2005) examined the HCBS program in Missouri, the APS evaluation (2005) examined the Wisconsin Family Care program in Wisconsin, while Rigler et al. (2004) looked at the experience in Kansas, Mitchell et al (2004) focused in Michigan and Wieland et al (2010) examined South Carolina experience. Two studies by Konetzka et al (2012) and Marek et al (2005) did not utilize multivariate analysis while the others did. The most common data sources for these studies were MDS, Medicaid claims, and state HCBS data such as CARE and CIRTS. The most commonly used outcome measures were ADL and depression. Less commonly used measures included inappropriate use of medication (Rigler et al., 2004), avoidable hospitalization (Konetzka et al., 2012), cognition and incontinence (Marek et al., 2005), end-of-life outcomes such as hospice referrals and advance directives (Mitchell et al., 2004), and mortality (Wieland et al., 2010). None of the studies reported results using comprehensive, validated measures of quality of life (only the APS study reported descriptive statistics on quality of life measures but not multivariate analysis results), social functioning, community integration, or life satisfaction. Findings regarding the effect of HCBS varied across studies. The APS evaluation (2005), one of the few studies that used propensity matching and multi-level analysis, found that the Wisconsin Family Care program, a capitated, managed long-term care program for HCBS users, reduced the overall Medicaid long-term care and hospitalization cost significantly compared to the matched comparison group. Through path analysis, they found that reduction in the overall Medicaid total cost, as well as long-term care cost, was mediated through improving function (ADL) and decreasing hospitalizations and increasing outpatient service use. Konetzka et al. (2012) reported that HCBS users were more likely to have avoidable hospitalization than non-HCBS counterparts among Medicaid beneficiaries in the U.S. However, this study was cross-sectional and used descriptive analysis without risk adjustment. Muramatsu et al. (2010) reported that states with higher spending on HCBS were associated with improved mental health outcomes among their highly impaired seniors. This study utilized a nationally representative sample and multi-level mixed effects regression analysis. The longitudinal study by Marek et al. (2005) reported that a HCBS program in Missouri improved cognition, depression, ADL, incontinence compared to the matched cohort of NH residents. Three other state specific longitudinal studies reported, however, that HCBS were more likely to: increase use of inappropriate medications (Rigler et al., 2004); decrease completion of advance directives and increase pain and shortness of breath compared to non HCBS nursing home residents (Mitchell et al., 2004); and lead to shorter survival length compared to PACE program participants (Wieland et al., 2010).In sum, of the five longitudinal studies utilizing multivariate analysis, two studies reported that compared to non-HCBS users, HCBS users experienced positive outcomes including improved function, increased outpatient service use, and decreased depression (APS, 2005; Muramatsu et al., 2010), while three studies reported that HCBS users experienced worse outcomes than non-HCBS users, primarily nursing home residents, such as higher risks of inappropriate medication use, shorter survival length, and experience of pain and short breath, and decreased chance of completing advance directives (Mitchell et al., 2004; Rigler et al., 2004; Wieland et al., 2010). Considering these results, it is important to note that two studies reporting positive effects of HCBS (APS, 2005; Muramatsu et al., 2010) utilized more advanced and stronger design than the other three studies including use of a nationally representative sample of older adults, propensity score matching, and advanced multivariate statistical analysis such as multilevel mixed effects analysis and path analysis. Summary of Individual Studies on Nursing Home Admission Six studies, all of which were retrospective studies with 1 cross-sectional (Hahn, Thomas, Hyer, Andel, & Meng, 2011) and 5 with longitudinal design (APS, 2005; Miller, 2011; Muramatsu et al., 2007; Muramatsu, Hoyem, Yin, & Campbell, 2008; Thomas et al., 2012) examined the effect of HCBS on nursing home admission rates. All studies used multivariate analysis approach. One study (Hahn et al., 2011) included covariates at market/regional level and individual level examining the experience in Florida. Another study (Thomas et al., 2012) also included covariates at market/regional level and individual level examining the experience at the national level. One study examined the effect of Wisconsin Family Care program on nursing home and home health costs (APS, 2005). Three studies (Miller, 2011; Muramatsu et al., 2007; Muramatsu et al., 2008) examined the experience at the national level. All studies reported that HCBS reduced nursing home admission. APS (2005) report found that individuals enrolled in Family Care program had significantly lower nursing home cost and home health cost compared to non-Family Care program enrollees. Hahn et al. (2011) reported that higher HCBS county expenditure was associated with reduced number of low-care NH residents while Muramatsu et al. (2008) reported that states with higher HCBS spending had reduced risk of NH admission among childless seniors and seniors at the end of life. Miller (2011) reported that HCBS state resources combined with limited NH supply reduced NH admission among seniors. Thomas et al. (2012) however reported that while the Older Americans Act services reduced low-care NH residents, state Medicaid HCBS waiver expenditure did not reduce the number of low-care residents.Overall, a consistent finding across studies was that higher state expenditures on HCBS was associated with reduced nursing home admission, and in case of Wisconsin Family Care, home health care cost, as well as nursing home cost, was reduced as a result of the program. Although none of these studies used a RCT design, the APS study (2005) utilized propensity score matching method to control for selection bias. The time period covered by these studies ranged from 1995 thru 2009. The literature review by Wysocki et al. (2012) also drew a similar conclusion that the overall the literature supports strong association between HCBS and decreased use of nursing home use.Summary of Individual Studies on CostNine studies examined the effect of HCBS on LTSS cost (APS, 2005; Eiken, Burwell, & Sredl, 2013; Kane et al., 2013; Kaye, LaPlante, & Harrington, 2009; Kitchener, Ng, Miller, & Harrington, 2006; Mitchell, Salmon, Polivka, & Soberon-Ferrer, 2006; Shapiro, Loh, & Mitchell, 2011; Shireman & Rigler, 2004). All studies utilized secondary data sources (mainly claims data). All studies except for one (APS, 2005; Kitchener et al., 2006) examined the outcome longitudinally. Six studies conducted multivariate analysis (Kaye, LaPlante, & Harrington, 2009; Mitchell, Salmon, Polivka, & Soberon-Ferrer, 2006; Shapiro, Loh, & Mitchell, 2011; Shireman & Rigler, 2004). Three studies examined the effect of HCBS on cost at the national level (Eiken et al., 2013; Kaye et al., 2009; Kitchener et al., 2006), while the other studies examined the experiences in selected states. Three studies examined the woodwork effect on a national level (Eiken et al., 2013; Keye et al., 2009) and state level (Kane et al., 2013). A descriptive, national study by Eiken et al., 2013 found that Medicaid LTSS cost after adjusting for inflation and national estimate of functional limitation growth was 1.8% per year from 1999-2009. Another national study using multivariate approach by Keye et al. (2009) also found that between 1995 and 2005, HCBS grew faster than inflation (56.7% vs. 110%), nursing home use increased 3.4% in low HCBS states whiles NH spending decreased by 15.3% in high HCBS areas. However, they also found that although LTSS expenditures, on average across states, grew by 7.3% (with large decrease in 2003-2005), the LTSS expenditure decreased by 7.9% in the established HCBS states. Kane et al. (2013) examined the experiences in six states, AR, FL, MN, NM, TX, VT, WA, and reported in their descriptive study that from 2001 to 2005, the number of NH residents declined in 6 states, however, increases in HCBS waiver and state plan expenditures led to a net increase of 10% in LTSS expenditures.Studies examining the effects of HCBS on cost and its variations across HCBS programs reported varying findings. The APS (2005) study reported that the Wisconsin Family Care program enrollees had significantly less total Medicaid cost and long-term care cost by reducing institutionalization and improving function than non-Family Care enrollees. Shireman and Rigler (2004) reported that Medicaid cost (average cost per user) was lower for HCBS users than NH users. Three studies examined variations of LTC and HCBS cost in Florida. Two studies (Mitchell et al., 2006; Shapiro, Loh, & Mitchell, 2011) reported that HCBS program cost savings varied across programs in Florida. Of particular note is the study by Shapiro and colleagues (2011) which used propensity matching to control for selection bias, reported that there is little evidence of HCBS saving acute care cost. Lastly, an evaluation report by the state of Florida on their HCBS program (OPPAGA, 2010) also found that there was considerable variation in the effectiveness of HCBS across programs. For example, they found that one of the HCBS programs, Nursing Home Diversion cost was substantially higher than the cost of other HCBS programs in the state although this program reduced nursing home admission at a higher rate than other two comparison programs.In sum, findings from recent studies suggest limited evidence for the woodwork effect hypothesis. Two national studies using descriptive analysis reported that the number of enrollees in HCBS, as well as cost, increased over the last decade. However, such increase was not substantial after adjusting for inflation and disability rates. One multivariate analysis study examining the trend across states found that LTSS expenditures varied by states. States with established HCBS programs experienced decrease in their LTSS expenditures, and found no evidence to support the woodwork effect. In addition, three studies reported overall less Medicaid expenditure for HCBS users compared to nursing home users. Summary of Key Methodological Limitations of StudiesKey methodological limitations of the majority of studies reviewed concern two issues: limited internal validity (ability to make a causal inference) and external validity (generalizability) of study findings. The first major limitation is lack of a randomized study design or an appropriate statistical technique, such as instrumental variables to address the issue of selection bias across the intervention (i.e., HCBS users) and comparison groups (non-HCBS users). Among current studies published since 2000 that were reviewed by ADDIN EN.CITE <EndNote><Cite AuthorYear="1"><Author>Wysocki</Author><Year>2012</Year><RecNum>75</RecNum><DisplayText>Wysocki et al. (2012)</DisplayText><record><rec-number>75</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">75</key></foreign-keys><ref-type name="Report">27</ref-type><contributors><authors><author>Wysocki, A.</author><author>Butler, M.</author><author>Kane, R. L.</author><author>Kane, R. A.</author><author>Shippee, T.</author><author>Sainfort, F.</author></authors></contributors><titles><title>Long-Term Care for Older Adults: A Review of Home and Community-Based Services Versus Institutional Care</title><secondary-title>Effective Health Care Program: Comparative Effectiveness Review</secondary-title></titles><volume>81</volume><dates><year>2012</year><pub-dates><date>Nov</date></pub-dates></dates><pub-location>Rockville, MD</pub-location><publisher>Agency for Healthcare Research and Quality</publisher><accession-num>23256217</accession-num><urls></urls><language>eng</language></record></Cite></EndNote>Wysocki et al. (2012) and reviewed in this report, there was no randomized control trial study. The second limitation related to most of observational studies is poor or limited types of potential confounders measured or controlled for in analyses. In evaluation studies of different states’ HCBS programs, findings from these studies may have been biased due to unmeasured state and time-varying factors, and other uncontrolled factors that may have influenced the spending such as nursing home diversion policies (e.g., preadmission screening). Among studies that evaluated the effects of HCBS on delaying nursing home admission or cost within the same state, consistent findings were that ADDIN EN.CITE <EndNote><Cite><Author>Weissert</Author><Year>2013</Year><RecNum>73</RecNum><DisplayText>(Weissert & Frederick, 2013)</DisplayText><record><rec-number>73</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">73</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Weissert, W. G.</author><author>Frederick, L.</author></authors></contributors><auth-address>Department of Political Science, Faculty Associate, Pepper Institute on Aging and Public Policy, Director, Masters of Public Health Degree Program, Florida State University, Tallahassee, Florida 32306, USA. wweissert@fsu.edu</auth-address><titles><title>The woodwork effect: estimating it and controlling the damage</title><secondary-title>J Aging Soc Policy</secondary-title><alt-title>Journal of aging & social policy</alt-title></titles><periodical><full-title>J Aging Soc Policy</full-title><abbr-1>Journal of aging & social policy</abbr-1></periodical><alt-periodical><full-title>J Aging Soc Policy</full-title><abbr-1>Journal of aging & social policy</abbr-1></alt-periodical><pages>107-33</pages><volume>25</volume><number>2</number><edition>2013/04/11</edition><dates><year>2013</year></dates><isbn>1545-0821 (Electronic)
0895-9420 (Linking)</isbn><accession-num>23570506</accession-num><urls></urls><electronic-resource-num>10.1080/08959420.2013.766073</electronic-resource-num><remote-database-provider>NLM</remote-database-provider><language>eng</language></record></Cite></EndNote>(Weissert & Frederick, 2013): (1) those attracted to HCBS tend to be people who are younger, better supported, less dependent, and more mentally intact than their nursing home counterparts, and (2) only a small proportion of LTC clients are likely to enter nursing homes within the coming year even though they receive no HCBS. Hence, use of more rigorous design (e.g., RCT) is needed for future studies. In addition, in observational studies, it would be important to use more advanced statistical analysis strategies to control for potential selection bias by developing and using instrumental variables that may help reduce selection bias. The third issue is limited time frame of many studies. In the review by Wysoki and colleague (2012), there were 22 cross-sectional studies while there were only 14 longitudinal studies. Lack of distinction between long-standing and new LTC users and following individuals across different providers or settings over time is another major issue. Follow-up times for tracking outcomes were often short in most studies, making it difficult to examine the long-term effect of HCBS. In addition, few studies used an admission cohort although outcomes may differ for newcomers to the LTSS system compared with those who have lived with limitations or received services for a longer period of time. The fourth issue is that most studies suffer from use of non-probability sampling introducing systematic sampling bias, thus, make it difficult to generalize results from a particular study. In most state specific studies, generalizability of their findings is limited because each HCBS program evaluation is specific to the unique characteristics of each state, while there is a great variability across states in terms of their HCBS coverage and nursing home diversion policies. In studies that examined state variations, due to limitations in data availability, often excluded in analysis were states without overall HCBS claims data or capitated managed care data. In addition to conducting more randomized experimental design with a longer follow-up period using randomly selected subjects in studies, future observational or quasi-experimental studies should include the following elements: Prospective design Use of advanced statistical techniques such as propensity matching to control for selection biasUse of appropriate statistical techniques to control for multi-level confounding variables Use of longer follow-up periodUse of admission cohort without duplicated dataInclusion of a comprehensive set of unmeasured state/regional/individual characteristic variables and time-varying factors (e.g., county or state level provider availability, rural vs. urban status, recipients’ or caregivers’ experiences of care and how informal care may have affected the type, frequency, or intensity of HCBS, and beneficiary outcomes) Inclusion of key beneficiary outcome measures (e.g., quality of life, social interaction and community integration, life satisfaction)Evaluation of aggregate Medicaid spending as well as average costs per recipientConclusionIn evaluating the available empirical research on the effect of HCBS on beneficiary outcomes and cost, the four reviews included in this report drew different conclusions. Two literature reviews (Grabowski, 2006; Wysocki et al., 2012) concluded that there was not sufficient evidence to support positive or negative effects of HCBS on beneficiary outcomes as well as the HCBS’ cost effectiveness due to methodological limitations in past research. Weissert and Frederick (2013) however concluded that there was strong empirical evidence to support the woodwork effect hypothesis because the reduction in nursing home use due to HCBS was so small that it was not enough to offset the costs of HCBS. At the same time, the AARP report concluded that there was strong evidence for lower per-individual, average costs for HCBS compared with institutional care.The review of 19 individual studies included in this report suggests that while results of studies on beneficial effects of HCBS on individual outcomes are mixed, more recent and rigorously designed studies reported favorable effects of HCBS. Two studies reporting positive effects of HCBS such as improved function, increased outpatient service use, and decreased depression (APS, 2005; Muramatsu et al., 2010) utilized more advanced and stronger design than the other studies. Regarding the effect of HCBS on nursing home admission and cost, results from various studies are consistent. Overall, a consistent finding across studies was that higher state expenditures on HCBS was associated with reduced nursing home admission, and in case of Wisconsin Family Care, home health care cost and nursing home cost were reduced as a result of the program. This conclusion is consistent with that of Wysocki et al. (2012) who also found that there was a strong association between HCBS and decreased use of nursing home use. Regarding the woodwork effect, findings from recent studies suggest limited evidence to support the hypothesis. Two national studies using descriptive analysis reported that the number of enrollees in HCBS, as well as cost, increased over the last decade. However, such increase was not substantial after adjusting for inflation and disability rates. One multivariate analysis study examining the trend across states found that LTSS expenditures varied by states. States with established HCBS programs experienced a decrease in their LTSS expenditures, and found no evidence to support the woodwork effect. In addition, three studies reported overall less Medicaid expenditure for HCBS users compared to nursing home users. In conclusion, despite methodological limitations of past research, recent studies with more advanced and rigorous research design suggest findings that support cost effectiveness of HCBS programs. However, more research is needed that utilizes prospective, longitudinal design and advanced statistical analysis techniques and examines a broad range of beneficiary and family caregiver outcomes among various, population groups. Appendix A Narrative Summary of Each Article/Report Reviewed Literature Review Articles/Report1. AARP 2013 Report ADDIN EN.CITE <EndNote><Cite><Author>Fox-Grage</Author><Year>2013</Year><RecNum>117</RecNum><DisplayText>(Fox-Grage & Walls, 2013)</DisplayText><record><rec-number>117</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">117</key></foreign-keys><ref-type name="Report">27</ref-type><contributors><authors><author>Fox-Grage, W. </author><author>Walls, J.</author></authors></contributors><titles><title>State Studies Find Home and Community-Based Services to Be Cost-Effective</title><secondary-title>Spotlight </secondary-title></titles><dates><year>2013</year></dates><pub-location>Washington, DC</pub-location><publisher>Public Policy Institute, AARP</publisher><urls></urls></record></Cite></EndNote>(Fox-Grage & Walls, 2013)Purpose/Research Question(s): To collect public HCBS cost-effectiveness studies from the states. Overall Design: Review of the grey literature published between 2005 and 2012, which included state-specific public studies, evaluations, and fiscal analyses. Included studies addressed the actual or potential state fiscal impact (or justification) of HCBS alternatives to nursing facility care or the fiscal impact of HCBS programs using state-specific data. Sample/Data Collection: In 2011, state Medicaid and aging and disability agency administrators were asked if they used state HCBS cost-effectiveness studies and, if so, to supply the name and link to the study, if possible. These questions were part of a much larger annual LTSS economic survey of the AARP Public Policy Institute, Health Management Associates, and National Association of States United for Aging and Disability (NASUAD). In 2012, the authors sent follow-up emails to the states that did not respond to the survey, and the authors also conducted a corresponding literature review. Analysis: After collecting the studies, the authors read, wrote summaries, and categorized the fiscal elements of the studies. Results: A total of 38 studies were included in the review. The studies that evaluated the cost effectiveness of HCBS supported Medicaid “balancing” and other efforts to move more resources toward HCBS rather than institutional care. Although few studies document absolute cost savings, the studies consistently found much lower per-individual, average costs for HCBS compared with institutional care. Overall, the findings illustrate cost reductions by diverting and transitioning individuals from nursing home care to HCBS. However, only two studies and reports appear to have used quasi-experimental design (Felix et al., 2011) and multivariate analysis (Department of Georgia, 2006). The remaining studies were mostly descriptive and a few applied risk-adjustment to their analysis (Lewin Group 2011 report for Rhode Island). Overall, most of the studies contained quantitative analyses, which included information on spending, utilization, enrollment, and costs: 33 studies analyzed spending; 30 studies analyzed Medicaid utilization, 14 analyzed Older Americans Act utilization, and 15 analyzed state or other funded programs (many studies looked at utilization from more than one program); 28 studies analyzed client enrollment; 19 studies reported savings or a reduction in the growth of costs; 9 studies contained a cost-benefit analysis; and 2 studies analyzed return on investment. In addition to spending data, the studies provided a wealth of qualitative information, including demographics, health status, service access and capacity, social factors, and client satisfaction and health outcomes: 27 studies analyzed demographics; 19 studies analyzed service access and capacity; 17 studies analyzed health status; 16 studies analyzed social factors; and 5 studies each analyzed client satisfaction and health outcomes. 2. ADDIN EN.CITE <EndNote><Cite AuthorYear="1"><Author>Grabowski</Author><Year>2006</Year><RecNum>90</RecNum><DisplayText>Grabowski (2006a)</DisplayText><record><rec-number>90</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">90</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Grabowski, D. C.</author></authors></contributors><auth-address>Harvard Medical School, USA.</auth-address><titles><title>The cost-effectiveness of noninstitutional long-term care services: review and synthesis of the most recent evidence</title><secondary-title>Med Care Res Rev</secondary-title><alt-title>Medical care research and review : MCRR</alt-title></titles><periodical><full-title>Med Care Res Rev</full-title><abbr-1>Medical care research and review : MCRR</abbr-1></periodical><alt-periodical><full-title>Med Care Res Rev</full-title><abbr-1>Medical care research and review : MCRR</abbr-1></alt-periodical><pages>3-28</pages><volume>63</volume><number>1</number><edition>2006/05/12</edition><keywords><keyword>Community Health Services/ economics</keyword><keyword>Cost-Benefit Analysis</keyword><keyword>Dementia/therapy</keyword><keyword>Evidence-Based Medicine</keyword><keyword>Home Care Services/ economics</keyword><keyword>Humans</keyword><keyword>Long-Term Care</keyword><keyword>United States</keyword></keywords><dates><year>2006</year><pub-dates><date>Feb</date></pub-dates></dates><isbn>1077-5587 (Print)
1077-5587 (Linking)</isbn><accession-num>16686071</accession-num><urls></urls><remote-database-provider>NLM</remote-database-provider><language>eng</language></record></Cite></EndNote>Grabowski (2006a)Purpose/Design ADDIN EN.CITE <EndNote><Cite AuthorYear="1"><Author>Grabowski</Author><Year>2006</Year><RecNum>90</RecNum><DisplayText>Grabowski (2006a)</DisplayText><record><rec-number>90</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">90</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Grabowski, D. C.</author></authors></contributors><auth-address>Harvard Medical School, USA.</auth-address><titles><title>The cost-effectiveness of noninstitutional long-term care services: review and synthesis of the most recent evidence</title><secondary-title>Med Care Res Rev</secondary-title><alt-title>Medical care research and review : MCRR</alt-title></titles><periodical><full-title>Med Care Res Rev</full-title><abbr-1>Medical care research and review : MCRR</abbr-1></periodical><alt-periodical><full-title>Med Care Res Rev</full-title><abbr-1>Medical care research and review : MCRR</abbr-1></alt-periodical><pages>3-28</pages><volume>63</volume><number>1</number><edition>2006/05/12</edition><keywords><keyword>Community Health Services/ economics</keyword><keyword>Cost-Benefit Analysis</keyword><keyword>Dementia/therapy</keyword><keyword>Evidence-Based Medicine</keyword><keyword>Home Care Services/ economics</keyword><keyword>Humans</keyword><keyword>Long-Term Care</keyword><keyword>United States</keyword></keywords><dates><year>2006</year><pub-dates><date>Feb</date></pub-dates></dates><isbn>1077-5587 (Print)
1077-5587 (Linking)</isbn><accession-num>16686071</accession-num><urls></urls><remote-database-provider>NLM</remote-database-provider><language>eng</language></record></Cite></EndNote>Grabowski (2006a) reviewed empirical research that (1) were published between 1996 and 2004, and (2) examined cost-effectiveness of four models of noninstitutional long-term care: Medicaid HCBS waivers, consumer-directed care, capitated long-term care, and case management for persons suffering from dementia. Regarding two relevant areas to this report, Medicaid HCBS waivers and capitated long-term care, Grabowski reviews and discusses the following: (1) early demonstration studies of HCBS, (2) rationale for the updated review of the HCBS evaluations, (3) key issues in evaluation of HCBS, (4) two evaluations of program expenditures of HCBS, and (5) methods and findings from studies that evaluated six capitated long-term care programs. Key Findings1. Early Demonstrations. Grabowski (2006) provided a succinct review of early demonstration studies of HCBS conducted in the 1980s and 1990s. Early study findings suggested that HCBS slightly reduced nursing home use and spending, which did not lead to the overall decrease in the long-term care spending, and in fact, there was increased aggregate long-term care spending, primarily due to increased HCBS spending. Further, few of early studies of randomized experimental designs found statistically significant differences between the treatment and control groups in either survival or physical and mental functioning although younger, less disabled, and more socially supported individuals seemed to benefit from HCBS, and among general samples of users, psychosocial outcomes such as life satisfaction, social activity, social interaction, and informal caregiver satisfaction were higher under HCBS. 2. Rationale for the Updated Review. Grabowski provided that a main rationale for the updated review of the HCBS was that the environment in which these long-term care services were delivered had also significantly changed in the past 20 years (80s and 90s). 3. Key Issues in Evaluating HCBS. Grabowski identified key issues in evaluating HCBS as moral hazard problem (or woodwork effect) and distinction between cost analysis and cost effectiveness. Grabowski stated that cost-effectiveness depends on effectiveness of targeting (such that only individuals who otherwise would have consumed agency-based services use consumer-directed home care services) and one method of addressing moral hazard is through the use of a capitated payment arrangement in which providers receive a flat fee for each individual enrolled in a managed care plan. He further distinguished that cost analysis focuses only on costs whereas cost-effectiveness analysis evaluates costs against differences in effectiveness (e.g., health and functioning, longevity, unmet needs, satisfaction with care, informal caregiver (e.g., spouse) support, life satisfaction and morale, and the degree of social interaction (Kemper, Applebaum, and Harrigan, 1987). 4. Two Evaluations of HCBS Impact on Cost. Grabowski identified and reviewed two evaluations of aggregate program expenditures of HCBS. First evaluation of expenditures of waiver programs in Oregon, Washington, and Wisconsin was conducted by the U.S. General Accounting Office (GAO 1994). This evaluation compared unadjusted average expenditures for an individual in a nursing home relative to an individual in the waiver program and concluded that the average expenditures on a Medicaid nursing home recipient exceeded the average expenditures on a HCBS waiver recipient. The GAO observed that the number of nursing home beds decreased slightly in the three study states over the period 1982 through 1993, whereas beds increased by more than 20 % nationally during this period. On the basis of these two findings, the GAO concluded that HCBS Medicaid waiver programs lower long-term care spending. However, Grabowski identified the primary weakness in the GAO approach as evaluating average costs per recipient, rather than aggregate Medicaid spending in comparing HCBS waiver and nursing home expenditures. To evaluate “woodwork” effect, evaluating the overall aggregate long-term care spending would be more appropriate. Second evaluation of the effect of HCBS on overall Medicaid spending in three states, Colorado, Oregon, and Washington, was conducted by researchers from the Lewin Group and the AARP (Alecxih et al. 1996). These states were chosen because HCBS accounted for a significant proportion of total Medicaid long-term care recipients. This study compared projected and actual Medicaid long-term care costs over time, controlling for several key demand-and-supply side factors when data were available. Using the most conservative model assumptions, HCBS waiver spending generated 33.8 million dollars in savings in Colorado in 1994, $27.9 million dollars in savings in Oregon in 1993 and 49 million dollars in 1994, and $1 million dollars in savings in Washington in 1993 and 57.1 million dollars in 1994. Grabowski identified primary weaknesses of the evaluation including potential bias from selection of states, unmeasured state and time-varying factors, and other uncontrolled factors that may have influenced the spending such as nursing home diversion policies (e.g., preadmission screening), global budgeting, and other factors in an effort to control costs. Grabowski concluded that the methodological limitations of few available evaluation studies make it difficult to draw a definitive conclusion about the cost saving attributable to HCBS. 5. Evaluations of Six Capitated Long-Term Care Programs. Grabowski reviewed studies that evaluated six capitated long-term care programs - the Program of All-Inclusive Care for the Elderly (PACE), the Arizona Long-Term Care System (ALTCS), the Wisconsin Family Care program, the STAR+PLUS program, the Minnesota Senior Health Options (MSHO), and Social/Health Maintenance Organization (S/HMOII) demonstration in Nevada. A comprehensive evaluation of PACE conducted by Abt Associates, Inc. (Chatterji et al. 1998; Irvin, Massey, and Dorsey 1997; White, Abel, and Kidder 2000) using multivariate methods, compared individuals who voluntarily enrolled in PACE with those individuals who went through the PACE application process but decided not to enroll. PACE was associated with statistically significant outcomes such as greater adult day health care use, lower nurse home visits, fewer hospitalizations, fewer nursing home admissions, a higher probability of receiving ambulatory care, greater survival, an increased number of days in the community, better health, better quality of life, greater satisfaction with overall care arrangements, and better functional status. The Arizona Long-Term Care System (ALTCS) was evaluated using multivariate analysis strategies by comparing service use and quality of outcomes among those in the ALTCS with individuals from the bordering state of New Mexico were used as a comparison group, and comparing actual ALTCS spending with projected spending if the ALTCS had not been implemented, and comparing data on nursing home entry, length of stay, and costs from twonational nursing home samples (McCall et al. 1996; McCall and Korb 1997; Weissert et al. 1997). A multivariate analysis indicated that Arizona nursing home residents were more likely to experience a pressure ulcer, a fever, and require indwelling urinary catheter use than their New Mexico counterparts. There was no statistical difference in nursing home falls and the number of psychotropic drugs prescribed.An independent review of the Texas STAR+PLUS program by the Public Policy Research Institute at Texas A&M examined utilization of services compared to the year preceding the program’s implementation, quality of care for depression and diabetes, and actual costs under STAR+PLUS with projected costs if STAR+PLUS had not been implemented (Border et al. 2002). This evaluation did not adjust for potential confounders in its analysis. Unadjusted quality of care was found to be adequate under the STAR+PLUS program based on member and provider surveys along with focused studies of depression and diabetes patients to determine whether their care met state guidelines.Independent evaluations of the Wisconsin Family Care program by the Lewin Group (Alecxih et al. 2002) and APS Healthcare, Inc. (2003) included evaluation of unadjusted quality and cost evaluation (based on multivariate analysis) by comparing Family Care participants were compared with participants in other community-based waiver programs within the state. Relative to a comparison group from other Wisconsin waiver participants, Family Care participants reported more positive outcomes with regard to choice and self-determination, satisfaction with services, community integration, and health and safety. There were no statistical differences for hospital use, emergency room use, diagnosis of decubitis ulcers, and death for family care recipients. However, it is important to note that the 2005 evaluation of the Family Care by APS ADDIN EN.CITE <EndNote><Cite><Author>APS Healthcare</Author><Year>2005</Year><RecNum>118</RecNum><DisplayText>(APS Healthcare, 2005)</DisplayText><record><rec-number>118</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">118</key></foreign-keys><ref-type name="Report">27</ref-type><contributors><authors><author>APS Healthcare,</author></authors></contributors><titles><title>Family Care Independent Assessment: An Evaluation of Access, Quality and Cost Effectiveness for Calendar Year 2003 - 2004</title><short-title>Family Care Independent Assessment</short-title></titles><dates><year>2005</year></dates><urls></urls></record></Cite></EndNote>(APS Healthcare, 2005), was significantly rigorous in its methodological approach and design, and reported favorable results of its cost-effectiveness. The review of the more recent 2005 report is discussed under the State/Federal/Organizational Report section of the report.An evaluation of the MSHO was conducted using baseline information between October 1998 and June 1999 and a resurvey between August 2000 and February 2001 (Kane et al. 2003; Kane and Homyak 2003) and multivariate analyses of data from the sample consisting if MSHO enrollees and two comparison groups: dually eligible individuals living in the counties where MSHO was offered but who did not enroll in it (used for control group in cost analysis) and dually eligible individuals living in counties where the MSHO was not offered. A multivariate analysis of the MSHO did not show substantial differences in outcomes across function, satisfaction, and caregiver burden across the treatment and control groups. The evaluation of the S/HMO II focused on the effects of the demonstration on health and functioning, service use, and quality of care of its members from July 1997 through April 1999 (Department of Health and Human Services 2003). Using multivariate methods, the evaluation compared enrollees in S/HMO II sites with beneficiaries at other sites that continued to operate as regular Medicare risk plans, and the evaluation also examined if the S/HMO II enrollees received additional services that were unique to S/HMO sites such as care coordination. Additional evaluation, a case study of the demonstration program was conducted using health plan reports, claims data, and administrator interviews for the period 1999 through 2001 (Newcomer, Harrington, and Kane 2002). The S/HMO II was not found to improve health or functional status relative to the Medicare risk plan. There was also no evidence that the quality of care, as measured by the provision of routine preventive care, frequency of physician visits for individuals with certain chronic conditions, and rates of preventable hospitalizations, was any different under the S/HMO II relative to individuals in other Medicare HMO or individuals in traditional FFS Medicare. Lastly, Grabowski summarized the findings from these reports by concluding that while quality of care and access to services were found to either improve or remain stable across all six programs, the evaluations of capitated programs have produced mixed evidence regarding whether the programs have increased or decreased program costs. The PACE, Wisconsin Family Care, MSHO, and S/HMO II evaluations found higher program costs, and the ALTCS and the Texas STAR+PLUS evaluations found lower program costs under capitation. Grabowski further discussed several key methodological limitations of these evaluations including: (1) lack of randomized study design or an appropriate statistical technique such as instrumental variables to address the issue of selection bias across the treatment and comparison groups; (2) limited generalizability of these findings given that each HCBS program evaluation is specific to unique characteristics of each state and there is a great variability across states in terms of their HCBS coverage; (3) poor measurement of quality in some evaluations (e.g., ALTCS); (4) the relatively short time frame of many of the evaluations; and (5) weak statistical methods used to evaluate certain programs (e.g., Texas STAR+PLUS program and quality of care in the Wisconsin Family Care program) that did not adjust for covariates that may confound observed differences across the treatment and comparison groups.3. ADDIN EN.CITE <EndNote><Cite AuthorYear="1"><Author>Weissert</Author><Year>2013</Year><RecNum>73</RecNum><DisplayText>Weissert and Frederick (2013)</DisplayText><record><rec-number>73</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">73</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Weissert, W. G.</author><author>Frederick, L.</author></authors></contributors><auth-address>Department of Political Science, Faculty Associate, Pepper Institute on Aging and Public Policy, Director, Masters of Public Health Degree Program, Florida State University, Tallahassee, Florida 32306, USA. wweissert@fsu.edu</auth-address><titles><title>The woodwork effect: estimating it and controlling the damage</title><secondary-title>J Aging Soc Policy</secondary-title><alt-title>Journal of aging & social policy</alt-title></titles><periodical><full-title>J Aging Soc Policy</full-title><abbr-1>Journal of aging & social policy</abbr-1></periodical><alt-periodical><full-title>J Aging Soc Policy</full-title><abbr-1>Journal of aging & social policy</abbr-1></alt-periodical><pages>107-33</pages><volume>25</volume><number>2</number><edition>2013/04/11</edition><dates><year>2013</year></dates><isbn>1545-0821 (Electronic)
0895-9420 (Linking)</isbn><accession-num>23570506</accession-num><urls></urls><electronic-resource-num>10.1080/08959420.2013.766073</electronic-resource-num><remote-database-provider>NLM</remote-database-provider><language>eng</language></record></Cite></EndNote>Weissert and Frederick (2013)Purpose/DesignIn this article, ADDIN EN.CITE <EndNote><Cite AuthorYear="1"><Author>Weissert</Author><Year>2013</Year><RecNum>73</RecNum><DisplayText>Weissert and Frederick (2013)</DisplayText><record><rec-number>73</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">73</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Weissert, W. G.</author><author>Frederick, L.</author></authors></contributors><auth-address>Department of Political Science, Faculty Associate, Pepper Institute on Aging and Public Policy, Director, Masters of Public Health Degree Program, Florida State University, Tallahassee, Florida 32306, USA. wweissert@fsu.edu</auth-address><titles><title>The woodwork effect: estimating it and controlling the damage</title><secondary-title>J Aging Soc Policy</secondary-title><alt-title>Journal of aging & social policy</alt-title></titles><periodical><full-title>J Aging Soc Policy</full-title><abbr-1>Journal of aging & social policy</abbr-1></periodical><alt-periodical><full-title>J Aging Soc Policy</full-title><abbr-1>Journal of aging & social policy</abbr-1></alt-periodical><pages>107-33</pages><volume>25</volume><number>2</number><edition>2013/04/11</edition><dates><year>2013</year></dates><isbn>1545-0821 (Electronic)
0895-9420 (Linking)</isbn><accession-num>23570506</accession-num><urls></urls><electronic-resource-num>10.1080/08959420.2013.766073</electronic-resource-num><remote-database-provider>NLM</remote-database-provider><language>eng</language></record></Cite></EndNote>Weissert and Frederick (2013) reviews 43 studies of HCBS programs published between 1963 and 2008. Specifically, they compare between the treatment (i.e., those receiving HCBS) and control group (those not receiving HCBS) regarding admission rates and length of stay in nursing home and hospital, and inpatient and outpatient saving, and cost of HCBS per capita. Key FindingsThey report several key consistent findings drawn from the literature: (1) those attracted to HCBS tend to be people who are younger, better supported, less dependent, and more mentally intact than their nursing home counterparts; (2) only a small proportion of LTC clients are likely to enter nursing homes within the coming year even though they receive no HCBS, more than two-thirds of 43 studies reviewed had rates of control group nursing home admission of less than 20%; and (3) most clients are likely to have experienced only a short nursing home stay when admitted. They further conclude that the current literature suggests that HCBS reduced nursing home use rates on average by only a small percentage, not enough to offset the costs of HCBS and HCBS has limited evidence to support its effect on reducing adverse health outcomes (e.g., ADL, mortality). They argue for an approach to develop individualized care plan that titrates care so that the low-risk (i.e., those coming out of woodwork) clients who are admitted to HCBS receive lower budget than those with high risk. They further suggest the need to provide evidence-based information and tools for assessment of risk and developing care plans to reduce the overall spending budget to make HCBS a break-even program. 4. ADDIN EN.CITE <EndNote><Cite AuthorYear="1"><Author>Wysocki</Author><Year>2012</Year><RecNum>75</RecNum><DisplayText>Wysocki et al. (2012)</DisplayText><record><rec-number>75</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">75</key></foreign-keys><ref-type name="Report">27</ref-type><contributors><authors><author>Wysocki, A.</author><author>Butler, M.</author><author>Kane, R. L.</author><author>Kane, R. A.</author><author>Shippee, T.</author><author>Sainfort, F.</author></authors></contributors><titles><title>Long-Term Care for Older Adults: A Review of Home and Community-Based Services Versus Institutional Care</title><secondary-title>Effective Health Care Program: Comparative Effectiveness Review</secondary-title></titles><volume>81</volume><dates><year>2012</year><pub-dates><date>Nov</date></pub-dates></dates><pub-location>Rockville, MD</pub-location><publisher>Agency for Healthcare Research and Quality</publisher><accession-num>23256217</accession-num><urls></urls><language>eng</language></record></Cite></EndNote>Wysocki et al. (2012)Purpose/DesignThis report was prepared for the Agency for Healthcare Research and Quality. The goal of the report was to provide a review of outcomes and cost of HCBS compared to nursing homes. ADDIN EN.CITE <EndNote><Cite><Author>Wysocki</Author><Year>2012</Year><RecNum>75</RecNum><DisplayText>(Wysocki et al., 2012)</DisplayText><record><rec-number>75</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">75</key></foreign-keys><ref-type name="Report">27</ref-type><contributors><authors><author>Wysocki, A.</author><author>Butler, M.</author><author>Kane, R. L.</author><author>Kane, R. A.</author><author>Shippee, T.</author><author>Sainfort, F.</author></authors></contributors><titles><title>Long-Term Care for Older Adults: A Review of Home and Community-Based Services Versus Institutional Care</title><secondary-title>Effective Health Care Program: Comparative Effectiveness Review</secondary-title></titles><volume>81</volume><dates><year>2012</year><pub-dates><date>Nov</date></pub-dates></dates><pub-location>Rockville, MD</pub-location><publisher>Agency for Healthcare Research and Quality</publisher><accession-num>23256217</accession-num><urls></urls><language>eng</language></record></Cite></EndNote>(Wysocki et al., 2012) compared LTC for older adults delivered through HCBS with care provided in NHs by evaluating (1) the characteristics of older adults served through HCBS and in NHs; (2) the impact of HCBS and NH care on outcome trajectories of older adults; and (3) the per person costs of HCBS and NH care, costs for other services such as acute care. They reviewed RCTs and observational studies that directly compared LTC for older adults (age ≥60) served through HCBS and in NHs and published between 1995-March 2012, in English, and in United States and other economically developed countries with well-established health and LTC systems. They also reviewed assisted living (AL), which is not included in the current report’s review. They compared and qualitatively synthesized the characteristics of LTC recipients and the impact of the setting on outcome trajectories for physical function, cognition, mental health, mortality, use of acute care services, harms, and costs. They also assessed the risk of bias (i.e., study’s ability to achieve good internal validity, causal explanation) and graded the overall strength of evidence for each examined outcome based on risks of bias, consistency of finding across studies, directness (presence of single, direct link between the intervention and outcome), and precision (certainty about an effect estimate of a given outcome).Key FindingsThey identified 42 relevant studies (37 peer reviewed, 5 grey literature) but none was RCT. Of the 37 peer-reviewed articles, 22 evaluated recipient characteristics at a specific time, and 15 analyzed outcome trajectories over time (of which 14 used longitudinal design). On average, NH residents had more limitations in physical and cognitive function than both HCBS recipients and AL residents, but differences in severity levels of mental health and clinical status between groups were mixed. The 14 studies that compared the outcome trajectories of HCBS recipients or AL residents with NH residents over time had a high risk of bias, resulting in low or insufficient evidence for all outcomes examined. In comparing AL with NH, low-strength evidence suggested no differences in outcomes for physical function, cognition, mental health, and mortality. In comparing HCBS with NHs, low-strength evidence suggested that HCBS recipients experienced higher rates of some harms while NH residents experienced higher rates of other harms. Evidence was also insufficient for cost comparisons. The nine studies included in this review that compared HCBS with NH are reviewed under the Peer-Review Articles section of the report PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5Eb3R5PC9BdXRob3I+PFllYXI+MjAxMDwvWWVhcj48UmVj
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ADDIN EN.CITE.DATA (Doty, Cohen, Miller, & Shi, 2010; Florida Department of Elder Affairs, 2011; Marek et al., 2005; Mehdizadeh, May 2007; J. S. Miller, Shi, & Cohen, 2008; S. L. Mitchell et al., 2004; Rigler, Perera, Jachna, Shireman, & Eng, 2004; Shireman & Rigler, 2004; Wieland et al., 2010). Wysocki and colleagues concluded that determining whether and how the delivery of LTC through HCBS versus NHs affects outcome trajectories of older adults is difficult due to scant evidence and the methodological limitations of studies reviewed. They also concluded that the supporting evidence from grey literature sources suggests that cost comparisons are typically incomplete and do not include many relevant sources, including other public program expenditures, individual expenditures, and family burden.Several key limitations of current literature included. First, most studies did not sufficiently describe the settings and services received. Although the nature of HCBS clients and services can vary widely, few studies provided complete descriptions of clients or services, making it difficult to compare between different modes of care. Second, none of the studies examined recipients’ or caregivers’ experiences of care and few examined how informal care may have affected the type, frequency, or intensity of formal care services or how it may have interacted with outcomes. Third, few studies had rigorous design (including no RCT among studies reviewed) to adequately address the problems of selection bias or attrition, complicating attempts to make indirect comparisons of the effects on trajectories. This lack of RCT was considered to be a major challenge given the authors’ assessment that use of propensity scores may be impeded by the large degree of heterogeneity, which reduces the accuracy of predictive equations and multivariate analyses would encounter similar problems whereas strong candidates for instrumental variables will be hard to identify. Fourth, lack of distinction between long-standing and new LTC users and following individuals across different providers or settings over time is another major issue. Fewstudies used an admission cohort although outcomes may differ for newcomers to the LTC system compared with those who have lived with limitations or received services for a long period of time. Moreover, follow-up times for tracing outcomes of interest were often short. Fifth, most studies were not explicit about the composition of the people included within each group especially the studies examining post-acute care. Although post-acute care typicallylasts less than 30 days and therefore, those with post-acute care experience may have different characteristics and preferences from LTC users. Sixth, the variation in outcome measures and data collection used across studies made it difficult to compare results. Moreover, there was a concern related to ceiling or floor effect is that HCBS recipients and NH residents may have different starting points for their respective trajectories. Given their greater level of disability at the outset, NH residents may have less opportunity to decline and may show little change in the typical measures used. Peer-Review Articles DOMAIN: Beneficiary Outcomes - Health, Function, Hospitalization, Mortality, End-of-life, Adverse Medication Use(Konetzka, Karon, & Potter, 2012) (outcome areas: hospital admission) Purpose/Research Question(s): To describe the U.S. population that uses HCBS in terms of demographic and health related attributes and to assess one important dimension of their health outcomes: potentially avoidable hospital admissions.Overall Design: Retrospective analysis of Medicaid service users in 2005. Sample/Data Collection: Used the Medicaid Analytic eXtract dataset which was merged with Medicare Provider Analysis and Review files from all fifty states and the District of Columbia. Analysis: Defined HCBS users as recipients who gave any indication that they used or planned to use these services who were categorized into four groups: IR/DD, serious mental illness, 65 and older frail, and younger users with physical disabilities. Defined potentially avoidable hospitalization using composite measures developed and validated building on existing AHRQ Prevention Quality Indicators. However, these measures were not risk adjusted. Results: They found that in 2005 there were 2.2 million users of Medicaid home and community-based services-almost 4 % of the total Medicaid population-and that two-thirds of these users were dually eligible for Medicare and Medicaid. Users of home and community-based services were particularly vulnerable to avoidable hospital admissions, compared to the full Medicaid (twice more likely) and US populations. These hospitalizations occur at substantial cost to public payers (estimated as 3 billion in annual Medicare and Medicaid expenditures). Limitations: Use of cross-sectional, unadjusted data; thus need more rigorous analysis to control for confounding and examine pathways. Future studies should examine and control for variation within and between states, especially whether more extensive or more supportive services are associated with lower rates of hospitalization. (Marek et al., 2005) (outcome areas: health/function) Purpose/Research Question(s): To compare clinical outcomes between older adults who resided in NHs and a group of similarly matched older adults who received services in Aging in Place (AIP) program (a community-based, long-term care program consisting of nurse coordination of the HCBS program and Medicare home health services). Overall Design: Quasi experimental, using an individually matched group of NH residents for comparison. Sample/Data Collection: A total of 78 AIP participants were matched with 78 NH residents on admission period, activities of daily living (ADLs), cognitive status, and age. The Minimum Data Set (MDS) was collected on the AIP group at admission and every 6 months over a 30-month period.Analysis: The clinical outcomes were ADLs, cognitive function, depression, incontinence, and pressure ulcers. Cognition was measured by the MDS Cognitive Performance Scale (CPS), ADLs by the sum of 5 MDS ADL items, depression by the MDS-Depression Rating Scale, and incontinence by rating on 2 MDS items related to urinary continence. Variables included in the matching strategy were age, AIP enrollment date and NH admission date, ADLs, and cognitive function. The NH admission date, ADLs, and cognitive function were derived from the MDS. The Cochran-Mantel-Haenszel method was used to test the association between the AIP intervention and clinical outcomes.Results: The AIP group clinical outcomes were better at a statistically significant level (less than .05) for the following outcomes: (a) cognition at 6, 12, and 18 months (p =.00); (b) depression at 6 and 12 months (p =.00); (c) ADL at 6 (p =.02), 12 (p =.04), and 24 (p =.00) months; and (d) incontinence at 24 (p =.02) months. In all 4 outcome measures, the AIP group stabilized or improved outcome scores whereas the NH group's outcome scores deteriorated. Limitations: Lack of RCT design, convenience sample.(Muramatsu, Hoyem, Yin, & Campbell, 2008) (outcome areas: nursing home admission/place of death) Purpose/Research Question(s): To examine whether states' spending on home- and community-based services (HCBS) affects place of death, taking into consideration county health care resources and individuals' family, sociodemographic, and health factors. Specifically, examined whether states' HCBS spending would delay or prevent end-of-life nursing home admission.Overall Design: Secondary data analysis of exit interview data from respondents in the Health and Retirement Study.Sample/Data Collection: Used exit interview data from respondents in the Health and Retirement Study born in 1923 or earlier who died between 1993 and 2002 (final analytic sample N =3,320), this is a nationally representative sample in the U.S. Analysis: Discrete-time survival analysis using time-fixed and time-varying covariates of the risk of end-of-life nursing home relocation and logistic regression analysis to investigate the HCBS effects on place of death separately for those who relocated to a nursing home and those who remained in the community. State commitment to HCBS was measured by two variables: total HCBS expenditures divided by the 65+ population and percentage of LTC expenditures going to HCBS rather than nursing homes. Data sources to develop these 2 variables are: Medicaid data (home health, personal care, nursing home and HCBS waiver), Older Americans Act, Social Services Block Grant, State source programs, US Census data. Results: Of the total sample of N =3,320, approximately one-quarter died at home, another quarter in a nursing home, and the rest in hospitals, hospice, and other location. The analytic sample consisted of 2528 (1615 community and 913 nursing home) residents from 36 states, after excluding those who died in hospice or other unspecified places (n =301), cases with missing or inconsistent state identifiers (n =272), those who moved out of the area since the interview before death (n =124), and those with missing data for specific variables (n =95). Higher state HCBS was associated with lower risk of nursing home relocation, regardless of state HCBS measures and county-level controls. Controlling for individual level characteristics, higher HCBS expenditure was associated with lower likelihood of EOL nursing home placement, especially among people who had Medicaid. When measured in HCBS expenditures per 65+, state HCBS had significant main effects and interaction with Medicaid. The significant interaction indicated differential HCBS effects: doubling per-capita HCBS expenditures (a 100% increase) would result in a 25% reduction in the risk of nursing home relocation. For those without Medicaid, the effect (-0.0191) was not statistically significant. When measured in the percentage of LTC expenditures, state HCBS had significant main effects but there was no statistically significant interaction effect. State HCBS expenditures were not significantly associated with place of death, regardless of the use of an alternative HCBS measure (percentage of LTC expenditures).Limitations: Only financial aspect of the state policies was incorporated in the analysis (but not other policy or cultural factors that may facilitate or inhibit HCBS support). Other nursing home characteristics or EOL care needs care not examined. The sample did not include all 50 states. This study used a longitudinal, observation study design, thus, limited ability to control for selection bias. (Muramatsu, Yin, & Hedeker, 2010) (outcome areas: health/function ) Purpose/Research Question(s): Drawing on stress theory, authors tested two hypotheses: (1) informal caregiving availability would be associated with lower depression among older adults, and the association would be stronger among those with higher functional disability and those with recent functional declines; and (2) living in a state that generously supports HCBS would protect older adults with functional limitations from depression and that such protective state effects would be larger for those without informal support. Overall Design: Secondary data analysis using HRS dataSample/Data Collection: Person-level data were drawn from files produced by the Rand Center for the Study of Aging supplemented by other public data files, such as “exit interview”, “tracker”, “other person”, helper”, and “region” files. A restricted data file containing state identifiers permitted us to link state-level data to the person-level data. Analytic sample consisted of 6,535 respondents representing 18,770 observations. Analysis: Multi-level mixed-effects logistic regression analysis, involving three levels of data: states, persons, and time points (<=5) using Health and Retirement Study (HRS) data for 1993, 1995, 1998, 2000, and 2002 from cohorts born in 1923 or earlier. Results: Availability of help with functional limitations from non-spouse family/friends was strongly associated with lower depression (p≤.01), whereas current receipt of help from their spouse was marginally associated with higher depression (p≤.10). State HCBS support had no statistically significant main effects. They found significant two-way interactions between ADL/IADL limitations and state HCBS support indicating that those with systematically higher levels of ADL/IADL limitations were more likely to be depressed and that they benefited more from living in a state with higher HCBS expenditures. Those who recently experienced more dramatic declines in daily living functions benefited even more from living in a state with higher HCBS support. Three-way interactions among functional limitations, state HCBS and informal support availability - found significant interaction effects among state HCBS, informal help and underlying cognitive limitations. People with higher levels of cognitive problems had higher rates of depression. For those with non-spouse family help, state HCBS support did not make much difference in the relationship between cognitive problems and depression. Higher state HCBS was associated with lower depression; among those with higher cognitive function, state HCBS support had no or positive relationships with depression. Living in a state that generously supports HCBS would protect older adults from stressful effects of severe cognitive problems, when no informal support was available. Limitations: Limitations include: attrition at later data measurement points, lack of direct assessment of depression among those with severe cognitive impairment (proxy report), and exclusion of certain states limiting generalizability. (Rigler, Perera, Jachna, Shireman, & Eng, 2004) (outcome areas: harmful medication use) Purpose/Research Question(s): To examine the relationship between disease burden and inappropriate medication use in 3 groups of frail elders - community-dwelling, persons receiving HCBS, and nursing home residents adjusting for demographic and clinical differences. Overall Design: Retrospective analyses of Medicaid claims data from May 2000 through April 2001 of Kansas Medicaid beneficiaries.Sample/Data Collection: The final sample included 3185 persons in the 3 cohorts (1163 community-dwelling, 858 frail elders receiving HCBS, 1164 nursing home residents). Demographic, clinical, and medication data were extracted from the Medicaid claims data. Unconditionally inappropriate medications were identified using the 1997 Beers criteria. The Cumulative Illness Rating Scale for Geriatrics was used to calculate the disease burden sum, classified as 0 or 1, 2 or 3, 4 or 5, or > or =6 disease categories. Analysis: Odds ratios for inappropriate medication use at each level of disease burden in each cohort were derived using multivariable models adjusted for demographic and clinical factors, including overall level of medication use.Results: Inappropriate medication use was determined to have occurred in 21%, 48%, and 38% of the respective cohorts (community-dwelling, persons receiving HCBS or frail elderly, and nursing home residents) and was highest in frail elder cohort members with the greatest disease burden (61%).(Mitchell, Morris, Park, & Fries, 2004) (outcome areas: mortality, end-of-life care) Purpose/Research Question(s): To describe and compare the end-of-life experience of persons dying with advanced dementia in the nursing home and home care settings.Overall Design: Retrospective cohort study.Sample/Data Collection: Persons 65 years or older with advanced dementia who died within 1 year of admission to either a nursing home in Michigan between July 1, 1998 until December 31, 2000 (n =2730), or the state's publicly funded home and community-based services from October 1, 1998 until December 31, 2001 (n =290). Data were derived from the Minimum Data Set (MDS)-Nursing home Version 2.0 for the institutionalized sample, and the MDS-Home Care for the community-based sample. Variables from the MDS assessment completed within 180 days of death were used to describe the end-of-life experiences of these two groups.Analysis: Logistic regression.Results: Nursing home residents dying with advanced dementia were older, had greater functional impairment, and more behavior problems compared to home care clients. Few subjects in the nursing home (10.3%) and home care (15.6%) cohorts were perceived to have less than 6 months to live. Only 5.7% of nursing home residents and 10.7% home care clients were referred to hospice. Hospitalizations were frequent: nursing home, 43.7%; home care, 31.5%. Pain and shortness of breath were common in both settings. End-of-life variables independently associated with nursing home versus home care included: hospice (adjusted odds ratio [AOR] 0.26, 95% confidence interval [CI], 0.16-0.43), life expectancy less than 6 months (AOR 0.31; 95% CI, 0.20-0.48), advance directives (AOR, 1.48; 95% CI, 1.11-1.96), pain (AOR, 0.38; 95% CI, 0.29-0.50), shortness of breath (AOR 0.20; 95% CI (0.13-0.28), and oxygen therapy (AOR, 2.47; 95% CI, 1.51-4.05). Limitations: The study examined experiences in a care setting, not necessarily at the location of death; potential inaccuracy in MDS data, limited ability to adjust for selection bias between home care and nursing home, and limited generalizability (data are from the state of Michigan). (Wieland, Boland, Baskins, & Kinosian, 2010) (outcome areas: mortality) Purpose/Research Question(s): To compare long-term survival among frail elders requiring LTC, specifically among those enrolled in an aged and disabled waiver program, PACE, and nursing homes (NHs).Overall Design: Retrospective cohort analysis over 5 year observation window. Sample/Data Collection: 2,040 entrants into one of the three programs, an aged and disabled waiver program, PACE, and nursing homes (NHs) in South Carolina. Analysis: Kaplan-Meier curves. To address cohort risk imbalance, they employed an established mortality risk index, which showed external validity in waiver, PACE, and NH cohorts (log-rank tests =105.42, 28.72, and 52.23, respectively, all p < .001; c-statistics =.67, .58, .65, p < .001). Results: Compared with waiver (n =1,018) and NH (n =468) admissions, PACE participants (n =554) were older, more cognitively impaired, and had intermediate activities of daily living dependency. PACE mortality risk (72.6% high-to-intermediate) was greater than in waiver (58.8%), and similar to NH (71.6%). Median NH survival was 2.3 years. Median PACE survival was 4.2 years versus 3.5 in waiver (unstratified, log rank =.394; p =.53), but accounting for risk, PACE's advantage is significant (log rank =5.941 (1); p =.015). Compared to waiver, higher risk admissions to PACE were most likely to benefit (moderate: PACE median survival =4.7 years vs. waiver 3.4; high risk: 3.0 vs. 2.0). Long-term outcomes of LTC alternatives warrant greater research and policy attention.Limitations: Retrospective design with limited ability to control for selection bias and limited generalizability.DOMAIN: Nursing Home AdmissionPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5IYWhuPC9BdXRob3I+PFllYXI+MjAxMTwvWWVhcj48UmVj
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ADDIN EN.CITE.DATA (Hahn et al., 2011)Purpose/Research Question(s): The goal of the study was to examine the relationship between county-level HCBS waiver dollars and the number of “Low-Care” NH residents. The main question was if increased Medicaid HCBS waiver expenditure decreased the likelihood of low-care persons to stay in NHs (i.e., low care persons to stay in community).Overall Design: Cross-sectional, secondary data analysis using the following data sources: DOEA - HCBS wavier dollars per county for 2007 calendar year data, OSCAR (facility characteristics), MDS (resident characteristics), and ARF (county level market characteristics)Sample/Data Collection: Florida NH facilities (N=653 NHs)Analysis: Outcome variable was percent of low-care residents defined as in Thomas & Mor (2012). Main predictor variable were average per enrollee HCBS waiver dollars for each county (denominator=enrollees); and six waivers: (a) Aged and Disabled Adult Services, (b) Adult Day Health Care, (c) Assisted Living for the Elderly, (d) Channeling for the Frail Elder, (e) Nursing Home Diversion, and (f) Alzheimer’s Disease. However, Adult Day Health Care was excluded because data were not available for that year. Covariates included facility level characteristics – percent of male residents, Medicaid beneficiaries, Medicare beneficiaries, occupancy rate, chain membership, for-profit status, number of total beds, HHI index, and resident age; and county level characteristics – number of home health agencies per 1,000 people aged 65 and older, number of assisted living facility beds, and hospital beds. HLM analysis was used. Results: Descriptive findings included: average Medicaid NH reimbursement per resident was 178 dollars per day (63,642 dollars per year); average Medicaid HCBS dollars per enrollee was 1163 dollars per month (13.956 dollars per year); percent of low-care resident was 8%.Multivariate analysis findings included: (1) the role of cost of HCBS was significant, additional 10,000 dollars on HCBS waiver per enrollee was associated with 3.5% decrease in low-care residents per county (p=.03). This translates into the following: additional 10,000 dollars on HCBS waiver per enrollee equaled reduction of 3 to 4 low-care residents in 100-bed NHs. This also meant that 10,000 dollars additional multiplied by 33,824 HCBS beneficiaries in 2007, which equaled to 338 million dollars as additional expenditure, and 1,380 fewer NH residents multiplied by 62,251 dollars, which meant $90 million dollars saving. Thus, HCBS waiver did not translate into total saving. Influence of other facility level covariates included: % Medicaid (+), occupancy rate (ns), % Medicare (-), chain membership (ns), for-profit status (-), number of total beds (ns), HHI index (ns), % of male (+), and age (-). None of the county level covariates were significant. Overall, HCBS expenditure increase reduced the percentage of low-care nursing home residents. However, the overall estimates suggest that the saving from reducing low-care nursing home residents do not offset the dollar increase in HCBS expenditure. Limitations: Limitations include: (1) cross-sectional study looking at Florida, limited internal or external validity; (2) assumptions - estimates suggest widespread increase in HCBS but does not account for those who may be receiving multiple services, and these estimates assume that all individuals would require increased spending on HCBS; but these confounders could not be accounted for in cross sectional data; (3) use of the wavier enrollees as denominator instead of other alternatives (e.g., those who were eligible but not enrolled or total number of 65+); and (4) lack of a specific level of cognitive decline as an exclusion criteria BUT in general, low-care residents have significantly better cognitive functioning compared with other NH residents (73% of the low-care residents in that study had either little or no cognitive impairment). (Muramatsu et al., 2007) (outcome areas: nursing home admission) Purpose/Research Question(s): To assess association between states' generosity in providing HCBS affects the risk of nursing home admission among older Americans and how family availability moderates such effects.Overall Design: Secondary data analysis of exit interview data from respondents in the Health and Retirement Study. Andersen’s behavioral model of health services use was used as a theoretical framework.Sample/Data Collection: Used Health and Retirement Study panel data from respondents born in 1923 or earlier, the final analytic sample included 5,224 respondents.Analysis: Discrete time survival analysis of first long-term (90 or more days) nursing home admissions that occurred between 1995 and 2002.Results: State HCBS effects were conditional on child availability among older Americans. Living in a state with higher HCBS expenditures was associated with lower risk of nursing home admission among childless seniors (p <.01). However, the association was not statistically significant among seniors with living children. Doubling state HCBS expenditures per person aged 65 or older would reduce the risk of nursing home admission among childless seniors by 35%. Limitations: Similar limitations as Muramatsu, Hoyem, Yin, & Campbell, 2009.(Muramatsu, Hoyem, Yin, & Campbell, 2008) (outcome areas: nursing home admission/place of death) Purpose/Research Question(s): To examine whether states' spending on home- and community-based services (HCBS) affects place of death, taking into consideration county health care resources and individuals' family, sociodemographic, and health factors. Specifically, the study examined whether states' HCBS spending would delay or prevent end-of-life nursing home admission.Overall Design: Secondary data analysis of exit interview data from respondents in the Health and Retirement Study.Sample/Data Collection: Used exit interview data from respondents in the Health and Retirement Study born in 1923 or earlier who died between 1993 and 2002 (final analytic sample N=3,320), this is a nationally representative sample in the U.S. Analysis: Discrete-time survival analysis using time-fixed and time-varying covariates of the risk of end-of-life nursing home relocation and logistic regression analysis to investigate the HCBS effects on place of death separately for those who relocated to a nursing home and those who remained in the community. State commitment to HCBS was measured by two variables: total HCBS expenditures divided by the 65+ population and percentage of LTC expenditures going to HCBS rather than nursing homes. Data sources to develop these 2 variables are: Medicaid data (home health, personal care, nursing home and HCBS waiver), Older Americans Act, Social Services Block Grant, state source programs, and US Census data. Results: Of the total sample of N =3,320, approximately one-quarter died at home, another quarter in a nursing home, and the rest in hospitals, hospice, and other location. The analytic sample consisted of 2528 (1615 community and 913 nursing home) residents from 36 states, after excluding those who died in hospice or other unspecified places (n =301), cases with missing or inconsistent state identifiers (n=272), those who moved out of the area since the interview before death (n=124), and those with missing data for specific variables (n=95). Higher state HCBS was associated with lower risk of nursing home relocation, regardless of state HCBS measures and county-level controls. Controlling for individual level characteristics, higher HCBS expenditure was associated with lower likelihood of EOL nursing home placement, especially among people who had Medicaid. When measured in HCBS expenditures per 65+, state HCBS had significant main effects and interaction with Medicaid. The significant interaction indicated differential HCBS effects: doubling per-capita HCBS expenditures (a 100% increase) would result in a 25% reduction in the risk of nursing home relocation. For those without Medicaid, the effect was not statistically significant. When measured in the percentage of LTC expenditures, state HCBS had significant main effects but there was no statistically significant interaction effect. State HCBS expenditures were not significantly associated with place of death, regardless of the use of an alternative HCBS measure (percentage of LTC expenditures).Limitations: Only financial aspect of the state policies was incorporated in the analysis (but not other policy or cultural factors that may facilitate or inhibit HCBS support). Other nursing home characteristics or EOL care needs care not examined. The sample did not include all 50 states. This study used a longitudinal, observation study design, thus, limited ability to control for selection bias. (Miller, 2011) (outcome areas: nursing home admission) Purpose/Research Question(s): To examine state-level rates of nursing home use for the period from 2000 to 2007, and used multivariate fixed-effects models to examine associations between state sociodemographic, economic, supply, and programmatic characteristics and rates of use.Overall Design: Retrospective secondary data analysis. Sample/Data Collection: Data sources included CMS Nursing Home Data Compendium, Medicaid LTC expenditure data from Form 64 data compiled by Thomson Reuters, US Census data, CDC Behavioral Risk Factor Surveillance Survey, and CDC annual HIV/AIDS Surveillance Reports. Analysis: Outcome measures were nursing home use rates for the total population and by age group. Included independent/covariates were HCBS expenditure (state’s share of LTC dollars devoted to HCBS), per capita nursing home, home health agency, residential care bed supply, state income/wealth level. Used multivariate fixed-effects models. Results: Nursing home use declined among older adults (aged ≥65 years) in 36 states and the District of Columbia but increased among older working-age adults (aged 31-64 years) in all but 2 states. State characteristics associated with these trends differed by age group. Relatively greater state investment in Medicaid home- and community-based services coupled with reduced nursing home capacity was associated with reduced rates of nursing home care for adults aged 65 years and older. Limitations: No distinction between short-term or long-term nursing home admission. CDC data do not fully capture chronic condition/severity characteristics of community-dwelling individuals. Limited state policy variables are included in the analysis. ADDIN EN.CITE <EndNote><Cite><Author>Thomas</Author><Year>2013</Year><RecNum>150</RecNum><DisplayText>(Thomas, 2013)</DisplayText><record><rec-number>150</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">150</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Thomas, Kali S.</author></authors></contributors><titles><title>The Relationship Between Older Americans Act In-Home Services and Low-Care Residents in Nursing Homes</title><secondary-title>Journal of Aging and Health</secondary-title></titles><periodical><full-title>J Aging Health</full-title><abbr-1>Journal of aging and health</abbr-1></periodical><dates><year>2013</year><pub-dates><date>December 10, 2013</date></pub-dates></dates><urls><related-urls><url>;(Thomas, 2013)Purpose/Research Question(s): The goal of the study was to examine relationship between Older American Act (OAA) service dollars and rate of low-care NH residents. The main question is whether the increase in OAA service expenditure decreased the likelihood of low-care persons to stay in NHs (i.e., low care persons to stay in community).Overall Design: Longitudinal secondary data analysis using the following data sources - SPR (OAA expenditure data), OSCAR (facility characteristics), MDS (resident characteristics), ARF (county level market characteristics), and RHF (Medicare enrollment/claims data linked with MDS).Sample/Data Collection: U.S. NH facilities with N=145,648 facility-year observations from 16,030 free standing certified NHs in the U.S. during 2000-2009.Analysis: Facility fixed effects model using STATA and Huber-White robust variance estimators to adjust for within-state clustering over time with unit of analysis, facility-year. Outcome variable included percent of low-care residents defined as requiring no assistance in any of the 4 ADL (bed, toilet, transfer, eating) and do not belong to one of the two in RUG-III categories - special rehab or clinically complex. Main Predictor variables include OAA dollars adjusted to 2009 dollars, for 1000, 65+ people for six services (personal care, homemaker, chores, home delivered meals, adult day care, and case management). Covariates included facility characteristics including Medicaid, occupancy, skilled nursing days, HMO, and county characteristics including number of home health agencies per 1,000 65+, number of NH beds in the county. State characteristics included Medicaid dollars on HCBS and adjusted Medicaid payment rate. Results: OAA, specifically home delivered meals significantly reduce the % of low-care residents in each state controlling for other covariates. State expenditure for Medicaid HCBS waiver did not reduce the % of low-care residents. This is an important finding given that Hahn et al 2011 found that Medicaid waiver dollars in Florida was significantly associated with reduced % of low-care residents. Potential sources for the different findings include: Thomas & Mor (2012) is a longitudinal, national study whereas Hahn et al. (2011) study is cross-sectional for Florida only and also did not include OAA service variables in the analysis. Limitations: Assumption made in the study was that residents who do not require skilled clinical services or assistance meeting their ADLs could be sustained in the community. Future Research: test the assumption by conducting prospective study to follow people over time (e.g., percent discharged and readmitted, length of time from discharge to readmission). The study also did not distinguish between the types of low-care residents by Medicaid eligibility. Increased investment in OAA is more likely to affect the general population of older adults while increased investments in Medicaid funded HCBS are likely to only decrease the prevalence of low-care residents in NHs who are Medicaid or Medicaid LTC eligible. Therefore, future study should use a prospective study design to follow groups of low-care residents by eligibility type.The use of state reported expenditure data mean that there are possible problems with validity and consistency of the data from state to state [common potential problem with administrative data set use0. The use of older adults aged 65+ to adjust for OAA spending rather than the number of older adults aged 60+, for whom the federal dollars are allocated. However, census data only report projections for the aggregate numbers of 65+ in each year and OAA requires Title III programs to target or make it a priority to serve older adults with the greatest economic and social need]. The lack of a specific level of cognitive functioning as an exclusion criterion for low-care is another limitation. The future Research should use different criterion to determine the low-care vs. low disability residents (e.g., person with dementia may have low need for ADL but have memory/behavioral problems that make it difficult to be cared for in community care setting).DOMAIN: Cost (Eiken, Burwell, & Sredl, 2013) (outcome areas: cost) Purpose/Research Question(s): To test two aspects of the woodwork effect - (1) more people will use publicly funded services because publicly funded HCBS are more attractive, and (2) an increased number of HCBS users will increase the rate of overall public LTSS expenditures growth - using Medicaid LTSS data for 1999 thru 2007.Overall Design: Retrospective trend analysis using Medicaid LTSS data at the national level while adjusting for functional limitation and inflation. Sample/Data Collection: Medicaid LTSS beneficiaries from 1999 to 2007 in the U.S.Analysis: Adjust the increase in Medicaid LTSS beneficiaries to changes in the number of people with functional limitations (to determine if the increased number of people using HCBS reflect the changes in need or woodwork effect), and adjust Medicaid LTSS expenditures for inflation and number of people with functional limitations. Used the National Health Interview Survey estimates of adults in need of assistance with IADL and ADL, and used IADL limitation estimates to adjust the Medicaid LTSS beneficiary number. Data were adjusted for inflation using the Consumer Price Index for All Urban Consumers for all items. Results: The number of Medicaid LTSS beneficiaries increased at an annual rate of 0.7% controlling for the number of people with functional limitations. When adjusted for inflation, the Medicaid LTSS expenditures increased with an average of 4.0% per year from 1999 to 2009. When adjusted for both inflation and functional limitations, the Medicaid LTSS expenditures grew 1.8% per year. Authors conclude that the data do not provide strong evidence that the shift in Medicaid funding toward HCBS significantly increased or decreased overall Medicaid LTSS spending.Limitations: Medicaid LTSS beneficiary data include duplicate individuals, certain states provide services that other states do not provide, and data do not include the number of days the services were used, data accuracy is not uncertain. The functional impairment estimate is based on the general population while it is well known that Medicaid beneficiaries are in general more likely to have higher level of impairment. Further, lack of sophisticated, multivariate analysis controlling for individual/state level variables limits ability to draw any causal inference. (Kane et al., 2013) (outcome areas: utilization/cost) Purpose/Research Question(s): To assess change in numbers, expenditures, and case mix of nursing home residents as Medicaid investment in HCBS 1915(c) waivers increased in seven states (AR, FL, MN, NM, TX, VT, WA). Three research questions included: (1) how do the changes over time in HCBS correlate with changes in nursing home use?, (2) is an increase in HCBS associated with an increase in nursing home case mix by virtue of providing an alternative source of care for less dependent clients?, (3) how does the case mix of HCBS clients compare to that of nursing home residents? Overall Design: Retrospective cohort analysis using fee-for-service Medicaid LTSS beneficiary data from seven states (no managed care client data included in the analysis) between 2000 and 2005. Sample/Data Collection: The seven states provided Medicaid expenditure and utilization data from 2001 to 2005, including waiver and state plan utilization. The Minimum Data Set was used for nursing home residents. For three states (MN, FL, WA), community assessment data were also used.Analysis: Descriptive analysis (expenditure data were adjusted for inflation). Results: In six states, the number of nursing home clients decreased as the numbers of HCBS clients grew (exception was Florida). In most states, the number of additional waiver clients often greatly exceeded reductions in nursing home residents. Nursing home payments decreased moderately, but this decrease was offset by increases in HCBS waiver and state plan expenditures, leading to a net increase of 10% in LTSS expenditures from 2001 to 2005. Increases in waiver expenditures outpaced increases in waiver clients, indicating expansion of services on top of expansion in clients. States that showed substantial increases in HCBS showed only modest increases in nursing home case mix. The case mix for nursing home residents was more acute than that for HCBS users. Spending growth was greater for states offering limited noninstitutional services than for states with large, well-established noninstitutional programs. Authors concluded that the more acute case mix in nursing homes suggested that HCBS served some individuals who were previously cared for in nursing homes but many who were not. Authors called for more proactive strategies such as diversion. Expansion of HCBS appears to entail a short-term increase in spending, followed by a reduction in institutional spending and long-term cost savings. Limitations: Lack of more sophisticated, multivariate analysis limits ability to draw any causal inference. (Kaye, LaPlante, & Harrington, 2009) (outcome areas: cost) Purpose/Research Question(s): To test the woodwork effect hypothesis by examining aggregate cost instead of looking at cost per person served. Overall Design: Retrospective, longitudinal analysis of data on LTSS expenditures at the national level.Sample/Data Collection: Analysis of the CMS data from all states on LTSS expenditure from 1995 thru 2005. Analysis: Calculated per capita LTSS expenditure for each state (dollars/population estimate) adjusted for inflation for medical costs in addition to average income and need for LTSS. Analyzed data for Mental Retardation/Developmental Disability group separately from people with other types of disabilities. Results: Between 1995 and 2005, the HCBS grew faster than inflation (56.7% vs. 110%), nursing home use increased 3.4% in low HCBS states (defined as states that spent less than the median proportion of total 2005 LTC spending devoted to HCBS), while NH spending decreased by 15.3% in high HCBS areas. LTSS expenditures, on average across states, grew by 7.3% (with a large decrease in 2003-2005) while it decreased by 7.9% in the established HCBS states (states that were pioneers in offering extensive noninstitutional services and have experienced stabilized rate in HCBS expansion). Expanding states experienced growth of 24.2% in their expenditures between the periods. Further examination showed that high HCBS cost is seen in the first 2 years, then, cost is stabilized and declines over time. Nursing home cost decline was observed after 3 years of expansion. Limitations: Limitations include (1) incomplete or inaccurate reporting of expenditures according to the date of payment (not date of provision of services); (2) lack of data on services and expenditure data on services provided under capitated managed programs (mostly for Arizona which was excluded from the analysis) or a small number of programs that target frail elderly that are distinct from other services (mostly Texas and these programs were excluded from analysis); and (3) some missing or incomplete waiver data for particular waivers or states, which were replaced with their average numbers. (Kitchener, Ng, Miller, & Harrington, 2006 (outcome areas: cost) Purpose/Research Question(s): To report the comparative cost of Medicaid HCBS and institutional care, specifically three per participant expenditure comparisons between Medicaid HCBS waivers and institutional care: (1) program expenditure (waivers vs. the comparable level of institutional provision); (2) total Medicaid expenditure (program plus other Medicaid expenditure such as physician, and prescription drug costs); and (3) estimated total public expenditure (Medicaid expenditures plus state and federal supplemental- income payments, SSI/SSP).Overall Design: Retrospective analysis for one calendar year at the national level. Sample/Data Collection: Secondary data analysis of 2002 CMS data on to present three per participant expenditure comparisons between Medicaid HCBS waivers (which require that participants have an institutional level of care need). Data include information on individual Medicaid 1915(c) HCBS waiver programs as the unit of analysis, with annual data analyzed for the most recent reported year (2002). The state of Arizona is excluded from this study because it operates its Medicaid LTC program under a unique statewide 1115 demonstration waiver.Analysis: Descriptive analysis.Results: This analysis estimates that when compared with Medicaid institutional care in 2002, HCBS waivers produced a national average public expenditure saving of 43,947 dollars per participant. The national average per-participant nursing facility waiver program expenditures of 15,784 dollars were 63% lower than the comparable average per-participant nursing facility expenditures of 42,292 dollars. Reported per-participant program expenditures are lower for Medicaid waivers serving every target group when compared with state-estimated program expenditures for institutions at the same level of care. When estimated the room and board costs from SSI/SSP for waiver participants, the national annual average total public expenditures on each waiver participant was 42,713 dollars in 2002. Of this total, Medicaid paid 35,434 dollars (83%) per-participant in program and other expenditures, while other public sources (SSI/SSP) are estimated to have paid 7,279 dollars (17 %). In 2002, Medicaid HCBS waivers at every level of care produced estimated public expenditure savings (at varying levels) for individual participants when compared with state estimates of comparable institutional provision.Limitations: Limitations include: (1) potential inaccuracy of data reported on CMS Form 372 (source of the data used for the current study, but they are not the actual claims data by state); (2) variability in the required eligibility and need criteria (i.e., level of need) which has not been accounted for in the analysis; (3) use of liberal proxies of “other state and sub-state expenditures” on waiver participants; (4) not examining the informal cost of care provided to both waiver and institutional participants; and (5) this is not a comprehensive cost effectiveness evaluation because the study does not examine to what extent to which people who would otherwise go into an institution was actually using HCBS and the current study is not examining the woodwork effect. (Mitchell, Salmon, Polivka, & Soberon-Ferrer, 2006) (outcome areas: access/utilization & cost) Purpose/Research Question(s): To compare inpatient days, nursing home days, and total Medicaid claims for five HCBS programs for in-home and assisted living services in Florida (Aged and Disabled Adult - only FFS program, Assisted Living for the Elderly, Channeling, Nursing Home Diversion, and Frail Elder Project). Overall Design: Retrospective, longitudinal cohort study of Medicaid enrollees in Florida aged 60 and older, who were enrolled for the first time in any of five Medicaid HCBS programs and who had at least one assessment (N=6,014) over 3 year-observation window.Sample/Data Collection: A single cohort of Medicaid enrollees in Florida aged 60 and older, who were enrolled for the first time in any of five Medicaid HCBS programs and who had at least one assessment (N=6,014). Sources of data included Medicaid claims, and HCBS assessment datasets (CARES and CIRTS). Analysis: Used two-stage probit regression and ordinary least squares regression in order to test the independent effects of explanatory variables on outcomes and cost. Key outcome measures were per member per month (PMPM) inpatient and NH days as well as PMPM inpatient claims and total Medicaid claims. Predictor and covariate variables included demographic characteristics, ADL, IADL, caregiver availability, chronic conditions, service areas, Medicaid bed occupancy rate for nursing homes. Results: After controlling for differences in frailty, chronic health conditions, presence of dementia, and available caregiver, they found that Medicaid HCBS programs had a differential effect on hospital and nursing home utilization and cost. For example, NH Diversion (NHD) program had the highest cost with poor outcomes (highest total Medicaid claims and highest rate of inpatient days) while Aged and Disabled Adult (ADA) program had better outcomes but with higher NH days. Frailty-adjusted (by comparing beneficiaries who met diversion criteria) comparisons across five programs showed that Nursing Home Diversion program had highest average number of inpatient days (14.6) compared with the lowest number by Channeling (1.8 days), ADA program had highest nursing home days (116.6) compared with lowest number by Frail Elder Project (62.6 days), and NHD had the highest annual claims rate of $56,214 dollars compared to the lowest by Frail Elder Project ($34,186 dollars). Limitations: Missing cases, exclusion of NH enrollees, limited ability to control for selection bias, and limited generalizability. (Shapiro, Loh, & Mitchell, 2011) (outcome areas: cost) Purpose/Research Question(s): To estimate Medicaid cost-savings of selected five HCBS programs in the State of Florida. Used Medicaid claims and CIRTS data for SFY 2000-2005 (five programs included: Alzheimer’s Disease Initiative (ADI), Community Care for the Elderly (CCE), Home Care for the Elderly (HCE), Medicaid Waiver (MW, also known as the Aged & Disabled Adult Waiver), and Older Americans Act IIIB (OA3B).Overall Design: Retrospective cohort study. Sample/Data Collection: Analysis: Used a propensity score matching procedure to simulate random assignment of seniors into matched treatment (HCBS users) and comparison (waitlist) groups. Examined Medicaid expenditures in outpatient, inpatient, prescription drugs, nursing home and other areas. Controlled for demographic characteristics, ADL, IADL, and mental health status. Analyses were conducted using a linear panel regression on the full sample, controlling for individual heterogeneity and year-specific changes.Results: Some HCBS programs in Florida show evidence of Medicaid cost-savings. Median Medicaid cost-savings varied widely, ranging from a cost overage of US$277 dollars PMPM for the MW to a cost-savings of US$229 dollars PMPM for ADI. ADI, CCE, and HCE produced median cost savings while MW and OA3B produced cost overages. HCBS programs in Florida show evidence of Medicaid cost-savings mainly from the reduction in use of Medicaid nursing home expenses. There is little evidence of cost-savings for inpatient care, outpatient care, physician services, prescription drugs, long-term home health care, transportation, and other Medicaid claims. Small total Medicaid cost-savings in all cost items examined for the CCE program, insignificant savings for ADI, MW, and OA3B programs, and an increase in costs for the HCE program. On examining individual cost items separately, the Medicaid cost-savings from HCBS service use mainly comes from substantial nursing home cost-savings.(Shireman & Rigler, 2004) (outcome areas: cost) Purpose/Research Question(s): To examine relative health care utilization patterns, and estimate the difference in Medicaid expenditures for frail elders receiving HCBS vs. nursing home residents in Kansas. Overall Design: Retrospective cohort analysis. Data Collection/Sample: Medicaid claims data. Results: After adjusting for key demographic and clinical variables, mean monthly expenditures were $1,281 dollars lower for the FE cohort. Since NH and FE populations are dissimilar, these care options may not be easily interchangeable at the individual level.State Evaluation Report ADDIN EN.CITE <EndNote><Cite AuthorYear="1"><Author>APS Healthcare</Author><Year>2005</Year><RecNum>118</RecNum><DisplayText>APS Healthcare (2005)</DisplayText><record><rec-number>118</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">118</key></foreign-keys><ref-type name="Report">27</ref-type><contributors><authors><author>APS Healthcare,</author></authors></contributors><titles><title>Family Care Independent Assessment: An Evaluation of Access, Quality and Cost Effectiveness for Calendar Year 2003 - 2004</title><short-title>Family Care Independent Assessment</short-title></titles><dates><year>2005</year></dates><urls></urls></record></Cite></EndNote>APS Healthcare (2005) Purpose/Research Question(s): To evaluate cost effectiveness of the Wisconsin Family Care program. Overall Design: Quasi-experimental design. Although randomization was not used to control for selection bias, a control group was matched to the experimental group by using propensity score matching and additional matching of the two groups across a number of descriptive measures: average age, gender, target group (developmentally disabled, physically disabled, frail elderly), institutional residents, residents of Milwaukee County, Medicaid LTC waiver status (before Family Care enrollment), Medicare eligibility, and average scores for CDPS, FSIS, and RUCA.Analysis: Two statistical adjustment techniques were used to further control for individual variation and population composition heterogeneity, proportional weighting, and multiple regression analysis (e.g., path analysis for cost-effectiveness analysis, two-level hierarchical linear models to account for individual level, and county level variations). They examined utilization, quality of care, and cost-effectiveness by comparing the two groups over a 2 year period. Covariates that were controlled for included functional status, illness burden, geographic area of residence, institutional residence, last year of life and background characteristics such as gender and target group membership. Results: Overall findings of the evaluation were favorable in terms of the program’s impact on cost effectiveness. The multilevel analysis found that average individual monthly Medicaid costs for members of the four non-Milwaukee Family Care counties were 452 dollars lower than the comparison group and for frail elderly members of the Milwaukee County Care Management Organization (CMO) were 55 dollars lower than those for the comparison group over the two-year period of analysis. The path analysis revealed that Family Care produces Medicaid savings both directly by controlling service costs and indirectly by favorably affecting Family Care members. It was also found that Family Care reduced health related costs both directly and indirectly. Regarding specific types of healthcare cost, during the study period, the Milwaukee County frail elder members' home health care costs increase 393%. The initial average individual monthly cost difference for personal care services among Milwaukee County frail elder members relative to the comparison group rose from 62 dollars at baseline to 416 dollars by the end of the study. Outpatient hospital costs for Family Care members in the Milwaukee County elderly and non-Milwaukee County developmentally disability groups declined over the study period so that these Family Care groups ended the study with lower average individual monthly outpatient hospital costs (10 dollars and 17 dollars) than the comparison groups (12 dollars and 29 dollars). Inpatient hospital costs significantly decreased for the elderly in both the non- Milwaukee CMO counties and the Milwaukee County CMO. At baseline, these two study groups exceeded the comparison group by 5 dollars and 98 dollars, respectively, in average individual monthly inpatient hospital costs, but significantly decreased over the study period and were 65 dollars and 18 dollars less than the comparison group by the end of the study. Inpatient hospital costs and utilization significantly decreased over the study period for the individuals in the non-Milwaukee CMO and by the end of the study were 59 dollars less in average monthly inpatient hospital costs than the comparison group. Limitations: Lack of randomization. OPPAGA REPORT 2010Purpose/Research Question(s): To compare effectiveness of the Florida’s three HCBS waiver programs in NH delay and cost.Overall Design: Retrospective analysis of Florida Medicaid claims, DOEA’s general revenue expenditures, CARES, and Milliman Inc.'s data on provider data on services delivered within the NHD waiver program.Sample/Data Collection: For both outcomes (NH placement delay and cost), included were who were 65 years of age or older, eligible for Medicaid and Medicare Parts A and B, met a nursing home level of care, and met at least one of the requirements regarding ADL/dementia diagnosis/needing help with medication. For NH delay, examined cross-section of newly enrolled recipients during January 2005-June 2008, for 42 month period; and for the cost analysis, included were newly enrolled recipients between January 2005-June 2006, following them for 24 months.Analysis: Outcome variables were an extended nursing home stay defined as receiving NH care for at least 30 days within two months and total state cost per member per month. Main predictor variable was three waiver programs - Aged and Disabled Adult; Assisted Living for the Elderly, and Nursing Home Diversion. Covariates included: functional impairments (number of primary and instrumental activities of daily living requiring some or total assistance), health status (number of chronic health conditions and whether the person has bed sores, dementia, or is incontinent), cognitive functioning (inability to perform a simple cognitive task), caregiver availability, and participants’ marital status, age, gender, race, and whether they died during the study period or received nursing home care within the three years before the study period. No service provider or market level variables were included. Survival analysis and OLS - however, it is unclear if the survival analysis adjusted for time-dependent covariates. Results: NHD has a lower risk rate for NH placement than the other two but costs substantially higher. Limitations: The analysis does not account for how the delay in NH placement accounts for the total cost (i.e., how the delay in NH translates into saving to the state). Also the analysis does not account for the effects of other potentially influential confounders. Other limitations include limited ability to control for selection bias as well as to identify the role of provider or market level variables. Table 1. Summary of Study Design by Domain DOMAIN: Beneficiary Outcomes??Reference?Outcomes?Design?Prospective / Longitudinal?Period?AnalysisCovariates by LevelSample - State or NationalState Regional PersonAPS (2005)Function; Illness Burden Quasi experimentalRetrospective; Longitudinal2003 - 2004Multivariate - Propensity matching; MLM; rate of changeNANOYESWI (Medicaid)Konetzka et al. (2012)Avoidable hospitalizationSecondary data analysisRetrospective; Cross-sectional2005Descriptive, no risk adjustmentNONONONational (Medicaid)Marek et al. (2005)FunctionQuasi experimentalProspective; Longitudinal30 monthsUnivariate - Cochran-Mantel-Haenszel method NONOYESMO (Medicaid)Mitchell et al. (2004)End-of-Life - Pain, feeding tube, referral to hospice, advanced directives Secondary data analysisRetrospective; Longitudinal1998-2001Multivariate - Logistic regressionNONOYESMI (Medicaid)Muramatsu et al. (2010)Function; Mental health Secondary data analysis Retrospective; Longitudinal1993, 1995, 1998, 2000, and 2002 Multivariate -Multi-level mixed-effects logistic regression analysisSOMENOYESNationally Representative Sample of Older Adults Rigler (2004)Inappropriate medication useSecondary data analysisRetrospective; Longitudinal2000-2001Multivariate - Logistic regressionNONOYESKS (Medicaid)PEVuZE5vdGU+PENpdGUgQXV0aG9yWWVhcj0iMSI+PEF1dGhvcj5XaWVsYW5kPC9BdXRob3I+PFll
YXI+MjAxMDwvWWVhcj48UmVjTnVtPjg1PC9SZWNOdW0+PERpc3BsYXlUZXh0PldpZWxhbmQgZXQg
YWwuICgyMDEwKTwvRGlzcGxheVRleHQ+PHJlY29yZD48cmVjLW51bWJlcj44NTwvcmVjLW51bWJl
cj48Zm9yZWlnbi1rZXlzPjxrZXkgYXBwPSJFTiIgZGItaWQ9ImZ4YTVlcHJldXNkcDUxZXd2eGw1
OTB2OXYwMjk1OWV3enpwcyI+ODU8L2tleT48L2ZvcmVpZ24ta2V5cz48cmVmLXR5cGUgbmFtZT0i
Sm91cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PGNvbnRyaWJ1dG9ycz48YXV0aG9ycz48YXV0
aG9yPldpZWxhbmQsIEQuPC9hdXRob3I+PGF1dGhvcj5Cb2xhbmQsIFIuPC9hdXRob3I+PGF1dGhv
cj5CYXNraW5zLCBKLjwvYXV0aG9yPjxhdXRob3I+S2lub3NpYW4sIEIuPC9hdXRob3I+PC9hdXRo
b3JzPjwvY29udHJpYnV0b3JzPjxhdXRoLWFkZHJlc3M+RGl2aXNpb24gb2YgR2VyaWF0cmljcywg
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ADDIN EN.CITE.DATA Wieland et al. (2010)Mortality Secondary data analysisRetrospective; Longitudinal5 yearsMultivariate - Kaplan-Meier curvesNONOYESSC (Medicaid)DOMAIN: Nursing Home Admission??Reference?Outcomes?Design?Prospective / Longitudinal?Period?AnalysisCovariates by LevelSample - State or NationalState Regional PersonAPS 2005NHQuasi experimentalRetrospective; Longitudinal2003 - 2004Multivariate - Propensity matching; MLM; rate of changeNANOYESWI (Medicaid)PEVuZE5vdGU+PENpdGUgQXV0aG9yWWVhcj0iMSI+PEF1dGhvcj5IYWhuPC9BdXRob3I+PFllYXI+
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ADDIN EN.CITE.DATA Muramatsu et al. (2007)NHSecondary data analysisRetrospective; Longitudinal1995-2002Multivariate - Discrete time survival analysisYESNOYESNationally Representative Sample of Older Adults ADDIN EN.CITE <EndNote><Cite AuthorYear="1"><Author>Muramatsu</Author><Year>2008</Year><RecNum>47</RecNum><DisplayText>Muramatsu et al. (2008)</DisplayText><record><rec-number>47</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">47</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Muramatsu, N.</author><author>Hoyem, R. L.</author><author>Yin, H.</author><author>Campbell, R. T.</author></authors></contributors><auth-address>Institute for Health Research and Policy, University of Illinois at Chicago, Chicago, Illinois 60612, USA. naoko@uic.edu</auth-address><titles><title>Place of death among older Americans: does state spending on home- and community-based services promote home death?</title><secondary-title>Med Care</secondary-title><alt-title>Medical care</alt-title></titles><periodical><full-title>Med Care</full-title><abbr-1>Medical care</abbr-1></periodical><alt-periodical><full-title>Med Care</full-title><abbr-1>Medical care</abbr-1></alt-periodical><pages>829-38</pages><volume>46</volume><number>8</number><edition>2008/07/31</edition><keywords><keyword>Aged</keyword><keyword>Aged, 80 and over</keyword><keyword>Community Health Services/economics/ statistics & numerical data</keyword><keyword>Death</keyword><keyword>Humans</keyword><keyword>Logistic Models</keyword><keyword>Nursing Homes/economics/ statistics & numerical data/trends</keyword><keyword>Residence Characteristics</keyword><keyword>Terminal Care</keyword></keywords><dates><year>2008</year><pub-dates><date>Aug</date></pub-dates></dates><isbn>1537-1948 (Electronic)
0025-7079 (Linking)</isbn><accession-num>18665063</accession-num><urls></urls><custom2>PMC2708119</custom2><custom6>Nihms66857</custom6><electronic-resource-num>10.1097/MLR.0b013e3181791a79</electronic-resource-num><remote-database-provider>NLM</remote-database-provider><language>eng</language></record></Cite></EndNote>Muramatsu et al. (2008)NH / Place of DeathSecondary data analysisRetrospective; LongitudinalNAMultivariate - Discrete-time survival analysis /logistic regressionYES NOYESNationally Representative Sample of Older Adults ADDIN EN.CITE <EndNote><Cite AuthorYear="1"><Author>Thomas</Author><Year>2013</Year><RecNum>150</RecNum><DisplayText>Thomas (2013)</DisplayText><record><rec-number>150</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">150</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Thomas, Kali S.</author></authors></contributors><titles><title>The Relationship Between Older Americans Act In-Home Services and Low-Care Residents in Nursing Homes</title><secondary-title>Journal of Aging and Health</secondary-title></titles><periodical><full-title>J Aging Health</full-title><abbr-1>Journal of aging and health</abbr-1></periodical><dates><year>2013</year><pub-dates><date>December 10, 2013</date></pub-dates></dates><urls><related-urls><url> (2013)OtherSecondary data analysisRetrospective; Longitudinal2000-2009Multivariate - Fixed effects modelYESYESYESNational (NH Residents)DOMAIN: Cost??Reference?Outcomes?Design?Prospective / Longitudinal?Period?AnalysisCovariates by LevelSample – State or NationalState Regional PersonAPS 2005Overall Cost Quasi experimentalRetrospective; Longitudinal2003 - 2004Multivariate - Propensity matching; MLM; rate of changeNANOYESWI (Medicaid)Eiken et al., 2013Woodwork effectSecondary data analysisRetrospective; Longitudinal1999 thru 2007Descriptive with adj for inflation and functional limitationNONOSOMENational (Medicaid)Kane et al., 2013Woodwork effectSecondary data analysisRetrospective; Longitudinal2000-2005Descriptive (with adjustment for inflation)NONONOAR, FL, MN, NM, TX, VT, WA (Medicaid)Kaye et al., 2009Woodwork effectSecondary data analysisRetrospective; Longitudinal1995-2005Multivariate with adjustment for inflation for medical costs, average income and need for LTSS NONONONational (Medicaid)Kitchener et al., 2006Overall costSecondary data analysisRetrospective; Cross-sectional2002Descriptive NONONONational (Medicaid) Mitchell et al., 2006Variations in cost by HCBS programsSecondary data analysis1999-20023 yearsMultivariate - Two-stage probit regression and ordinary least squares regression NOSOMEYESFL (Medicaid) ADDIN EN.CITE <EndNote><Cite AuthorYear="1"><Author>Shapiro</Author><Year>2011</Year><RecNum>91</RecNum><DisplayText>Shapiro et al. (2011)</DisplayText><record><rec-number>91</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">91</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Shapiro, Adam</author><author>Loh, Chung-Ping</author><author>Mitchell, Glenn</author></authors></contributors><titles><title>Medicaid Cost-Savings of Home- and Community-Based Service Programs for Older Persons in Florida</title><secondary-title>Journal of Applied Gerontology</secondary-title></titles><periodical><full-title>Journal of Applied Gerontology</full-title></periodical><pages>3-21</pages><volume>30</volume><number>1</number><dates><year>2011</year><pub-dates><date>February 1, 2011</date></pub-dates></dates><urls><related-urls><url> et al. (2011)Variations in cost by HCBS programsSecondary data analysisRetrospective; Longitudinal2000-2005Multivariate - Propensity score matching procedure NONOYESFL(Medicaid)PEVuZE5vdGU+PENpdGUgQXV0aG9yWWVhcj0iMSI+PEF1dGhvcj5TaGlyZW1hbjwvQXV0aG9yPjxZ
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ADDIN EN.CITE.DATA Shireman and Rigler (2004)Overall costSecondary data analysisRetrospective; LongitudinalUnknownMultivariateNONOYESKS(Medicaid)OPPAGA (2010)Variations in cost by HCBS programsSecondary data analysisRetrospective; Longitudinal2005-?MultivariateNANO?YESFL(Medicaid)Table 2. Summary of Findings by Domain DOMAIN: Beneficiary Outcomes?OutcomesFindings APS 2005Function; Illness Burden; Hospitalization and ER visits Compared with the comparison group (other FFS service beneficiaries), Wisconsin Family Care program beneficiaries were likely to have (1) less functional impairment; (2) greater outpatient service visit; (3) greater inpatient hospital admission and ER visit; (4) lower outpatient hospital visit and cost; and (5) lower inpatient hospital cost. No difference between the two groups in terms of changes in illness burden. Konetzka et al., 2012Avoidable hospitalizationHCBS users more likely to have avoidable hospitalization than non-HCBS users among Medicaid beneficiaries.Marek et al., 2005FunctionHCBS users were more likely to experience in improvement in cognition (at months 6, 12, 18), depression (at months 6, 12), ADL(at months 6, 12, 24), and incontinence (at month 24) than NH resident counterparts.Mitchell et al., 2004End-of-Life - Pain, feeding tube, referral to hospice, advanced directives HCBS users were more likely to be referred to hospice, receive anti-anxiety medication while they were also less likely to have advance directive, more likely to have pain and shortness of breath, and more pneumonia than NH resident counterparts.Muramatsu et al., 2010Function; Mental health Individuals living in states with higher HCBS expenditures are likely to have lower depression than those living in states with lower HCBS spending. Rigler 2004Inappropriate medication useHCBS users were more likely to have inappropriate medication use than NH resident counterparts.PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XaWVsYW5kPC9BdXRob3I+PFllYXI+MjAxMDwvWWVhcj48
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ADDIN EN.CITE.DATA (Wieland et al., 2010)Mortality HCBS users were likely to have shorter survival length than PACE users. DOMAIN: Nursing Home Admission?OutcomesFindings APS 2005NH admission and costCompared with the comparison group (other FFS service beneficiaries), Wisconsin Family Care program beneficiaries were likely to have less overall NH cost and home health service cost. PEVuZE5vdGU+PENpdGUgQXV0aG9yWWVhcj0iMSI+PEF1dGhvcj5IYWhuPC9BdXRob3I+PFllYXI+
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ADDIN EN.CITE.DATA Hahn et al. (2011)NH admission by low-care residentHigher HCBS county expenditures were associated with lower number of low-care NH residents. Saving from reducing low-care NH residents was less than HCBS Cost. ADDIN EN.CITE <EndNote><Cite AuthorYear="1"><Author>Miller</Author><Year>2011</Year><RecNum>95</RecNum><DisplayText>N. A. Miller (2011)</DisplayText><record><rec-number>95</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">95</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Miller, Nancy A.</author></authors></contributors><titles><title>Relations among home- and community-based services investment and nursing home rates of use for working-age and older adults: A state-level analysis</title><secondary-title>American Journal of Public Health</secondary-title></titles><periodical><full-title>American Journal of Public Health</full-title></periodical><pages>1735-1741</pages><volume>101</volume><number>9</number><dates><year>2011</year><pub-dates><date>2011/09/01</date></pub-dates></dates><publisher>American Public Health Association</publisher><isbn>0090-0036</isbn><urls><related-urls><url>. A. Miller (2011)NH admissionStates with higher HCBS expenditures and limited NH supply were associated with lower NH admission rate. PEVuZE5vdGU+PENpdGUgQXV0aG9yWWVhcj0iMSI+PEF1dGhvcj5NdXJhbWF0c3U8L0F1dGhvcj48
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ADDIN EN.CITE.DATA Muramatsu et al. (2007)NH admissionStates with higher HCBS expenditures were associated with reduced risk of NH admission among childless seniors. ADDIN EN.CITE <EndNote><Cite AuthorYear="1"><Author>Muramatsu</Author><Year>2008</Year><RecNum>47</RecNum><DisplayText>Muramatsu et al. (2008)</DisplayText><record><rec-number>47</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">47</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Muramatsu, N.</author><author>Hoyem, R. L.</author><author>Yin, H.</author><author>Campbell, R. T.</author></authors></contributors><auth-address>Institute for Health Research and Policy, University of Illinois at Chicago, Chicago, Illinois 60612, USA. naoko@uic.edu</auth-address><titles><title>Place of death among older Americans: does state spending on home- and community-based services promote home death?</title><secondary-title>Med Care</secondary-title><alt-title>Medical care</alt-title></titles><periodical><full-title>Med Care</full-title><abbr-1>Medical care</abbr-1></periodical><alt-periodical><full-title>Med Care</full-title><abbr-1>Medical care</abbr-1></alt-periodical><pages>829-38</pages><volume>46</volume><number>8</number><edition>2008/07/31</edition><keywords><keyword>Aged</keyword><keyword>Aged, 80 and over</keyword><keyword>Community Health Services/economics/ statistics & numerical data</keyword><keyword>Death</keyword><keyword>Humans</keyword><keyword>Logistic Models</keyword><keyword>Nursing Homes/economics/ statistics & numerical data/trends</keyword><keyword>Residence Characteristics</keyword><keyword>Terminal Care</keyword></keywords><dates><year>2008</year><pub-dates><date>Aug</date></pub-dates></dates><isbn>1537-1948 (Electronic)
0025-7079 (Linking)</isbn><accession-num>18665063</accession-num><urls></urls><custom2>PMC2708119</custom2><custom6>Nihms66857</custom6><electronic-resource-num>10.1097/MLR.0b013e3181791a79</electronic-resource-num><remote-database-provider>NLM</remote-database-provider><language>eng</language></record></Cite></EndNote>Muramatsu et al. (2008)NH at the end of lifeStates with higher HCBS expenditures were associated with reduced risk of NH admission at the EOL among Medicaid beneficiaries. ADDIN EN.CITE <EndNote><Cite AuthorYear="1"><Author>Thomas</Author><Year>2013</Year><RecNum>150</RecNum><DisplayText>Thomas (2013)</DisplayText><record><rec-number>150</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">150</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Thomas, Kali S.</author></authors></contributors><titles><title>The Relationship Between Older Americans Act In-Home Services and Low-Care Residents in Nursing Homes</title><secondary-title>Journal of Aging and Health</secondary-title></titles><periodical><full-title>J Aging Health</full-title><abbr-1>Journal of aging and health</abbr-1></periodical><dates><year>2013</year><pub-dates><date>December 10, 2013</date></pub-dates></dates><urls><related-urls><url> (2013)NH admission by low-care residentState HCBS expenditure was not associated with the number of low-care NH residents. DOMAIN: Cost?OutcomesFindings APS (2005)Overall cost Compared with the comparison group (other FFS service beneficiaries), Wisconsin Family Care program beneficiaries had lower total Medicaid cost and total Medicaid long-term care cost. Eiken et al., 2013Woodwork effectBetween 1999 and 2007, total number of Medicaid LTSS beneficiaries increased by 25% with 2.8% growth rate. Number of Medicaid LTSS beneficiaries in NH decreased by 0.4% per year. The total number of Medicaid HCBS beneficiaries increased by 5.1% per year. Medicaid LTSS cost after adjusting for inflation and national estimate of functional limitation growth was 1.8% per year from 1999-2009.Kane et al., 2013Woodwork effectFrom 2001 to 2005, the number of NH residents declined in 6 states.Increase in HCBS waiver and state plan expenditures led to a net increase of 10% in LTSS expenditures.Kaye et al., 2009Woodwork effectBetween 1995 and 2005, the HCBS grew faster than inflation (56.7% vs. 110%), nursing home use increased 3.4% in low HCBS states whiles NH spending decreased by 15.3% in high HCBS areas. LTSS expenditures, on average across states, grew by 7.3% (with large decrease in 2003-2005). The LTSS expenditure decreased by 7.9% in the established HCBS states. Kitchener et al., 2006Overall costIn 2002, the national average per-participant HCBS expenditures 63 % lower than the comparable average per-participant NH expenditures. Mitchell et al., 2006Variations in cost by HCBS programsHCBS program costs vary across programs. NH Diversion (NHD) program had the highest cost with poor outcomes (highest total Medicaid claims and highest rate of inpatient days).The Aged and Disabled Adult (ADA) program had better outcomes but with higher NH days. ADDIN EN.CITE <EndNote><Cite AuthorYear="1"><Author>Shapiro</Author><Year>2011</Year><RecNum>91</RecNum><DisplayText>Shapiro et al. (2011)</DisplayText><record><rec-number>91</rec-number><foreign-keys><key app="EN" db-id="fxa5epreusdp51ewvxl590v9v02959ewzzps">91</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Shapiro, Adam</author><author>Loh, Chung-Ping</author><author>Mitchell, Glenn</author></authors></contributors><titles><title>Medicaid Cost-Savings of Home- and Community-Based Service Programs for Older Persons in Florida</title><secondary-title>Journal of Applied Gerontology</secondary-title></titles><periodical><full-title>Journal of Applied Gerontology</full-title></periodical><pages>3-21</pages><volume>30</volume><number>1</number><dates><year>2011</year><pub-dates><date>February 1, 2011</date></pub-dates></dates><urls><related-urls><url> et al. (2011)Variations in cost by HCBS programsHCBS program cost savings vary across programs within the state. Little evidence of HCBS saving medical care cost. PEVuZE5vdGU+PENpdGUgQXV0aG9yWWVhcj0iMSI+PEF1dGhvcj5TaGlyZW1hbjwvQXV0aG9yPjxZ
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ADDIN EN.CITE.DATA Shireman and Rigler (2004)Overall costHCBS cost (per person) is lower than NH cost. OPPAGA, 2010Variations in cost by HCBS programsHCBS programs vary in reducing NH admission rate. NHD reduces NH placement than two other programs in FL. Cost of NHD is substantially higher than the other two programs. References ADDIN EN.REFLIST APS Healthcare. (2005). Family Care Independent Assessment: An Evaluation of Access, Quality and Cost Effectiveness for Calendar Year 2003 - 2004.Doty, P., Cohen, M. A., Miller, J., & Shi, X. (2010). Private long-term care insurance: value to claimants and implications for long-term care financing. Gerontologist, 50(5), 613-622. doi: 10.1093/geront/gnq021Eiken, S., Burwell, B., & Sredl, K. (2013). An examination of the woodwork effect using national medicaid long-term services and supports data. J Aging Soc Policy, 25(2), 134-145. doi: 10.1080/08959420.2013.766054Florida Department of Elder Affairs. (2011). Long-Term Care Community Diversion Pilot Project 2009-2010 Legislative Report Prepared by Fox-Grage, W., & Walls, J. (2013). State Studies Find Home and Community-Based Services to Be Cost-Effective Spotlight Washington, DC: Public Policy Institute, AARP.Grabowski, D. C. (2006a). The cost-effectiveness of noninstitutional long-term care services: review and synthesis of the most recent evidence. Med Care Res Rev, 63(1), 3-28. Grabowski, D. C. (2006b). The cost-effectiveness of noninstitutional long-term care services: Review and synthesis of the most recent evidence. Medical care research and review, 63(1), 3-28. Hahn, E. A., Thomas, K. S., Hyer, K., Andel, R., & Meng, H. (2011). Predictors of low-care prevalence in Florida nursing homes: the role of Medicaid waiver programs. Gerontologist, 51(4), 495-503. doi: 10.1093/geront/gnr020Kane, R. L., Lum, T. Y., Kane, R. A., Homyak, P., Parashuram, S., & Wysocki, A. (2013). Does home- and community-based care affect nursing home use? J Aging Soc Policy, 25(2), 146-160. doi: 10.1080/08959420.2013.766069Kaye, H. S., LaPlante, M. P., & Harrington, C. (2009). Do noninstitutional long-term care services reduce Medicaid spending? Health Affairs, 28(1), 262-272. doi: 10.1377/hlthaff.28.1.262Kitchener, M., Ng, T., Miller, N., & Harrington, C. (2006). Institutional and community-based long-term care: a comparative estimate of public costs. J Health Soc Policy, 22(2), 31-50. doi: 10.1300/J045v22n02_03Konetzka, R. T., Karon, S. L., & Potter, D. E. (2012). Users of Medicaid home and community-based services are especially vulnerable to costly avoidable hospital admissions. Health Aff (Millwood), 31(6), 1167-1175. doi: 10.1377/hlthaff.2011.0902Marek, K. D., Popejoy, L., Petroski, G., Mehr, D., Rantz, M., & Lin, W. C. (2005). Clinical outcomes of aging in place. Nurs Res, 54(3), 202-211. Mehdizadeh, S. (May 2007). PASSPORT Cost Neutrality: How Do the Total Medicaid and Other Public Costs of Maintaining a PASSPORT Consumer in the Community Compare to That of a Nursing Facility Resident? . Oxford, OH: Scripps Gerontology Center Miami University.Miller, J. S., Shi, X., & Cohen, M. A. (2008). Private Long- Term Care Insurance: Following an Admission Cohort over 28 Months to Track Claim Experience, Service Use and Transitions. Prepared by LifePlans, Inc. for the Office of Disability, Aging and Long- Term Care Policy, Office of the Assistant Secretary for Planning and Evaluation, under Contract #HHS-100-02-0014. . Washington, D.C.: U.S. Department of Health and Human Services.Miller, N. A. (2011). Relations among home- and community-based services investment and nursing home rates of use for working-age and older adults: A state-level analysis. American Journal of Public Health, 101(9), 1735-1741. doi: 10.2105/AJPH.2011.300163Mitchell, G., Salmon, J. R., Polivka, L., & Soberon-Ferrer, H. (2006). 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