University of Manchester
Early intervention in psychosis: a health economic evaluation using the net benefit approach in a real world settingAuthors: Caragh Behan, Brendan Kennelly, Eric Roche, Laoise Renwick, Sarah Masterson, John Lyne, Brian O’ Donoghue, John Waddington, Catherine McDonough, Paul McCrone, Mary ClarkeAbstractBackgroundEarly intervention in psychosis (EIP) is a complex intervention, usually delivered in a specialist stand-alone setting, which aims to improve outcomes in people with psychosis. Economic evaluation is a useful framework to guide the evaluation of an intervention by using a metric which evaluates the joint costs and effects. AimsTo evaluate whether there is a net benefit to the health sector and society when EIP is delivered in a real world setting.MethodTwo contemporaneous incidence-based cohorts presenting with a first episode psychosis aged 18-65 were evaluated. ResultsFrom the health sector perspective, the probability that EIP was cost-effective was 0.77 and the incremental net benefit (INB) of EIP was €2,465 (95% CI -€4,418 to €9,347) when society placed a value of €6,000, the cost of an in-patient relapse, on preventing a relapse requiring in-patient admission or home care. Following adjustment for covariates, the probability that EI was cost-effective was 1 and the INB to the health sector was €3,105 (95% CI - €8,453 to €14,663). From the societal perspective, the adjusted probability that EIP was cost-effective was 1, and the INB was €19,928 (95% CI -€2,075 to €41,931).ConclusionEIP has a modest INB from the health sector perspective but a large INB from the societal perspective. The choice of outcome measure and perspective of the study are critical when presenting an economic evaluation of a complex intervention such as EIP to policymakers and service planners.Early intervention in psychosis: a health economic evaluation using the net benefit approach in a real world settingIntroductionEvidence on the cost-effectiveness of Early Intervention in psychosis (EIP) comes from a heterogeneous group of studies, which show that EIP primarily achieves savings through a reduction in in-patient admissions PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5NaWhhbG9wb3Vsb3M8L0F1dGhvcj48WWVhcj4xOTk5PC9Z
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ADDIN EN.CITE.DATA (1-4). The majority of evidence for the costs and effects of EIP come from specialist stand-alone centres with a youth-oriented approach delivering EIP to a population aged 16-35 and compared to standard treatment as usual (TAU). Critics argue that TAU has evolved since these studies were performed, and current community mental health (CMH) care, delivering more sophisticated treatments such as home based treatment and assertive outreach treatment can deliver effective EIP. PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5DYXN0bGU8L0F1dGhvcj48WWVhcj4yMDEyPC9ZZWFyPjxJ
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ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5DYXN0bGU8L0F1dGhvcj48WWVhcj4yMDEyPC9ZZWFyPjxJ
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ADDIN EN.CITE.DATA (5, 6) Interventions shown to have an effect in a trial setting may lose efficacy in real world settings where delivery is constrained by loss of fidelity and problems with sustainability. Economic evaluation can facilitate the examination of whether a complex intervention translates into the local context, thereby generating information relevant for service planning and policy makers. Cost-effectiveness evaluations typically report Incremental Cost-Effectiveness Ratios (ICERs). ICERs involve a ratio and there are difficulties in interpreting the value of the ICER and in generating a measure of uncertainty, and they are not amenable to regression analysis. PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5Ib2NoPC9BdXRob3I+PFllYXI+MjAwMjwvWWVhcj48SURU
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ADDIN EN.CITE.DATA (7, 8) Reformulating the cost-effectiveness question to generate a linear net benefit (NB) facilitates interpretation of the results of the evaluation, and allows use of regression techniques to adjust for socio-demographic and clinical differences between the treatment as usual (TAU) and intervention groups. While EIP is part of the core mental health service in countries such as Canada, the UK and Australia, other countries have been trying to implement EIP in health systems that face significant challenges, both in terms of financing and sustaining services. In Ireland, a number of health service reforms have presented challenges for service delivery. EIP is one of three National Clinical Programmes in mental health; presently coverage of the population is only 10%. Other challenges include strict delineation between Child and Adolescent Mental Health Services (CAMHS) and General Adult Mental Health Services (MHS), with no models of care for EIP which cross this divide.AimThe aim of this study was to conduct a cost-effectiveness evaluation of EIP in a real world setting in comparison to best practice TAU using the NB framework. This study is presented according to the CHEERS guidelines for economic evaluations. ADDIN EN.CITE <EndNote><Cite><Author>Husereau</Author><Year>2013</Year><IDText>Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement</IDText><DisplayText>(9)</DisplayText><record><dates><pub-dates><date>Mar</date></pub-dates><year>2013</year></dates><keywords><keyword>Checklist</keyword><keyword>Comparative Effectiveness Research</keyword><keyword>Costs and Cost Analysis</keyword><keyword>Delphi Technique</keyword><keyword>Economics</keyword><keyword>Guidelines as Topic</keyword><keyword>Health Policy</keyword><keyword>Humans</keyword><keyword>Publishing</keyword><keyword>Quality Control</keyword><keyword>Reference Standards</keyword></keywords><urls><related-urls><url> Health Economic Evaluation Reporting Standards (CHEERS) statement</title><secondary-title>BMJ</secondary-title></titles><pages>f1049</pages><contributors><authors><author>Husereau, D.</author><author>Drummond, M.</author><author>Petrou, S.</author><author>Carswell, C.</author><author>Moher, D.</author><author>Greenberg, D.</author><author>Augustovski, F.</author><author>Briggs, A. H.</author><author>Mauskopf, J.</author><author>Loder, E.</author><author>CHEERS Task Force</author></authors></contributors><edition>2013/03/25</edition><language>eng</language><added-date format="utc">1541141660</added-date><ref-type name="Journal Article">17</ref-type><rec-number>1186</rec-number><last-updated-date format="utc">1541141660</last-updated-date><accession-num>23529982</accession-num><electronic-resource-num>10.1136/bmj.f1049</electronic-resource-num><volume>346</volume></record></Cite></EndNote>(9)Methods The study sample consisted of two incidence-based cohorts presenting to five catchment area services in Ireland between 2010 and 2012. Data were collected at first presentation and at one year follow up.followed-up at one year. Individuals presenting to the catchment area services with a first episode of psychosis aged between 18 and 65 were included. Inclusion criteria were being in their first episode of psychosis (FEP) and aged between 18 and 65. Exclusion criteria were intellectual disability, being on antipsychotic medication for more than 30 days prior to study inception, and having a diagnosis of psychosis secondary to a general medical condition. The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. Ethical approval for the study was obtained from the local ethics committees of the relevant services (ID 406 St John of God Provincial Ethics Committee). One cohort presented to an EIP service which operated as a specialist hub delivering EI to three Community Mental Health Team (CMHT) services. The EI service offered an early detection and phase specific intervention strategy. Anyone referred to the EI service was offered a rapid assessment within 72 hours of referral to establish the presence of psychosis. Where possible, the assessor also interviewed a family member. Care during any in-patient admission and medication management remained the responsibility of the CMHT. The TAU cohort presented to a best practice CMHT service with a home based treatment team and an assertive outreach team. Patients presenting to the TAU service received a structured diagnostic interview (SCID-IV) and assessment by a research registrar following presentation (on average within 41 days) but otherwise received standard care. Following the assessment, the participant was offered one or all of three phase specific interventions. Cognitive Behavioural Therapy for psychosis (CBTp) was delivered in group format over 12 sessions. Family education and intervention was delivered in group format over 6 sessions. A psychosocial intervention was delivered in individual sessions for as many as were required. Over the period of the study the psychosocial intervention was not consistently offered due to resource reasons. A follow-up assessment was conducted at one year. In both cohorts, each participant was assessed using a structured diagnostic interview (SCID-IV) to establish a diagnosis of psychosis. ADDIN EN.CITE <EndNote><Cite><Author>First</Author><Year>2002</Year><IDText>Structured Clinical Interview for DSM-IV-TR Axis I Disorders, Research Version, Non-Patient Edition (SCID-I/NP)</IDText><DisplayText>(10)</DisplayText><record><titles><title>Structured Clinical Interview for DSM-IV-TR Axis I Disorders, Research Version, Non-Patient Edition (SCID-I/NP)</title><secondary-title>Biometrics Research</secondary-title></titles><contributors><authors><author>First, Michael B.</author><author>Spitzer, Robert L.</author><author>Gibbon, Miriam.</author><author>Williams, Janet BW.</author></authors></contributors><added-date format="utc">1410723172</added-date><pub-location>New York</pub-location><ref-type name="Generic">13</ref-type><dates><year>2002</year></dates><rec-number>621</rec-number><last-updated-date format="utc">1410723554</last-updated-date><contributors><secondary-authors><author>New York State Psychiatric Institute</author></secondary-authors></contributors><volume><style font="default" size="100%">First, M. B., R. L. Spitzer, M. Gibbon, and J. B. W. Williams. "Structured Clinical Interview for DSM-IV-TR Axis I Disorders, Research Version, Non-Patient Edition (SCID-I/NP). New York, New York State Psychiatric Institute."</style><style face="italic" font="default" size="100%">Biometrics Research</style><style font="default" size="100%">?(2002).</style></volume></record></Cite></EndNote>(10) Information on health service and resource use was collected using the Client Socio-demographic service and receipt inventory (CSSRI) for the one year period. PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5LbmFwcDwvQXV0aG9yPjxZZWFyPjE5OTA8L1llYXI+PElE
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ADDIN EN.CITE.DATA (11, 12) The CSSRI was modified for use in the Irish context. This information was verified and supplemented using medical records and contact with the primary care service. Unit costs were derived from previously published national cost of illness studies, other national studies which reported unit cost data, personal contact with the individual services and personal contact with the finance department of the Health Service Executive (HSE) in Ireland. Where national cost data were not obtainable, we used data from the PSSRU in the UK and converted the costs to euro using PPP. ADDIN EN.CITE <EndNote><Cite><Author>Curtis</Author><Year>2012</Year><IDText>Unit Costs of Health and Social Care 2012</IDText><DisplayText>(13)</DisplayText><record><urls><related-urls><url> Costs of Health and Social Care 2012</title></titles><contributors><authors><author>Curtis, Leslie</author></authors></contributors><added-date format="utc">1421166139</added-date><pub-location>The University of Kent, Canterbury</pub-location><ref-type name="Edited Book">28</ref-type><dates><year>2012</year></dates><rec-number>691</rec-number><publisher>Personal Social Services Research Unit</publisher><last-updated-date format="utc">1421166759</last-updated-date><contributors><secondary-authors><author>PRSSU</author></secondary-authors></contributors></record></Cite></EndNote>(13). For opportunity costs, hours of lost productivity were valued according to the Human Capital Approach (HCA). ADDIN EN.CITE <EndNote><Cite><Author>Drummond</Author><Year>2015</Year><IDText>Methods for the Economic Evaluation of Health Care Programmes</IDText><DisplayText>(8)</DisplayText><record><keywords><keyword>Medical care Cost effectiveness.</keyword><keyword>Medical care, Cost of Evaluation.</keyword><keyword>Health Services economics [MESH]</keyword><keyword>Economics, Medical [MESH]</keyword></keywords><isbn>0198529449
0198529457
9780198529446
9780198529453</isbn><titles><title>Methods for the Economic Evaluation of Health Care Programmes</title><secondary-title>Oxford Medical Publications</secondary-title></titles><pages>x, 445 p.</pages><call-num>RA410.5
RA410.5 .D77</call-num><contributors><authors><author>Drummond, Michael F.</author><author>Sculpher, Mark J.</author><author>Claxton, Karl</author><author>Stoddart Greg L.</author><author>Torrance, George W.</author></authors></contributors><section>1-445</section><edition>4rd</edition><added-date format="utc">1403023879</added-date><pub-location>Oxford, England</pub-location><ref-type name="Book">6</ref-type><dates><year>2015</year></dates><rec-number>258</rec-number><publisher>Oxford University Press</publisher><last-updated-date format="utc">1468680053</last-updated-date><contributors><secondary-authors><author>Oxford University Press</author></secondary-authors></contributors></record></Cite></EndNote>(8) The average industrial wage for the time period of the study as published by the CSO was used to value lost productivity. ADDIN EN.CITE <EndNote><Cite><Author>Central</Author><Year>2012</Year><IDText>Statistical Yearbook of Ireland</IDText><DisplayText>(14)</DisplayText><record><urls><related-urls><url> Yearbook of Ireland</title></titles><contributors><authors><author>Central Statistics Office</author></authors></contributors><added-date format="utc">1468757067</added-date><pub-location>Dublin, Ireland</pub-location><ref-type name="Government Document">46</ref-type><dates><year>2012</year></dates><rec-number>1048</rec-number><publisher>Central Statistics Office</publisher><last-updated-date format="utc">1468757587</last-updated-date></record></Cite></EndNote>(14) We used the proxy good method to value informal care and applied the hourly wage of the person who would replace that form of care, including carers and childcare services. ADDIN EN.CITE <EndNote><Cite><Author>Drummond</Author><Year>2015</Year><IDText>Methods for the Economic Evaluation of Health Care Programmes</IDText><DisplayText>(8)</DisplayText><record><keywords><keyword>Medical care Cost effectiveness.</keyword><keyword>Medical care, Cost of Evaluation.</keyword><keyword>Health Services economics [MESH]</keyword><keyword>Economics, Medical [MESH]</keyword></keywords><isbn>0198529449
0198529457
9780198529446
9780198529453</isbn><titles><title>Methods for the Economic Evaluation of Health Care Programmes</title><secondary-title>Oxford Medical Publications</secondary-title></titles><pages>x, 445 p.</pages><call-num>RA410.5
RA410.5 .D77</call-num><contributors><authors><author>Drummond, Michael F.</author><author>Sculpher, Mark J.</author><author>Claxton, Karl</author><author>Stoddart Greg L.</author><author>Torrance, George W.</author></authors></contributors><section>1-445</section><edition>4rd</edition><added-date format="utc">1403023879</added-date><pub-location>Oxford, England</pub-location><ref-type name="Book">6</ref-type><dates><year>2015</year></dates><rec-number>258</rec-number><publisher>Oxford University Press</publisher><last-updated-date format="utc">1468680053</last-updated-date><contributors><secondary-authors><author>Oxford University Press</author></secondary-authors></contributors></record></Cite></EndNote>(8) Costs were reported in Euro for the year 2012. The reference case was from the perspective of the health sector. Costs accruing to the health sector relating to the one year period following presentation with the FEP were collected. These included mental health in-patient admission costs, general medical admission costs related to the FEP, home-based treatment costs, CMHT? service costs, costs from primary care, and external mental health resources related to the FEP including counselling, medication and investigation costs. Secondary analysis was from the societal perspective. The cost of lost productivity was collected by applying the average industrial wage to the number of days lost from employment secondary to the FEP. The one year follow-up period allowed sufficient time for the outcome to occur and there was no requirement to apply a discount rate to the costs. The primary outcome was defined as a relapse of psychosis which was sufficiently severe to require admission to hospital or to the home-based treatment team (HBT). Information on relapse was collected from the hospital electronic records and from the CMH written medical records. Information to determine lost productivity and employment status at one year was collected from clinical interview and/or medical records review and documented using the CSSRI. Data were analysed in Microsoft excel 2010 and Stata 13.0. Univariate analysis of outcome data were carried out using chi squared tests, parametric data were analysed using students t-tests and non-parametric data were analysed using Mann-Whitney U tests. Multivariate analyses of outcome data were carried out using logistic regression. As cost data are usually highly skewed, cost data were analysed using a generalized linear model with a gamma family and a log link. Cost and outcome data were adjusted for socio-demographic and baseline clinical characteristics for the multivariate analyses. The NB statistic was generated using the equation NB=λ.E-C, where NB is the net benefit, E is the effectiveness (i.e. avoidance of a relapse requiring admission or HBT) and C are the service costs. λ is a theoretical, but unknown, value placed on the outcome by society. Cost and effectiveness data were bootstrapped to 1000 replications using sampling with replacement to generate 95% confidence estimates. The proportion of these replications that were greater than zero indicated the probability that EI was more cost-effective than TAU. The probabilities were used to generate cost-effectiveness acceptability curves (CEAC). As there is no guidance for choosing the λ values when the outcome is not a quality adjusted life year (QALY), a range of values of willingness to pay were plotted. Sensitivity analyses of the costs and outcomes were conducted and a secondary analysis included the societal perspective using the value of lost productivity.Results Of 307 people presenting to services who fulfilled the inclusion criteria, 270 were eligible for follow-up at one year, 212 were assessed at one year, and 201 people included in the cost-effectiveness analysis. Reasons for non-inclusion in the cost-effectiveness analysis (6%) were incomplete CSSRIs or attendance at private in-patient services. Table 1 shows the socio-demographic and clinical characteristics of the sample. There were no statistically significant differences in baseline characteristics as regards gender, marital status, living independently at presentation, the proportion born in Ireland and the proportion with English as their first language. The TAU cohort were younger at presentation (28 years v 33 years, Z =-2.646, p=0.008). The TAU cohort had a significantly higher proportion in employment at baseline (47% v 27%, χ2 =7.823, df1, p=0.005). The majority of the EI cohort lived in urban areas (98% v 39%, χ2 =87.34, df1, p<0.001). The TAU cohort were living in areas with higher levels of deprivation (decile 9 v. decile 4, z=5.554, p<0.001).Table 1 Baseline characteristics of the study sample Categorical variables n (%)Total(201)TAU(77)EI(124)Statisticp valueGenderMale113 (56)48 (62)65 (52)1.8980.168Never married123 (61)50 (65)73 (59)0.736 0.391Living independently135 (67)82 (68)53 (67)0.008 0.930EducationFinished high school equivalent136 (68)48 (64)88 (71)1.049 0.306Employed70 (35)36 (47)34 (27)7.8230.005Urban 151 (75)30 (39)121 (98)87.347 <0.001Irish born153 (76)59 (77)94 (76)0.017 0.895SSD112 (56)41 (53)71 (57)0.309 0.578Under 35 at presentation127 (63)56 (73)71 (57)4.8870.027Continuous variables Median (IQR)Age at presentation32 (18)28 (15)33 (16)-2.646 0.008Deprivation Index7 (7)9 (4)4 (8)5.454<0.001SF Index9 (3)8 (5)9 (2)-4.351 <0.001GAF at baseline30 (10)27 (9)30 (13.5)-2.781 0.005TAU: Treatment as usual; EI: Early intervention; IQR: Inter quartile range; SF: Social fragmentation Index; GAF: Global assessment of functioning scale; SSD: schizophrenia spectrum disorderCost-effectiveness resultsThe data were initially evaluated using the standard ICER (Table 2). From the health sector perspective, the intervention dominated. The intervention cost €1,681 (SE €3,247) less and more relapses were avoided (0.10 (SE 0.06)). The unadjusted ICER was €17,078 saved per relapse avoided. The bootstrapped estimates of the ICER were plotted on the cost-effectiveness plane and show that the intervention dominated in 63% of replications. Following adjustment for socio-demographic and clinical characteristics, the intervention dominated in 95% of replications (see figure 1). From the societal perspective, the intervention dominated in 74% of replications and following adjustment for socio-demographic and clinical characteristics, the intervention dominated in 95% of replications. The unadjusted ICER was €25,543 saved per relapse avoided from the societal perspective.Table 2 Incremental cost-effectiveness ratioMean (SE)TAU (77)EI (124)Difference ?95% CI (N) ?Health sector perspectiveCost €23,862 (2,835)22,181 (1,857)-1,681 (3,247)-4,721 to 8,083Effect (relapse avoided)0.74 (0.50)0.84 (0.03)0.10 (0.06)-0.21 to 0.02ICER health sector-17,078Societal perspectiveCost €25,554 (2,823)22,707 (1,863)-2,846 (3,246)-3,768 to 9,018Effect (relapse avoided)0.74 (0.50)0.84 (0.03)0.10 (0.06)-0.21 to 0.02ICER societal-25,543? Bootstrapped to 1000 replications; CI: Confidence Interval; N: normal based; ICER: Incremental cost-effectiveness ratio; SE: standard error; costs rounded up, all other figures rounded to 2 decimal placesFigure 2 Cost-effectiveness planeUsing the NB framework, implementing the intervention resulted in an incremental net benefit (INB) to the health sector of €1,796 (SE €3,376). This fell to €1,200 (SE €5,410) following adjustment for socio-demographic and clinical characteristics, even when society placed no value on avoiding a relapse requiring admission or home based treatment. When a value of €6,000, the approximate cost of an in-patient relapse in the literature, was placed on avoiding such a relapse, implementing the intervention resulted in an INB of approximately €2,465 (SE €3,389) to the health sector, and €3,105 (SE €5,890) following adjustment for socio-demographic and clinical characteristics. The standard errors of the mean were large and the 95% confidence intervals were wide reflecting the degree of uncertainty around the cost data. When the value of λ was €0, the probability that the intervention was cost-effective was 0.71 in the unadjusted model, and following adjustment for socio-demographic and clinical characteristics, the probability that EI was cost-effective fell to 0.59. From the societal perspective, implementing the intervention resulted in an INB of €34,694 (SE €8,994). This fell to €17,604 (SE €10,933) following adjustment for socio-demographic and clinical characteristics, even when society placed no value on avoiding a relapse requiring admission or HBT. When λ was valued at €6,000, implementing the intervention resulted in an INB to society of approximately €35,363 (SE €8,081), and €19,928 (SE €11,212) following adjustment for socio-demographic and clinical characteristics. The probability that the intervention was cost-effective was 1, before and after adjustment for socio-demographic and clinical characteristics. Figure 2 shows the probabilities that the intervention was cost-effective for a range of values of willingness to pay (λ).Figure 2 Cost-effectiveness acceptability curvesSensitivity analyses were conducted to test the assumptions in the model and the data. Varying the proportion of relapses to 25% (the minimum relapse rate aimed for in the IRIS guidelines ADDIN EN.CITE <EndNote><Cite><Author>IRIS</Author><Year>2012</Year><IDText>IRIS Guidelines Update</IDText><DisplayText>(15)</DisplayText><record><urls><related-urls><url>iris-.uk</url></related-urls></urls><titles><title>IRIS Guidelines Update</title><secondary-title>IRIS (2012) IRIS Guidelines Update. IRIS Initiative Ltd. 
iris-.uk</secondary-title></titles><contributors><authors><author>IRIS</author></authors></contributors><added-date format="utc">1408106311</added-date><pub-location>iris-.uk</pub-location><ref-type name="Generic">13</ref-type><dates><year>2012</year></dates><rec-number>394</rec-number><publisher>IRIS Initiative Ltd.</publisher><last-updated-date format="utc">1420671883</last-updated-date></record></Cite></EndNote>(15)) and adjusting for baseline costs had no effect on the result. Neither did restricting the analysis to those seen by clinical interview in comparison to those whose data was extracted from medical records.Subgroup analyses were performed to evaluate for the effect of heterogeneity on the outcome. Limiting the intervention to people with schizophrenia spectrum disorder (SSD) increased the cost-effectiveness of the intervention. Limiting the intervention to the under 35s decreased the cost-effectiveness of the intervention. Including people presenting with psychosis secondary to a medical condition decreased the cost-effectiveness of the intervention (see Table 3).Table 3 Subgroup analysesWhen Lambda (λ ) = €6KReference case (n=201)Under 35s(n=128)SSD(n=120)Including GMC(n=205)Health sector perspectiveUnadjusted Δ INB € All mean (SE) ?95% CI ?2,465 (3,389)-4,418 to 9,347-864 (3,889)-8,497 to 6,7687,642 (5,433)-3,017 to 18,302970 (3,618)-6,130 to 8,071Probability CE health sector0.770.640.930.60Adjusted ??Δ INB € All mean (SE) ?95% CI ?3,105 (5,890)-8,453 to 14,663231 (7,754)-14,985 to 15,4476,899 (8,712)-10,197 to 23, 995721 (5,966)-10,985 to 13,125Probability CE health sector 10.9870.9980.99Societal perspectiveUnadjusted Δ INB € All mean (SE) ?95% CI ?35,363 (8,081)17,582 to 53,14434,882 (10,962)12,683 to 57,13449,611 (11,459)22,444 to 76,77733,582 (8,028)-15,897 to 51,267Probability CE societal 1111Adjusted Δ INB € All mean (SE) ?95% CI ?19,928 (11,212)-2,075 to 41,93122,509 (15,603)-8,109 to 53,12721,977 (17,188)-11,752 to 55,70516,779 (10,977)-4,762 to 38,319Probability CE societal 110.9961Δ : difference in means; CE: cost-effective; CI: confidence interval; EI: early intervention; GMC: general medical INB: incremental net benefit; SE: standard error; SSD: schizophrenia spectrum disorder; €, Euro; ? bootstrapped to 1000 replications?? adjusted for age, gender, marital status, employment at baseline, diagnosis, GAF at baseline, the use of drugs, the presence of depression, catchment area and Social Fragmentation Index decile; set seed was the same as the unadjusted model to facilitate replication; cost data rounded up: all other figures rounded to 3 decimal placesDiscussionThe evidence for the cost-effectiveness of EI in psychosis comes from a range of published studies with heterogeneous methods and outcomes. The majority of studies use a historical TAU control PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5NaWhhbG9wb3Vsb3M8L0F1dGhvcj48WWVhcj4xOTk5PC9Z
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ADDIN EN.CITE.DATA (22-24), one uses data linkage ADDIN EN.CITE <EndNote><Cite><Author>Tsiachristas</Author><Year>2016</Year><IDText>Economic impact of early intervention in psychosis services: results from a longitudinal retrospective controlled study in England</IDText><DisplayText>(25)</DisplayText><record><dates><pub-dates><date>Oct</date></pub-dates><year>2016</year></dates><urls><related-urls><url> impact of early intervention in psychosis services: results from a longitudinal retrospective controlled study in England</title><secondary-title>BMJ Open</secondary-title></titles><pages>e012611</pages><number>10</number><contributors><authors><author>Tsiachristas, A.</author><author>Thomas, T.</author><author>Leal, J.</author><author>Lennox, B. R.</author></authors></contributors><edition>2016/10/20</edition><language>eng</language><added-date format="utc">1495473153</added-date><ref-type name="Journal Article">17</ref-type><rec-number>1152</rec-number><last-updated-date format="utc">1495473259</last-updated-date><accession-num>27798015</accession-num><electronic-resource-num>10.1136/bmjopen-2016-012611</electronic-resource-num><volume>6</volume></record></Cite></EndNote>(25) and two studies evaluate the cost-effectiveness of EI in comparison to TAU in a RCT. PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5IYXN0cnVwPC9BdXRob3I+PFllYXI+MjAxMzwvWWVhcj48
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ADDIN EN.CITE.DATA (3, 4) In those studies where patient-level data were used, the settings were primarily specialist EI services delivering EI to a younger cohort with a maximum age of 40-45 from the health sector perspective. The published studies showed that EI results in cost savings primarily through a reduction in in-patient admissions. This study adds to the literature on the cost-effectiveness of EIP by considering both the health sector and societal perspectives using patient-level data. Use of the NB approach, which takes into account the joint effect of costs and effects upon each other, facilitated the evaluation of uncertainty ADDIN EN.CITE <EndNote><Cite><Author>Hoch</Author><Year>2002</Year><IDText>Something old, something new, something borrowed, something blue: a framework for the marriage of health econometrics and cost-effectiveness analysis</IDText><DisplayText>(7)</DisplayText><record><dates><pub-dates><date>Jul</date></pub-dates><year>2002</year></dates><keywords><keyword>Baltimore</keyword><keyword>Community Mental Health Services</keyword><keyword>Cost-Benefit Analysis</keyword><keyword>Health Services Research</keyword><keyword>Homeless Persons</keyword><keyword>Humans</keyword><keyword>Mental Disorders</keyword><keyword>Models, Econometric</keyword><keyword>Outcome Assessment (Health Care)</keyword><keyword>Random Allocation</keyword><keyword>Randomized Controlled Trials as Topic</keyword><keyword>Regression Analysis</keyword><keyword>Therapeutic Community</keyword><keyword>Treatment Outcome</keyword></keywords><urls><related-urls><url> old, something new, something borrowed, something blue: a framework for the marriage of health econometrics and cost-effectiveness analysis</title><secondary-title>Health Econ</secondary-title></titles><pages>415-30</pages><number>5</number><contributors><authors><author>Hoch, J. S.</author><author>Briggs, A. H.</author><author>Willan, A. R.</author></authors></contributors><language>eng</language><added-date format="utc">1403021254</added-date><ref-type name="Journal Article">17</ref-type><rec-number>256</rec-number><last-updated-date format="utc">1403021322</last-updated-date><accession-num>12112491</accession-num><electronic-resource-num>10.1002/hec.678</electronic-resource-num><volume>11</volume></record></Cite></EndNote>(7). This is particularly useful where the design of the study is not a RCT. Traditionally the ICER has been used in economic evaluation. The ICER approach examines costs and effects in isolation and does not handle the estimation of uncertainty well. PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5Ib2NoPC9BdXRob3I+PFllYXI+MjAwMjwvWWVhcj48SURU
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ADDIN EN.CITE.DATA (7, 8) To date, there has only been one other study examining the cost-effectiveness of EI using the NB regression approach. That study evaluated a specialist EI service in comparison to more traditional TAU community model, and showed a high likelihood that EI was cost-effective if outcomes such as quality of life and vocation were taken into account. ADDIN EN.CITE <EndNote><Cite><Author>McCrone</Author><Year>2010</Year><IDText>Cost-effectiveness of an early intervention service for people with psychosis</IDText><DisplayText>(4)</DisplayText><record><dates><pub-dates><date>May</date></pub-dates><year>2010</year></dates><keywords><keyword>Adolescent</keyword><keyword>Adult</keyword><keyword>Community Mental Health Services</keyword><keyword>Cost-Benefit Analysis</keyword><keyword>Delivery of Health Care</keyword><keyword>Female</keyword><keyword>Follow-Up Studies</keyword><keyword>Health Care Costs</keyword><keyword>Humans</keyword><keyword>London</keyword><keyword>Male</keyword><keyword>Patient Care Team</keyword><keyword>Psychotic Disorders</keyword><keyword>Time Factors</keyword><keyword>Treatment Outcome</keyword><keyword>Young Adult</keyword></keywords><urls><related-urls><url> of an early intervention service for people with psychosis</title><secondary-title>Br J Psychiatry</secondary-title></titles><pages>377-82</pages><number>5</number><contributors><authors><author>McCrone, P.</author><author>Craig, T. K.</author><author>Power, P.</author><author>Garety, P. A.</author></authors></contributors><language>eng</language><added-date format="utc">1353791745</added-date><ref-type name="Journal Article">17</ref-type><auth-address>Centre for the Economics of Mental Health, PO 24, Health Service and Population Research Department, Institute of Psychiatry, King's College London, London SE5 8AF, UK. p.mccrone@iop.kcl.ac.uk</auth-address><rec-number>60</rec-number><last-updated-date format="utc">1501360535</last-updated-date><accession-num>20435964</accession-num><electronic-resource-num>196/5/377 [pii]
10.1192/bjp.bp.109.065896</electronic-resource-num><volume>196</volume></record></Cite></EndNote>(4)Examination of the societal perspective by including the impact of EI on productivity showed that delivering EI had a large INB in all populations and a probability of 1 of being cost-effective. This highlights the need to look beyond the health sector at the wider benefits of mental health interventions. In this case, lost productivity referred only to days of employment lost due to illness, and did not include days of education, or any other activities that require role replacement such as that of the carer. This study further evaluated whether cost savings made in specialist centres translate to a real world setting. Most countries have a rigid boundary between child and adult mental health services. This study examines whether EI is cost-effective in a setting where there is no transitional youth model of EIP, and EI is delivered through the community mental health setting to an adult population over 18, albeit one with a specialist dedicated EI hub delivering the interventions. EI services have traditionally been advocated for younger people, and yet there are a substantial proportion of people who become psychotic or present for care for the first time over the age of 45. This study included the older population (18-65) in the intervention and analyses. This is a particularly relevant question from a policy perspective. Recent economic problems and policy changes have led to the consideration of extending EI to this population in the UK and the ‘Early Intervention Access and Waiting Time Standard’ published in 2016 specifically states that the target population should be people aged 14-65. ADDIN EN.CITE <EndNote><Cite><Author>NHS England</Author><Year>2016</Year><IDText>Implementing the Early Intervention in Psychosis Access and Waiting Time Standard: Guidance</IDText><DisplayText>(26)</DisplayText><record><isbn>Reference 04294</isbn><titles><title>Implementing the Early Intervention in Psychosis Access and Waiting Time Standard: Guidance</title></titles><contributors><authors><author>NHS England, the National Collaborating Centre for Mental Health and the National Institute for Health and Care Excellence</author></authors></contributors><edition>Reference 04294</edition><added-date format="utc">1481991836</added-date><ref-type name="Government Document">46</ref-type><dates><year>2016</year></dates><rec-number>1118</rec-number><publisher>NHS England Publications Gateway</publisher><last-updated-date format="utc">1481992105</last-updated-date><contributors><secondary-authors><author>NHS England, the National Collaborating Centre for Mental Health and the National Institute for Health and Care Excellence</author></secondary-authors></contributors></record></Cite></EndNote>(26)The NB approach was useful in this context, as it facilitated evaluation of sub-groups in which an intervention is potentially more or less cost-effective. In this study, the subgroups were identified a priori for policy reasons. Internationally, many EIP services restrict by age (usually 15-35) and by diagnosis (usually functional psychosis). Delivering EI to the functional psychosis SSD sub-group was highly cost-effective from both a health sector and a societal perspective. This was most likely due to the fact that the proportion of relapses was higher in this subgroup in the TAU cohort (0.18 v. 0.10). As the NB is affected more by costs when the effect size approaches zero, a bigger effect size in this sub-group demonstrated a different INB profile. In contrast, the evaluation of the 18-35 subgroup in this setting, revealed that EI was less likely to be cost-effective from the health sector perspective. The INB favoured traditional CMHT until the willingness to pay for the intervention was over €15,000 per relapse avoided. By contrast, there was an INB from the societal perspective even when the value of λ or willingness to pay was €0. There are policy implications to this finding, as delivering EI in a setting with no youth model of mental health, such as in countries like Ireland with a strict boundary between CAMS and adult MHS; may have no benefit from the perspective of the health payer. The youth model of mental health delivers EI across this boundary, usually across an age range of 14-25 years. This makes sense from a theoretical perspective, as this range of ages is the peak time for the potential onset of mental health disorders in the developing adolescent and young adult brain. Therefore, when examining the cost-effectiveness of delivering EI to a youth sub-group attending an adult EI service, the data suggest that EI is not cost-effective. The final subgroup analysis tested the effect of including people with organic psychosis, or psychosis secondary to a general medical condition (GMC). Internationally, research on FEP and services delivering EI typically excludes people presenting with organic psychosis. A case can be made that people with psychosis secondary to a GMC will still present to EI services, and the costs of treating them can still be incurred, as in a real world setting it is not always immediately apparent that the cause of psychosis is medical rather than functional. These cases can generate high costs and the effect of EI is uncertain, as the psychosis is often resolved by treating the underlying medical condition. Health economic analyses are usually concerned with the mean value, as this allows policy makers, service planners and decision makers to consider the total cost and effect of an intervention, rather than the median which is not subject to interpretation in a meaningful way. In this sample, despite the total number presenting with an organic psychosis being small - seven over three years of whom four were followed up and were eligible for inclusion as a sensitivity analysis of this study- there was a substantial impact on the results of the analysis. The marked change in the INB by excluding four cases from the analysis also illustrates the degree of uncertainty associated with cost data, and this uncertainty should be taken into account when presenting this information to service planners and policy makers.There are a number of strengths to this study. Previous studies of EI have compared EI to older models of TAU. This TAU cohort received best practice community mental health care, including HBT and assertive community outreach, all models of care designed to deliver acute care in the community where that is appropriate. This study also used robust methodology for the case finding and evaluation of people presenting with a FEP. While one of the two private hospitals in Ireland which may have admitted people with a FEP from any of the five catchment areas was not contacted, the other private hospital was situated in one of the catchment areas covered by the study. Otherwise, both samples are epidemiological samples of FEP presenting to community mental health services in the five catchment areas included in the study. Each person attending the EI service received a comprehensive diagnostic interview and assessment by trained assessors with good inter-rater reliability. Of those presenting to the TAU catchment area, 80% were assessed at baseline with a comprehensive diagnostic interview and assessment by trained assessors, also with good inter-rater reliability. The patient-level direct and indirect costs included in this study were collected in a structured, standardised manner. As a year is a long time for patient recall with the CSSRI, the information provided by patients was supplemented by corroborating it with information on resource use from medical records and by contacting primary care practices. Evidence shows that using patient recall alone underestimates resource use and therefore costs. ADDIN EN.CITE <EndNote><Cite><Author>Gillespie</Author><Year>2016</Year><IDText>A comparison of medical records and patient questionnaires as sources for the estimation of costs within research studies and the implications for economic evaluation</IDText><DisplayText>(27)</DisplayText><record><dates><pub-dates><date>Sep</date></pub-dates><year>2016</year></dates><urls><related-urls><url> comparison of medical records and patient questionnaires as sources for the estimation of costs within research studies and the implications for economic evaluation</title><secondary-title>Fam Pract</secondary-title></titles><contributors><authors><author>Gillespie, P.</author><author>O'Shea, E.</author><author>Smith, S. M.</author><author>Cupples, M. E.</author><author>Murphy, A. W.</author></authors></contributors><language>ENG</language><added-date format="utc">1478351243</added-date><ref-type name="Journal Article">17</ref-type><rec-number>1084</rec-number><last-updated-date format="utc">1478351243</last-updated-date><accession-num>27587565</accession-num><electronic-resource-num>10.1093/fampra/cmw088</electronic-resource-num></record></Cite></EndNote>(27)With regard to potential limitations, the study design is not as robust as that of an RCT and there are potential sources of observed and unobserved bias. While not an RCT, the use of two comparative incidence-based cohorts in a well-defined population with regression analysis to control for observed population differences, can facilitate the evaluation of complex interventions in a real world setting and may have more generalisability. ADDIN EN.CITE <EndNote><Cite><Author>Lamont</Author><Year>2016</Year><IDText>New approaches to evaluating complex health and care systems</IDText><DisplayText>(28)</DisplayText><record><urls><related-urls><url> approaches to evaluating complex health and care systems</title><secondary-title>BMJ</secondary-title></titles><pages>i154</pages><contributors><authors><author>Lamont, T.</author><author>Barber, N.</author><author>Pury, J.</author><author>Fulop, N.</author><author>Garfield-Birkbeck, S.</author><author>Lilford, R.</author><author>Mear, L.</author><author>Raine, R.</author><author>Fitzpatrick, R.</author></authors></contributors><language>eng</language><added-date format="utc">1457383521</added-date><ref-type name="Journal Article">17</ref-type><dates><year>2016</year></dates><rec-number>912</rec-number><last-updated-date format="utc">1457383521</last-updated-date><accession-num>26830458</accession-num><volume>352</volume></record></Cite></EndNote>(28) There was potential sample bias as there were observed and potentially unobserved differences between the two cohorts. The TAU cohort was younger, and from a predominantly rural and more deprived setting with higher levels of unemployment. The EI cohort was a mixture of individuals from a predominantly affluent area with a relatively older population and a smaller proportion from deprived areas and rural areas. Using the NB framework to conduct the cost-effectiveness analysis allowed adjusting for differences in the socio-demographic and catchment area level characteristics in the analysis. Propensity score matching can be used to simulate the conditions of an RCT design. ADDIN EN.CITE <EndNote><Cite><Author>Heckman</Author><Year>1998</Year><IDText>Matching as an Econometric Evaluation Estimator</IDText><DisplayText>(29)</DisplayText><record><urls><related-urls><url>, 1467937X</isbn><custom1>Full publication date: Apr., 1998</custom1><titles><title>Matching as an Econometric Evaluation Estimator</title><secondary-title>The Review of Economic Studies</secondary-title></titles><pages>261-294</pages><number>2</number><contributors><authors><author>Heckman, James J.</author><author>Ichimura, Hidehiko</author><author>Todd, Petra</author></authors></contributors><added-date format="utc">1461690214</added-date><ref-type name="Journal Article">17</ref-type><dates><year>1998</year></dates><rec-number>962</rec-number><publisher>[Oxford University Press, Review of Economic Studies, Ltd.]</publisher><last-updated-date format="utc">1461690445</last-updated-date><volume>65</volume></record></Cite></EndNote>(29) However, the optimal conditions for use of matching usually require more observations in the control group than the treatment group. In this case there were more observations in the treatment group than the control group and this excluded a large number of people from the analysis as they did not have a match. Therefore the propensity score was used as a covariate in the initial analysis; however as this did not yield any extra information in comparison to including the covariates themselves, the score was not ultimately included in the final model. Rather, the NB approach was used, facilitating the use of regression to control for observed differences between the groups. There are also unobserved differences between the two groups that are not included. The unit cost data in the study are from a variety of sources as there are no published national sources of unit cost data in Ireland. While considerable time and resources were devoted to generating the unit costs used in this study, there are still some unit costs lacking and some were incomplete, possibly leading to an underestimate of the cost information. This is particularly relevant in the intervention cost which did not include capital costs or non-contact costs. The lack of published national unit costs limits the ability to compare studies of this type as the cost data may differ by study. The primary outcome used for this study was limited to one that could be reliably extracted from the clinical records at one year, a limitation of the study which was imposed by the pragmatic difficulties of doing research in a real world setting. The gold standard outcome measure of choice in economic evaluations is the quality adjusted life year (QALY), which has accepted values of willingness to pay per QALY improvement in different health settings internationally. ADDIN EN.CITE <EndNote><Cite><Author>Drummond</Author><Year>2015</Year><IDText>Methods for the Economic Evaluation of Health Care Programmes</IDText><DisplayText>(8)</DisplayText><record><keywords><keyword>Medical care Cost effectiveness.</keyword><keyword>Medical care, Cost of Evaluation.</keyword><keyword>Health Services economics [MESH]</keyword><keyword>Economics, Medical [MESH]</keyword></keywords><isbn>0198529449
0198529457
9780198529446
9780198529453</isbn><titles><title>Methods for the Economic Evaluation of Health Care Programmes</title><secondary-title>Oxford Medical Publications</secondary-title></titles><pages>x, 445 p.</pages><call-num>RA410.5
RA410.5 .D77</call-num><contributors><authors><author>Drummond, Michael F.</author><author>Sculpher, Mark J.</author><author>Claxton, Karl</author><author>Stoddart Greg L.</author><author>Torrance, George W.</author></authors></contributors><section>1-445</section><edition>4rd</edition><added-date format="utc">1403023879</added-date><pub-location>Oxford, England</pub-location><ref-type name="Book">6</ref-type><dates><year>2015</year></dates><rec-number>258</rec-number><publisher>Oxford University Press</publisher><last-updated-date format="utc">1468680053</last-updated-date><contributors><secondary-authors><author>Oxford University Press</author></secondary-authors></contributors></record></Cite></EndNote>(8) The primary outcome used in this study has some limitations. Relapse requiring admission or HBT does not have a defined societal threshold ratio or value of WTP. However; relapse has a significant impact on outcome. Relapse limits recovery and is distressing for the participant and their family and carers, and is a significant predictor of costs. Between 30 and 70% of people with FEP will relapse. ADDIN EN.CITE <EndNote><Cite><Author>Addington</Author><Year>2007</Year><IDText>Relapse rates in an early psychosis treatment service</IDText><DisplayText>(30)</DisplayText><record><dates><pub-dates><date>01</date></pub-dates><year>2007</year></dates><urls><related-urls><url> rates in an early psychosis treatment service
Acta Psychiatrica Scandinavica Volume 115, Issue 2</title><secondary-title>Acta Psychiatrica Scandinavica</secondary-title></titles><pages>126-131</pages><number>2</number><contributors><authors><author>Addington, D.</author><author>Addington, M. D. Jean</author><author>Patten, S.</author></authors></contributors><added-date format="utc">1421336003</added-date><ref-type name="Electronic Article">43</ref-type><rec-number>738</rec-number><last-updated-date format="utc">1421336033</last-updated-date><volume>115</volume></record></Cite></EndNote>(30) There is a significant cost difference between those who relapse and require admission and those who do not require admission, one study finding a cost difference of ?6,000 between those who did not relapse requiring admission (?2,000) and those who did (?8,000), and we used this figure as a benchmark for willingness to pay to avoid relapse. ADDIN EN.CITE <EndNote><Cite><Author>Almond</Author><Year>2004</Year><IDText>Relapse in schizophrenia: costs, clinical outcomes and quality of life</IDText><DisplayText>(31)</DisplayText><record><dates><pub-dates><date>Apr</date></pub-dates><year>2004</year></dates><keywords><keyword>Adult</keyword><keyword>Cost of Illness</keyword><keyword>England</keyword><keyword>Epidemiologic Methods</keyword><keyword>Female</keyword><keyword>Health Care Costs</keyword><keyword>Hospitalization</keyword><keyword>Humans</keyword><keyword>Male</keyword><keyword>Middle Aged</keyword><keyword>Outcome Assessment (Health Care)</keyword><keyword>Prognosis</keyword><keyword>Psychiatric Status Rating Scales</keyword><keyword>Quality of Life</keyword><keyword>Recurrence</keyword><keyword>Schizophrenia</keyword><keyword>Socioeconomic Factors</keyword></keywords><urls><related-urls><url> in schizophrenia: costs, clinical outcomes and quality of life</title><secondary-title>Br J Psychiatry</secondary-title></titles><pages>346-51</pages><contributors><authors><author>Almond, S.</author><author>Knapp, M.</author><author>Francois, C.</author><author>Toumi, M.</author><author>Brugha, T.</author></authors></contributors><language>ENG</language><added-date format="utc">1478352425</added-date><ref-type name="Journal Article">17</ref-type><rec-number>1094</rec-number><last-updated-date format="utc">1478352425</last-updated-date><accession-num>15056580</accession-num><volume>184</volume></record></Cite></EndNote>(31) While relapse is a pertinent outcome, this is also a potential limitation of the study, as in-patient admission and HBT are both components of cost. There was potential selection bias in the one year follow-up data. Due to differences in the ethical approval from each ethics committee, the tracing procedures in each cohort were different. Not all of the eligible EI sample was followed up at one year, while almost all the TAU sample had follow-up at one year either by clinical interview or by using medical records. The impact of this potential selection bias was tested by examining the total sample in the reference case analysis, and then by re-conducting the analysis only in those followed up by clinical interview in both samples, to test the assumptions. There were no statistically significant different socio-demographic or clinical characteristics between those followed up by clinical interview and those followed up by clinical record. Specifically, there was no statistically significant difference in the primary outcome measure. There were some differences in the cost data, and therefore in the NB statistic in the repeat analysis. The probability that EI was cost-effective shifted down and to the right; however the trajectory of the NB statistic remained the same. As previously alluded to, the literature suggests that patient reports of health service resource use are often higher than resource use taken from medical records, so this suggests that the cost data in the overall sample is an underestimate of the costs in the TAU group rather than an over-estimate. ConclusionThis study adds to the evidence base on the economic evaluation of EI in psychosis. Use of patient-level data from a mix of urban and rural settings, evaluation of an intervention taking place in a real world setting and extensive consideration of the context in which the study took place provide additional insights into how EI services make their impact. Previous research has found that EI makes its cost savings by reducing inpatient admissions. Modelling studies have shown that the societal impact of EI is larger than its impact on the health sector through the effects EI has on employment and education. ADDIN EN.CITE <EndNote><Cite><Author>Park</Author><Year>2014</Year><IDText>Early intervention for first‐episode psychosis: Broadening the scope of economic estimates</IDText><DisplayText>(24)</DisplayText><record><keywords><keyword>decision modelling</keyword><keyword>economics</keyword><keyword>employment</keyword><keyword>psychotic disorder</keyword><keyword>suicide</keyword><keyword>No terms assigned</keyword></keywords><urls><related-urls><url> intervention for first‐episode psychosis: Broadening the scope of economic estimates</title><secondary-title>Early Intervention in Psychiatry</secondary-title></titles><contributors><authors><author>Park, A‐La</author><author>McCrone, Paul</author><author>Knapp, Martin</author></authors></contributors><added-date format="utc">1410195320</added-date><pub-location>United Kingdom</pub-location><ref-type name="Journal Article">17</ref-type><dates><year>2014</year></dates><remote-database-provider>EBSCOhost</remote-database-provider><rec-number>446</rec-number><publisher>Wiley-Blackwell Publishing Ltd.</publisher><last-updated-date format="utc">1420769048</last-updated-date><accession-num>2014-17487-001</accession-num><electronic-resource-num>doi:?10.1111/eip.12149</electronic-resource-num><remote-database-name>psyh</remote-database-name></record></Cite></EndNote>(24) This study has provided evidence using patient-level data that EI, delivered in a real world setting, in a mental health system which has no youth oriented specialist EI service, can still provide a modest INB to the health sector even when the value of preventing a relapse requiring admission is unknown, and shows that EI has a large INB and is extremely likely to be cost-effective when a societal perspective is taken. As mental health interventions will often impact on outcomes outside the health service such as employment, housing and education, policy makers and service planners should be aware of this, and consider alternate sources of funding mental health interventions as benefits accrue beyond the health service. Source of funding:This study was funded by a Health Research Board (HRB) Grant HPF-2011-042. There was no other source of funding and no conflict of interests to report. The PI of the HRB grant also worked in the EI service.References ADDIN EN.REFLIST 1.Mihalopoulos C, McGorry PD, Carter RC. Is phase-specific, community-oriented treatment of early psychosis an economically viable method of improving outcome? Acta Psychiatr Scand. 1999; 100(1): 47-55.2.Mihalopoulos C, Harris M, Henry L, Harrigan S, McGorry P. Is early intervention in psychosis cost-effective over the long term? Schizophr Bull. 2009; 35(5): 909-18.3.Hastrup LH, Kronborg C, Bertelsen M, Jeppesen P, Jorgensen P, Petersen L, et al. Cost-effectiveness of early intervention in first-episode psychosis: economic evaluation of a randomised controlled trial (the OPUS study). Br J Psychiatry. 2013; 202(1): 35-41.4.McCrone P, Craig TK, Power P, Garety PA. Cost-effectiveness of an early intervention service for people with psychosis. Br J Psychiatry. 2010; 196(5): 377-82.5.Castle DJ. The truth, and nothing but the truth, about early intervention in psychosis. Aust N Z J Psychiatry. 2012; 46(1): 10-3.6.Bosanac P, Patton GC, Castle DJ. Early intervention in psychotic disorders: faith before facts? Psychol Med. 2010; 40(3): 353-8.7.Hoch JS, Briggs AH, Willan AR. Something old, something new, something borrowed, something blue: a framework for the marriage of health econometrics and cost-effectiveness analysis. Health Econ. 2002; 11(5): 415-30.8.Drummond MF, Sculpher MJ, Claxton K, L. SG, Torrance GW. Methods for the Economic Evaluation of Health Care Programmes. Oxford University Press, 2015.9.Husereau D, Drummond M, Petrou S, Carswell C, Moher D, Greenberg D, et al. Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement. BMJ. 2013; 346: f1049.10.First MB, Spitzer RL, Gibbon M, Williams JB. Structured Clinical Interview for DSM-IV-TR Axis I Disorders, Research Version, Non-Patient Edition (SCID-I/NP). In: Biometrics Research (ed NYSP Institute): 2002.11.Knapp M, Beecham J. Costing mental health services. Psychol Med. 1990; 20(4): 893-908.12.Chisholm D, Knapp MR, Knudsen HC, Amaddeo F, Gaite L, van Wijngaarden B. Client Socio-Demographic and Service Receipt Inventory--European Version: development of an instrument for international research. EPSILON Study 5. European Psychiatric Services: Inputs Linked to Outcome Domains and Needs. Br J Psychiatry Suppl. 2000; (39): s28-33.13.Curtis L. Unit Costs of Health and Social Care 2012. (ed PRSSU). Personal Social Services Research Unit, 2012.14.Office CS. Statistical Yearbook of Ireland. Central Statistics Office, 2012.15.IRIS. IRIS Guidelines Update. In: IRIS (2012) IRIS Guidelines Update IRIS Initiative Ltd wwwiris-initiativeorguk. IRIS Initiative Ltd., 2012.16.Mihalopoulos C, Harris M, Henry L, Harrigan S, McGorry P. Is Early Intervention in Psychosis Cost-Effective Over the Long Term? Schizophrenia Bulletin. 2009; 35(5): 909-18.17.Cullberg J, Mattsson M, Levander S, Holmqvist R, Tomsmark L, Elingfors C, et al. Treatment costs and clinical outcome for first episode schizophrenia patients: a 3-year follow-up of the Swedish "Parachute Project" and two comparison groups. Acta Psychiatr Scand. 2006; 114(4): 274-81.18.Goldberg K, Norman R, Hoch JS, Hoch J, Schmitz N, Windell D, et al. Impact of a specialized early intervention service for psychotic disorders on patient characteristics, service use, and hospital costs in a defined catchment area. Can J Psychiatry. 2006; 51(14): 895-903.19.Wong KK, Chan SKW, Lam MML, Hui CLM, Hung SF, Tay M, et al. Cost-effectiveness of an early assessment service for young people with early psychosis in Hong Kong. Australian and New Zealand Journal of Psychiatry. 2011; 45(8): 673-80.20.Behan C, Cullinan J, Kennelly B, Turner N, Owens E, Lau A, et al. Estimating the Cost and Effect of Early Intervention on In-Patient Admission in First Episode Psychosis. J Ment Health Policy Econ. 2015; 18(2): 57-62.21.Cocchi A, Mapelli Vi, Meneghelli A, Preti A. Cost-effectiveness of treating first-episode psychosis: five-year follow-up results from an Italian early intervention programme. Early Intervention in Psychiatry. 2011; 5(3): 203-11.22.Serretti A, Mandelli L, Bajo E, Cevenini N, Papili P, Mori E, et al. The socio-economical burden of schizophrenia: A simulation of cost-offset of early intervention program in Italy. European Psychiatry. 2009; 24(1): 11-6.23.McCrone P, Knapp M, Dhanasiri S. Economic impact of services for first-episode psychosis: a decision model approach. Early Interv Psychiatry. 2009; 3(4): 266-73.24.Park AL, McCrone P, Knapp M. Early intervention for first‐episode psychosis: Broadening the scope of economic estimates. Early Intervention in Psychiatry. 2014.25.Tsiachristas A, Thomas T, Leal J, Lennox BR. Economic impact of early intervention in psychosis services: results from a longitudinal retrospective controlled study in England. BMJ Open. 2016; 6(10): e012611.26.NHS England tNCCfMHatNIfHaCE. Implementing the Early Intervention in Psychosis Access and Waiting Time Standard: Guidance. (ed tNCCfMHatNIfHaCE NHS England). NHS England Publications Gateway, 2016.27.Gillespie P, O'Shea E, Smith SM, Cupples ME, Murphy AW. A comparison of medical records and patient questionnaires as sources for the estimation of costs within research studies and the implications for economic evaluation. Fam Pract. 2016.28.Lamont T, Barber N, Pury J, Fulop N, Garfield-Birkbeck S, Lilford R, et al. New approaches to evaluating complex health and care systems. BMJ. 2016; 352: i154.29.Heckman JJ, Ichimura H, Todd P. Matching as an Econometric Evaluation Estimator. The Review of Economic Studies. 1998; 65(2): 261-94.30.Addington D, Addington MDJ, Patten S. Relapse rates in an early psychosis treatment serviceActa Psychiatrica Scandinavica Volume 115, Issue 2. In: Acta Psychiatrica Scandinavica: 126-312007.31.Almond S, Knapp M, Francois C, Toumi M, Brugha T. Relapse in schizophrenia: costs, clinical outcomes and quality of life. Br J Psychiatry. 2004; 184: 346-51. ................
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