Internal Auditing in Homecare - HCCA Official Site
Tips and Tricks for Internal Auditing in the Home Care Industry
In a nutshell, get to know your systems and the data contained within it.
Internal Auditing for a Home Care provider can be a challenging and rewarding career. However, given the voluminous nature of the individual daily transactions (e.g. visit notes) indicative of our industry, you are going to need help in order to cost effectively audit a substantial portion of your organization’s significant risks. Assistance can be your PC and the programs probably already installed on it.
Most computer systems today capture endless pieces of data concerning every element of the home care encounter. From referral information, insurance verification, visit billing and payroll generation through cash application and contractual allowance write-off, the computer is a huge digital warehouse of data – often presented one patient at a time. Obtaining useful management/audit/investigative information, in a summarized manner, is another story.
The computer can be a valuable tool to analyze reams of data, in more ways and much more efficiently than you could ever do by hand. However, most computer systems in the healthcare industry are antiquated and inflexible for obtaining customized information needed for specialized purposes, such as a billing review or a potential fraud investigation. However, with a basic understanding of mathematical logic and tools such as Microsoft Excel, Microsoft Access, the Office of Inspector General’s “Rat-Stat” statistical sampling program and a good data conversion utility such as Monarch, raw data can be downloaded directly from a mainframe or minicomputer system and manipulated to perform almost any need.
By obtaining all transactions across a branch or enterprise wide, you can quickly examine up to 100% of an identified activity. By using data analysis to validate conflicts, identify unusual patterns and create unique summaries, you can potentially perform Internal Audit related reviews such as the following examples:
1. Analyze dates and times of patient care on visit notes to detect potentially overlapping visits and duplicate charges to payors.
2. Analyze dates and times and address of patient care to determine compliance with any “subsequent visit” patient discount requirements prevalent in Medicaid programs.
3. Extract data for use in summarizing and complying with regulatory required reporting needs.
4. Analyze a history of Accounts Receivable adjustments and determine at what account balance level an automatic write-off makes fiscal sense.
5. Ensure contractual allowances have been applied to the net realizable accounting value of each invoice to avoid inadvertently overstating revenue and receivables.
6. Extract and analyze payments made to caregivers for on-call services and note excessive payments.
7. Analyze collector productivity and days spent between follow-up efforts.
8. Analyze timeliness of and compliance with credit balance refund requirements to federally funded health programs.
9. Analyze and compare homebound status indicators on the OASIS data collection set to information contained in a patient’s Plans of Care.
10. Analyze the referrals made to other providers and whether standards of first contact/first visit are being met.
11. For centralized intake facilities, ascertain if standards of insurance verification, eligibility and authorization processes are performed within management’s desired timeframes.
12. Analyze patient’s payment habits such as credit card usage versus manual payments via check.
13. Analyze Accounts Payable vouchers for duplicate, excessive or non-allowable travel, entertainment or marketing expenses.
14. Detection of and quantification of fraud by the potential use of non-billable payroll codes.
When performing the more traditional audit of a limited sample size, for instance, having to actually view the visit notes for the appropriateness of clinical documentation and existence of patient signatures, using a statistically valid sample is best. In this scenario, a download of all possible transactions in the population should be imported into a spreadsheet. Rat-Stat could be used to easily generate a statically valid and randomly selected list of transactions that require examination. If your sample ever becomes the focus of or is the result of a governmental mandate, you will need to perform statistic sampling and report errors using this tool. Download it from .
By extracting data at its most basic level (such as per visit or shift), you can sort and summarize it in ways not possible given the limitations of preconfigured reports. For a larger organization with multiple branch locations, this is a useful feature to validate and test the effects of potential management decisions with enterprise-wide implications.
Excel is a powerful and easy to use program for filtering data and creating nested “IF” formulas that compare fields of data to each other. The “Data, Filter, AutoFilter” command is another simple but powerful query to summarize data. You can use it in conjunction with the “SUBTOTAL” function to quickly count and sum possible assertions on the fly. However, should your data exceed 66,000 records, you will need to use Access due to row limitations within Excel. While Access is more difficult to use initially, its strength is apparent in creating customized sorts and queries from multiple sources of data tables. It is well worth the investment in a class or two if you find yourself with these needs. However, output Access data into Excel whenever possible for printing purposes, it’s just much easier to generate reports this way.
However, before you can rely on raw data coming out a computer system, it’s important to test and validate the underlying transactions. This relates to our most often used, proactive audit suggestion, creating hard computer edits within data entry. It’s an overused cliché but “garbage in, garbage out” really applies in Healthcare. There is nothing more frustrating than spending several hours extracting and analyzing 100,000 billing records only to discover five variations on each patient’s address due to spelling inconsistencies or absent naming conventions. If you really want to prevent billing problems because of unknown social security numbers entered into the system as “999-99-9999”, create hard edits in the computer system to force compliance during all data entry phases. Otherwise, employees can (and will) purposely and inadvertently circumvent data entry at times. It’s always best to fix mistakes upfront.
Monies invested in programming the proper edits into your computer system upfront will return huge labor saving, policy compliance and billing efficiency dividends in the future. These are the Internal Auditor’s (and the Company’s) best friend. Have your Internal Audit function constantly scan for new and improved computer edits during their operational audits.
Mark Tumolo, CPA
Director of Internal Audit
Gentiva Health Services
Melville, NY
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