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Data file: Research conducted at Kaiser Permanente in Northern California reveals the high prevalence of cancer rates among the plan's seniors and offers some valuable cost benchmarks. Among the findings of interest to plans and providers at full risk: the average costs of the disease can run double or more the typical Medicare PMPM rate.
The Joint Commission's ORYX-PLUS option offers standardized measurement, risk adjustment, and reporting of outcomes not available in the less comprehensive ORYX program. This should create a wealth of truly comparable data against which to benchmark. There are additional costs: $2,500 to the Joint Commission, plus more expensive software and maintenance. This means the program is probably best suited for those systems that already have significant investments in information systems. As ORYX-PLUS eventually will issue performance report cards to the public on participants, there are the risks associated with disclosure. On the other hand, participating hospitals will be able to boast participation in a voluntary disclosure program aimed at excellence.
There are few regional or national benchmarking sources for home care agencies, but two new accreditation requirements--ORYX and OASIS--will build vast national databases. OASIS, an outcomes measurement survey required by the Health Care Financing Administration, promises a standardized measurement and reporting set. However, the home care industry is well behind hospitals in collecting, compiling, and reporting outcomes. Don't expect a national database before the year 2000.
Data Benchmarks: Why are hospitals so eager to snap up physician practices when they're losing so much money in the process? This month's column provides the details from a new survey on physician practice acquisition, plus some insights on what hospitals can do differently to keep dollars from going down the drain.
With the increase in fraud and abuse investigations, healthcare financial managers should examine their organization's medical record coding procedures. The Federal government and third-party payers are looking specifically for improper billing of outpatient services, unbundling of procedures to increase payment, assigning higher-paying DRG codes for inpatient claims, and other abuses. A recent benchmarking study of Medicare Provider Analysis and Review (MEDPAR) data has established national norms for hospital coding and case mix based on DRGs and has revealed the majority of atypical coding cases fall into six DRG pairs. Organizations with a greater percentage of atypical cases--those more likely to be scrutinized by Federal investigators--will want to conduct suitable review and be sure appropriate documentation exists to justify the coding.
Through the application of some basic statistical techniques, HIM professionals can assist in healthcare benchmarking and management at the organizational level. The author offers an example of how one hospital used data analysis to make decisions that promoted better patient care.
In this second part of our two-part series on mining hospital admissions data, Ronald Lagoe, executive director of the Hospital Executive Council, a four-hospital system in Syracuse, NY shows how admissions data readily available from various state agencies can be analyzed for patterns by age groups. As he points out below, this information will be particularly valuable as Medicare managed care takes over. For a discussion of data sources, methodology and analysis, see part one, beginning on p. 81 of the June Healthcare Benchmarks.
Consumer and employer demands, financial pressures, and accreditation requirements have propelled disease management into its own fledgling industry, but there is still no one-stop shop for information, at least not for free. Experts suggest using a disease management vendor's guaranteed savings, not the fee per patient, as a benchmark. Middle- to high-priced vendors are generally the most cost-effective. Factors that affect costs include your patient mix, the amount of risk you want the vendor to assume, and how many bells and whistles you want in your program.
The first article of this series highlighted the five most widely used performance measurement systems for comparing laboratory and clinical department operations. This column has since taken an in-depth tour of two of the systems, the MECON PEERx and the Laboratory Management Index Program. We also have taken a slight detour to discuss the ORYX initiative, which has been mandated for certain types of health-care organizations accredited by the Joint Commission. In this issue we return to a more detailed analysis of one of the five most commonly used benchmarking systems for clinical services, HBS International, Inc.
You need a range of national and local data to make your benchmarking successful: national to help you keep your finger on the pulse and local to help you differentiate your service. Never rely on national averages. Instead, find a better performer and study its processes to find out the reasons behind the data. No matter what your local situation is, you always can learn from someone else, particularly if they're different from you.
Plus, check out benchmark data on Medicare and Medicaid administrative costs. Every provider knows that HMOs take a slice of the Medicare or Medicaid premium for their administrative costs before they determine provider capitation. But how much does administration really cost? Here's some PMPM data from a study by the Sherlock Company.
The nation's best-performing hospitals, as determined by two healthcare management and consulting firms, still register results that separate them from the pack. The hospitals' successes are chronicled in 100 Top Hospitals: Benchmarks for Success, an annual analysis that uses nine measures of clinical, operational and financial performance to rate hospitals.
As HIM professionals look for ways to become more competitive and achieve the best results, the importance of discovering best practices becomes more apparent. Here's how one team used a benchmarking project to provide specific best practices that reduced accounts receivable days.
AIM: To determine whether a two pass audit cycle of diabetes complication screening improves screening rates. METHODS: General practitioners in North Canterbury were invited to participate in a diabetes complications screening audit. Key complication screening tasks and maximum screening intervals were agreed. Patients with diabetes were identified in the primary care setting. General practitioners were given the option of participating in group feedback sessions between the first and second passes of the audit cycle. RESULTS: 106 general practitioners and 2234 patients participated in the first pass. Ninety-three of these 106 general practitioners and 2169 patients participated in the second pass. Screening rates either improved or remained unchanged and a small improvement was seen in the study population's risk factor profile (i.e. total cholesterol and glycated haemoglobin). The group feedback sessions facilitated discussion on interpretation of results from the benchmarking exercise, the optimal time interval between screening procedures and the development of general practice diabetes data sets. CONCLUSION: This two pass primary care audit of diabetes complications screening resulted in improved screening rates for diabetes complications and a small improvement in the study population's risk factor profile.
Data Library: Compare your departmental expenses, administrative expense ratio, length of stay, and other clinical-financial data to benchmarks for your census region. A new CD-rom product that provides access to four years of Medicare Cost Report data for every reporting hospital in the nation allows users to slice and dice the data by more than 200 different performance measures.
Data-driven cardiac network improves outcomes, reduces costs. Thirty-seven high-volume network member hospitals are using detailed demographic, procedure, and outcomes data in benchmarking and marketing efforts, and network physicians are using the aggregate data on 120,000 angioplasty and bypass procedures in research studies. Here are the details, plus sample reports.
Data Library: Length-of-stay benchmarks by ICD-9, DRG codes, managed care vs. FFS. A new study comparing thousands of discharges within 57 different categories shows HMO lengths of stay similar to FFS. The data come from practicing surgeons' opinions and guidelines from actuarial firm Milliman & Robertson. See how your rates compare.
Data File: Here's some benchmark data on Medicare lengths of stay and average hospital charges from the Louisville, KY-based Data Advantage Corp. Providers can use the data to help determine their competitiveness and better assess discounts sought by Medicare risk plans.