Biomedical subjects

Jeff Beich

Publications and source records attributed to Jeff Beich.

3 recordsLinked to original sources

PubMed2006

The role of disease management in pay-for-performance programs for improving the care of chronically ill patients.

To date, pay-for-performance programs targeting the care of persons with chronic conditions have primarily been directed at physicians and provide an alternative to health plan-sponsored chronic disease management (DM) programs. Both approaches require similar infrastructure, and each has its own advantages and disadvantages for program implementation. Pay-for-performance programs use incentives based on patient outcomes; however, an alternative system might incorporate measures of structure and process. Using a conceptual framework, the authors explore the variation in 50 diabetes DM programs using data from the 2002 National Business Coalition on Health's eValue8 Request for Information (RFI). The authors raise issues relevant to the assignment of accountability for patient outcomes to either health plans or physicians. They analyze the association between RFI scores measuring structures and processes, and HEDIS diabetes intermediate outcome measures. Finally, the strengths and weaknesses of using the RFI scores as an alternative metric for pay-for-performance programs are discussed.

Chronic Disease↗

PubMed2003

Determining the value of disease management programs.

BACKGROUND: Increasing prevalence, rising costs, and persisting deficiencies in quality of care for chronic diseases pose economic and policy challenges to providers and purchasers. Disease management (DM) programs may address these challenges, but neither purchasers nor providers can assess their value. The potpourri of current quality indicators provides limited insight into the actual clinical benefit achieved. A conference sponsored by the Agency for Healthcare Research and Quality (AHRQ) and held in October 2002 explored new approaches to measuring and reporting the value of DM for diabetes mellitus. RESULTS: Quantifying the value of DM requires measuring clinical benefit and net impact on health care costs for the entire population with diabetes. If quality is measured with indicators that are clearly linked to outcomes, clinical benefit can be estimated. Natural history models combine the expected benefits of improvements in multiple indicators to yield a single, composite measure, the quality-adjusted life-year. Such metrics could fairly express, in terms of survival and complications prevention, relatively disparate DM programs' benefits. Measuring and comparing health care costs requires data validation and appropriate case-mix adjustment. Comparing value across programs may provide more accurate assessments of performance, enhance quality improvement efforts within systems, and contribute generalizable knowledge on the utility of DM approaches. CONCLUSIONS: Conference attendees recommended pilot projects to further explore use of natural history models for measuring and reporting the value of DM.

Chronic Disease↗

PubMed2002

Measuring outcomes of type 2 diabetes disease management program in an HMO setting.

BACKGROUND: There is a need to evaluate empirical disease management programs used in managing chronic diseases such as diabetes mellitus in managed care settings. METHODS: We analyzed data from 252 patients with type 2 diabetes before and 1 year after enrollment in a disease management program. We examined clinical indicators such as HbA1C, HDL, LDL, total cholesterol, diastolic blood pressure, and BMI in addition to self-reported health status measured by SF-36 instrument. RESULTS: All clinical indicators showed statistically and clinically significant improvements. Only vitality and mental health showed statistically significant improvements in health status. Weak to moderate significant correlation between clinical indicators and health status was observed. CONCLUSIONS: Disease management can be effective at making significant clinical improvements for participants in a mixed-model HMO setting. No strong relationship between clinical indicators and health status was found. Future research is needed using a more specific health status measuring instrument and a randomized clinical trial design.

Adult↗