PubMed · 10175892
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A J Slomski. 1998-01-26. How much are groups paying doctors?. https://pubmed.ncbi.nlm.nih.gov/10175892/
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OBJECTIVE: To develop Clinical Risk Groups (CRGs), a claims-based classification system for risk adjustment that assigns each individual to a single mutually exclusive risk group based on historical clinical and demographic characteristics to predict future use of healthcare resources. STUDY DESIGN/DATA SOURCES: We developed CRGs through a highly iterative process of extensive clinical hypothesis generation followed by evaluation and verification with computerized claims-based databases containing inpatient and ambulatory information from 3 sources: a 5% sample of Medicare enrollees for years 1991-1994, a privately insured population enrolled during the same time period, and a Medicaid population with 2 years of data. RESULTS: We created a system of 269 hierarchically ranked, mutually exclusive base-risk groups (Base CRGs) based on the presence of chronic diseases and combinations of chronic diseases. We subdivided Base CRGs by levels of severity of illness to yield a total of 1075 groups. We evaluated the predictive performance of the full CRG model with R2 calculations and obtained values of 11.88 for a Medicare validation data set without adjusting predicted payments for persons who died in the prediction year, and 10.88 with a death adjustment. A concurrent analysis, using diagnostic information from the same year as expenditures, yielded an R2 of 42.75 for 1994. CONCLUSION: CRGs performance is comparable to other risk adjustment systems. CRGs have the potential to provide risk adjustment for capitated payment systems and management systems that support care pathways and case management.
This paper studies the relationship between health status and insurance participation, and between insurance status and medical use in the context of a social health insurance with an equalization fund (SHIEF). Under this system, revenues from a mandatory payroll tax are collected into a single pool (equalization fund) that reimburses for-profit insurance companies according to a capitated formula. Although competition should induce insurers to control costs without reducing the quality of service necessary to attract consumers, limitations in the capitation formula might induce insurers to select against bad risks, and limitations in the contribution system might induce more healthy individuals to evade enrollment. A three-equation model having social health insurance, private health insurance, and using medical services is estimated using a 1997 Colombian household survey. Consistent with similar studies, participation in SHIEF increases medical care use. On the other hand, the evidence on selection is somewhat mixed: individuals who report good health status are more likely to participate in SHIEF, while those without a chronic condition are less likely to participate in SHIEF.