Use of risk adjustment in setting budgets and measuring performance in primary care Ⅱ: advantages, disadvantages, and practicalities

摘要

Risk adjustment could help to improve decisions about budgets as well as help measure the performance of doctors. In the first of these two articles we discussed why risk adjustment could become more important in the United Kingdom and how it works in the United States. In this article we consider the benefits and problems of risk adjustment and assess how one US system would perform in the United Kingdom. In the United States, risk adjustment is starting to be used to adjust capitation or other types of payments to healthcare providers such as family practices, multi-specialty medical groups, or consortiums of physicians and hospitals (integrated delivery systems). For large populations (such as that of a broad geographical area), age, sex, and ecological measures may be adequate for this purpose. But for smaller populations, such as those managed by one family practice or a small consortium of physicians, risk adjustment helps ensure that providers who manage patients with more complex medical problems have their budgets adjusted to take this into account (box). The use of risk adjustment systems has also given doctors and health maintenance organisations a powerful incentive to provide more accurate and complete diagnostic data. The second important use of risk adjustment is to adjust for case mix when comparing practice patterns across providers. For example, the NHS plan states that it "promises better performance and accountability systems to reduce variations in service across England." The performance indicators published by the Department of Health show wide variation in performance among doctors in both primary and secondary care. However, as they do not take into account differences in case mix, we do not know how valid such indicators are as measures of clinical efficiency and efficacy. Risk adjustment can help correct such variations for underlying differences in population case mix and thus could lead to fairer and more accurate performance measures for providers.