- C Orchard
- National Casemix Office, Information Management Group of the NHS Executive, Winchester, Hampshire SO23 9JA.
Governments are increasingly concerned to compare the quality and effectiveness of healthcare interventions but find this a complex matter. Crude hospital statistics can be dangerously misleading and need adjusting for case mix, but identifying and weighting the patient characteristics which affect prognosis are problematical for conceptual, methodological, and practical reasons. These include the inherently uncertain nature of prognosis itself and the practical difficulties of collecting and quantifying data on the outcomes of interest for specific healthcare interventions and known risk factors such as severity.
Need for outcome measures
The combined pressures of “medical inflation,”1 fiscal constraints, and a shift in attitudes towards publicly funded services during the 1980s have made the search for measures of quality, efficiency, and effectiveness in health care a government priority in industrialised countries. Providers of health services are increasingly required to account for the resources they use. In order to do so they must devise ways of measuring the outcomes of their activities and the extent to which these meet specified objectives, be they medical, social, or financial.
The complexity of what hospitals do makes such measurement difficult even in the narrow specialty of acute care, not least because the resources used, the choice of treatments, and the observed results (Donabedian's structure, process, and outcome2) are so dependent on the sorts and conditions of patients admitted - the hospital “case mix.” Attempts to measure this to date have focused largely on resource consumption, by collating diagnosis and procedure codes in order to form groups which are homogeneous in costs (proxied by length of hospital stay). However, if comparisons of performance between hospitals are to be meaningful, diagnosis related groups or their English equivalents, healthcare resource groups, will have to be supplemented by measures of input and output. In other words, data about patients will need to be …
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