Process versus outcome indicators in the assessment of quality of health care

TLDR

Outcome differences in health care arise from case mix, data collection, chance, and quality, and while process measures are sensitive and direct, outcome measures capture all aspects of care and are intrinsically more interesting. The paper reviews the strengths and weaknesses of outcome versus process performance indicators and proposes that standardizing data collection and developing validated case‑mix adjustment systems can improve outcome indicators. Outcome indicators are worthwhile only when health‑care variations can produce significant outcome differences and the outcome is common enough for detection; otherwise process measurement and risk‑management strategies are preferable.

Abstract

This paper reviews the relative strengths and weaknesses of outcome and process measures as performance indicators in health care. Differences in outcome may be due to case mix, how the data were collected, chance, or quality of care. Health care is only one determinant of health and other factors have important effects on health outcomes, such as nutrition, environment, lifestyle and poverty. The advantages of process measures are that they are more sensitive to differences in the quality of care and they are direct measures of quality. However, outcome measures are of greater intrinsic interest and can reflect all aspects of care, including those that are otherwise difficult to measure such as technical expertise and operator skill. Outcome indicators can be improved if efforts are made to standardize data collection and case mix adjustment systems are developed and validated. It is argued that this is worth doing only where it is likely that variations in health care might lead to significant variations in health outcome and where the occurrence of the outcome is sufficiently common that the outcome indicator will have the power to detect real differences in quality. If these conditions are not met, then alternative strategies such as process measurement and risk management techniques may be more effective at protecting the public from poor quality care.