Measuring quality of care with routine data: avoiding confusion between performance indicators and health outcomes

Objective To investigate the impact of factors outside the control of prima ry care on performance indicators proposed as measures of the quality of pr imary care. Design Multiple regression analysis relating admission rates standardised f or age and sex for asthma, diabetes, and epilepsy to socioeconomic populati on characteristics and to the supply of secondary care resources. Setting 90 family health services authorities in England, 1989-90 to 1994-5 . Results At health authority level socioeconomic characteristics, health sta tus, and secondary care supply factors explained 45% of the variation in ad mission rates for asthma, 33% for diabetes, and 55% for epilepsy. When heal th authorities were ranked, only four of the 10 with the highest age-sex st andardised admission rates for asthma in 1994-5 remained in the top 10 when allowance was made for socioeconomic characteristics, health status, and s econdary care supply factors. There was also substantial year to year varia tion in the rates. Conclusion Health outcomes should relate to crude rates of adverse events i n the population. These give the best indication of the size of a health pr oblem. Performance indicators, however, should relate to those aspects of c are which can be altered by the staff whose performance is being measured.