Primary Care

Socioeconomic inequalities in indicator scores for diabetes: poor quality or poor measures?

BMJ 2004; 329 doi: https://doi.org/10.1136/bmj.329.7477.1269 (Published 25 November 2004) Cite this as: BMJ 2004;329:1269
  1. P G Shekelle1, professor (shekelle{at}rand.org)
  1. 1 West Los Angeles Veterans Affairs Medical Center, 11301 Wilshire Blvd., Los Angeles, CA 90073, USA

    Hippisley-Cox et al report on scores for quality indicators for diabetes among a large number of UK patients and practices and how these vary depending on sex, ethnicity, and material deprivation.1 For many of the indicators, scores were worse for women and worse in practices with a high proportion of ethnic patients and those with high levels of material deprivation. This revelation of worse measures of care for women, poor people, and people from ethnic minority groups is not unique; there is a robust literature in America showing these same findings across numerous conditions,2 3 and similar findings have been reported in England.4 The question relevant to policy, particularly in light of the new general practitioner contract, is what do these differences in scores mean?

    In America, these differences are usually interpreted as meaning that lower scores denote poorer quality of care. Should the same be true in the United Kingdom? For the most part, I think the answer is yes. The exception is the four measures reported on by Hippisley-Cox et al that are outcomes (proportion of patients with HBA1C values under 7.5% or under 10%; blood pressure less than 145/85 mm Hg; serum cholesterol concentration less than 5 mmol/l). Although these are undoubtedly good outcomes to strive for (since they are strongly related to health outcomes such as fewer microvascular and macrovascular complications from diabetes), they are determined by many factors other than medical care. The problem of adjusting for case mix is one reason I do not generally favour the use of outcomes as comparative measures of quality.

    Most of the measures reported by the authors, however, are process measures, are almost or entirely under the control of the doctor or practice, and are much less sensitive to the need to adjust for differences in case mix. For example, only a scale and a tape measure are needed to record body mass index, but it was done significantly less often in women, poor people, and people from ethnic minority groups. This was also the case for flu vaccination. It is hard to explain these findings other than by poorer quality of care.

    So, what is to be done? I think that these data mostly show that women, poor people, and people from ethnic minority groups get poorer quality of care than do white men living in leafy areas. Some evidence shows that in the United Kingdom, financial incentives, such as those in the new general practitioner contract, will help reduce (although not eliminate) these disparities.5 I do, however, favour attempts to tweak the existing general practitioner contract to recognise that achieving the outcome targets will vary depending on where the practice is located. This could be done by weighting the payments for outcome indicators by some measure of deprivation. But this attempted tweak will come at a price: it will be more complex, for sure; it will precipitate arguments over who is deprived and how much extra the payment should be; and it may have unexpected consequences. Still, I believe the search for policy that best promotes quality, efficiency, and equity in health care is a dynamic one. The key here is both to perform adequate evaluations of the new general practitioner contract and to have policy makers who are willing to make changes when evidence accumulates that the policy is either not achieving its intended effect or producing unintended, and unwanted, side effects.

    Footnotes

    • Competing interests None declared.

    References

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