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Did pay-for-performance work in the UK?

February 15, 2010 in International Health Care Systems, P4P, Quality | No comments

A paper by Sutton, Elder Guthrie and Watt (2010) describes the UK’s National Health Service’s (NHS) adoption of the Quality and Outcomes Framework (QOF) in April 2004. In general, P4P programs can have positive or negative spillovers.  An example of a positive spillover would be the adoption of EMR to comply with certain P4P initiatives, but which also improves productivity in other areas.  A negative spillover would occur if physicians focus on getting the P4P bonuses, but decrease effort in unmeasured areas which could be more important to the patient’s health.

The authors describe the QOF more fully as follows:

In the first 2 years of the QOF scheme, practices were rewarded according to the performance they reported on 146 indicators. Through their performance on these indicators, practices earned up to 1050 QOF points. Practices were rewarded for these points according to a complex, non-linear function of the prevalence of disease in, and size of, their registered populations…An average practice was paid £75 per point in the first year and £125 per point in the second year of the scheme.

Seventy-six of the indicators, and 57% of the financial rewards, were offered for the quality of clinical care. These 76 indicators were focused on the care of people with 10 targeted chronic diseases and involved the maintenance of disease registers, the verification of diagnoses, the recording and management of risk factors and the provision of selected treatments. Points were awarded based on reported coverage rates if they were above a lower threshold of 25%. Maximum points were awarded if the coverage rate equalled or exceeded an upper threshold, which varied across indicators.

The authors examine whether the QOF increased effort levels for physician treatment of five groups of patients who had diseases for which physicians could earn QOF bonuses.  The paper also examines changes in quality for “Untargeted” patients, who did not have any diseases for which physicians could earn additional income under QOF.  The analysis is based on a before and after structure.  It evaluates the change in both quality metrics that were reimbursed under QOF and the quality metrics which were not subject to QOF bonuses.  If there are negative spillovers, one would expect the rewarded metrics would increase after QOF, but the unrewarded quality would decrease as physicians shift their priorities.

The paper finds that the effect on incentivized factors was substantially larger on the targeted patient groups (+19.9 percentage points) than on the untargeted groups (+5.3 percentage points).  The authors claim that there was no obvious evidence of effort diversion but there was evidence of substantial positive spillovers (+10.9 percentage points) onto non-incentivized factors for the targeted groups.

One issue here is that paper only looks at observable quality metrics.  The physician may believe that observable quality that is not currently rewarded will be rewarded in the future.  Thus, these positive spillovers may extend over to quality factors observable by the NHS.  On the other hand, unobserved quality may have decreased, but this would not have shown up in the econometric analysis.

  • Sutton, Elder Guthrie and Watt (2010) “Record rewards: the effects of targeted quality incentives on the recording of risk factors by primary care providers,” Health Economics, v19(1):1-13.

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Are Family Physicians good for you?

October 1, 2008 in Physician Compensation, Supply of Medical Services | Permalink

Does an increase in family physicians (FPs) increase individual health? A naive research might believe that we could uncover whether or not this was true by comparing the average health levels of areas with lots of doctors with the average health levels of areas with few doctors. However, doctors often work where there are lots of sick people. Thus we can find a spurious correlation between FP quantity and individual health level.

Gravelle, Morris and Sutton (HSR 2008) aim to find the true relationship between FP quantity and individual health. They use data from the Health Survey for England and the General Medical Services (GMS) Statistics database. The authors note that family physicians may be attracted to areas where healthy patients live if these areas have attractive amenities not captured in the data. On the other hand, FPs might be attracted to areas where lots of sick people live since FP compensation is based on an age-related capitation payment. The authors claim that the following 2 instruments will be correlated with physician supply but uncorrelated with individual patient health: semidetached house prices and age-related capitation payments.

In the first stage, Gravelle and co-authors find that a larger age-related capitation payment attracts more FPs while increased house price decreases FP supply. The authors conclude the following:

“FP supply is positively associated with individual self-assessed health. If no allowance is made for the endogeneity of FP supply, the effect is not statistically significant…When FP supply is instrumented by age-related capitation, a 1 SD increase in FP supply increases the probability of reporting very good health by 4.1 percent. The results are robust to transformations of the health variable and to alternative specifications of the effects of individual age on health.”

Appendix

In the paper, the authors use the ln(FP supply) as the key dependent variable. However, ln(FP supply) is an estimated figure. Thus, when the authors calculate the standard errors, they use a bootstrap methodology as follows:

  1. Draw a sample of 351areas (local authorities) with replacement from the area-level data set.
  2. Estimate the ln(FP supply) equations for each of the 3 years—1997, 1998, and 1999.
  3. Estimate the individual-level health equation using predicted ln(FP supply) plus the individual and area-level covariates. The individual observations are weighted by the number of times the LA in which an individual lives was drawn in the first stage bootstrap sample.

The reported standard error of the instrumented ln FP supply coefficient is the standard deviation of the estimated coefficients on ln FP supply from 200 replications of this procedure.

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