RESULTADOS EN EL ÍTEM 5

(In)equity in health care is a central point of attention of many health care systems and tackling this inequity has been an important objective in the development and reorganization of health services. ⁶³ There is widespread concern that the focus on quality improving systems driven by financial incentives may lead to a widening of the existing inequity in health care. Within this report the impact of the introduction of the Quality and Outcome Framework in the UK on equity in treatment and (intermediate) outcomes was investigated. More specifically with this study we want to target the following three sub domains: the immediate effect of the implementation of QOF on the existing inequity in treatment and (intermediate) outcomes, the effects on long term and the contribution of exception reporting in treatment and (intermediate) outcomes.

Several limitations in the selected studies complicate the formulation of the evidence, prompting utmost prudence in interpreting and generalizing the results of this study.

In the assessment of equal access to care it is essential to look for differences in social or ethnic background, gender … between the users of health care and the non-users of health care, both with the same need for care. None of the studies addresses this issue:

they do not include information on the ratio users/non-users (both in equal need for care) and on the variation in the characteristics of the users and the non-users. This makes it impossible in this study to pronounce upon overall equity in access.

The majority of the studies make no judgments about the appropriateness of the indicators or the treatment targets for both groups. As a result, similar screening or treatment rates can actually mean under treatment of certain groups, hence inequity

63.In none of the selected studies normative need, felt need or expressed need is taken into consideration when observing differences in treatment and/or (intermediate) treatment outcomes. In the majority of the studies the authors (inexplicitly) adopt a comparative approach to need: when variations are found between the treatment rates and outcomes of two groups of patients with the same condition (e.g. low-income versus high-income diabetic patients), inequity is presumed. Characteristic of a comparative approach of need is that it makes no judgments about the appropriateness of the indicators or the treatment targets for both groups. E.g. when no differences are found in the cervical screening rates between population A and B most of the selected studies would presume equity. However knowing some groups have a higher risk on cervical cancer related to number of sexual partners, similar screening rates actually mean under treatment of this second group and so inequity.

As a result utmost prudence is necessary when interpreting the results of the studies:

the absence of social, gender or age differences should not automatically be interpreted as absence of inequities. ⁶³

Questions can be asked about the relevance and the completeness of the indicators that are used to measure quality. Although initiatives such as the QOF cover many important aspects of quality of care, the inherent strength and complexity of the doctor-patient relationship supports quality at a much deeper level which is not captured by the QOF indicators. The same reasoning applies to the fact that the selected publications mainly focus on intermediate outcomes and less on final outcome measures. To what extent equity in intermediate outcomes or process indicators predict final outcomes, not to speak to what extent the found (in)equities in health care predict (in)equities in health?

The selected studies have weak study designs according to the labels presented in chapter 4. Of the 27 studies studying the pay-for-performance initiative in the UK

• 17 have a cross-sectional design with only one point of measurement;

• 7 studies have a serial cross-sectional design with several points of measurement in time (of which only 3 with both measurements before and after the introduction of the new initiative)

• 3 studies have a longitudinal design with several points of measurement in time and linking of the data from the same study subject (e.g. patient) over time

This means that only 6 of the 27 studies have a study design that is appropriate to describe the effects of the implementation of the initiative. None of these 6 studies report on the effects more than two year after the implementation of the initiative. The most recent data analyzed in the 32 reported studies are from 2007 ^{148, 169}

An important number of studies use the practice outcomes and/or use area level scores of deprivation as a proxy for the socioeconomic status of the patient. These studies assume that the eventually associations observed at the practice or area level reflect the same association at the individual level. This may not be true, a problem known as the ecological fallacy 133 , 160 , 164.

Notwithstanding these limitations this study comes to some interesting findings that can certainly contribute to the knowledge base of the equity debate.

As discussed in section 5.2.1 the quality of care in the UK generally improved with the introduction of QOF and for the majority of the observed indicators all citizens benefit from this improvement. However, the extent to which different patient groups benefit tends to vary and to be highly dependent on the type and complexity of the indicator(s) under study, the observed patient groups (age groups, males versus females, socioeconomic groups or ethnic groups), the characteristics of the study (design, level of analysis, covariates, …) and the level of detail of the studied indicators.

Before the implementation of the QOF a clear gap in health care for older patients was documented for stroke care, for CHD care and for diabetes care. After the introduction of the QOF, for all observed diseases the net gap^d becomes smaller. For the existing inequities in health care for women, deprived patients and patients from other than white ethnic backgrounds, the results are not as clear as for the elderly patients. Pre-contract, for women a net gap in health care was documented for stroke, for CHD and for diabetes care. For health care related to stroke the net gender gap got smaller after the implementation of the QOF. For CHD and diabetes care the net gender gap increased.

Considering socioeconomic groups, the relatively small gap for stroke care and CHD care increased after the implementation of the QOF, whether for diabetes care the gap got smaller. Finally, the small existing gap in CHD care for ethnic minorities disappeared after the introduction of the QOF.

When looking at inequity at a more detailed level, the level of individual indicators, the findings become even more complex, scattered and sometimes contradictory.

Hereby we summarize the most marked results:

• Post-contract improvements in blood pressure control and statin prescribing increased for both white CHD patients and black CHD patients but to a larger extent for blacks, completely attenuating the disparities evident pre-contract. The same results were found for the measurement of blood pressure in the South Asian patients.

• Regarding stroke related QOF indicators, for the recording of a magnetic resonance imaging/computed tomography scan, smoking, cholesterol, antiplatelet or anticoagulant therapy, and influenza vaccination, a significant difference between the most and least deprived patients was found.

• Recording of HbA1c and the achievement of BP goals increased more in white diabetes patients than in black diabetic patients and in South Asian diabetic patients resulting in a widening of the existing ethnic disparities in care for blacks and Asians.

• Similar increases in HbA1c measuring and BP measuring were found across all ethnic groups except for the Black Caribbean group who had lower achievement in BP goals and in HbA1c targets.

d Net result or net gap: If the total number of indicators in which inequity appears pre-contract > the total number of indicators in which inequity appears post-contract, the net result is a decrease of the gap. If the total number of indicators in which inequity appears pre-contract < the total number of indicators in which inequity appears post-contract, the net result is an increase of the gap.

In general we see that all citizens benefit from the improvements in quality of care and the extent to which they benefit determine whether the existing gap narrows (when the least off have a larger growth than the best off) or increases (if the least off have a smaller growth than the best off). However, for some indicators a new gap arises there where there was no gap pre-contract. For example a significant difference between the most and least deprived patients emerged after the contract for the recording of blood pressure, the recording of smoking status and giving smoking advice. Also pre-contract diabetic women were as likely as men to have their HbA1c, blood pressure, serum creatinine and cholesterol recorded where post-contract inequities in these indicators appeared.

For some indicators, the increase in quality of care for the initially deprived groups was even larger than for the other patients, resulting in an inversion of the gap or a ‘positive discrimination’: for the measurement of BMI, the measurement of cholesterol and the control of BP a positive discrimination of South Asian patients with CHD compared to white British patients with CHD was described.¹⁵⁷. Also for one indicator in diabetes care (serum creatinine recorded) the inequity inversed towards a pro-elderly distribution of the indicator ¹²⁸.

In 2000, Victoria et al formulated the inverse equity hypothesis. This hypothesis proposes that affluent groups in society preferentially benefit from new interventions, leading to an initial increase in inequalities. Deprived groups only begin to benefit once affluent groups have extracted maximum benefit. Health inequalities ultimately diminish because deprived groups start with a lower baseline level of health and health care uptake and have higher potential gains ^{148 , 235}. The above results do not unanimously confirm the first part of the hypothesis (i.e. just after the introduction of a new intervention the more affluent areas or groups in society benefit most).

With regard to the persistency of these changes over time only two studies were found

84 , 142. In the first year after the introduction a clear socioeconomic gradient was

recorded, with progressively lower achievement and greater variation in achievement, with increasing area deprivation. However this gradient was not steep.

Both Doran et al. (2008) and Ashworth et al (2007) showed that after 3 years this existing (but small) gradient between deprived areas had almost disappeared. ^{84 , 142} Moreover, using regression models including area, practice, patient and GP characteristics, Doran was able to prove that the increase in achievement over time was not significantly associated with area deprivation but was very strongly associated with previous practice performance: “the lower the achievement in the previous year, the greater the increase in achievement.” ⁸⁴

This is a very important finding because it might indicate that the QOF indeed is a truly equitable public-health intervention since the improvements in quality achievement by practices are inversely related to previous performance and not to the level of deprivation of the area where the practice is located. However, alternative explanations for the described phenomenon could also exist: it is possible that the increase in quality already started before the introduction of the QOF (there are some indications for this) and that the better off groups already nearly reached their full growing potential by the time the QOF was introduced. ⁸⁴ This might explain the reduction of some of the pre-contract health care gaps as described in the previous paragraph⁸⁴.

With regard to exception reporting there is some concern that this might be used as an excuse for substandard care of patients or to exclude patients for whom the targets had been missed, mostly socially deprived patients or patients with a different ethnic background, rather than because of a genuine clinical reason (also known as ‘gaming’).

The most recent and most comprehensive study that addresses this topic is the study of Doran et al (2008); they report that the characteristics of the patients (e.g. gender, socioeconomic position) explain only 2.7% of the variance in exception reporting. This does not confirm earlier studies with more limited study designs reporting that practices in financially deprived areas are more likely to exclude patients (McLean 2006).

Doran et al (2008) conclude that “Exception reporting brings substantial benefits to pay-for-performance programmes, providing that the process has been used appropriately.

In England, rates of exception reporting have generally been low, with little evidence of widespread gaming” ⁸⁴. However, it can be argued that nevertheless the exclusion system succeeds in not being socially selective, it does not succeed in rewarding the additional work required in deprived areas ²³⁰.

In general, hopeful results were found. It can be states that after the introduction of the QOF at least some of the existing inequities became smaller and the positive effects seem to continue over the years. Still it is important to keep in mind that equity in health care is just a small piece of the larger jigsaw of determinants explaining inequity in health.