Potential quasi experiments and additional indicators

This section lists a selection of NHS interventions implemented in the 2000s that the experts we consulted suggested may have had an impact on health inequality that could potentially be identified using quasi experimental evaluation, based on the indicators of the kind we have developed in this project. This list helped inform the selection of our two disease-specific domains, since a number of them relate to coronary heart disease and diabetes. It may also provide researchers with useful ideas for future work using quasi-experiments to identify the effects of NHS interventions on social inequalities in health and healthcare.

The list includes interventions which have already been at least partially evaluated, but that one or more experts felt warrant further and more rigorous quasi experimental evaluation. As well as NHS interventions, the list also includes some public health interventions that go beyond healthcare services and/or NHS funding, but that may nevertheless impact upon some of the healthcare outcome indicators we measure in this project, such as preventable

hospitalisation and amenable mortality.

 The Health Inequality National Support Team programme 2007-9 for improving primary care for cardiovascular disease and diabetes in disadvantaged adults

 The Equitable Access to Primary Medical Care Programme 2008-10 which invested in opening new GP practices in under-doctored areas

 The two-week cancer waiting time target from GP referral to specialist consultation, introduced in 2007

 Changes in sub-national (PCT level) NHS expenditure during the 2000s and changes in sub-national (CCG level) NHS expenditure during the 2010s

 The impacts on socioeconomic inequality in preventable hospitalisation and amenable mortality for coronary heart disease and diabetes of the quality and outcomes

framework primary care pay for performance scheme introduced from 2004

 Changes to the quality and outcomes framework incentive payments in the late 2000s

 Diffusion of primary percutaneous coronary intervention (PPCI) following emergency admission for acute ST-elevation myocardial infarction, during the 2000s

 The national NHS Bowel Cancer Screening Programme from 2006 (this may be an example of “intervention-generated inequality”: this intervention is cost-effective but may have increased health inequality due to lower uptake in deprived groups)

 NHS intensive smoking cessation services in England from 1999

 Cuts in particular local areas to community healthcare services disproportionately used by disadvantaged groups e.g. community midwifery services, out-of-hours primary care services

 Proactive hospital-based diabetes services introduced in some areas during the 2000s

 Screening and brief interventions for alcohol misuse

 Early intervention for psychosis including those identified as 'at risk'

Additional indicators

We list below a selection of additional equity indicators that were considered but rejected for the particular purposes of this project. We include this list to explain why some indicator ideas were not selected for inclusion in our suite of prototype equity indicators, and also to inform the deliberations of future researchers and analysts seeking to improve our equity indicators and develop new ones.

 Multi-morbidity according to patient level inpatient hospital records: the proportion of the general population with a hospital record of three or more chronic conditions from hospital visits in the last two years. This indicator was rejected for the purposes of this project due to potential selection bias, since not all people with multi-morbidity are admitted to hospital for inpatient treatment. However, it could nevertheless potentially be useful in future work as a contextual indicator of

of equity in healthcare outcomes such as preventable hospitalisation and amenable mortality.

 Multi-morbidity according to practice level primary care quality and outcomes framework data: the proportion of people with two or more chronic conditions based on quality and outcomes framework data. This was rejected due to potential under- recording in deprived patients which may vary between local areas and over time, potentially leading to bias in both time series comparisons and local equity monitoring comparisons. In sensitivity analysis, we also explored ways of using this indicator to improve the risk adjustment of indicators of equity in healthcare outcomes. However, because it is only available at practice level rather than individual level, yet is highly correlated with age, we found that adding this variable yielded unstable results and little explanatory power over risk adjustment for age and sex alone. At national level, however, this indicator could provide a useful convergent validity check on multi- morbidity according to patient level inpatient hospital records.

 Multi-morbidity according to mortality records: the proportion of people who died in the indicator year with two or more chronic conditions based on secondary

mentions of causes of death. This was rejected due to lack of reliable coding of causes of death on mortality records, and change over time in coding. It may be possible to improve upon this by linking information from hospital records at individual level; but again this would still suffer from the bias described above that not all individuals visit hospital.

 Post-hospital mortality: 12-month mortality after discharge per 1,000 hospital discharges. This was rejected since it yields a somewhat out-of-date indicator: either a one year data lag or a focus on patients admitted the year prior to the indicator year. There is also a risk of indicator revision the year after initial release, since we found that the HES-ONS mortality link data required to compute this indicator are

sometimes subject to substantial data revision the following year.

 Excess hospital stays: proportion of inpatients with excess length of stay as defined by healthcare resource group (HRG) trim points. This was rejected due to concerns about time series comparability. HRG coding systems change over time, and HRG

trim points only provide a relative definition of an “excess” stay for a particular treatment based on the changing year-specific distribution of stays, rather than an absolute definition based on clinical judgement. Data on “delayed discharges”, which reflect a more accurate and more absolute definition, are currently only available at hospital level rather than the patient level or small area level required for equity indicators.

 Experienced access to primary care: the average of a selection of indicators of patient reported experiences of primary care access from the National GP Patient Survey. This was rejected for our purposes, since the National GP Patient Survey only started in 2006/7 and the response rate of about 30% varies substantially between local areas (CCGs) which may hamper local equity comparisons. This indicator may be useful, however, for future national equity monitoring work.

 Specialist doctor visits: annual probability of a first outpatient visit, adjusted for age and sex, based on outpatient hospital episode statistics data. This was rejected since whenever diverse forms of utilisation are grouped together it is hard to tell whether more utilisation reflects better access to care, worse quality of care or worse health. However, more specialised sub-indicators may be worth pursuing – in particular, percentage of first outpatient visits with immediate discharge (potentially reflecting an unnecessary referral), percentage of first outpatient visits with priority referral, and percentage of first outpatient visits the patient “did not attend” (DNA).

 High need service users: rate per 100,000 general population (perhaps distinguishing adults and children) of patients with multiple unplanned admissions in the same year (say > 10). This was rejected on the basis of small numbers problems for local monitoring. However, this may be a useful indicator for national monitoring.

 Hospital complications: annual preventable hospital complications, rate per 100,000 population adjusted for age and sex. This was rejected since there is no official list of “preventable” complications across the full range of hospital activity, and drawing up a list of this kind would be a major clinical research task.

 Hospital expenditure: annual expenditure per 100,000 general population (all ages), based on the total number of outpatient visits and planned and unplanned inpatient admissions weighted by HRG prices. This was rejected since this groups together diverse forms of utilisation and so it is hard to tell whether more expenditure reflects better access to care, worse quality of care or worse health.

 Bed-days following emergency admission: average person-based cumulative time spent in hospital during 12 months following an emergency admission in April to June (Quarter 1). This was rejected since it is similar to repeat hospitalisation within the indicator year and without further refinement would yield a longer time lag. Also, by focusing on bed days rather than number of admissions this indicator may tend to reflect aspects of social care supply that are outside the control of the NHS, as well as the quality of care co-ordination between healthcare and social care settings for which the NHS is at least partly responsible.