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P92 Are some areas more equal than others? Socioeconomic inequality in avoidable emergency hospitalisation within English local authorities from 2004/5 to 2011/12
  1. J Sherringham1,
  2. M Asaria2,
  3. H Barrat1,
  4. R Raine1,
  5. R Cookson2
  1. 1Applied Health Research, University College London, London, UK
  2. 2Centre for Health Economics, University of York, York, UK

Abstract

Background Local NHS planners have a statutory duty to consider reducing socioeconomic inequality in healthcare outcomes, in collaboration with local government. However, local healthcare monitoring currently focuses on averages rather than inequalities. We illustrate new methods of local equity monitoring by comparing the performance of local areas in reducing inequality in avoidable emergency hospital admissions for chronic conditions between 2004/5 and 2011/12.

Methods We used local authority (LA) as a proxy for local health service commissioning geography, including healthcare, public health, social care and other local services that may influence health outcomes. We linked inpatient hospital activity, deprivation data and population data at neighbourhood level. We measured absolute inequality both nationally and within each LA by applying the slope index of inequality (SII) at neighbourhood level to model the relationship between deprivation and rates of avoidable hospitalisation in each year of the study. The SII represents the modelled gap between the most and least deprived neighbourhoods. We used the national and LA level SIIs to identify LAs performing significantly better or worse than the national average in any given year and to identify areas where equity performance was improving or worsening at the fastest rates.

Results Over the seven year period 21% of LAs performed significantly better than the national average (ranging between 13% and 24%), and 13% performed significantly worse (ranging between 14% and 17%). Local equity was fairly stable between consecutive years (kappa 0.46–0.56, indicating ‘moderate’ agreement) but started to diverge over the seven year period (0.33, indicating ‘fair’ agreement).

Conclusion It is possible to identify local areas performing significantly better and worse than the national average on reducing health inequality. Inequalities within local authorities are fairly stable between consecutive years, but over time there are cumulative patterns of change. Identifying areas that are steadily improving or worsening in terms of their health equity performance is the first step in identifying policies to encourage, avoid or ameliorate when tackling health inequality is an objective.

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