title: Measuring the gap: quantifying and comparing local health inequalities.
abstract: Primary Care Trusts (PCTs) and Local Strategic Partnerships (LSPs) are being asked to assess local health inequalities in order to prioritize local action, to set local targets for reducing levels of health inequality locally and to demonstrate measurable progress. Despite this, little guidance has been provided on how to quantify health inequalities within PCTs and LSPs. This paper advocates the use of a metric, the slope index of inequality, which provides a consistent measure of health inequalities across local populations. The metric can be presented as a relative gap, which is easily understood and enables levels of inequality to be compared between health conditions, lifestyles and rates of service provision at any one time, or across different time periods. The metric is applied to Sunderland Teaching PCT, using routine data sources. Examples of the results and their uses are presented. It is suggested that more widespread use of the metric could enable levels of health inequalities to be compared across PCTs and lead to the development of local health inequality and inequity benchmarks.
authors.affiliation: Derwentside PCT, Shotley Bridge Community Hospital, Consett Co., Durham DH8 ONB. alow@btinternet.com
authors.forename: Anne
authors.initials: A
authors.lastname: Low
authors.forename: Allan
authors.initials: A
authors.lastname: Low
mesh_terms: D018672:Community Health Planning; D006292:Health Priorities; D006297:Health Services Accessibility / Q000706:statistics & numerical data*; D006305:Health Status Indicators; D006801:Humans; D015233:Models, Statistical; D009026:Mortality; D020380:Needs Assessment; D011204:Poverty Areas; D011320:Primary Health Care / Q000458:organization & administration / Q000592:standards / Q000706:statistics & numerical data*; D011787:Quality of Health Care; D012935:Social Justice; D012959:Socioeconomic Factors; D006113:United Kingdom / Q000453:epidemiology; D035862:Vulnerable Populations / Q000145:classification* / Q000706:statistics & numerical data