title: Health equity audits in general practice: a strategy to reduce health inequalities.
abstract: BACKGROUND
  This quality improvement project was set in Tower Hamlets, east London, with the aim of reducing health inequalities by ethnicity, age and gender in the management of three common chronic diseases.
  
  
  METHODS
  Routinely collected clinical data were extracted from practice computer systems using Morbidity Information Query and Export Syntax (MIQUEST) and Egton Medical Information Systems (EMIS) Web, between 2007 and 2010. Health equity audits for 38 practices in Tower Hamlets primary care trust (PCT) were constructed to cover key process and outcome measures for each of the three major chronic diseases: coronary heart disease (CHD), type 2 diabetes mellitus and chronic obstructive pulmonary disease (COPD). The equity audit was disseminated to practices along with facilitation sessions.
  
  
  RESULTS
  We show evidence of baseline inequalities in each condition across the three east London PCTs. The intervention tracked four key indicators (cholesterol levels in CHD, blood pressure and haemoglobin A1c levels in diabetes and % smoking in COPD). Performance for physician-driven interventions improved, but smoking rates remained static. All ethnic groups showed improvement, but there was no evidence of a reduction in differences between ethnic groups. Reductions in gender and age group differences were noted in diabetes and CHD.
  
  
  CONCLUSIONS
  Using routine clinical data, it is possible to develop practice-level health equity reports. These can unmask previously hidden inequalities between groups, and promote discussion with practice teams to stimulate strategies for improvements in performance. Steady improvements in chronic disease management were observed, however, systematic differences between ethnic groups remain. We are not able to attribute observed changes to the audits. These reports illustrate the importance of collecting ethnicity data at practice level. Tools such as this audit can be adapted to monitor inequalities in primary care settings.
authors: 1Research Fellow, Centre for Primary Care and Public Health, Blizard Institute, Queen Mary University of London, London, UK.
authors: Ellena
authors: E
authors: Badrick
authors: 2Reader, Centre for Primary Care and Public Health, Blizard Institute, Queen Mary University of London, London, UK.
authors: Sally
authors: S
authors: Hull
authors: 3Research Fellow, Centre for Primary Care and Public Health, Blizard Institute, Queen Mary University of London, London, UK.
authors: Rohini
authors: R
authors: Mathur
authors: 4Programme Manager, Centre for Primary Care and Public Health, Blizard Institute, Queen Mary University of London, London, UK.
authors: Shamin
authors: S
authors: Shajahan
authors: 5Senior Clinical Lecturer, Centre for Primary Care and Public Health, Blizard Institute, Queen Mary University of London, London, UK.
authors: Kambiz
authors: K
authors: Boomla
authors: 6Statistician, Centre for Primary Care and Public Health, Blizard Institute, Queen Mary University of London, London, UK.
authors: Stephen
authors: S
authors: Bremner
authors: 7Reader, Centre for Primary Care and Public Health, Blizard Institute, Queen Mary University of London, London, UK.
authors: John
authors: J
authors: Robson
mesh_terms: D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D054869:Clinical Audit; D003327:Coronary Disease / Q000191:economics / Q000208:ethnology / Q000628:therapy; D016208:Databases, Factual; D003924:Diabetes Mellitus, Type 2 / Q000191:economics / Q000208:ethnology / Q000628:therapy; D005260:Female; D058006:General Practice / Q000592:standards* / Q000706:statistics & numerical data; D054624:Health Status Disparities; D054625:Healthcare Disparities / Q000191:economics / Q000208:ethnology / Q000706:statistics & numerical data*; D006801:Humans; D016015:Logistic Models; D008131:London / Q000453:epidemiology; D008297:Male; D008875:Middle Aged; D054525:Minority Health / Q000191:economics / Q000706:statistics & numerical data*; D010043:Outcome and Process Assessment, Health Care / Q000706:statistics & numerical data*; D011204:Poverty Areas; D029424:Pulmonary Disease, Chronic Obstructive / Q000191:economics / Q000208:ethnology / Q000628:therapy*; D019984:Quality Indicators, Health Care / Q000639:trends; D017678:Sex Distribution; D013222:State Medicine / Q000592:standards / Q000706:statistics & numerical data