Association of population and practice factors with potentially avoidable admission rates for chronic diseases in London: cross sectional analysis

J R Soc Med. 2006 Feb;99(2):81-9. doi: 10.1258/jrsm.99.2.81.


Objectives: To examine the association between underlying ill health, material deprivation and primary care supply factors and hospital admission rates for potentially avoidable admissions in primary care trusts in London.

Design: Cross sectional analysis at primary care trusts level using routine data from multiple sources.

Setting: All 31 primary care trusts in London with a total resident population of 7 million patients.

Main outcome measures: Age-standardized hospital admission rates for asthma, diabetes, heart failure, hypertension and chronic obstructive pulmonary disease.

Results: Admission rates varied widely for the conditions examined across the 31 primary care trusts. In 2001, age adjusted admission rates for asthma varied from 76 to 189 per 100,000 and for diabetes from 38 to 183 per 100,000. There was a significant association between higher admission rates and measures of underlying ill health and material deprivation but not quantitative measures of primary care service provision. Provision of specialist chronic disease services in primary care for diabetes but not for asthma were significantly associated with reduced admission rates. There was no association of prescribing levels in primary care trusts with admission rates for any of the conditions examined.

Conclusions: Although hospital admission for some chronic diseases is potentially avoidable and rates of hospital admission for these conditions are possible indicators of the quality of care, they should be interpreted in conjunction with measures of population composition and deprivation. Failure to do this may result in primary care trusts and general practitioners being criticized for aspects of health care utilization that are not under their direct control.

Publication types

  • Multicenter Study

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Child
  • Child, Preschool
  • Chronic Disease / therapy*
  • Hospitalization / statistics & numerical data*
  • Humans
  • Infant
  • Infant, Newborn
  • London
  • Middle Aged
  • Primary Health Care / statistics & numerical data*
  • Regression Analysis
  • Socioeconomic Factors