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HSR: General
OP69 The use of NHS Routine Data to Analyse The Effects of Healthcare Interventions
  1. E V Cecil1,
  2. M Soljak1,
  3. D Osipovic2,
  4. S Peckham2,
  5. A Majeed1
  1. 1Primary Care and Public Health, Imperial College, London, UK
  2. 2Health Services Research and Policy, LSHTM, London, UK


Background In 2007, the strategy ‘Healthcare for London’ planned the establishment of polyclinics in each PCT to help improve the primary care infrastructure. These polyclinics serve as a hub for a group of GP practices which combined form a polysystem. We aimed to investigate the impact of services provided in a polysystem on unplanned (emergency) admissions, using routine NHS activity data. In one polysystem case study, a pulmonary rehabilitation service for COPD was established. In another, a diabetes patient education programme was offered.

Methods We used routine Hospital Episodes Statistics inpatient data from 2004/5 to 2009/10 covering around 1500 London practices. Differences in adjusted trends in emergency admission rates were compared between the polysystem GP practices case studies and other London practices. Multilevel regression models assessed standardized rate ratios, controlling for year variation, GP practice and population factors. We incorporated interaction terms to allow the effects of the polysystem to vary independently by year.

Results Over the study period COPD emergency admission rates fell across London with a yearly admission rate ratio of (95% CI) 0.98 (0.97, 0.99, p<0.001). The rates in the study polysystem did not differ from the rest of London at baseline and there was not enough evidence to suggest that the introduction of the polysystem service in May 2007 had any effect on the admission rates. A total of 12% of the registered COPD population was seen as new contacts in the first year of the service.

Diabetes emergency admission rates have been falling across London over the study period with a yearly admission rate ratio (95% CI) of 0.98 (0.96, 0.99, p=0.001). In the first year of the diabetes intervention, the rate of emergency admissions for diabetes fell by 80% in patients from the polysystem practices compared with London, with an interaction factor (95% CI) of 0.20 (0.13, 0.31) p<0.001 and this fall was maintained in the following year. Intervention in this London Polysystem covered 70% of the diabetic population. The power to detect an effect was increased due to the coverage.

Conclusion NHS routine data can be used to assess the impact of health service interventions that are aimed at reducing admissions. Commissioners must be aware that to assess the impact of interventions, the implementation needs to be on a large scale and that medium term follow up is required in order to study the trends.

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