Quality indicators for general practice.
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Biomedical subjects
Publications and source records attributed to I F Mackenzie.
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BACKGROUND: Although the link between depression, unemployment, and measures of deprivation and morbidity has been previously documented, the relationship between general practice prescribing of antidepressants, morbidity, and the social demography of general practice populations is poorly understood. AIM: To consider whether morbidity and the social demography of general practice populations influence the prescribing costs of individual practices. METHOD: Data were analysed, using a forward stepwise regression procedure, of all 78 practices served by the Cornwall and Isles of Scilly Health Authority. Data on prescribing for antidepressants were provided by the Prescription Pricing Authority for the period from July to December 1995 and converted into defined daily doses (DDDs) to standardize for the variation in prescribing practice between general practitioners. RESULTS: A significant positive correlation exists between the rates of prescribing DDDs of antidepressants by general practices and the prevalence of permanent sickness in the areas in which these practices serve. CONCLUSION: Demonstrating an association between morbidity and prescribing rates for depression may prove helpful in setting prescribing budgets.
BACKGROUND: Increasingly, additional resources for infrastructure development and healthcare are directed at deprived areas. The commitment of the present government to reducing inequalities in health is likely to focus attention on identifying and providing special help to areas considered to be particularly deprived. This study compares the use of different deprivation measures at electoral ward level to rank wards according to deprivation and illustrates how the use of different deprivation measures may influence resourcing decisions. METHODS: The 20 local authority electoral wards making up the city of Plymouth, Devon, were studied. Some of the wards within Plymouth are amongst the most deprived in England. The scores for each ward for different measures of deprivation--Townsend, Jarman, the Department of Environment's Index of Local Conditions and Breadline Britain--were calculated and the wards ranked according to the deprivation score for each measure. Decisions on funding bids and resource allocation for wards within Plymouth were reviewed in the light of the relative deprivation status of the wards according to the various measures. RESULTS: The ranking of electoral wards for the selected measures of deprivation showed variation according to the measure used. The measure of deprivation chosen may have influenced resourcing decisions. CONCLUSION: Measures of deprivation are closely correlated one with another. However, by judicious choice of the deprivation measure used a ward can achieve a marked change in rank order. This may exert considerable influence on the decisions made by government departments, local authorities and health authorities when allocating resources.
BACKGROUND: General practitioners and primary health care teams are asked to take an increasing role in assessing needs and priorities for the people they serve. We describe a model, using routinely available data, to provide health and social information to all general practices in an English Health Authority (South & West Devon, population 586,000, containing 103 general practices) to inform practice-based needs assessment. METHOD: Practice-coded hospital activity information was used where available, otherwise the FHSA population register was used to assign spatially referenced data (OPCS birth files, OPCS mortality files, cancer registration files and census information) to practices. Additionally, indicative incidences and prevalences were calculated for each practice using age- and sex-specific rates derived from national surveys (Survey of Morbidity Statistics from General Practice and the OPCS Health Survey for England). RESULTS: Information was produced for each practice on births, lifestyle, social factors, incidence and prevalence, hospital activity and mortality. Patient numbers rather than rates were presented. General practitioners commented that this approach gave an understanding of the size of health and social problems and fitted with the concept of numbers needed to treat. CONCLUSION: Public health involvement in practice-based needs assessment is essential. Current public health input has mainly been on a selective individual practice basis and is very resource intensive. This approach allows all practices to have immediate access to a wide range of health and social information presented in a way that is easily understood and informs debate on health needs within the practice.