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Abstract Objective To establish current practice in the use of Read codes for diabetes. Design Cross sectional study. Setting 17 practices in the Battersea primary care group in southwest London. Data sources Computerised medical records. Main outcome measures Number of codes in use in all practices; variation in the use of codes between practices; and prevalence of Read code use in diabetic patients. Results At least 9 separate Read code groupings and 25 individual diabetes codes were in use in the 17 general practices. Only one Read code (C10, diabetes mellitus) and its subcodes was being used in all 17 practices, but its use varied from 14% to 98% of patients with diabetes. The use of other key Read codes for monitoring the care of patients with diabetes also varied widely between practices; for example, < 20% of practices used the code for the location of care. Less than half of patients (45%) with diabetes had their type of diabetes coded, and even fewer (21%) had measures such as the examination of the retina coded. Conclusions The use of Read codes for diabetes needs to be standardised and coding levels improved if valid diabetic registers are to be constructed and the quality of care is to be monitored effectively. Until all patients with diabetes have the C 10 Read code recorded, clinicians will have to use a wide range of Read codes and prescribing data to ensure that diabetes registers are complete. [ABSTRACT FROM AUTHOR]

Objectives: To identify patients with ischaemic heart disease by using a practice computer and to estimate the work required to do so.Design: Cross sectional study. Data from the notes and from the computer records of 1680 patients were used to build a database. This was used to compare different methods of identifying patients with ischaemic heart disease.Setting: 11 general practices in the Battersea primary care group in south London.Subjects: 1 in 40 random sample of patients aged 45[ ]or older.Main outcome measures: Numbers of patients identified with ischaemic heart disease.Results: The combination of the Read code for ischaemic heart disease (G3) and a prescription for a nitrate had a 73% sensitivity and a yield (100/positive predictive value) of one case of ischaemic heart disease for every 1.2 sets of notes reviewed. By searching the records of patients also receiving aspirin, atenolol, digoxin, or a statin, the sensitivity was increased to 96% but the yield fell to one in three.Conclusion: Although commonly used to identify cases, a computer search for G3 code or nitrate missed almost 30% of patients with ischaemic heart disease. A substantially higher percentage of patients can be identified by adding other drugs to the search strategy. [ABSTRACT FROM AUTHOR]

Presents a study to evaluate the association between medical practice size and the quality of care of patients with ischemic heart disease. How an association between size and outcome may be important in primary care settings; Statement that the trend in the British National Health Service towards larger general practices by itself has little impact on the quality of chronic disease management in primary care; Participants; Methods; Results; Comments.

Presents medical related media programs in Great Britain. Theater presentation on patient activities in hospitals; A program on community care of people with chronic mental illness; Success of the Geel community care program.