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Identifying patients with ischaemic heart disease in general practice: cross sectional study of paper and computerised medical records.


ABSTRACT:

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.

SUBMITTER: Gray J 

PROVIDER: S-EPMC27471 | biostudies-literature | 2000 Sep

REPOSITORIES: biostudies-literature

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Publications

Identifying patients with ischaemic heart disease in general practice: cross sectional study of paper and computerised medical records.

Gray J J   Majeed A A   Kerry S S   Rowlands G G  

BMJ (Clinical research ed.) 20000901 7260


<h4>Objectives</h4>To identify patients with ischaemic heart disease by using a practice computer and to estimate the work required to do so.<h4>Design</h4>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.<h4>Setting</h4>11 general practices in the Battersea primary care group in south London.<h4>Subjects</h4>1 in 40 random sample  ...[more]

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