Optimal strategies for identifying patients with myocardial infarction in general practice
Peter T Donnan1, Hamish T Dougall, Frank M Sullivan
1Tayside Centre for General Practice, Kirsty Semple Way, University of Dundee, Dundee DD2 4BF, Scotland, UK. p.t.donnan@dundee.ac.uk
Insights
Identifying myocardial infarction patients in general practice is crucial for secondary prevention. Combining Read codes with hospitalization records offers a highly sensitive and specific strategy for accurate patient identification.
Area of Science:
- Cardiology
- General Practice
- Health Informatics
Background:
- Effective secondary prevention of coronary heart disease (CHD) requires accurate identification of eligible patients in general practice.
- Optimizing patient identification strategies minimizes effort while maximizing detection rates.
Purpose of the Study:
- To evaluate different search criteria for identifying patients with a history of myocardial infarction (MI) within general practice records.
- To determine the most efficient and accurate method for case ascertainment.
Main Methods:
- Cross-sectional survey of 10 general practices in Tayside, Scotland.
- Analysis of a random sample of 5061 registered subjects aged over 35.
- Evaluation of search criteria using sensitivity, specificity, positive predictive value (PPV), and yield.
Main Results:
- A Read code for ischaemic heart disease (IHD) showed high sensitivity (95%) but low PPV (52%).
- Combining a Read code for MI with hospitalization records achieved 100% sensitivity and high yield (1 in 1.11).
- For poor quality Read coding, using hospital records or medication data (aspirin/nitrates) was optimal.
Conclusions:
- A combination of MI Read codes and hospitalization records accurately identifies patients with a history of MI.
- This strategy offers 100% sensitivity and specificity with excellent yield for secondary CHD prevention.
- Alternative strategies exist for practices with suboptimal data quality.
Background:
In order to provide evidence-based secondary prevention of coronary heart disease (CHD) in general practice, eligible patients need to be identified. The optimal strategy is one in which all appropriate patients are identified with the least effort.
Objective:
The purpose of the study was to determine the optimal strategy to identify subjects with a myocardial infarction (MI) from general practice records using different search criteria.
Methods:
The study was a cross-sectional survey of 10 general practices in Tayside, Scotland. A random sample of all subjects aged over 35 (n = 5061) and registered with the general practices was obtained. The main outcome measures were sensitivity, specificity, positive predictive value (PPV) and yield (the number of records that need to be examined to detect a "true case").
Results:
Of the sample of 5061, 207 (4.1%) were defined to have had a "gold standard" MI. A Read code for ischaemic heart disease (IHD) had the highest sensitivity (95%) but with a poor PPV (52%). All searches had high specificities. The addition of a record of hospitalization for MI to the Read code for MI gave 100% sensitivity and high yield (1 in 1.11). In situations where the Read coding is of poor quality, the alternative search strategy of a hospital record of MI or receiving aspirin or nitrates was optimum.
Conclusions:
Patients who had experienced an MI can be easily identified from a combination of a Read code for MI and a record of hospitalization for an MI giving 100% sensitivity and specificity with a yield of 1 in 1.11.
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