Coding, recording and incidence of different forms of coronary heart disease in primary care
Nawaraj Bhattarai1, Judith Charlton, Caroline Rudisill
1Department of Primary Care and Public Health Sciences, King's College London, London, United Kingdom. nawaraj.bhattarai@kcl.ac.uk
Insights
Coding for coronary heart disease (CHD) in electronic records often lacks specificity, impacting research accuracy. Improving primary care coding practices is crucial for reliable CHD event tracking and analysis.
Area of Science:
- Cardiology
- Health Informatics
- Epidemiology
Background:
- Coronary heart disease (CHD) coding in electronic medical records is essential for clinical care and research.
- Variations in coding practices can affect the accuracy of CHD incidence and prevalence data.
- Primary care electronic records are a significant source of health data.
Purpose of the Study:
- To evaluate the accuracy and incidence of coronary heart disease (CHD) coding within primary care electronic medical records.
- To assess the recording of specific CHD events like angina and myocardial infarction.
- To analyze trends in CHD coding and related procedures over time.
Main Methods:
- Utilized data from the UK General Practice Research Database, including over 300,000 participants.
- Analyzed 271 READ diagnostic codes related to CHD, including angina, myocardial infarction (MI), coronary artery bypass grafting (CABG), and percutaneous transluminal coronary angioplasty (PCTA).
- Employed time-to-event analyses to determine the occurrence of different code categories post-index date.
Main Results:
- Over 75,000 unique CHD codes were identified in nearly 25,000 participants.
- A significant proportion of incident and prevalent CHD codes lacked clinical specificity.
- Between 2000-2010, overall CHD incidence and angina incidence declined, while MI incidence remained stable; PCTA procedures increased, and CABG decreased.
Conclusions:
- Primary care electronic records frequently use non-specific CHD codes, hindering differentiation between clinical presentations.
- There is a critical need to enhance coding practices in primary care for improved data quality.
- Code selection and sensitivity analyses are vital for accurate research utilizing CHD electronic health records.
Objectives:
To evaluate the coding, recording and incidence of coronary heart disease (CHD) in primary care electronic medical records.
Methods:
Data were drawn from the UK General Practice Research Database. Analyses evaluated the occurrence of 271 READ medical diagnostic codes, including categories for 'Angina', 'Myocardial Infarction', 'Coronary Artery Bypass Grafting' (CABG), 'percutaneous transluminal coronary angioplasty' (PCTA) and 'Other Coronary Heart Disease'. Time-to-event analyses were implemented to evaluate occurrences of different groups of codes after the index date.
Results:
Among 300,020 participants aged greater than 30 years there were 75,197 unique occurrences of coronary heart disease codes in 24,244 participants, with 12,495 codes for incident events and 62,702 for prevalent events. Among incident event codes, 3,607 (28.87%) were for angina, 3,262 (26.11%) were for MI, 514 (4.11%) for PCTA, 161 (1.29%) for CABG and 4,951 (39.62%) were for 'Other CHD'. Among prevalent codes, 20,254 (32.30%) were for angina, 3,644 (5.81%) for MI, 34,542 (55.09%) for 'Other CHD' and 4,262 (6.80%) for CABG or PCTA. Among 3,685 participants initially diagnosed exclusively with 'Other CHD' codes, 17.1% were recorded with angina within 5 years, 5.6% with myocardial infarction, 6.3% with CABG and 8.6% with PCTA. From 2000 to 2010, the overall incidence of CHD declined, as did the incidence of angina, but the incidence of MI did not change. The frequency of CABG declined, while PCTA increased.
Conclusion:
In primary care electronic records, a substantial proportion of coronary heart disease events are recorded with codes that do not distinguish between different clinical presentations of CHD. The results draw attention to the need to improve coding practice in primary care. The results also draw attention to the importance of code selection in research studies and the need for sensitivity analyses using different sets of codes.
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