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ORIGINAL ARTICLE
Year : 2016  |  Volume : 5  |  Issue : 2  |  Page : 291-297

International Classification of Primary Care-2 coding of primary care data at the general out-patients' clinic of General Hospital, Lagos, Nigeria


1 Department of Family Medicine, General Hospital Lagos, Lagos Island, Nigeria
2 Department of Primary and Community Care, Radboud University Medical Centre, Nijmegen, The Netherlands
3 Department of Primary and Community Care, Radboud University Medical Centre, Nijmegen, The Netherlands; Australian Primary Health Care Research Institute, Australian National University, Canberra, Australia

Correspondence Address:
Olawunmi Abimbola Olagundoye
Department of Family Medicine, General Hospital Lagos, No. 1-3, Broad Street, Lagos Island, Lagos State
Nigeria
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/2249-4863.192341

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Background: Primary care serves as an integral part of the health systems of nations especially the African continent. It is the portal of entry for nearly all patients into the health care system. Paucity of accurate data for health statistics remains a challenge in the most parts of Africa because of inadequate technical manpower and infrastructure. Inadequate quality of data systems contributes to inaccurate data. A simple-to-use classification system such as the International Classification of Primary Care (ICPC) may be a solution to this problem at the primary care level. Objectives: To apply ICPC-2 for secondary coding of reasons for encounter (RfE), problems managed and processes of care in a Nigerian primary care setting. Furthermore, to analyze the value of selected presented symptoms as predictors of the most common diagnoses encountered in the study setting. Materials and Methods: Content analysis of randomly selected patients' paper records for data collection at the end of clinic sessions conducted by family physicians at the general out-patients' clinics. Contents of clinical consultations were secondarily coded with the ICPC-2 and recorded into excel spreadsheets with fields for sociodemographic data such as age, sex, occupation, religion, and ICPC elements of an encounter: RfE/complaints, diagnoses/problems, and interventions/processes of care. Results: Four hundred and one encounters considered in this study yielded 915 RfEs, 546 diagnoses, and 1221 processes. This implies an average of 2.3 RfE, 1.4 diagnoses, and 3.0 processes per encounter. The top 10 RfE, diagnoses/common illnesses, and processes were determined. Through the determination of the probability of the occurrence of certain diseases beginning with a RfE/complaint, the top five diagnoses that resulted from each of the top five RfE were also obtained. The top five RfE were: headache, fever, pain general/multiple sites, visual disturbance other and abdominal pain/cramps general. The top five diagnoses were: Malaria, hypertension uncomplicated, visual disturbance other, peptic ulcer, and upper respiratory infection. From the determination of the posterior probability given the top five RfE, malaria, hypertension, upper respiratory infection, refractive error, and conjuctivitis were the five most frequent diagnoses that resulted from a complaint of a headache. Conclusion: The study demonstrated that ICPC-2 can be applied to primary care data in the Nigerian context to generate information about morbidity and services provided. It also provided an empirical basis to support diagnosis and prognostication in a primary care setting. In developing countries where the transition to electronic health records is still evolving and fraught with limitations, more reliable data collection can be achieved from paper records through the application of the ICPC-2.


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