70, 489 primary care encounters: retrospective analysis of morbidity at a primary care centre in Ireland. (November 2016)

• Record Type: Journal Article
• Authors: Molony, D.; Beame, C.; Behan, W.; Crowley, J.; Dennehy, T.; Quinlan, M.; Cullen, W.
• Is Part Of: Irish journal of medical science. Volume 185:Number 4(2016)
• Page Start: 805
• Page End: 811
• Publication Date: 2016-11
• Subjects: Morbidity -- Primary care -- Epidemiology -- ICPC; Medicine -- Periodicals; Medicine -- Periodicals; 610
• DOI: 10.1007/s11845-015-1367-5
• Languages: English
• ISSNs: 0021-1265

Abstract

Abstract Background While considerable changes are happening in primary care in Ireland and considerable potential exists in intelligence derived from practice-based data to inform these changes, relatively few large-scale general morbidity surveys have been published. Aims To examine the most common reasons why people attend primary care, specifically 'reasons for encounter' (RFEs) among the general practice population and among specific demographic groups (i.e., young children and older adults). Methods We retrospectively examined clinical encounters (which had a diagnostic code) over a 4-year time period. Descriptive analyses were conducted on anonymised data. Results 70, 489 RFEs consultations were recorded (mean 13.53 recorded RFEs per person per annum) and consultations involving multiple RFEs were common. RFE categories for which codes were most commonly recorded were: 'general/unspecified' (31.6 %), 'respiratory' (15.4 %) and 'musculoskeletal' (12.6 %). Most commonly recorded codes were: 'medication renewal' (6.8 %), 'cough' (6.6 %), and 'health maintenance/prevention' (5.8 %). There was considerable variation in the number of RFEs recorded per age group. 6239 RFEs (8.9 %) were recorded by children under 6 years and 15, 295 RFEs (21.7 %) were recorded by adults aged over 70. RFEs recorded per calendar month increased consistently through the study period and there was a marked seasonal and temporal variation in the number of RFEs recorded. Conclusions Practice databases can generate intelligence on morbidity and health service utilisation in the community. Future research to optimise diagnostic coding at a practice level and to promote this activity in a more representative sample of practices is a priority.