D Swan1,2,3, A Hannigan4, S Higgins5, R McDonnell5, D Meagher4, W Cullen4,6. 1. Graduate Entry Medical School, University of Limerick, Limerick, Ireland. davina.swan@ucd.ie. 2. Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. davina.swan@ucd.ie. 3. School of Medicine and Medical Sciences, University College Dublin, Dublin 4, Ireland. davina.swan@ucd.ie. 4. Graduate Entry Medical School, University of Limerick, Limerick, Ireland. 5. Irish Primary Care Research Network, The Irish College of General Practitioners, 4/5 Lincoln Place, Dublin 2, Ireland. 6. School of Medicine and Medical Sciences, University College Dublin, Dublin 4, Ireland.
Abstract
BACKGROUND: In Ireland, as in many other healthcare systems, mental health service provision is being reconfigured with a move toward more care in the community, and particularly primary care. Recording and surveillance systems for mental health information and activities in primary care are needed for service planning and quality improvement. AIMS: We describe the development and initial implementation of a software tool ('mental health finder') within a widely used primary care electronic medical record system (EMR) in Ireland to enable large-scale data collection on the epidemiology and management of mental health and substance use problems among patients attending general practice. METHODS: In collaboration with the Irish Primary Care Research Network (IPCRN), we developed the 'Mental Health Finder' as a software plug-in to a commonly used primary care EMR system to facilitate data collection on mental health diagnoses and pharmacological treatments among patients. The finder searches for and identifies patients based on diagnostic coding and/or prescribed medicines. It was initially implemented among a convenience sample of six GP practices. RESULTS: Prevalence of mental health and substance use problems across the six practices, as identified by the finder, was 9.4% (range 6.9-12.7%). 61.9% of identified patients were female; 25.8% were private patients. One-third (33.4%) of identified patients were prescribed more than one class of psychotropic medication. Of the patients identified by the finder, 89.9% were identifiable via prescribing data, 23.7% via diagnostic coding. CONCLUSIONS: The finder is a feasible and promising methodology for large-scale data collection on mental health problems in primary care.
BACKGROUND: In Ireland, as in many other healthcare systems, mental health service provision is being reconfigured with a move toward more care in the community, and particularly primary care. Recording and surveillance systems for mental health information and activities in primary care are needed for service planning and quality improvement. AIMS: We describe the development and initial implementation of a software tool ('mental health finder') within a widely used primary care electronic medical record system (EMR) in Ireland to enable large-scale data collection on the epidemiology and management of mental health and substance use problems among patients attending general practice. METHODS: In collaboration with the Irish Primary Care Research Network (IPCRN), we developed the 'Mental Health Finder' as a software plug-in to a commonly used primary care EMR system to facilitate data collection on mental health diagnoses and pharmacological treatments among patients. The finder searches for and identifies patients based on diagnostic coding and/or prescribed medicines. It was initially implemented among a convenience sample of six GP practices. RESULTS: Prevalence of mental health and substance use problems across the six practices, as identified by the finder, was 9.4% (range 6.9-12.7%). 61.9% of identified patients were female; 25.8% were private patients. One-third (33.4%) of identified patients were prescribed more than one class of psychotropic medication. Of the patients identified by the finder, 89.9% were identifiable via prescribing data, 23.7% via diagnostic coding. CONCLUSIONS: The finder is a feasible and promising methodology for large-scale data collection on mental health problems in primary care.
Entities:
Keywords:
Electronic medical record; Mental health; Primary care; Software plug-in; Substance use
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