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Modelling Medications for Public Health Research

Most patients with chronic disease are prescribed multiple medications, which are recorded in their personal health records. This is rich information for clinical public health researchers but also a challenge to analyse. This paper describes the method that was undertaken within the Public Health R...

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Detalles Bibliográficos
Autores principales: van Gaans, D., Ahmed, S., D’Onise, K., Moyon, J., Caughey, G., McDermott, R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: University of Illinois at Chicago Library 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5266755/
https://www.ncbi.nlm.nih.gov/pubmed/28149446
http://dx.doi.org/10.5210/ojphi.v8i2.6809
Descripción
Sumario:Most patients with chronic disease are prescribed multiple medications, which are recorded in their personal health records. This is rich information for clinical public health researchers but also a challenge to analyse. This paper describes the method that was undertaken within the Public Health Research Data Management System (PHReDMS) to map medication data retrieved from individual patient health records for population health researcher’s use. The PHReDMS manages clinical, health service, community and survey research data within a secure web environment that allows for data sharing amongst researchers. The PHReDMS is currently used by researchers to answer a broad range of questions, including monitoring of prescription patterns in different population groups and geographic areas with high incidence/prevalence of chronic renal, cardiovascular, metabolic and mental health issues. In this paper, we present the general notion of abstraction network, a higher level network that sits above a terminology and offers compact and more easily understandable view of its content. We demonstrate the utilisation of abstraction network methodology to examine medication data from electronic medical records to allow a compact and more easily understandable view of its content.