TY - JOUR
T1 - Estimating morbidity rates based on routine electronic health records in primary care: observational study
AU - Nielen, Mark M J
AU - Spronk, Inge
AU - Davids, Rodrigo
AU - Korevaar, Joke C
AU - Poos, René
AU - Hoeymans, Nancy
AU - Opstelten, Wim
AU - van der Sande, Marianne A B
AU - Biermans, Marion C J
AU - Schellevis, Francois G
AU - Verheij, Robert A
N1 - FTX; DOAJ; (CC BY 4.0);
©Mark M J Nielen, Inge Spronk, Rodrigo Davids, Joke C Korevaar, René Poos, Nancy Hoeymans, Wim Opstelten, Marianne A B van der Sande, Marion C J Biermans, Francois G Schellevis, Robert A Verheij. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 26.07.2019.
PY - 2019
Y1 - 2019
N2 - BACKGROUND: Routinely recorded electronic health records (EHRs) from general practitioners (GPs) are increasingly available and provide valuable data for estimating incidence and prevalence rates of diseases in the population. This paper describes how we developed an algorithm to construct episodes of illness based on EHR data to calculate morbidity rates.OBJECTIVE: The goal of the research was to develop a simple and uniform algorithm to construct episodes of illness based on electronic health record data and develop a method to calculate morbidity rates based on these episodes of illness.METHODS: The algorithm was developed in discussion rounds with two expert groups and tested with data from the Netherlands Institute for Health Services Research Primary Care Database, which consisted of a representative sample of 219 general practices covering a total population of 867,140 listed patients in 2012.RESULTS: All 685 symptoms and diseases in the International Classification of Primary Care version 1 were categorized as acute symptoms and diseases, long-lasting reversible diseases, or chronic diseases. For the nonchronic diseases, a contact-free interval (the period in which it is likely that a patient will visit the GP again if a medical complaint persists) was defined. The constructed episode of illness starts with the date of diagnosis and ends at the time of the last encounter plus half of the duration of the contact-free interval. Chronic diseases were considered irreversible and for these diseases no contact-free interval was needed.CONCLUSIONS: An algorithm was developed to construct episodes of illness based on routinely recorded EHR data to estimate morbidity rates. The algorithm constitutes a simple and uniform way of using EHR data and can easily be applied in other registries.
AB - BACKGROUND: Routinely recorded electronic health records (EHRs) from general practitioners (GPs) are increasingly available and provide valuable data for estimating incidence and prevalence rates of diseases in the population. This paper describes how we developed an algorithm to construct episodes of illness based on EHR data to calculate morbidity rates.OBJECTIVE: The goal of the research was to develop a simple and uniform algorithm to construct episodes of illness based on electronic health record data and develop a method to calculate morbidity rates based on these episodes of illness.METHODS: The algorithm was developed in discussion rounds with two expert groups and tested with data from the Netherlands Institute for Health Services Research Primary Care Database, which consisted of a representative sample of 219 general practices covering a total population of 867,140 listed patients in 2012.RESULTS: All 685 symptoms and diseases in the International Classification of Primary Care version 1 were categorized as acute symptoms and diseases, long-lasting reversible diseases, or chronic diseases. For the nonchronic diseases, a contact-free interval (the period in which it is likely that a patient will visit the GP again if a medical complaint persists) was defined. The constructed episode of illness starts with the date of diagnosis and ends at the time of the last encounter plus half of the duration of the contact-free interval. Chronic diseases were considered irreversible and for these diseases no contact-free interval was needed.CONCLUSIONS: An algorithm was developed to construct episodes of illness based on routinely recorded EHR data to estimate morbidity rates. The algorithm constitutes a simple and uniform way of using EHR data and can easily be applied in other registries.
U2 - 10.2196/11929
DO - 10.2196/11929
M3 - A1: Web of Science-article
C2 - 31350839
SN - 2291-9694
VL - 7
JO - JMIR Medical Informatics
JF - JMIR Medical Informatics
IS - 3
M1 - e11929
ER -