ArticleJMIR medical informatics2019
Estimating Morbidity Rates Based on Routine Electronic Health Records in Primary Care: Observational Study.
Article in JMIR medical informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
48 citing papers in PubMed.
- Characteristics and motives of non-responders in a stepwise cardiometabolic disease prevention program in primary care.European journal of public health · 2021Trial
- Opportunistic screening versus usual care for detection of atrial fibrillation in primary care: cluster randomised controlled trial.BMJ (Clinical research ed.) · 2020Trial
- Article
- Does Health-Based Prospective Risk Adjustment Adequately Compensate for Individuals Diagnosed With a New Chronic Disease?Medical care research and review : MCRR · 2026Article
- Health problems of people with intellectual disabilities in general practice: dynamic cohort study between 2012 and 2021 with Dutch routine care data.The British journal of general practice : the journal of the Royal College of General Practitioners · 2026Article
- Data resource profile: the Intego-II primary care database.International journal of epidemiology · 2025Article
- Remote versus in-person consultations for acute cystitis: antibiotic treatment and clinical outcomes, a retrospective cohort study.BJGP open · 2025Article
- Observational
- Determinants of consent for electronic health information exchange: an observational retrospective study.Health research policy and systems · 2025Observational
- Implications of Data Extraction and Processing of Electronic Health Records for Epidemiological Research: Observational Study.Journal of medical Internet research · 2025Observational
- Adherence to antibiotic prescribing guidelines in Dutch primary care: an analysis of national prescription data on ear and respiratory tract symptoms and conditions among 384 general practices.Family practice · 2025Article
- The Occurrence of Health Symptoms in General Practice Before and After the Explantation of Cosmetic Breast Implants.Aesthetic surgery journal · 2025Article
- Depression care trajectories and associations with subsequent depressive episode: a registry-based cohort study (The Norwegian GP-DEP study).BMC primary care · 2025Article
- Epidemiological trends and economic burden of genital warts in Dutch primary care.BMJ public health · 2025Article
- Article
- Living in the vicinity of pesticide-treated crop fields: Exploring associated perceptions and psychological aspects in relation to self-reported and registry-based health symptoms.BMC psychology · 2024Article
- Dutch GP healthcare consumption in COVID-19 heterogeneous regions: an interregional time-series approach in 2020-2021.BJGP open · 2024Article
- Deriving Treatment Decision Support From Dutch Electronic Health Records by Exploring the Applicability of a Precision Cohort-Based Procedure for Patients With Type 2 Diabetes Mellitus: Precision Cohort Study.Online journal of public health informatics · 2024Article
- The impact of tinnitus on Dutch general practices: A retrospective study using routine healthcare data.PloS one · 2024Article
- Prenatal Exposure to the 1944-45 Dutch Famine and Risk for Dementia up to Age 75: An Analysis of Primary Care Data.Current Alzheimer research · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRoutinely 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.
objectiveThe 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.
methodsThe 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.
resultsAll 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.
conclusionsAn 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.