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Use of Electronic Health Records and Geographic Information Systems in Public Health Surveillance of Type 2 Diabetes

2016-03-17Artigo científico Acesso aberto
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dc.contributor.authorSilva, Liliana Laranjo
dc.contributor.authorRodrigues, David
dc.contributor.authorPereira, Ana Marta
dc.contributor.authorRibeiro, Rogério T
dc.contributor.authorBoavida, José Manuel
dc.contributor.institutionEscola Nacional de Saúde Pública (ENSP)
dc.contributor.institutionNOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)
dc.contributor.institutionInstituto de Estudos de Literatura e Tradição (IELT - NOVA FCSH)
dc.contributor.pblJMIR Publications
dc.date.accessioned2021-03-29T22:14:14Z
dc.date.available2021-03-29T22:14:14Z
dc.date.issued2016-03-17
dc.description.abstractBACKGROUND: Data routinely collected in electronic health records (EHRs) offer a unique opportunity to monitor chronic health conditions in real-time. Geographic information systems (GIS) may be an important complement in the analysis of those data. OBJECTIVE: The aim of this study was to explore the feasibility of using primary care EHRs and GIS for population care management and public health surveillance of chronic conditions, in Portugal. Specifically, type 2 diabetes was chosen as a case study, and we aimed to map its prevalence and the presence of comorbidities, as well as to identify possible populations at risk for cardiovascular complications. METHODS: Cross-sectional study using individual-level data from 514 primary care centers, collected from three different types of EHRs. Data were obtained on adult patients with type 2 diabetes (identified by the International Classification of Primary Care [ICPC-2] code, T90, in the problems list). GISs were used for mapping the prevalence of diabetes and comorbidities (hypertension, dyslipidemia, and obesity) by parish, in the region of Lisbon and Tagus Valley. Descriptive statistics and multivariate logistic regression were used for data analysis. RESULTS: We identified 205,068 individuals with the diagnosis of type 2 diabetes, corresponding to a prevalence of 5.6% (205,068/3,659,868) in the study population. The mean age of these patients was 67.5 years, and hypertension was present in 71% (144,938/205,068) of all individuals. There was considerable variation in diagnosed comorbidities across parishes. Diabetes patients with concomitant hypertension or dyslipidemia showed higher odds of having been diagnosed with cardiovascular complications, when adjusting for age and gender (hypertension odds ratio [OR] 2.16, confidence interval [CI] 2.10-2.22; dyslipidemia OR 1.57, CI 1.54-1.60). CONCLUSIONS: Individual-level data from EHRs may play an important role in chronic disease surveillance, namely through the use of GIS. Promoting the quality and comprehensiveness of data, namely through patient involvement in their medical records, is crucial to enhance the feasibility and usefulness of this approach.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent2268057
dc.identifier.doi10.2196/publichealth.4319
dc.identifier.issn2369-2960
dc.identifier.otherPURE: 2434856
dc.identifier.otherPURE UUID: aacd1aea-f97f-40f9-90c4-5c5884e082a0
dc.identifier.otherPubMed: 27227147
dc.identifier.otherPubMedCentral: PMC4869237
dc.identifier.otherScopus: 85031933608
dc.identifier.urihttp://hdl.handle.net/10362/114663
dc.language.isoeng
dc.peerreviewedyes
dc.subjectdiabetes mellitus
dc.subjectelectronic health records
dc.subjectgeographic information systems
dc.subjecthealth records
dc.subjectpersonal
dc.subjectprimary health care
dc.subjectSDG 3 - Good Health and Well-being
dc.titleUse of Electronic Health Records and Geographic Information Systems in Public Health Surveillance of Type 2 Diabetesen
dc.title.subtitleA Feasibility Studyen
dc.typejournal article
degois.publication.firstPage
degois.publication.issue1
degois.publication.lastPage
degois.publication.titleJMIR public health and surveillance
degois.publication.volume2
dspace.entity.typePublication
rcaap.rightsopenAccess

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