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Identification of validated case definitions for chronic disease using electronic medical records: a systematic review protocol.

ABSTRACT: Primary care electronic medical record (EMR) data are being used for research, surveillance, and clinical monitoring. To broaden the reach and usability of EMR data, case definitions must be specified to identify and characterize important chronic conditions. The purpose of this study is to identify all case definitions for a set of chronic conditions that have been tested and validated in primary care EMR and EMR-linked data. This work will provide a reference list of case definitions, together with their performance metrics, and will identify gaps where new case definitions are needed.We will consider a set of 40 chronic conditions, previously identified as potentially important for surveillance in a review of multimorbidity measures. We will perform a systematic search of the published literature to identify studies that describe case definitions for clinical conditions in EMR data and report the performance of these definitions. We will stratify our search by studies that use EMR data alone and those that use EMR-linked data. We will compare the performance of different definitions for the same conditions and explore the influence of data source, jurisdiction, and patient population.EMR data from primary care providers can be compiled and used for benefit by the healthcare system. Not only does this work have the potential to further develop disease surveillance and health knowledge, EMR surveillance systems can provide rapid feedback to participating physicians regarding their patients. Existing case definitions will serve as a starting point for the development and validation of new case definitions and will enable better surveillance, research, and practice feedback based on detailed clinical EMR data.PROSPERO CRD42016040020.

SUBMITTER: Souri S

PROVIDER: S-EPMC5322672 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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Identification of validated case definitions for chronic disease using electronic medical records: a systematic review protocol.

Souri Sepideh S Symonds Nicola E NE Rouhi Azin A Lethebe Brendan C BC Garies Stephanie S Ronksley Paul E PE Williamson Tyler S TS Fabreau Gabriel E GE Birtwhistle Richard R Quan Hude H McBrien Kerry A KA

Systematic reviews 20170223 1

<h4>Background</h4>Primary care electronic medical record (EMR) data are being used for research, surveillance, and clinical monitoring. To broaden the reach and usability of EMR data, case definitions must be specified to identify and characterize important chronic conditions. The purpose of this study is to identify all case definitions for a set of chronic conditions that have been tested and validated in primary care EMR and EMR-linked data. This work will provide a reference list of case de ...[more]

PMID: 28231810

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Project description:BackgroundTo date, there has been no validated method to identify cases of pelvic floor disorders in primary care electronic medical record (EMR) data. We aimed to develop and validate symptom-based case definitions for urinary incontinence, fecal incontinence and pelvic organ prolapse in women, for use in primary care epidemiologic or clinical research.MethodsOur retrospective study used EMR data from the Southern Alberta Primary Care Research Network (SAPCReN) and the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) in southern Alberta. Trained researchers remotely reviewed a random sample of EMR charts of women aged 18 years or older from 6 rural and urban clinics to validate case definitions for urinary incontinence, fecal incontinence and pelvic organ prolapse. We calculated sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV), and estimated SAPCReN prevalence as appropriate.ResultsCharts of 900 women were included. Sensitivity was 81.9% (95% confidence interval [CI] 75.1-87.2) for urinary incontinence, 61.2% (95% CI 46.2-74.5) for fecal incontinence, and 51.8% (95% CI 40.6-62.8) for pelvic organ prolapse. Corresponding specificity values were 71.9% (95% CI 68.4-75.1), 99.2% (95% CI 98.2-99.6) and 98.8% (95% CI 97.7-99.4), PPVs 40.6% (95% CI 35.4-46.0), 81.1% (95% CI 64.3-91.4) and 81.1% (95% CI 67.6-90.1), and NPVs 94.4% (95% CI 92.1-96.1), 97.8% (95% CI 96.5-98.6) and 95.3% (95% CI 93.6-96.6). The SAPCReN-observed prevalence for urinary incontinence was 29.7% (95% CI 29.3-30.0), but the adjusted prevalence was 2.97%.InterpretationThe case definition for urinary incontinence met our standard for validity (sensitivity and specificity > 70%), and the case definitions for fecal incontinence and pelvic organ prolapse had PPVs greater than 80%. The urinary incontinence definition may be used in epidemiologic research, and those for fecal incontinence and pelvic organ prolapse may be used in quality-improvement studies or creation of disease registries. Our symptom-based case definitions could also be adapted for research in other EMR settings.

Project description:BackgroundEngaging patients in the delivery of health care has the potential to improve health outcomes and patient satisfaction. Patient portals may enhance patient engagement by enabling patients to access their electronic medical records (EMRs) and facilitating secure patient-provider communication.ObjectiveThe aim of this study was to review literature describing patient portals tethered to an EMR in inpatient settings, their role in patient engagement, and their impact on health care delivery in order to identify factors and best practices for successful implementation of this technology and areas that require further research.MethodsA systematic search for articles in the PubMed, CINAHL, and Embase databases was conducted using keywords associated with patient engagement, electronic health records, and patient portals and their respective subject headings in each database. Articles for inclusion were evaluated for quality using A Measurement Tool to Assess Systematic Reviews (AMSTAR) for systematic review articles and the Quality Assessment Tool for Studies with Diverse Designs for empirical studies. Included studies were categorized by their focus on input factors (eg, portal design), process factors (eg, portal use), and output factors (eg, benefits) and by the valence of their findings regarding patient portals (ie, positive, negative, or mixed).ResultsThe systematic search identified 58 articles for inclusion. The inputs category was addressed by 40 articles, while the processes and outputs categories were addressed by 36 and 46 articles, respectively: 47 articles addressed multiple themes across the three categories, and 11 addressed only a single theme. Nineteen articles had high- to very high-quality, 21 had medium quality, and 18 had low- to very low-quality. Findings in the inputs category showed wide-ranging portal designs; patients' privacy concerns and lack of encouragement from providers were among portal adoption barriers while information access and patient-provider communication were among facilitators. Several methods were used to train portal users with varying success. In the processes category, sociodemographic characteristics and medical conditions of patients were predictors of portal use; some patients wanted unlimited access to their EMRs, personalized health education, and nonclinical information; and patients were keen to use portals for communicating with their health care teams. In the outputs category, some but not all studies found patient portals improved patient engagement; patients perceived some portal functions as inadequate but others as useful; patients and staff thought portals may improve patient care but could cause anxiety in some patients; and portals improved patient safety, adherence to medications, and patient-provider communication but had no impact on objective health outcomes.ConclusionsWhile the evidence is currently immature, patient portals have demonstrated benefit by enabling the discovery of medical errors, improving adherence to medications, and providing patient-provider communication, etc. High-quality studies are needed to fully understand, improve, and evaluate their impact.

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Identification of validated case definitions for chronic disease using electronic medical records: a systematic review protocol.

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Identification of validated case definitions for chronic disease using electronic medical records: a systematic review protocol.

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