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Validating a case definition for adult asthma in primary care electronic medical records.

ABSTRACT: Although asthma is one of the most common chronic conditions affecting Canadians, its epidemiologic characteristics and burden in primary care contexts are poorly understood. The aim of this study was to develop and validate a case definition to identify adults with asthma who consult family physicians and to estimate the prevalence of asthma in that setting in Canada. This validation study utilized a database of electronic medical records (EMRs) from the Southern Alberta Primary Care Research Network, a node of the Canadian Primary Care Sentinel Surveillance Network (SAPCReN-CPCSSN). The population included patients over age 17y of any gender and health status who had visited an SAPCReN-CPCSSN primary care provider during the period December 1, 2014-December 31, 2016. The validation of the case definition involved comparing a case-finding algorithm to caseness determined by an expert physician review of the records of 1000 patient in the CPCSSN database. The case definition, which included the ICD-9 code 493 and asthma-related text words, had 83.33% sensitivity (95% CI: 63.61-93.88%), 99.28% specificity (95% CI: 98.51-99.67%), a positive predictive value of 74.07% (95% CI: 55.03-87.14%), and a negative predictive value of 99.59% (95% CI: 98.93-99.86%). The prevalence of adult asthma in CPCSSN primary care practices in southern Alberta was 4.20% (95% CI: 4.09-4.31). The strong validation metrics suggest that this case definition is valid for both clinical and research purposes. The validated case definition may be used to improve patient care and improve understanding of the prevalence and burden of asthma in primary care in Canada.

SUBMITTER: Cave AJ

PROVIDER: S-EPMC7275082 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Validating a case definition for adult asthma in primary care electronic medical records.

Cave Andrew J AJ Soos Boglarka B Gillies Christina C Drummond Neil N Pham Anh N Q ANQ Williamson Tyler T

NPJ primary care respiratory medicine 20200605 1

Although asthma is one of the most common chronic conditions affecting Canadians, its epidemiologic characteristics and burden in primary care contexts are poorly understood. The aim of this study was to develop and validate a case definition to identify adults with asthma who consult family physicians and to estimate the prevalence of asthma in that setting in Canada. This validation study utilized a database of electronic medical records (EMRs) from the Southern Alberta Primary Care Research N ...[more]

PMID: 32503968

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Project description:To investigate the performance of parent-reported data in identifying physician-confirmed asthma.Validation study using linkage between the Avon Longitudinal Study of Parents and Children (ALSPAC) and electronic patient records held within the General Practice Research Database (GPRD).Participants were those eligible to participate in ALSPAC who also had a record in the GPRD; this included 765 individuals, just under 4% of ALSPAC-eligible participants. The analysis was based on 141 participants with complete parent-reported asthma data.The main GPRD outcome measure was whether a child had a diagnosis of asthma before they were nine. Parent-reported measures were doctor diagnosis of asthma (before mean age 7.5 years), various outcomes based on wheezing and breathlessness recorded longitudinally between 6 months and 8.5 years. Secondary outcomes were bronchial hyper-responsiveness (BHR), forced expiratory volume in 1 s/forced vital capacity ratio and skin prick test responses.Among the 141 participants with complete parent-reported data, 26 (18%) had an asthma diagnosis before age nine. Using general practitioner (GP)-recorded asthma as the gold standard, the question 'Has a doctor ever diagnosed your child with asthma?' was both sensitive (88.5%) and specific (95.7%). 'Ever wheezed' had the highest sensitivity (100%) but low specificity (60%). More specific definitions were obtained by restricting to those who had wheezed on more than one occasion, experienced frequent wheeze and/or wheezed after the age of 3, but these measures had low sensitivities. BHR only identified 50% of those with a GP-recorded diagnosis.Parental reports of a doctor's diagnosis agree well with a GP-recorded diagnosis. High specificity for asthma can be achieved by using detailed wheezing questions, although these definitions are likely to exclude mild cases of asthma. Our study shows that linkage between observational studies and electronic patient records has the potential to enhance epidemiological research.

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:BackgroundIdentifying cases of disease in primary care electronic medical records (EMRs) is important for surveillance, research, quality improvement and clinical care. We aimed to develop and validate a case definition for type 1 diabetes mellitus using EMRs.MethodsFor this exploratory study, we used EMR data from the Southern Alberta Primary Care Network within the Canadian Primary Care Sentinel Surveillance Network (CPCSSN), for the period 2008 to 2016. For patients identified as having diabetes mellitus according to the existing CPCSSN case definition, we asked family physicians to confirm the diabetes subtype, to create the reference standard. We used 3 decision-tree classification algorithms and least absolute shrinkage and selection operator logistic regression to identify variables that correctly distinguished between type 1 and type 2 diabetes cases.ResultsWe identified a total of 1309 people with type 1 or type 2 diabetes, 110 of whom were confirmed by their physicians as having type 1 diabetes. Two machine learning algorithms were useful in identifying these cases in the EMRs. The first algorithm used "type 1" text words or age less than 22 years at time of initial diabetes diagnosis; this algorithm had sensitivity 42.7% (95% confidence interval [CI] 33.5%-52.5%), specificity 99.3% (95% CI 98.6%-99.7%), positive predictive value 85.5% (95% CI 72.8%-93.1%) and negative predictive value 94.9% (95% CI 93.5%-96.1%). The second algorithm used a combination of free-text terms, insulin prescriptions and age; it had sensitivity 87.3% (95% CI 79.2%-92.6%), specificity 85.4% (95% CI 83.2%-87.3%), positive predictive value 35.6% (95% CI 29.9%-41.6%) and negative predictive value 98.6% (95% CI 97.7%-99.2%).InterpretationWe used machine learning to develop and validate 2 case definitions that achieve different goals in distinguishing between type 1 and type 2 diabetes in CPCSSN data. Further validation and testing with a larger and more diverse sample are recommended.

Project description:BackgroundMost asthma diagnoses and patient care take place in primary care settings. Electronic medical records (EMRs) offer an opportunity to utilize technology to improve asthma diagnosis and care. The purpose of this study was to create and validate separate case definitions for suspected and confirmed asthma in primary care EMRs, to enable surveillance, benchmarking, and quality improvement in primary care settings. The objective of this study was to develop a case definition for suspected and confirmed asthma for use in a primary care sentinel surveillance system.MethodsA single chart abstractor conducted a manual audit of 776 randomly selected patient charts from an academic primary care practice EMR in Kingston, Ontario. Following the single chart abstractor classification, a consensus on chart classification as "not asthma", "suspected asthma", or "confirmed asthma" was achieved between the abstractor, a family physician, and a respirologist using Canadian Thoracic Society (CTS) criteria. Case definition algorithms based on billing codes, clinical data elements and medications were applied to the site's Canadian Primary Care Sentinel Surveillance Network (CPCSSN) data for the same charts and compared to abstractor classifications to determine each algorithm's measurement properties.ResultsThe prevalence of suspected and confirmed asthma were 7.3% (n = 54) and 2.4% (n = 18), respectively. None of the proposed case definitions could differentiate between suspected and confirmed asthma. One algorithm consisting of billing, clinical, and medication elements had the highest Youden's Index for either suspected or confirmed asthma. The algorithm had a sensitivity of 81%, a specificity of 96%, positive predictive value of 71%, negative predictive value of 98%, and a Youden's Index of 0.77 for combined suspected or confirmed asthma cases.ConclusionAn EMR case definition for suspected or confirmed adult asthma has been validated for use in CPCSSN. Implementation of this case definition will enable the development of a surveillance electronic tool (eTool) for adult asthma that can foster quality improvement.

Project description:BackgroundIneffective transitions of care continue to be a source of risk for patients. Although there has been widespread implementation of electronic medical record (EMR) systems, little is currently known about hospitalists' and primary care providers' (PCPs) direct communication preferences at discharge using messaging capabilities in a shared EMR system.ObjectiveWe examined how hospitalists and PCPs with a shared EMR prefer to directly communicate at the time of hospital discharge by identifying preferred modes, information prioritization, challenges, facilitators, and proposed solutions.DesignA sequential, explanatory mixed methods study with surveys and semi-structured interviews.ParticipantsThirty-eight academic hospitalists and 63 PCPs working in outpatient clinics in a single safety net hospital system with a shared EMR.Main approachDescriptive statistics were used to analyze survey responses. Interviews were analyzed using immersion/crystallization and a mixture of inductive and deductive thematic analysis.Key resultsPCPs preferred direct communication at discharge through a message within the EMR while hospitalists preferred a message within the EMR and email. Qualitative results identified key themes related to patient care and direct communication: value of direct communication, safety, social determinants of health, and clinical judgment. Both groups prioritized direct communication for high-risk medications, pending and follow-up studies, and high-risk patients that hospitalists were concerned about. Overall, both hospitalists and PCPs reported that ensuring patient safety, flagging patients with social challenges, and expressing concerns about patients based on clinical judgment were key communication priorities.ConclusionsHospitalists and primary care providers report considerable overlap in preferences for direct communication at the time of hospital discharge through a shared EMR. Specifically, both groups reported similar concerns regarding patient safety and continuity during transitions. Direct messaging within the EMR could enable "closed loop" communication that helps ensure safe transitions of care for high-risk patients.

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Validating a case definition for adult asthma in primary care electronic medical records.

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Validating a case definition for adult asthma in primary care electronic medical records.

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