ArticleApplied clinical informatics2020
Heart Failure Dashboard Design and Validation to Improve Care of Veterans.
Article in Applied clinical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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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.
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Who cites it
11 citing papers in PubMed.
- DASH-HF Study: A Pragmatic Quality Improvement Randomized Implementation Trial for Patients With Heart Failure With Reduced Ejection Fraction.Circulation. Heart failure · 2023Trial
- Predicted Mortality and Cardiology Follow-up Following Heart Failure Hospitalizations Among Veterans Health Administration Patients.Journal of cardiac failure · 2025Article
- Development and Optimization of the Veterans Affairs' National Heart Failure Dashboard for Population Health Management.Journal of cardiac failure · 2024Article
- Dashboarding to Monitor Machine-Learning-Based Clinical Decision Support Interventions.Applied clinical informatics · 2024Article
- Strategies to enhance remote monitoring adherence among patients with cardiovascular implantable electronic devices.Heart rhythm O2 · 2023Article
- An Electronic Dashboard to Improve Dosing of Hydroxychloroquine Within the Veterans Health Care System: Time Series Analysis.JMIR medical informatics · 2023Article
- Beyond Information Design: Designing Health Care Dashboards for Evidence-Driven Decision-Making.Applied clinical informatics · 2023Article
- Developing the VA Geriatric Scholars Programs' Clinical Dashboards Using the PDSA Framework for Quality Improvement.Applied clinical informatics · 2022Article
- Electronic Health Records and Heart Failure.Heart failure clinics · 2022Review
- Human Factors and Organizational Issues in Health Informatics: Innovations and Opportunities.Yearbook of medical informatics · 2021Review
- Digital Health Surveillance Strategies for Management of Coronavirus Disease 2019.Mayo Clinic proceedings. Innovations, quality & outcomes · 2021Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEarly electronic identification of patients at the highest risk for heart failure (HF) readmission presents a challenge. Data needed to identify HF patients are in a variety of areas in the electronic medical record (EMR) and in different formats.
objectiveThe purpose of this paper is to describe the development and data validation of a HF dashboard that monitors the overall metrics of outcomes and treatments of the veteran patient population with HF and enhancing the use of guideline-directed pharmacologic therapies.
methodsWe constructed a dashboard that included several data points: care assessment need score; ejection fraction (EF); medication concordance; laboratory tests; history of HF; and specified comorbidities based on International Classification of Disease (ICD), ninth and tenth codes. Data validation testing with user test scripts was utilized to ensure output accuracy of the dashboard. Nine providers and key senior management participated in data validation.
resultsA total of 43 medical records were reviewed and 66 HF dashboard data discrepancies were identified during development. Discrepancies identified included: generation of multiple EF values on a few patients, missing or incorrect ICD codes, laboratory omission, incorrect medication issue dates, patients incorrectly noted as nonconcordant for medications, and incorrect dates of last cardiology appointments. Continuous integration and builds identified defects-an important process of the verification and validation of biomedical software. Data validation and technical limitations are some challenges that were encountered during dashboard development. Evaluations by testers and their focused feedback contributed to the lessons learned from the challenges.
conclusionContinuous refinement with input from multiple levels of stakeholders is crucial to development of clinically useful dashboards. Extraction of all relevant information from EMRs, including the use of natural language processing, is crucial to development of dashboards that will help improve care of individual patients and populations.
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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.