Marva Foster1, Catherine Albanese2, Qiang Chen2, Kristen A Sethares3, Stewart Evans2, Lisa Soleymani Lehmann4,5,6, Jacqueline Spencer7, Jacob Joseph4,8. 1. Emergency Services, VA Boston Healthcare System, Boston, Massachusetts, United States. 2. Data Management Office, VA New England Healthcare System, Bedford, Massachusetts, United States. 3. College of Nursing and Health Sciences, University of Massachusetts, Dartmouth, Massachusetts, United States. 4. Department of Medicine, Brigham & Women's Hospital, Boston, Massachusetts, United States. 5. Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States. 6. Department of Medicine, VA Boston Healthcare System, Boston, Massachusetts, United States. 7. Primary Care, VA New England Healthcare System, Bedford, Massachusetts, United States. 8. Department of Cardiology, VA Boston Healthcare System, Boston, Massachusetts, United States.
Abstract
BACKGROUND: Early 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. OBJECTIVE: The 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. METHODS: We 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. RESULTS: A 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. CONCLUSION: Continuous 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. Georg Thieme Verlag KG Stuttgart · New York.
BACKGROUND: Early electronic identification of patients at the highest risk for heart failure (HF) readmission presents a challenge. Data needed to identify HFpatients are in a variety of areas in the electronic medical record (EMR) and in different formats. OBJECTIVE: The 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. METHODS: We 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. RESULTS: A 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. CONCLUSION: Continuous 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. Georg Thieme Verlag KG Stuttgart · New York.
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