Assessing Data Adequacy for High Blood Pressure Clinical Decision Support: A Quantitative Analysis

• Published in: Applied clinical informatics Vol. 12; no. 4; pp. 710 - 720
• Main Authors: Dorr, David A., D'Autremont, Christopher, Pizzimenti, Christie, Weiskopf, Nicole, Rope, Robert, Kassakian, Steven, Richardson, Joshua E., McClure, Rob, Eisenberg, Floyd
• Format: Journal Article
• Language: English
• Published: Rüdigerstraße 14, 70469 Stuttgart, Germany Georg Thieme Verlag KG 01.08.2021
• Subjects: Decision Support Systems, Clinical; Delivery of Health Care; Electronic Health Records; Humans; Hypertension; Research Article; Software; data quality; clinical decision support; hypertension
• ISSN: 1869-0327; 1869-0327
• DOI: 10.1055/s-0041-1732401

Abstract Objective  This study examines guideline-based high blood pressure (HBP) and hypertension recommendations and evaluates the suitability and adequacy of the data and logic required for a Fast Healthcare Interoperable Resources (FHIR)-based, patient-facing clinical decision support (CDS) HBP application. HBP is a major predictor of adverse health events, including stroke, myocardial infarction, and kidney disease. Multiple guidelines recommend interventions to lower blood pressure, but implementation requires patient-centered approaches, including patient-facing CDS tools. Methods  We defined concept sets needed to measure adherence to 71 recommendations drawn from eight HBP guidelines. We measured data quality for these concepts for two cohorts (HBP screening and HBP diagnosed) from electronic health record (EHR) data, including four use cases (screening, nonpharmacologic interventions, pharmacologic interventions, and adverse events) for CDS. Results  We identified 102,443 people with diagnosed and 58,990 with undiagnosed HBP. We found that 21/35 (60%) of required concept sets were unused or inaccurate, with only 259 (25.3%) of 1,101 codes used. Use cases showed high inclusion (0.9–11.2%), low exclusion (0–0.1%), and missing patient-specific context (up to 65.6%), leading to data in 2/4 use cases being insufficient for accurate alerting. Discussion  Data quality from the EHR required to implement recommendations for HBP is highly inconsistent, reflecting a fragmented health care system and incomplete implementation of standard terminologies and workflows. Although imperfect, data were deemed adequate for two test use cases. Conclusion  Current data quality allows for further development of patient-facing FHIR HBP tools, but extensive validation and testing is required to assure precision and avoid unintended consequences.