Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, Oregon, United States.
RTI International, Chicago, Illinois, United States.
Appl Clin Inform. 2021 Aug;12(4):710-720. doi: 10.1055/s-0041-1732401. Epub 2021 Aug 4.
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.
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.
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.
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.
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.
本研究检验了基于指南的高血压（HBP）和高血压建议，并评估了基于快速医疗互操作性资源（FHIR）的面向患者的临床决策支持（CDS）HBP 应用所需的数据和逻辑的适用性和充分性。HBP 是不良健康事件的主要预测因素，包括中风、心肌梗死和肾脏疾病。多项指南建议采取干预措施来降低血压，但实施需要以患者为中心的方法，包括面向患者的 CDS 工具。
我们定义了衡量从八项 HBP 指南中提取的 71 项建议的依从性所需的概念集。我们从电子健康记录（EHR）数据中为两个队列（HBP 筛查和 HBP 诊断）测量了这些概念的数据质量，包括四个 CDS 用例（筛查、非药物干预、药物干预和不良事件）。
我们确定了 102443 名确诊 HBP 患者和 58990 名未确诊 HBP 患者。我们发现，35 个所需概念集中的 21 个（60%）未被使用或不准确，只有 1101 个代码中的 259 个（25.3%）被使用。用例显示高包容性（0.9-11.2%）、低排斥性（0-0.1%）和缺失患者特定背景（高达 65.6%），导致 4 个用例中的 2 个数据不足以为准确的警报提供依据。
实施 HBP 建议所需的 EHR 数据质量高度不一致，反映了医疗保健系统的碎片化和标准术语和工作流程的不完全实施。尽管不完美，但数据被认为足以满足两个测试用例的要求。
当前的数据质量允许进一步开发面向患者的 FHIR HBP 工具，但需要进行广泛的验证和测试，以确保精度并避免意外后果。
