National Association of Chronic Disease Directors, 101 W Ponce de Leon, Decatur, GA 30030 (
Commonwealth Informatics, Waltham, Massachusetts.
Prev Chronic Dis. 2023 Sep 14;20:E80. doi: 10.5888/pcd20.230026.
Modernizing chronic disease surveillance with electronic health record (EHR) data may provide better data to improve hypertension prevention and control, but no consensus exists for an EHR-based surveillance definition for hypertension. The Multi-State EHR-Based Network for Disease Surveillance (MENDS) pilot surveillance system was used to develop and test an electronic phenotype for hypertension.
We used MENDS data from 1,671,279 patients in Louisiana to examine the effect of different analytic decisions on estimates of hypertension prevalence. Decisions included 1) whether to restrict surveillance to patients with recent blood pressure measurements, 2) varying the number and recency of encounters to define the population at risk of hypertension, 3) how to define hypertension (diagnosis codes, antihypertensive medication, blood pressure measurements, or combinations of these), and 4) how to handle multiple blood pressure measurements on the same day. Results were compared with independent estimates of hypertension prevalence in Louisiana from the Behavioral Risk Factor Surveillance System (BRFSS).
Applying varying criteria resulted in hypertension prevalence estimates ranging from 19.7% to 59.3%. A hypertension surveillance strategy that includes a population with at least 1 clinical encounter with measured blood pressure in the previous 2 years and identifies hypertension using all available data (≥1 diagnosis code, ≥1 antihypertensive medication, and ≥2 elevated blood pressure values ≥140/90 mm Hg on separate days) generated estimates in line with population-based survey data. This definition estimated the crude 2019 hypertension prevalence in the state of Louisiana as 43.4% (age-adjusted, 41.0%), comparable with the crude BRFSS estimate of 39.7% (age adjusted, 37.1%).
Applying different criteria to define hypertension using EHR data has a large effect on hypertension prevalence estimates. The proposed electronic phenotype generates hypertension prevalence estimates that align with independent estimates from BRFSS.
利用电子健康记录 (EHR) 数据实现慢性病监测现代化，可能会提供更好的数据，以改善高血压的预防和控制，但目前尚缺乏基于 EHR 的高血压监测定义的共识。多州基于 EHR 的疾病监测网络 (MENDS) 试点监测系统被用于开发和测试高血压的电子表型。
我们利用来自路易斯安那州 1671279 名患者的 MENDS 数据，考察了不同分析决策对高血压患病率估计值的影响。决策包括：1）是否将监测仅限于近期血压测量的患者；2）改变定义高血压风险人群的就诊次数和时间范围；3）如何定义高血压（诊断代码、抗高血压药物、血压测量值或这些的组合）；4）如何处理同一天的多次血压测量值。结果与来自行为风险因素监测系统 (BRFSS) 的路易斯安那州高血压患病率的独立估计值进行了比较。
应用不同标准得出的高血压患病率估计值从 19.7%到 59.3%不等。一种高血压监测策略，包括至少有 1 次最近 2 年内有测量血压的临床就诊，并且使用所有可用数据（≥1 个诊断代码、≥1 种抗高血压药物和≥2 次不同日期的≥2 次升高的血压值≥140/90mmHg）来识别高血压，可以生成与基于人群的调查数据一致的估计值。该定义估计路易斯安那州 2019 年高血压的粗患病率为 43.4%（年龄调整后为 41.0%），与 BRFSS 的粗估计值 39.7%（年龄调整后为 37.1%）相当。
使用 EHR 数据定义高血压时应用不同的标准对高血压患病率估计值有很大影响。所提出的电子表型生成的高血压患病率估计值与 BRFSS 的独立估计值一致。
