Generalizability of an EHR-network dataset to the United States for cardiovascular disease conditions: Comparison of Cerner real world data with the national inpatient sample

Nishant P Shah; Eric D Peterson; Courtney Page; Rosalia Blanco; Ann Marie Navar

doi:10.1016/j.ahj.2023.05.009

Generalizability of an EHR-network dataset to the United States for cardiovascular disease conditions: Comparison of Cerner real world data with the national inpatient sample

Am Heart J. 2023 Sep:263:64-72. doi: 10.1016/j.ahj.2023.05.009. Epub 2023 May 15.

Authors

Nishant P Shah¹, Eric D Peterson², Courtney Page³, Rosalia Blanco³, Ann Marie Navar²

Affiliations

¹ Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC.. Electronic address: nishant.shah@duke.edu.
² Department of Medicine, Division of Cardiology, University of Texas Southwestern Medical Center, Dallas, TX.
³ Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC.

PMID: 37196972
DOI: 10.1016/j.ahj.2023.05.009

Abstract

Background: Electronic Health Record (EHR) data from health systems are increasingly being combined for clinical research purposes. Yet, it remains unclear whether these large EHR data sources provide a representative assessment of national disease prevalence and treatment. To evaluate this, we compared Cerner RealWorldData (CRWD), a large EHR data source, to those seen in the National Inpatient Sample (NIS) for 3 cardiovascular conditions (myocardial infarction (MI), congestive heart failure (CHF), and stroke.

Methods: Adult patients (age ≥18 years) hospitalized with MI, CHF, and stroke were identified in both CRWD (86 health systems) and the NIS (4,782 hospitals). Patient demographics, comorbidities, procedures, outcomes (length of stay and in-hospital mortality) and hospital type (teaching or nonteaching) were compared between NIS and CRWD patients.

Results: Of 86 health systems participating in CRWD, 33 were excluded for potential data quality issues which accounted for about 11% of hospitalizations in the dataset, leaving 53 for inclusion in analysis which accounted for about 89% of hospitalizations in the dataset. Between January 1, 2017 and December 31, 2018, 116,956 MI, 188,107 CHF, and 93,968 stroke hospitalizations were identified in CRWD vs 2,245,300 MI, 4,310,745 CHF, and 1,333,480 stroke hospitalizations in the NIS. Patient demographics were similar among patients in CWRD and the NIS for all 3 cardiovascular groups except for ethnicity, with underrepresentation of Hispanic individuals in CRWD vs the NIS. Patients hospitalized in CRWD had a slightly higher proportion of coded co-morbidities compared with NIS hospitalizations due to a longer potential look-back period. For patients with MI, hospital mortality, length of stay, coronary artery bypass graft (CABG) rates, and percutaneous coronary intervention (PCI) rates were similar between CRWD and NIS. Additionally, there was similar in hospital mortality and length of stay for those with CHF and stroke hospitalizations between CRWD and NIS.

Conclusions: On aggregate, characteristics of hospitalizations for MI, CHF, and stroke using EHR data from one nationwide EHR-derived database, CRWD, appears similar to characteristics of hospitalizations in the nationally representative NIS. Important limitations of CRWD include lack of geographic representativeness, under-representation of Hispanic adults, and the need to exclude health systems for missing data.