Clinical Decision Support Leveraging Health Information Exchange Improves Concordance with Patients' Resuscitation Orders and End-of-Life Wishes
Year: 2025
Type: article
Abstract: This study aims to improve concordance between patient end-of-life preferences and code status orders by incorporating data from a state registry with clinical decision support (CDS) within the electronic health record (EHR) to preserve patient autonomy and ensure that patients receive care that aligns with their wishes. Leveraging a health information exchange (HIE) interface between the New York State Medical Orders for Life-Sustaining Treatment (eMOLST) registry and the EHR of our academic health system, we developed a bundled CDS intervention that displays eMOLST information at the time of code status ordering and provides an in-line alert when providers enter a resuscitation order discordant with wishes documented in the eMOLST registry. To evaluate this intervention, we performed a segmented regression analysis of an interrupted time series to compare the percentage of discordant orders before and after implementation among all hospitalizations for which an eMOLST was available. We identified a total of 3,648 visits that had an eMOLST filed prior to inpatient admission and a code status order placed during admission. There was a statistically significant decrease of discordant resuscitation orders of −5.95% after the intervention went live, with a relative risk reduction of 25% (95% CI: −9.95%, −1.94%; p = 0.009) in the pre- and post-intervention period. Logistic regression model after adjusting for covariates showed an average marginal effect of −5.12% after the intervention (CI: −9.75%, −0.50%; p = 0.03). Our intervention resulted in a decrease in discordant resuscitation orders. This study demonstrates that accessibility to eMOLST data within the provider workflow supported by CDS can reduce discrepancies between patient end-of-life wishes and hospital code status orders.
Source: Applied Clinical Informatics
DOI: 10.1055/a-2591-9040
Institutions: NYU Langone Health, New York University
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: green
Funder: York University
OpenAlex ID: W4409717380
