A Natural Language Processing-Based Approach for Identifying Hospitalizations for Worsening Heart Failure Within an Integrated Health Care Delivery System.

ABSTRACT:

Importance

The current understanding of epidemiological mechanisms and temporal trends in hospitalizations for worsening heart failure (WHF) is based on claims and national reporting databases. However, these data sources are inherently limited by the accuracy and completeness of diagnostic coding and/or voluntary reporting.

Objective

To assess the overall burden of and temporal trends in the rate of hospitalizations for WHF.

Design, setting, and participants

This cohort study, performed from January 1, 2010, to December 31, 2019, used electronic health record (EHR) data from a large integrated health care delivery system.

Exposures

Calendar year trends.

Main outcomes and measures

Hospitalizations for WHF (ie, excluding observation stays) were defined as

SUBMITTER: Ambrosy AP 

PROVIDER: S-EPMC8609413 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature