Development of an algorithm to assess unmeasured symptom severity in gynecologic care.

ABSTRACT:

Background

Healthcare disparities research is often limited by incomplete accounting for differences in health status by populations. In the United States, hysterectomy shows marked variation by race and geography, but it is difficult to understand what factors cause these variations without accounting for differences in the severity of gynecologic symptoms that drive the decision-making for hysterectomy.

Objective

This study aimed to demonstrate a method for using electronic health record-derived data to create composite symptom severity indices to more fully capture relevant markers that influence the decision for hysterectomy.

Study design

This was a retrospective cohort study of 1993 women who underwent hysterectomy between April 4, 2014, and December 31, 2017, fr

SUBMITTER: Doll KM 

PROVIDER: S-EPMC8916977 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature