Is it possible to automatically assess pretreatment digital rectal examination documentation using natural language processing? A single-centre retrospective study.

ABSTRACT:

Objectives

To develop and test a method for automatic assessment of a quality metric, provider-documented pretreatment digital rectal examination (DRE), using the outputs of a natural language processing (NLP) framework.

Setting

An electronic health records (EHR)-based prostate cancer data warehouse was used to identify patients and associated clinical notes from 1 January 2005 to 31 December 2017. Using a previously developed natural language processing pipeline, we classified DRE assessment as documented (currently or historically performed), deferred (or suggested as a future examination) and refused.

Primary and secondary outcome measures

We investigated the quality metric performance, documentation 6 months before treatment and identified patient and clinical fac

SUBMITTER: Bozkurt S 

PROVIDER: S-EPMC6661600 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature