Evaluation of interventions to improve electronic health record documentation within the inpatient setting: a protocol for a systematic review

Lucia Otero VarelaEmail author View ORCID ID profile,
Natalie Wiebe,
Daniel J. Niven,
Paul E. Ronksley,
Nicolas Iragorri,
Helen Lee Robertson and
Hude Quan

Systematic Reviews20198:54

https://doi.org/10.1186/s13643-019-0971-2

Received: 7 May 2018
Accepted: 4 February 2019
Published: 13 February 2019

Abstract

Background

Electronic health records (EHRs) are increasing in popularity across national and international healthcare systems. Despite their augmented availability and use, the quality of electronic health records is problematic. There are various reasons for poor documentation quality within the EHR, and efforts have been made to address these areas. Previous systematic reviews have assessed intervention effectiveness within the outpatient setting or within paper documentation. This systematic review aims to assess the effectiveness of different interventions seeking to improve EHR documentation within an inpatient setting.

Methods

We will employ a comprehensive search strategy that encompasses four distinct themes: EHR, documentation, interventions, and study design. Four databases (MEDLINE, EMBASE, CENTRAL, and CINAHL) will be searched along with an in-depth examination of the grey literature and reference lists of relevant articles. A customized hybrid study quality assessment tool has been designed, integrating components of the Downs and Black and Newcastle-Ottawa Scales, into a REDCap data capture form to facilitate data extraction and analysis. Given the predicted high heterogeneity between studies, it may not be possible to standardize data for a quantitative comparison and meta-analysis. Thus, data will be synthesized in a narrative, semi-quantitative manner.

Discussion

This review will summarize the current level of evidence on the effectiveness of interventions implemented to improve inpatient EHR documentation, which could ultimately enhance data quality in administrative health databases.