Development of Standard Indicators to Assess Use of Electronic Health Record Systems Implemented in Low- and Medium-Income Countries

Abstract

BackgroundElectronic Health Record Systems (EHRs) are being rolled out nationally in many low- and middle-income countries (LMICs) yet assessing actual system usage remains a challenge. We employed a nominal group technique (NGT) process to systematically develop high-quality indicators for evaluating actual usage of EHRs in LMICs.Methods An initial set of 14 candidate indicators were developed by the study team adapting the HIV Monitoring, Evaluation, and Reporting indicators format. A multidisciplinary team of 10 experts was convened in a two-day NGT workshop in Kenya to systematically evaluate, rate (using Specific, Measurable, Achievable, Relevant, and Time-Bound (SMART) criteria), prioritize, refine, and identify new indicators. NGT steps included introduction to candidate indicators, silent indicator ranking, round-robin indicator rating, and silent generation of new indicators. Results: Candidate indicators were rated highly on SMART criteria (4.05/5). NGT participants settled on 15 final indicators, categorized as system use (4); data quality (3), system interoperability (3), and reporting (5). Data entry statistics, systems uptime, and EHRs variable concordance indicators were rated highest. ConclusionThis study describes a systematic approach to develop and validate quality indicators for determining EHRs use and provides LMICs with a multidimensional tool for assessing success of EHRs implementations.

Users’ perception on factors contributing to electronic medical records systems use: a focus group discussion study in healthcare facilities setting in Kenya

“…They were determined from facilities’ EMRs use performance assessment, conducted in our ongoing evaluation study on the actual use of EMRs implementations in healthcare facilities in Kenya [ 30 ]. The assessment utilized computer-generated EMRs use empirical data based on various EMRs use indicator measures as outlined in Ngugi et al [ 37 ]. In that study, facility performance was determined by weighted mean calculated from the empirical data of two EMRs use indicators: Staff System Use (proportion of active system users) and Patient Identification (percentage of patient records with national identification number).…”

Users’ Perception on Factors Contributing to Electronic Medical Records Systems Use: A Focus Group Discussion Study in Healthcare Facilities Setting in Kenya

“…These study facilities were determined from facility performance assessment conducted in our ongoing evaluation study on the actual use of EMRs implemented in healthcare facilities in Kenya (Philomena et al, under review). The assessment utilized computer-generated EMRs use empirical data based on various EHRs use indicator measures (22). The selection criteria was guided by facility performance outcome determined by the weighted mean calculated from empirical data of two EHRs use indicators: Staff System Use (proportion of active system users) and Patient Identi cation (percentage of patient records with national identi cation number).…”

Evaluation of Management Information Systems for Pharmaceutical Inventory Control at The Hospital

“…Hospitals are required to be able to provide fast, precise and quality services, so to support pharmaceutical services, a tool is needed to achieve good health services (Murnita, et al, 2016). Therefore, management information system support is very necessary (Advistasari, et al, 2015;Ngugi et al, 2020).…”