A multivariate statistical evaluation of actual use of electronic health record systems implementations in Kenya

Abstract

Background Health facilities in developing countries are increasingly adopting Electronic Health Records systems (EHRs) to support healthcare processes. However, only limited studies are available that assess the actual use of the EHRs once adopted in these settings. We assessed the state of the 376 KenyaEMR system (national EHRs) implementations in healthcare facilities offering HIV services in Kenya. Methods The study focused on seven EHRs use indicators. Six of the seven indicators were programmed and packaged into a query script for execution within each KenyaEMR system (KeEMRs) implementation to collect monthly server-log data for each indicator for the period 2012–2019. The indicators included: Staff system use, observations (clinical data volume), data exchange, standardized terminologies, patient identification, and automatic reports. The seventh indicator (EHR variable Completeness) was derived from routine data quality report within the EHRs. Data were analysed using descriptive statistics, and multiple linear regression analysis was used to examine how individual facility characteristics affected the use of the system. Results 213 facilities spanning 19 counties participated in the study. The mean number of authorized users who actively used the KeEMRs was 18.1% (SD = 13.1%, p<0.001) across the facilities. On average, the volume of clinical data (observations) captured in the EHRs was 3363 (SD = 4259). Only a few facilities(14.1%) had health data exchange capability. 97.6% of EHRs concept dictionary terms mapped to standardized terminologies such as CIEL. Within the facility EHRs, only 50.5% (SD = 35.4%, p< 0.001) of patients had the nationally-endorsed patient identifier number recorded. Multiple regression analysis indicated the need for improvement on the mode of EHRs use of implementation. Conclusion The standard EHRs use indicators can effectively measure EHRs use and consequently determine success of the EHRs implementations. The results suggest that most of the EHRs use areas assessed need improvement, especially in relation to active usage of the system and data exchange readiness.

Factors Influencing Data Quality in Electronic Health Record Systems in 50 Health Facilities in Rwanda and the Role of Clinical Alerts: Cross-Sectional Observational Study

“…Data completeness was 78% (95% CI 70.8%-85.1%) for paper records and 76% (95% CI 67.8%-83.2%) for the EHR. They used the κ statistic to compare variables in both records, with results ranging from κ=0.93 for demographics, κ=0.86 for WHO stage, and κ=0.83 for “general appearance.” Furthermore, Ngugi et al [ 40 ] studied the clinical use and completeness of data entry in KenyaEMR at 219 HFs in Kenya. They showed a wide variation in data entry per month in different HFs and noted that this was likely affected by “patients’ volume, frequency of patients’ visits (encounters), EHRs mode of use, and active use of the system during care.” Haskew et al [ 41 ] studied the quality of data collection and the effects of clinical alerts on HIV patient care in Western Kenya before and after the cloud-based implementation of an OpenMRS EHR.…”