Accepted for/Published in: JMIR Human Factors
Date Submitted: Mar 28, 2023
Date Accepted: Jan 20, 2024
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Evaluation of a computer-aided clinical decision support system for point-of-care use in low-resource primary care settings
ABSTRACT
Background:
A computer-aided clinical decision support system (CDSS) based on the logic and philosophy of clinical pathways is critical for managing the quality of health care and for standardizing care processes. Using such a system at a point of care setting is becoming more frequent these days. However, in a low-resource setting (LRS), such systems are frequently overlooked.
Objective:
The purpose of the study was to evaluate a computer-aided CDSS in LRSs in general, and to assess user acceptance in particular.
Methods:
The computer-aided CDSS evaluation was carried out at Jimma Health Center and Jimma Higher Two Health Center, Jimma, Ethiopia. The evaluation was based on 22 parameters organized into six categories: ease of use, system quality, information quality, decision changes, process changes, and user acceptance. A Mann-Whitney U test was used to investigate whether the difference between the health centers was significant (two-tailed, 95% CI; α=.05). Pearson correlation and partial least squares structural equation modeling (PLS-SEM) was used to identify the relationship and factors influencing the overall acceptance of the computer-aided CDSS in LRS.
Results:
On the basis of 116 antenatal, pregnant, and postnatal cases, 73 computer-aided CDSS evaluation responses were recorded. We found that the two health centers did not differ significantly on 16 evaluation parameters. We did, however, detect a statistically significant difference in six parameters(P<.05). The PLS-SEM results show that the coefficient of determination, R2, of perceived user acceptance was 0.703. More precisely, the perceived ease of use (β=0.015, P=0.905) and information quality (β=0.149, P=0.246) had no positive effect on computer-aided CDSS acceptance, but rather system quality and perceived benefit of the computer-aided CDSS, with P-value < 0.05 and β=0.321 and β=0.486, respectively. Furthermore, perceived ease of use is influenced by information quality and system quality, with an R2 value of 0.479 indicating that the influence of information quality on ease of use was significant, but the influence of system quality on ease of use was not, with values of β=0.678 (P<.05) and β=0.021(P=.892), respectively. Moreover, the influence of decision changes (β=0.374, P<.05 ) and process changes (β=0.749, P<.05) was both significant on perceived benefit (R2 = 0.983).
Conclusions:
This study concludes that the users are more likely to accept and use the computer-aided CDSS at the point of care when it is easy to grasp the perceived benefit and system quality in terms of caregivers’ needs. We believe that the computer-aided CDSS acceptance model developed in this study reveals specific factors and variables, that constitute a step towards the effective adoption and deployment of a computer-aided CDSS in LRSs. Clinical Trial: NULL
Citation
