Design Approaches for Executable Clinical Pathways at the Point of Care in Limited Resource Settings to Support the Clinical Decision Process: Review of the State of the Art

Tegenaw, Geletaw Sahle; Amenu, Demisew; Ketema, Girum; Verbeke, Frank; Cornelis, Jan; Jansen, Bart M. P.

doi:10.1007/978-3-031-06368-8_13

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“…Step 2: We conducted a state-of-the-art review to investigate strategies and approaches for designing CDSS instruments for LRSs [ 10 ]. The aim was to review existing publications in the LRS context to explore recommended approaches and design considerations for building a CDSS.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of a Computer-Aided Clinical Decision Support System for Point-of-Care Use in Low-Resource Primary Care Settings: Acceptability Evaluation Study

Tegenaw,

Sori,

Teklemariam

et al. 2024

JMIR Hum Factors

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Background A 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 the user acceptance of a CDSS in LRSs. Methods The CDSS evaluation was carried out at the Jimma Health Center and the Jimma Higher Two Health Center, Jimma, Ethiopia. The evaluation was based on 22 parameters organized into 6 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 2 health centers was significant (2-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 CDSS in an LRS. Results On the basis of 116 antenatal care, pregnant patient care, and postnatal care cases, 73 CDSS evaluation responses were recorded. We found that the 2 health centers did not differ significantly on 16 evaluation parameters. We did, however, detect a statistically significant difference in 6 parameters ( P <.05). PLS-SEM results showed that the coefficient of determination, R 2 , of perceived user acceptance was 0.703. More precisely, the perceived ease of use (β=.015, P =.91) and information quality (β=.149, P =.25) had no positive effect on CDSS acceptance but, rather, on the system quality and perceived benefits of the CDSS, with P <.05 and β=.321 and β=.486, respectively. Furthermore, the perceived ease of use was influenced by information quality and system quality, with an R 2 value of 0.479, indicating that the influence of information quality on the ease of use is significant but the influence of system quality on the ease of use is not, with β=.678 ( P <.05) and β=.021( P =.89), respectively. Moreover, the influence of decision changes (β=.374, P <.05) and process changes (β=.749, P <.05) both was significant on perceived benefits (R 2 =0.983). Conclusions This study concludes that users are more likely to accept and use a CDSS at the point of care when it is easy to grasp the perceived benefits and system quality in terms of health care professionals’ needs. We believe that the CDSS acceptance model developed in this study reveals specific factors and variables that constitute a step toward the effective...

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Section: Introductionmentioning

confidence: 99%