Factors Influencing Health Workers’ Acceptance of Guideline-Based Clinical Decision Support Systems for Preventive Services in Thailand: Questionnaire-Based Study

TL;DR

This study explores why health workers in Thailand are likely to adopt a new clinical decision support system for preventive care.

Contribution

The study identifies positive attitudes and effort expectancy as key factors influencing CDSS adoption in preventive services.

Findings

79% of participants expressed a high intention to use the CDSS for preventive care.

Positive attitudes and effort expectancy were critical factors influencing CDSS adoption.

Barriers included data input accuracy, time constraints, and workflow disruption.

Abstract

A guideline-based clinical decision support system (CDSS) is a knowledge-based system designed to collect crucial data from electronic medical records to generate decision-making based on system data requirements and inputs from standard guidelines. Despite the potential to enhance health care delivery, the adoption rate of CDSSs in clinical practice remains suboptimal.

This study aimed to evaluate the determinants influencing the intention to use a new CDSS in preventive care within clinical practice.

A single-center, questionnaire-based, cross-sectional study was conducted among physicians and medical students responsible for providing comprehensive preventive services at the Continuity of Care Clinic, Siriraj Hospital, Thailand.

In total, 89 participants were enrolled. Relationships between factors impacting the adoption of CDSSs were analyzed using correlation and regression analysis. We found that physicians’ intentions to adopt the CDSS for preventive care were high, with 79% (70/89) of participants expressing their intention to use the system. According to the study’s conceptual framework, modified from the original unified theory of acceptance and use of technology model, physicians’ positive attitudes toward CDSS use in preventive services and a high level of effort expectancy emerged as crucial factors influencing the intention to use the new CDSS. The odds ratios for these factors were 5.44 (95% CI 1.62‐18.34, P=.006) and 7.60 (95% CI 1.55‐31.37, P=.01), respectively. Similar results were observed for medical students and for physicians who had graduated. The most prevalent barriers to CDSS implementation were related to physicians’ attitudes, followed by issues such as the accuracy and burden of data input, time constraints for clinicians, and the risk of workflow disruption.

There was a high intention to adopt the CDSS in preventive care. Positive physician attitudes toward CDSS use in preventive services and effort expectancy were found to be critical factors influencing the intention to use the new CDSS.

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