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ABSTRACT: Objectives
This study aims to identify a user acceptance model for the health referral system in Indonesia. The following factors classified into dimensions of organization, technology, process, and individual, were examined: patient centricity, regulation, data security, integration, responsiveness, effectiveness, efficiency, personal beliefs, and social influence.Methods
Quantitative data processing methods were used, including the online distribution of questionnaires to a total of 283 valid respondents who had previously used health referrals. Data processing was performed according to the ordinal logistic regression method using IBM SPSS Statistics 24.0 software.Results
The user acceptance model fit with a significance of 0.084, while only regulation, data security, integration, responsiveness, effectiveness, efficiency, personal beliefs, and social influence significantly influenced the patients' acceptance of health referrals.Conclusions
This study may build awareness in the community regarding the health referral system along with the ideal factors that encourage patients to utilize health referrals. In addition, the provision of health services by health facilities and regulators may take these factors into account so they may provide fair and equitable services for all the people of Indonesia; for example, providers and regulators can improve the utilization of information technology and guidebooks on the health referral system to facilitate communication and standardization among health facilities.
SUBMITTER: Handayani PW
PROVIDER: S-EPMC6304450 | biostudies-literature | 2018 Dec
REPOSITORIES: biostudies-literature
Heliyon 20181219 12
<h4>Objectives</h4>This study aims to identify a user acceptance model for the health referral system in Indonesia. The following factors classified into dimensions of organization, technology, process, and individual, were examined: patient centricity, regulation, data security, integration, responsiveness, effectiveness, efficiency, personal beliefs, and social influence.<h4>Methods</h4>Quantitative data processing methods were used, including the online distribution of questionnaires to a tot ...[more]