Electronic medical record systems: decision support examination framework for individual, security and privacy concerns using multi-perspective analysis

Electronic medical record (EMR) is currently a popular topic in e-health. EMR includes the health-related information of patients and forms the main factor of e-health applications. Moreover, EMR contains the legal records that are created in the medical centre and ambulatory environments. These records serve as the data source for electronic health record. Although hospitals utilise the EMR system, healthcare professionals experience difficultly in trusting this system. Studies devoted to EMR acceptance in hospitals are lacking, particularly those on the EMR system in the contexts of privacy and security concerns based on multi-criteria perspective. Thus, the current study proposes a decision support examination framework on how individual, security and privacy determinants influence the acceptance and use of EMR. The proposed framework is based on a multi-criteria perspective derived from healthcare professionals in Malaysia as frame of reference. The framework comprises four phases. The sub-factors of individual, security and privacy determinants were investigated in the two initial phases. Thereafter, the sub-factors were identified with uniform multi-criteria perspective to establish a decision matrix. The decision matrix used individual uniform as basis to cluster the sub-factors and user perspectives. Subsequently, a new 'multi-criteria decision-making (MCDM) approach' was adopted. Integrated technique for order of preference by similarity (TOPSIS) and analytic hierarchy process (AHP) were used as bases in employing the MCDM approach to rank each group of factors. K-means clustering was also applied to identify the critical factors in each group. Healthcare professionals in Malaysia were selected as respondents and 100 questionnaires were distributed to those employed in 5 Malaysian public hospitals. A conceptual model adapted from Unified theory of acceptance and use of technology 2 (UTAUT2) was employed to clarify the connection between individual, privacy and security determinants and EMR system acceptance and use in the selected context. After collecting the data sets (363), structural equation modelling was used to analyse data related to EMR acceptance and use. Results are as follows. (1) Five determinants (i.e. data integrity, confidentiality, non-repudiation, facilitating conditions and effort expectancy) exerted an explicit and important positive effect on EMR acceptance and use. (2) Three determinants (i.e. unauthorised, error and secondary use) exerted a direct and significant negative effect on EMR acceptance and use. (3) Three other determinants (i.e. authentication, performance expectancy and habit) insignificantly affected the behavioural intention of healthcare experts in Malaysia to use EMR.