JMIR Publications

ABSTRACT

Background:

With the widespread use of mobile technologies, mobile information systems (ISs) have become crucial tools in health care operations. Although the appropriate use of m-health may result in major advances in expanding health care coverage, increasing decision-making speeds, managing chronic conditions, and providing suitable health care in emergencies, prior studies argued that current m-health research does not adequately evaluate m-health interventions, and it does not provide sufficient evidence regarding the effects on health.

Objective:

To facilitate the widespread use of mobile health (m-health) systems, an accurate evaluation of the systems from the users’ perspective is essential after the implementation and use of the system in daily health care practices. This study extends the expectation–confirmation model by using characteristics of individuals, technology, and task to identify critical factors affecting m-health continuance and performance from the perspective of health care professionals (HCPs).

Methods:

A questionnaire survey was used to collect data from HCPs who were experienced in using m-health systems of a Taiwanese teaching hospital. In total, 282 questionnaires were distributed, and 201 complete and valid questionnaires were returned, thus indicating a valid response rate of 71.3%. The collected data were analyzed using the WarpPLS 5.0 software.

Results:

The results revealed that m-health continuance (R2 =.522) was mainly affected by perceived usefulness, technology maturity, individual habits, task mobility, and user satisfaction, whereas individual performance (R2 =.492) was affected by m-health continuance. In addition, user satisfaction (R2 =.548) was affected by confirmation and perceived usefulness of m-health, whereas perceived usefulness (R2 =.521) was affected by confirmation. This implied that confirmation played a key role in affecting perceived usefulness and user satisfaction; furthermore, the results showed that m-health continuance positively affected individual performance.

Conclusions:

The identified critical factors influencing m-health continuance and performance can be used as a useful assessment tool by hospitals that have implemented m-health systems to facilitate the use and infusion of the systems. Furthermore, the results can help health care institutions that intend to introduce or develop m-health applications in identifying critical issues and effectively allocating limited resources to m-health systems.