Healthc Inform Res.  2019 Oct;25(4):313-323. 10.4258/hir.2019.25.4.313.

Follow-Up Decision Support Tool for Public Healthcare: A Design Research Perspective

• Miah SJ
• Hasan N
• Gammack J

• KMID: 2462230
• DOI: http://doi.org/10.4258/hir.2019.25.4.313

Abstract

OBJECTIVES
Mobile health (m-Health) technologies may provide an appropriate follow-up support service for patient groups with post-treatment conditions. While previous studies have introduced m-Health methods for patient care, a smart system that may provide follow-up communication and decision support remains limited to the management of a few specific types of diseases. This paper introduces an m-Health solution in the current climate of increased demand for electronic information exchange.
METHODS
Adopting a novel design science research approach, we developed an innovative solution model for post-treatment follow-up decision support interaction for use by patients and physicians and then evaluated it by using convergent interviewing and focus group methods.
RESULTS
The cloud-based solution was positively evaluated as supporting physicians and service providers in providing post-treatment follow-up services. Our framework provides a model as an artifact for extending care service systems to inform better follow-up interaction and decision-making.
CONCLUSIONS
The study confirmed the perceived value and utility of the proposed Clinical Decision Support artifact indicating that it is promising and has potential to contribute and facilitate appropriate interactions and support for healthcare professionals for future follow-up operationalization. While the prototype was developed and tested in a developing country context, where the availability of doctors is limited for public healthcare, it was anticipated that the prototype would be user-friendly, easy to use, and suitable for post-treatment follow-up through mobility in remote locations.

Keyword

Clinical Decision Support; M-Health; Healthcare Information Technology; Follow-Up Care

MeSH Terms

Artifacts
Climate
Decision Support Systems, Clinical
Delivery of Health Care*
Developing Countries
Focus Groups
Follow-Up Studies*
Humans
Patient Care
Telemedicine

Figure

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  Figure 1 Design science research setting. CDS: Clinical Decision Support.

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  Figure 2 Follow-up CDS framework (front end and back end) using a mobile app. CDS: Clinical Decision Support, API: application programming interface.

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  Figure 3 Some specific screenshots of the proposed solution: (A) login naviagation, (B) home page with heath tracking navigation, (C) selection of speciating or specific area, and (D) requirement submission.

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