ArticleHealthcare informatics research2019
Follow-Up Decision Support Tool for Public Healthcare: A Design Research Perspective.
Article in Healthcare informatics research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- Integrated Personal Health Record in Indonesia: Design Science Research Study.JMIR medical informatics · 2023Article
- Article
- Dynamic Demand-Centered Process-Oriented Data Model for Inventory Management of Hemovigilance Systems.Healthcare informatics research · 2021Article
- Real-Time Monitoring System to Manage Mental Healthcare Emergency Unit.Healthcare informatics research · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesMobile 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.
methodsAdopting 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.
resultsThe 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.
conclusionsThe 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.
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Registered trials
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