Abstract
Population-focused care is gaining importance due to an increase in the number of people with long-term conditions. A population-focused care addresses the care needs of a group of patients who share a common trait. Primary health care (PHC) being the first point of contact with a health system, our work aims to predict and analyse this population-level workload at a PHC centre. We followed a design science research (DSR) to develop a workload prediction model. As a part of this work, we identified that current patient information models lack the ability to support population-level analysis. In this paper, we discuss an extended ontology of patient information models to support population-level workload analysis. We describe the three cycles of DSR applied to develop our ontology. Then, we discuss the existing health data models. Thus, this paper makes a domain-specific application of DSR to develop a patient information model that supports population-level analysis.
Recommended Citation
Dang Pham Thien, Duy and Kautz, Karlheinz, "Exploring the ACIS Community through the Analysis of Co-authorship across Institutions" (2017). ACIS 2017 Proceedings. 14.
https://aisel.aisnet.org/acis2017/14