Abstract
Managing the growing demand for care due to long-term conditions (LTCs) is a big challenge for primary care providers across the globe. We argue that population-level care for LTC patients registered at a primary health centre (PHC) is possible through workload prediction using care plans. In this paper, we try to answer two research questions: i) How can the future demand for care of the patients with LTCs be predicted? and ii) How is the future demand for care affected by changes? We present a rule-based simulation model that, given the patient details, will predict the number of LTC patients who will be visiting the primary health centre for the next year. Knowing this workload would help the medical practice to meet the upcoming demand for care effectively. Our approach also allows simulation of the effects of changes to practice and resourcing to foresee how these changes may impact the practice. Following the design science research approach, our prediction results have been shared with an expert and the feedback guides us to refine our model.
First Page
1192
Last Page
1204
Recommended Citation
Devananda, Manjula; Cranefield, Stephen; Winikoff, Michael; and Lloyd, Hywel, (2017). "WORKLOAD PREDICTION MODEL OF A PRIMARY HEALTH CENTRE". In Proceedings of the 25th European Conference on Information Systems (ECIS), Guimarães, Portugal, June 5-10, 2017 (pp. 1192-1204). ISBN 978-989-20-7655-3 Research Papers.
https://aisel.aisnet.org/ecis2017_rp/77