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Strategic Analytics to Drive Provincial Dialysis Capacity Planning: The Case of Ontario Renal Network

Strategic Analytics to Drive Provincial Dialysis Capacity Planning: The Case of Ontario Renal Network
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Author(s): Neal Kaw (University of Toronto, Canada), Somayeh Sadat (Tarbiat Modares University, Iran), Ali Vahit Esensoy (Cancer Care Ontario, Canada), Zhihui (Amy) Liu (Cancer Care Ontario, Canada), Sarah Jane Bastedo (Ontario Renal Network, Canada)and Gihad Nesrallah (St. Michael's Hospital, Canada)
Copyright: 2017
Pages: 27
Source title: Handbook of Research on Data Science for Effective Healthcare Practice and Administration
Source Author(s)/Editor(s): Elham Akhond Zadeh Noughabi (University of Calgary, Canada), Bijan Raahemi (University of Ottawa, Canada), Amir Albadvi (Tarbiat Modares University, Iran)and Behrouz H. Far (University of Calgary, Canada)
DOI: 10.4018/978-1-5225-2515-8.ch008

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Abstract

This chapter discusses applications of analytics at the strategic level of health system planning in the province of Ontario, Canada. To supplement the strategic priorities of the Ontario Renal Plan I, a roadmap developed by the Ontario Renal Network to guide its directions in coordinating renal care province-wide, an interactive user-friendly analytical capacity planning model was developed to forecast the growth of the prevalent chronic dialysis patient population and estimate consequent future need for hemodialysis stations at Ontario's dialysis facilities. The model also projects operational funding to care for dialysis patients, vascular surgeries to achieve arteriovenous fistula targets, peritoneal dialysis catheter insertions to achieve peritoneal dialysis prevalence targets, and incident dialysis patients to be sent home to achieve prevalent home dialysis targets. The model uses a variety of analytical methods, including time series analysis, mathematical optimization, geo-spatial analysis and Monte Carlo simulation.

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