Data-Driven Decision-making in Healthcare (7.3 3DHC)

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Data-Driven Decision-making in Healthcare (7.3 3DHC)

Phase:	Workpackage
Theme:	Health Systems, Practice, Policy and Regulatory Issues (WP7 POLICY-TECH)
Type:	Research
Status:	Active
Start Date:	2015-04-01
End Date:	2015-04-01
Project Leaders
Hirdes, John Lee, Joon

Affiliated Researchers

Alumni HQP

Kuspinar, Ayse

Project Overview

The objective of this project is to develop and prove the feasibility of home health monitoring and data-driven decision support systems based on various data sources. The outcomes of this work include: 1) a knowledge base of mHealth, machine learning, and artificial intelligence for healthy aging; 2) frailty prediction algorithms based on wearable data; and 3) interRAI Community Health Assessment decision support algorithms.

Award Term: April 1, 2015 - March 31, 2020

AGE-WELL NCE Investment: $ 469,091

Total Non-NCE Contribution: $ 123,534

Outputs

Title	Category	Date	Authors
Chasing feet in the wild: A proposed egocentric motion-aware gait assessment tool University of Waterloo	Scientific Excellence - Advancing Knowledge	2018-08-28	Mina Nouredanesh, Aaron Li, "Alan Godfrey", Jesse Hoey, James Tung
Ethics application:Tailoring the interRAI suite to identify and meet the needs and preferences of adults with disabilities	Scientific Excellence - Leadership	2019-11-07	Micaela Jantzi, John Hirdes
A higher proportion of home care recipients experience nonhip fractures than long-term care residents	Scientific Excellence - Advancing Knowledge	2020-02-12	Caitlin McArthur, Ioannidis G, Micaela Jantzi, Hiller L, Adachi JD, Lora Giangregorio, John Hirdes, Alexandra Papaioannou
The role of physicians in the era of big data. University of Waterloo	Scientific Excellence - Advancing Knowledge	2020-01-06	George Heckman, John Hirdes, McKelvie RS
Co-Creating Possibilities: Physical Fitness to Avoid Frailty	HQP Training	2017-07-04	Taciana Pontual, Maggie MacNeil, Kristina Chang, Carole Goodine, Arjun Puri, G M Mashrur E Elahi

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