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Co-designing a dashboard of predictive analytics and decision support to drive care quality and client outcomes in aged care : A mixed-method study protocol

Authors :
Ludlow, Kristiana
Westbrook, Johanna
Jorgensen, Mikaela
Lind, Kimberly E.
Baysari, Melissa T.
Gray, Leonard C.
Day, Richard O.
Ratcliffe, Julie
Lord, Stephen R.
Georgiou, Andrew
Braithwaite, Jeffrey
Raban, Magdalena Z.
Close, Jacqueline
Beattie, Elizabeth
Zheng, Wu Yi
Debono, Deborah
Nguyen, Amy
Siette, Joyce
Seaman, Karla
Miao, Melissa
Root, Jo
Roffe, David
O'Toole, Libby
Carrasco, Marcela
Thompson, Alex
Shaikh, Javed
Wong, Jeffrey
Stanton, Cynthia
Haddock, Rebecca
Ludlow, Kristiana
Westbrook, Johanna
Jorgensen, Mikaela
Lind, Kimberly E.
Baysari, Melissa T.
Gray, Leonard C.
Day, Richard O.
Ratcliffe, Julie
Lord, Stephen R.
Georgiou, Andrew
Braithwaite, Jeffrey
Raban, Magdalena Z.
Close, Jacqueline
Beattie, Elizabeth
Zheng, Wu Yi
Debono, Deborah
Nguyen, Amy
Siette, Joyce
Seaman, Karla
Miao, Melissa
Root, Jo
Roffe, David
O'Toole, Libby
Carrasco, Marcela
Thompson, Alex
Shaikh, Javed
Wong, Jeffrey
Stanton, Cynthia
Haddock, Rebecca
Source :
BMJ Open
Publication Year :
2021

Abstract

Introduction: There is a clear need for improved care quality and quality monitoring in aged care. Aged care providers collect an abundance of data, yet rarely are these data integrated and transformed in real-time into actionable information to support evidence-based care, nor are they shared with older people and informal caregivers. This protocol describes the co-design and testing of a dashboard in residential aged care facilities (nursing or care homes) and community-based aged care settings (formal care provided at home or in the community). The dashboard will comprise integrated data to provide an € at-a-glance' overview of aged care clients, indicators to identify clients at risk of fall-related hospitalisations and poor quality of life, and evidence-based decision support to minimise these risks. Longer term plans for dashboard implementation and evaluation are also outlined. Methods: This mixed-method study will involve (1) co-designing dashboard features with aged care staff, clients, informal caregivers and general practitioners (GPs), (2) integrating aged care data silos and developing risk models, and (3) testing dashboard prototypes with users. The dashboard features will be informed by direct observations of routine work, interviews, focus groups and co-design groups with users, and a community forum. Multivariable discrete time survival models will be used to develop risk indicators, using predictors from linked historical aged care and hospital data. Dashboard prototype testing will comprise interviews, focus groups and walk-through scenarios using a think-aloud approach with staff members, clients and informal caregivers, and a GP workshop. Ethics and dissemination: This study has received ethical approval from the New South Wales (NSW) Population & Health Services Research Ethics Committee and Macquarie University's Human Research Ethics Committee. The research findings will be presented to the aged care provider wh

Details

Database :
OAIster
Journal :
BMJ Open
Notes :
application/pdf
Publication Type :
Electronic Resource
Accession number :
edsoai.on1343979872
Document Type :
Electronic Resource