A resident-centered approach to nursing staff planning in long-term care using the Synergy tool
The Synergy tool was used to forecast long-term care (LTC) resident needs for nurse staffing planning. Forecasting techniques were applied to longitudinal resident needs data from 67 unique residents across four units in two LTC homes in British Columbia. Acuity and dependency needs scores were forecasted for a four-week period using an Error Trend Seasonality (ETS) model. The four units demonstrated changing or stable resident acuity and dependency needs during the forecasting period. Increasing, decreasing, or stable resident acuity needs during the forecasted period would suggest the unit would benefit from higher, lower, and similar regulated nurse staffing level than the previous period respectively. Increasing, decreasing, or stable resident dependency needs during the forecasted period would suggest the unit would benefit from higher, lower, and similar PSW staffing level than the previous period respectively. This integrated technique sheds light on proactively planning staffing needs based on considerations of resident needs.
Authors
- Minjeong Park (ORCID: https://orcid.org/0000-0002-2204-2901)
- Sheila A. Boamah (ORCID: https://orcid.org/0000-0001-6459-4416)
- Farinaz Havaei (ORCID: https://orcid.org/0000-0002-7769-7796)
- Maura MacPhee (ORCID: https://orcid.org/0000-0002-3603-8735)
- David Keselman (ORCID: https://orcid.org/0000-0003-0555-067X)
- Andy Ma (ORCID: https://orcid.org/0000-0001-9231-459X)
- Janice Sorensen (ORCID: https://orcid.org/0000-0002-6219-6630)
Institutions
- University of British Columbia Hospital (CA)
- University of British Columbia (CA)
- Fraser Health (CA)
- University Canada West (CA)
- McMaster University (CA)
Publication Details
- Journal
- Geriatric Nursing
- Published
- 2025-07-01
- DOI
- https://doi.org/10.1016/j.gerinurse.2025.103409
- Primary Topic
- Geriatric Care and Nursing Homes
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Canadian Institutes of Health Research