Résumé
Context: Many countries have aging populations. Thus, the need for palliative care will increase. However, the methods to estimate optimal staffing for specialist palliative care teams are rudimentary as yet. Objectives: To develop a population-need workforce planning model for community-based palliative care specialist teams and to apply the model to forecast the staff needed to care for all patients with terminal illness, organ failure, and frailty during the next 20 years, with and without the expansion of primary palliative care. Methods: We used operations research (linear programming) to model the problem. We used the framework of the Canadian Society of Palliative Care Physicians and the Nova Scotia palliative care strategy to apply the model. Results: To meet the palliative care needs for persons dying across Nova Scotia in 2019, the model generated an estimate of 70.8 nurses, 23.6 physicians, and 11.9 social workers, a total of 106.3 staff. Thereby, the model indicated that a 64% increase in specialist palliative care staff was needed immediately, and a further 13.1% increase would be needed during the next 20 years. Trained primary palliative care providers currently meet 3.7% of need, and with their expansion are expected to meet 20.3% by 2038. Conclusion: Historical, current, and projected data can be used with operations research to forecast staffing levels for specialist palliative care teams under various scenarios. The forecast can be updated as new data emerge, applied to other populations, and used to test alternative delivery models.
| Langue d'origine | English |
|---|---|
| Pages (de-à) | 1012-1022.e4 |
| Journal | Journal of Pain and Symptom Management |
| Volume | 61 |
| Numéro de publication | 5 |
| DOI | |
| Statut de publication | Published - mai 2021 |
Note bibliographique
Funding Information:Funding: This work was supported by the Nova Scotia Health Research Foundation Development and Innovation grant. The Nova Scotia Health Research Foundation has no role in study design; in the collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the article for publication.
Funding Information:
The authors thank NSH staff for their in-kind support by providing data. The analysis of census data and vital statistics death data was conducted at the Statistics Canada's Atlantic Research Data Centre at Dalhousie University, which is part of the Canadian Research Data Centre Network. The authors thank the Canadian Research Data Centre Network for facilitating the access to the data and the Atlantic Research Data Centre analyst Heather Hobson for her support and assistance. Our research assistants, Min Hu (PhD in Economics at Dalhousie University) developed the computer code to read the Vital Statistics Death database, Enayat Rajabi (Postdoctoral fellow in Computer Science at Dalhousie University) developed the computer code for the model solution, and Erin Raine (MHA student) developed the population projections for the networks in NS. Ron Dewar and Devbani Raha, Cancer Care Program, NSH, helped with CANPROJ software. Ruth Lavergne independently reviewed the article and provided insights before its submission. Funding: This work was supported by the Nova Scotia Health Research Foundation Development and Innovation grant. The Nova Scotia Health Research Foundation has no role in study design; in the collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the article for publication. The authors declare that there is no conflict of interest with respect to the research, authorship, and publication of this article. Ethical approval: Because the Canadian Research Data Centres64 follow the strict ethics and disclosure protocols of the Statistics Act, the Canadian Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans (TCPS2) article 2.2 (a)65 exempts the centre's approved projects from further research ethics board review. The nurse survey was exempt from ethics approval because it was an NSH quality improvement study.49 Other data were not person specific, and thus, their release was exempt from the need for ethics review.
Publisher Copyright:
© 2020
ASJC Scopus Subject Areas
- General Nursing
- Clinical Neurology
- Anesthesiology and Pain Medicine
PubMed: MeSH publication types
- Journal Article
- Research Support, Non-U.S. Gov't