Modeling the Multiple Sclerosis Specialist Nurse Workforce by Determination of Optimum Caseloads in the United Kingdom
- PMID: 33658899
- PMCID: PMC7906027
- DOI: 10.7224/1537-2073.2019-058
Modeling the Multiple Sclerosis Specialist Nurse Workforce by Determination of Optimum Caseloads in the United Kingdom
Abstract
Background: It is estimated that there are more than 100,000 people in the United Kingdom who have multiple sclerosis (MS). Patient experience and outcome are improved by access to a specialist nursing service. The aim of this study was to perform demand modeling to understand the need for MS nursing interventions, and thus inform modeling of the future UK MS nursing workforce.
Methods: Existing national data and specific workload and service data were collected from 163 MS specialist nurses who completed a questionnaire on activity and complexity of work both done and left undone.
Results: Data were received from across all of the United Kingdom. Twenty-nine percent of respondents were specialist nurses in the field for 3 years or less. Unpaid overtime was regularly performed by 83.4% of respondents. The MS specialist nurse was part of all areas of the patient journey. Areas of work left undone were psychological interventions, physical assessments, social interventions/benefits, and recommending or prescribing medications.
Conclusions: The current recommended caseload of 358 people with MS per full-time equivalent seems to be too high, with a considerable amount of work left undone, particularly psychosocial care. Factors such as travel time, complexity of caseload, changing drug therapies, and societal issues such as the benefits system contributed to driving demand/workload.
Keywords: Caseload; Modeling; Multiple sclerosis (MS); Workforce.
© 2021 Consortium of Multiple Sclerosis Centers.
Conflict of interest statement
Financial Disclosures: Drs Hannan and Roberts are employed by the Multiple Sclerosis Trust. The other authors declare no conflicts of interest.
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References
-
- Hall LE. Nursing: what is it? Can Nurse. 1964;60:150–154. - PubMed
-
- Pitkaaho T, Partanen P, Miettinen M, Vehvilainen-Julkunen K. Nonlinear relationships between nurse staffing and patients’ length of stay in acute care units: Bayesian dependence modelling. J Adv Nurs. 2015;71:458–473. - PubMed
-
- Ebright PR, Patterson ES, Chalko BA, Render ML. Understanding the complexity of registered nurse work in acute care settings. J Nurs Adm. 2003;33:630–638. - PubMed
-
- Raiborn CA. Managerial Accounting. Nelson Thomson Learning; 2004.
-
- Prevalence and incidence of multiple sclerosis. Multiple Sclerosis Trust website. Accessed April 2018. https://www.mstrust.org.uk/a-z/prevalence-and-incidence-multiple-sclerosis.
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