Modelling the Multiple Sclerosis Specialist Nurse Workforce by determination of optimum caseloads in the United Kingdom

Journal article


Punshon, G., Sopala, J., Hannan, G., Roberts, M., Vernon, K., Pearce, A. and Leary, A. (2019). Modelling the Multiple Sclerosis Specialist Nurse Workforce by determination of optimum caseloads in the United Kingdom. International Journal of MS Care.
AuthorsPunshon, G., Sopala, J., Hannan, G., Roberts, M., Vernon, K., Pearce, A. and Leary, A.
Abstract

Background
It is estimated that there are over 100,000 people in the UK who have Multiple Sclerosis. Access to a specialist nurse service improves patient experience and outcomes. The aim of this study was to publish a new, robust validated standard optimising the UK nursing workforce model.
Methods
Existing national data and specific workload and service data were collected from 163 multiple sclerosis specialist nurses who completed a questionnaire to collect information on activity and complexity of work both done and left undone.
Results
Data was received from all of the UK. Twenty-nine percent of respondents were specialist nurses in the field for three years or less. Unpaid overtime was regularly carried out by 83.4% of respondents. The multiple sclerosis specialist nurse was involved in all areas of the patient journey. Areas of work left undone were psychological interventions, physical assessment, social interventions/ benefits and recommending or prescribing medication.
Conclusions
The current recommended caseload of 358 per whole time equivalent appears 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.
Title: Modelling the Multiple Sclerosis Specialist Nurse Workforce by determination of optimum caseloads in the United Kingdom

Year2019
JournalInternational Journal of MS Care
PublisherThe Consortium of Multiple Sclerosis Centers
ISSN1537-2073
Publication process dates
Accepted11 Dec 2019
Deposited13 Dec 2019
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https://openresearch.lsbu.ac.uk/item/88qx1

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