ArticleBMJ open2020
Exploring and understanding the scope and value of the Parkinson's nurse in the UK (The USP Project): a realist economic evaluation protocol.
Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Towards realist-informed ripple effects mapping (RREM): positioning the approach.BMC medical research methodology · 2024Article
- Parkinson's Nurses Are Crucial for the Management of Parkinson's Disease: 2007-2024.Journal of Parkinson's disease · 2024Review
- A Narrative Review of Specialist Parkinson's Nurses: Evolution, Evidence and Expectation.Geriatrics (Basel, Switzerland) · 2022Review
- Covid-19 and Parkinson's disease: Nursing care, vaccination and impact on advanced therapies.International review of neurobiology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThere are multiple configurations of specialist nurses working in the field of Parkinson's. Parkinson's Nurse Specialists (PNSs) are recognised as playing a pivotal role; however, there is little published evidence to demonstrate their effectiveness. Further evidence is needed to establish which aspects of the PNSs provide the greatest benefit to people with Parkinson's and their families, and the cost-effectiveness of different models of care. METHODS AND ANALYSIS: Realist approaches explain how and why programmes work (or not) through striving to answer the question: what works, for whom and under what circumstances. This research uses a realist evaluation and aims to integrate an economic analysis within the realist framework. We refer to this as 'realist economic evaluation'. It comprises four phases: (1) developing resource-sensitive initial programme theories (IPTs) using surveys to gain a better understanding of the role and impact (costs and benefits) of the PNSs; (2) testing the IPTs through qualitative interviews and quantitative data analysis; (3) evaluating the cost and resource use implications alongside the benefits associated with the role of the PNSs and (4) iteratively refining the IPTs throughout the project. The IPTs will draw on both quantitative and qualitative data. The result of the study will be a series of refined programme theories, which will explain how specialist nurses work in the field of Parkinson's in the UK, what impact they have on people with Parkinson's and their families and carers, and at what cost. ETHICS AND DISSEMINATION: Northumbria University, the Health Research Authority and Health and Care Research Wales have approved this study. Key findings will be disseminated throughout the duration of the project online and through social media, and via annual and regional Parkinson's meetings and the Parkinson's UK Excellence Network. Academic dissemination will occur through publication and conference presentations.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.