Exploring user experiences of the National Institute of Health and Care Excellences Shared Decision Making learning package: an online qualitative study

Objective
To evaluate the user experience of the joint National Institute of Health and Care Excellence (NICE)/Keele University Shared Decision Making (SDM) learning package.

Design
A qualitative study using online semistructured interviews. Data were analysed using open coding followed by the construction of themes.

Setting
Participants were recruited and interviewed online via Microsoft Teams.

Participants
Healthcare professionals who had used the NICE SDM learning package and provided contact details between June 2021 and April 2022 were eligible to be contacted.

Intervention
The online learning package developed to support the implementation of the NICE SDM guideline.

Findings
12 participants from a variety of different professional backgrounds were interviewed and reported that the learning package was easy to use and the different formats for presenting the information were engaging. The package was available in discrete sections—‘bitesize’ chunks—which allowed the participants to fit their learning around their busy schedules. The package included virtual patients (VPs) which allowed users to practice their SDM skills and put the learning into practice. The VPs also stimulated reflection on current performance and a shift in approach to SDM in practice. Suggestions were made by participants to improve the usability and accessibility of the learning package.

Conclusion
The NICE SDM learning package was viewed favourably by the participants. The bitesize structure and interactivity were key positive elements. Many participants suggested that they had made changes to their practice as a result of using the package.

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Understanding symptom clusters, diagnosis and healthcare experiences in myalgic encephalomyelitis/chronic fatigue syndrome and long COVID: a cross-sectional survey in the UK

Objectives
This study aims to provide an in-depth analysis of the symptoms, coexisting conditions and service utilisation among people with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and long COVID. The major research questions include the clustering of symptoms, the relationship between key factors and diagnosis time, and the perceived impact of National Institute for Health and Care Excellence (NICE) guidelines on patient care.

Design
Cross-sectional survey using secondary data analysis.

Setting
Community-based primary care level across the UK, incorporating online survey participation.

Participants
A total of 10 458 individuals responded to the survey, of which 8804 confirmed that they or a close friend/family member had ME/CFS or long COVID. The majority of respondents were female (83.4%), with participants from diverse regions of the UK.

Primary and secondary outcome measures
Primary outcomes included prevalence and clustering of symptoms, time to diagnosis, and participant satisfaction with National Health Service (NHS) care, while secondary outcomes focused on symptom management strategies and the perceived effect of NICE guidelines.

Results
Fatigue (88.2%), postexertional malaise (78.2%), cognitive dysfunction (88.4%), pain (87.6%) and sleep disturbances (88.2%) were the most commonly reported symptoms among participants with ME/CFS, with similar patterns observed in long COVID. Time to diagnosis for ME/CFS ranged widely, with 22.1% diagnosed within 1–2 years of symptom onset and 12.9% taking more than 10 years. Despite updated NICE guidelines, only 10.1% of participants reported a positive impact on care, and satisfaction with NHS services remained low (6.9% for ME/CFS and 14.4% for long COVID).

Conclusions
ME/CFS and long COVID share overlapping but distinct symptom clusters, indicating common challenges in management. The findings highlight significant delays in diagnosis and low satisfaction with specialist services, suggesting a need for improved self-management resources and better-coordinated care across the NHS.

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Evidence quality and uncertainties considered in appraisal documents of drugs for rare diseases in England and Germany: a data extraction protocol

Introduction
Rare disease treatments (RDTs) promise considerable patient benefit but the evidence to demonstrate their value in health technology assessment (HTA) is often limited. HTA outcomes for RDTs vary across countries and there are differences in how uncertainty is dealt with by HTA agencies. Yet, there is limited comparative research assessing how different HTA agencies consider issues affecting evidence quality and uncertainty in RDT appraisals. This protocol describes a systematic and consistent approach for data extraction from RDT appraisal documents produced to inform decisions by HTA agencies. By documenting data extraction rules transparently, we ensure reproducibility and reliability of analyses of the extracted data.

Methods and analysis
We will select RDT appraisals issued by the National Institute for Health and Care Excellence (NICE) in England and the Federal Joint Committee (GBA) in Germany, using predefined inclusion criteria. We will extract data from appraisal documents in accordance with the rules set out in this protocol. We will analyse the extracted data to investigate how issues affecting evidence quality and uncertainty as documented in appraisals are considered, highlighting the similarities and differences between countries and identifying factors that are associated with HTA outcomes.

Ethics and dissemination
This study was approved by the Ethics Committee of the London School of Hygiene & Tropical Medicine (reference number 29156). Study results will be submitted for publication in peer-reviewed journals.

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