Active Psychology & Behaviour NIHR-supported project Mental Health

Thrive-ms and consentor

In plain English

AI plain-English summary

The UK Multiple Sclerosis Register and the international MSBase registry each contain fewer than 1,000 UK patients out of 135,000 people with MS in the country, because entering data requires duplicating work already done in the electronic health record. This matters because the missing data hides real-world treatment outcomes, slows trial recruitment, and leaves underserved communities even less visible in research. Clinicians are also burning out from repetitive data entry, while promised efficiency gains from electronic health records have not materialised. The project tests two linked tools. THRIVE-MS uses an Epic Smartform to automatically pull disease-specific information from the existing health record, eliminating duplicate data entry. CONSENTOR combines a one-off consent form with a notification system that alerts clinicians when a patient becomes eligible for a trial or observational study. If successful, the tools could increase registry participation from under 1,000 to tens of thousands of UK patients, speed trial recruitment, reduce physician burnout, and be replicated in other hospitals, other electronic health record systems, and other diseases. The research is implementation-focused, not fundamental science—it aims to fix a broken data pipeline, not discover new biology.

View original technical description
The rapid improvement in our understanding of the pathogenesis of neuroimmunological conditions in the last decade has translated into a significant increase in the number of licensed treatments and clinical trials for neuroimmunological conditions. More patients now fulfil eligibility criteria for treatments and trials, greatly increasing the workload for healthcare professionals. The promised improvements in patient safety and administrative efficiency from enterprise-level electronic healthcare records have not materialised. A growing rate of physician burnout can be seen, largely associated with repetitive work being carried out. Invaluable real-world patient data are currently not entered into disease registries, primarily due to the additional time needed for duplicate date entry (into the healthcare record and the registry data collection portals) and to consent patients to each registry. Consequently, both the UKmultiple sclerosis (MS) Register and the international registry MSBase contain less than 1,000 UK patients (out of 135,000 UK people with MS). The under-served groups have an even poorer representation in these registries. Finally, there is very low patient awareness of trials, slow trial recruitment, and particularly low trial participation within underserved communities. We hypothesise that each problem will be improved through two projects: THRIVE-MS (Transforming Health Records for automated Real-world data generation, Improved care, Value and Efficiency) and CONSENTOR (Combined One-off Neuroimmunological conditions Study and trial Eligibility Notification Tool and Observational Research consent form). For THRIVE-MS, an Epic Smartform will be used to collect and manipulate disease-specific information. In addition to measuring these changes, this study will be used to: (1) justify the wider dissemination of THRIVE-MS/CONSENTOR in other hospitals around the country? (2) justify the replication of the THRIVE-MS/CONSENTOR in other commonly used enterprise-level electronic health records? (3) justify the replication of THRIVE-MS/CONSENTOR in other diseases.

Researchers

William Brown (Principal Investigator)

Related Research

Grants with similar aims, by meaning.

Remote Assessment of Disease and Relapse in Central Nervous System Disorders
A pilot study investigating the use of e-consent and syncing real work data with the UK Primary Sjogren’s Syndrome Registry
Rapidly evolving multiple sclerosis: opening the window of therapeutic opportunity
SUPPORT-HF 2 (Seamless User-centred Proactive Provision Of Risk-stratified Treatment for Heart Failure) - An internal pilot phase of a planned large-scale randomised trial of an integrated, technology-enabled care delivery model
Development of a stratification tool to predict Disease Modifying Treatment response in Paediatric Onset Multiple Sclerosis

Original classification

Neuroscience

Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.