Modelling recovery after common hand surgery procedures

Overview

This musculoskeletal data science DPhil will explore Ecological Momentary Computerised Adaptive Testing (EMCAT) as a transformative approach to modelling patient recovery after hand surgery. The successful candidate will use data from the EMCAT-2 study—a multicentre longitudinal cohort study capturing high-frequency patient-reported outcome (PRO) data—to investigate how cutting-edge psychometrics, time-series modelling, and digital health tools could improve the way we measure, monitor and compare recovery after hand surgery, and how this might impact trials, clinical care pathways and health system efficiency in future.

The work would take place within the Furniss Group at NDORMS. Please see the Furniss Group webpage for up-to-date details on its membership: https://www.ndorms.ox.ac.uk/research/research-groups/Genetics-and-epidemiology-of-common-hand-conditions

Research Aims

The project will focus on developing innovative analytical and methodological approaches to answer questions such as:

1. What are the best statistical techniques to model surgical recovery from high-frequency, longitudinal, patient-reported outcome data? 
2. How well can these models differentiate between patients who have recovered uneventfully, vs those who have experienced complications? 
3. To what extent can recovery trajectories be forecasted? Can longitudinal PRO data predict future complicated recovery? 
4. How should we compare the cost-effectiveness of surgeries that produce different recovery trajectories?

This DPhil will suit a highly motivated student with interests in health data science, psychometrics, digital health, or biostatistics. Experience in statistical programming (R, Python, or similar) is desirable, alongside enthusiasm for interdisciplinary collaboration between clinicians, statisticians, and health economists.

Prospective candidates should see the following papers/protocols:

https://www.jmir.org/2023/1/e47179/ 

https://www.isrctn.com/ISRCTN47966791

Training

The Botnar Institute plays host to the University of Oxford's Institute of Musculoskeletal Sciences, which enables and encourages research and education into the causes of musculoskeletal disease and their treatment. Training will be provided in techniques including R programming, longitudinal data analysis (including through machine learning techniques) and advanced psychometric modelling.

A core curriculum of lectures will be taken in the first term to provide a solid foundation in a broad range of subjects including musculoskeletal biology, inflammation, epigenetics, translational immunology, data analysis and the microbiome.  Students will also be required to attend regular seminars within the Department and those relevant in the wider University.

Students will be expected to present data regularly in Departmental seminars, the Furniss Group and to attend external conferences to present their research globally, with limited financial support from the Department.

Students will also have the opportunity to work closely with the Furniss Group and the Health Outcomes group at Charité Universitätsmedizin, Berlin.

Students will have access to various courses run by the Medical Sciences Division Skills Training Team and other Departments. All students are required to attend a 2-day Statistical and Experimental Design course at NDORMS (information will be provided once accepted to the programme).

How to Apply

Please contact the relevant supervisor(s), to register your interest in the project, and, if required, the departmental Education Team (graduate.studies@ndorms.ox.ac.uk), who will be able to advise you of the essential requirements for the programme and provide further information on how to make an official application.

Interested applicants should have, or expect to obtain, a first or upper second-class BSc degree or equivalent in a relevant subject and will also need to provide evidence of English language competence (where applicable). The application guide and form is found online and the DPhil will commence in October 2026.

Applications should be made to one of the following programmes using the specified course code.

D.Phil in Musculoskeletal Sciences (course code: RD_ML2)

D.Phil in Clinical Epidemiology and Medical Statistics (course code: RD_NNRA1)

For further information, please visit http://www.ox.ac.uk/admissions/graduate/applying-to-oxford. 

References

Harrison C et al. Remote Symptom Monitoring with Ecological Momentary Computerized Adaptive Testing: Pilot Cohort Study of a Platform for Frequent, Low-Burden, and Personalized Patient-Reported Outcome Measures. J Med Internet Res 2023;25:e47179 doi: 10.2196/47179

Harrison C et al. Using a computerised test to monitor and compare recovery after hand surgery. ISRCTN47966791 doi: https://doi.org/10.1186/ISRCTN47966791