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PhD Studentship in Clinical Informatics

Primary Supervisor: Dr Gwyneth Davies (UKRI Future Leaders Fellow/Clinical Associate Professor and Honorary Consultant Paediatrician)


Secondary Supervisors: Prof Neil Sebire and Prof Mario Cortina Borja

 

Great Ormond Street Hospital has invested in an electronic infrastructure to support clinical care and research. This includes the Epic Systems electronic health record (EHR)  and the Digital Research Environment (DRE). These create opportunities to investigate the added value of incorporating patient reported outcome measures (PROMs) into routine care and clinical research(1,2), and developing data processing pipelines for analytics. This has the potential to improve quality of clinical care and facilitate the adoption of clinical trials using routinely captured data (3). The latter has an increasing focus on PROMs yet at present these are not routinely collected at scale.

Aims:

The aim of this PhD studentship is to investigate the processes involving selection, integration and processing of electronically captured patient reported outcomes into EHR at Great Ormond Street Hospital (GOSH). This includes developing data pipelines, data visualisation and summary statistics for clinicians and patients/families, the feasibility of data collection and curation, and the potential value for standard care and clinical research.

PhD studentship

This clinical informatics PhD studentship will enable an in-depth study of electronically captured PROMs for children and young people within EHRs, focusing on the 'what' and 'how' aspects of data collection for PROMs which are not currently incorporated within routine clinical care. The optimal PROMs for children and young people at GOSH may depend on their underlying diagnosis, but there may also be generic measures of quality of life independent of this (4). How these measures are integrated into EHRs, and the development of data pipelines that would be required to efficiently curate and analyse data either cross-sectionally or longitudinally, require investigation (5,6). To optimise impact, this needs to be undertaken in conjunction with children and young people, their families, and clinical care teams.

The studentship will equip the student with skills in applied clinical informatics research, with exposure to a range of research methodologies which are both quantitative and qualitative in nature. The student will also acquire valuable generic skills, e.g.  training in peer-review and writing academic reports and papers, and experience in attending international conferences and actively participating in professional societies.

The initial focus will be on childhood long term respiratory conditions including cystic fibrosis, asthma, interstitial lung disease, bronchiectasis and those associated with sleep disordered breathing. Children with such diagnoses are routinely followed up in clinical encounters over many years (often lifelong). Although the research will initially focus on specific disease areas within respiratory medicine; the approach and methodology will support scalability across different conditions and settings. 

PhD student registration will be within the Population, Policy and Practice Research and Teaching Department (PPP) at the UCL Great Ormond Street Institute of Child Health (ICH). The student will be supported by a supervisory team with expertise in clinical informatics, statistics and data science, direct clinical experience of the Epic EHR system, care of children with chronic respiratory diseases, and awareness of the governance structures and considerations for the project. The primary supervisor (GD) will ensure that in addition to regular PhD meetings, the student is encouraged to actively participate in relevant activities at ICH and the GOSH DRIVE unit (e.g., the bi-weekly 'DRE Analytics and Machine Learning Review' meetings), gaining feedback from a broader audience. They will also be encouraged to join the PPP early career research group, and ICH mentorship scheme.  In addition, the student will be supported to explore opportunities within clinical informatics for their own academic career post-PhD. PPP also has strong links with the Royal Statistical Society and the student will be encouraged to participate in the Society’s activities, e.g., Young Statisticians’ groups.

Research plan:

The research plan will be developed by the student in conjunction with the supervisory team, but as a guide may follow:

1. Literature review and GOSH survey to inform selection of generic and condition-specific PROMs for linkage with EHR and DRE.

2. With involvement from children and young people to guide patient-facing components, develop solution to capture PROMs according to most appropriate measure(s) in (1) that can integrate with patient-level EHR data in DRE, with potential to select generic and/or disease-specific measures. This would be done using appropriate standards for definition and recording. It will include consideration of governance processes, validated PROM format and licensing, data visualisation and statistical analysis, and potential for scalability.  

3. With involvement from children and young people, design and develop a patient-facing electronic dashboard to track longitudinal change in PROM(s) in addition to their clinical outcomes already available via the existing patient-facing MyGOSH app.

4.Design and undertake a mixed methods study of the feasibility of electronically-captured PROMs data collection in routine care at GOSH (data completeness, acceptability). This will include frequency of data collection vs data completeness, age for completion by parent (proxy) or by child/young person, perceived utility by clinical teams and families.

5. Prospective data collection, visualisation and analytics to demonstrate feasibility of proof of principle (e.g. within 1-2 subspecialty groups over 6 month period).

Timeline:

- PhD registration: (Month 0)

- Literature review and research ethics approvals: (Months 0-3)

- Create, pilot and administer electronic survey for GOSH clinical teams re. existing PROM data collection (whether paper, routine, research only, measures in use): (Months 3-6)

- Develop points 2 and 3 within Research plan (Months 6-18)

-Conduct mixed methods study of feasibility of electronically captured PROMs within patient population at GOSH (involving patients from more than one specialty / diagnostic group), data processing, and integration within DRE (Months 12-24).

- Prospective data collection (Months 18-30).

- Analysis and write up: Throughout, with focus on months 30-36

- Dissemination and impact: Throughout, with focus on months 30-36

Ethics Approval:

The informatics component of the PhD project will be undertaken within the GOSH DRE, and appropriate approvals in line with the DRE governance processes will be sought prior to commencing the relevant components of this project. Deidentified data from routine clinical encounters at GOSH for children with chronic paediatric respiratory diseases will be imported into the DRE, collated, and analysed using its inbuilt software platforms. NHS research ethics and relevant approvals will be sought for prospective data collection with specific tools/additional outcomes according to progress within the PhD.

References:

1. Basch E.  Patient-reported outcomes—harnessing patients’ voices to improve clinical care. N Engl J Med. 2017;376(2):105-108.

2. Browne JP, Cano SJ, Smith S. Using patient-reported outcome measures to improve health care: time for a new approach. Med Care. 2017;55(10):901–4.

3. Bingham CO, Noonan VK, Auger C, et al. Montreal accord on patient-reported outcomes (PROs) use series – paper 4: patient-reported outcomes can inform clinical decision making in chronic care. J Clin Epidemiol. 2017;89:136–41.

4. Morris C, Janssens A, Allard A, et al. Informing the NHS Outcomes Framework: evaluating meaningful health outcomes for children with neurodisability using multiple methods including systematic review, qualitative research, Delphi survey and consensus meeting. Southampton (UK): NIHR Journals Library; 2014 May. (Health Services and Delivery Research, No. 2.15.) Chapter 4, Systematic review of patient-reported outcomes for children and young people. Available from: https://www.ncbi.nlm.nih.gov/books/NBK259784/