Digital trials

Electronic Health Records (EHRs) are the digital version of the patients medical record. Electronic Data Capture (EDC) systems are used to store trial data collected during a clinical trial. Manually keying in data from an EHR to an EDC system results in data management time spent on transferring data, quality checking the data and answering queries. With the use of EHRs increasing streamlining trial data management is important to the future of clinical trials.

Find a Study is the clinical trials discovery platform at UCLH, which enables clinicians and patients to find trials that are open. The aim is to increase trial recruitment and to improve the visibility and transparency of research activity at UCLH. The platform is powered by Keytrials, a software engine for the storage and analysis of information on clinical trials, and is endorsed and supported by the National Institute for Health Research (NIHR) and the UCLH Biomedical Research Centre (BRC).

The need

Making information abFind a studyout clinical trials readily available to patients and their clinicians, is essential to recruiting participants to trials.  CRIU created Find a Study as a way of addressing this need.

Find a Study – which supersedes the old UCLH Research Gateway – is integrated with Epic, the electronic health record system (EHRS) used at UCLH since Spring 2019, Epic allows clinicians, nurses and other health care professionals to have access to all relevant patient information in a single patient record. The integration of Find a Study means that with just one click, clinicians can now see all recruiting trials that their patients may be eligible for. 

As Dr Nick McNally, Chief Operating Officer at UCLH/UCL BRC, states, “We know we could be recruiting many more patients to clinical trials and the way to do that is to make our trials portfolio more accessible and more transparent”.

Recruitment to trials is usually the last step in the lengthy process of introducing a new treatments. Before being used as standard care, all new drug treatments must be carefully and thoroughly tested to determine whether they are safe and effective.

Find a study screenshot

Next steps

In future we aim to develop an ‘auto-matching’ system where the platform will automatically suggest which trials a patient is suitable for, based on information in the patient’s EHR and eligibility criteria of studies. This would be a first in the UK, integrating a clinical trials discovery platform and EHR.

Phase 1 of the co-design, implementation and evaluation of Find a Study across the Trust is currently under way, with the aim to capture the impact on clinical work practices. This phase is crucial as a proof of concept to understanding how we can successfully inform organisational change.  In Phase 2, we are planning to liaise with patient and public forums to create a version for non-clinical users. The ambition is to scale this successful platform across the NHS and harness learning in a single space.

We have a ‘Find a Study’ app for Android as well as iOS app in development. More details soon!

Electronic Health Records (EHRs) are the digital version of the patients medical record. Electronic Data Capture (EDC) systems are used to store trial data collected during a clinical trial. Manually keying in data from an EHR to an EDC system results in data management time spent on transferring data, quality checking the data and answering queries. With the use of EHRs increasing streamlining trial data management is important to the future of clinical trials. 

The COVID-19 pandemic has shown how important it is to be digitally enabled to ensure continuity of patient care and safeguarding staff. Being able to work remotely and have access to patient data electronically has ensured that key trial data has been transferred to the sponsor in a timely fashion without compromising the safety of our staff or the integrity of the trial.  

Archer is an EHR2EDC automation application allowing the transfer of trial data from an EHR to EDC system.   Automation of data transfer would reduce the burden on clinical trials teams to manually transfer the data which can be a laborious process as a result allowing clinical trials teams to focus on patient care. EHR2EDC automation is expected to improve the quality of the data being transferred resulting in a reduction in monitoring queries from the trial sponsors. These are just some examples of time saving that can result in cost savings for UCLH, with the financial pressures facing the NHS this is certainly a welcome innovation.

The Cancer Clinical Trials Unit at UCLH will be running a pilot study with AstraZeneca to assess the effectiveness of the Archer system in improving the efficiency of the clinical trial process. The EHRs research team has worked with IgniteData to implement the connection to Archer with successful testing in the live environment. With the ever increasing complexity of trials and the data required, the ability to automate data transfer would revolutionise the way we can manage clinical trial data at UCLH and other healthcare institutions. 

Press releases:

https://www.ignitedata.co.uk/news/uclh-astrazeneca-and-ignitedata-test-data-automation-in-clinical-trial/ https://www.ignitedata.co.uk/news/zs-and-ignitedata-partner-to-transform-patient-data-automation-for-clinical-trials/ 

https://www.ignitedata.co.uk/news/a-decade-of-research-into-the-benefits-of-ehr2edc-solutions/

Archer - fast, accurate data for modern clinical trials

The unstructured data in the EHR system (e.g. free text notes, images) represent a valuable data asset and comprise an estimated 80% of the record [2]. The free-text notes in particular capture a lot of valuable structured data items that are not recorded formally recorded in structured data fields [3] in the EHR (e.g. symptoms, drugs etc.). CogStack is a text-analytics platform designed to help clinicians and researchers extract structured data from the free-text contents of the EHR. CogStack essentially provides three services: the first is a data ingestion pipeline which allows the platform to ingest and harmonise the free text records in the EHR. The second is a suite of natural language processing tools to facilitate the extraction of structured clinical data from the ingested documents and lastly CogStack provides a set of tools for data scientists and clinicians to interact with the ingested data and mined structured data.

CogStack has been used as part of several clinical projects. Examples include identifying symptoms and comorbidities for normal pressure hydrocephalus undergoing surgery and predicting next steps for patient care (e.g. does patient need a referral or to be discharged). To find out more about the deployment of CogStack at UCLH please read our latest publication (https://medinform.jmir.org/2022/8/e38122) [1]

[1] Noor K, Roguski L, Bai X, Handy A, Klapaukh R, Folarin A, Romao L, Matteson J, Lea N, Zhu L, Asselbergs F, Wong W, Shah A, Dobson R

Deployment of a Free-Text Analytics Platform at a UK National Health Service Research Hospital: CogStack at University College London Hospitals

JMIR Med Inform 2022;10(8):e38122

URL: https://medinform.jmir.org/2022/8/e38122

DOI: 10.2196/38122

[2] Why Unstructured Data Holds the Key to Intelligent Healthcare Systems. HIT Consultant. 2015. URL: https://hitconsultant.net/2015/03/31/tapping-unstructured-data-healthcares-biggest-hurdle-realized/ [accessed 2022-07-08]

[3] Poulos J, Zhu L, Shah AD. Data gaps in electronic health record (EHR) systems: An audit of problem list completeness during the COVID-19 pandemic. Int J Med Inform 2021 Jun;150:104452