Development and usability testing of an electronic patient-reported outcome (ePRO) solution for patients with inflammatory diseases in an Advanced Therapy Medicinal Product (ATMP) basket trial.

BACKGROUND: Electronic patient-reported outcome (ePRO) systems are increasingly used in clinical trials to provide evidence of efficacy and tolerability of treatment from the patient perspective. The aim of this study is twofold: (1) to describe how we developed an electronic platform for patients to report their symptoms, and (2) to develop and undertake usability testing of an ePRO solution for use in a study of cell therapy seeking to provide early evidence of efficacy and tolerability of treatment and test the feasibility of the system for use in later phase studies. METHODS: An ePRO system was designed to be used in a single arm, multi-centre, phase II basket trial investigating the safety and activity of the use of ORBCEL-C™ in the treatment of patients with inflammatory conditions. ORBCEL-C™ is an enriched Mesenchymal Stromal Cells product isolated from human umbilical cord tissue using CD362+ cell selection. Usability testing sessions were conducted using cognitive interviews and the 'Think Aloud' method with patient advisory group members and Research Nurses to assess the usability of the system. RESULTS: Nine patient partners and seven research nurses took part in one usability testing session. Measures of fatigue and health-related quality of life, the PRO-CTCAE™ and FACT-GP5 global tolerability question were included in the ePRO system. Alert notifications to the clinical team were triggered by PRO-CTCAE™ and FACT-GP5 scores. Patient participants liked the simplicity and responsiveness of the patient-facing app. Two patients were unable to complete the testing session, due to technical issues. Research Nurses suggested minor modifications to improve functionality and the layout of the clinician dashboard and the training materials. CONCLUSION: By testing the effectiveness, efficiency, and satisfaction of our novel ePRO system (PROmicsR), we learnt that most people with an inflammatory condition found it easy to report their symptoms using an app on their own device. Their experiences using the PROmicsR ePRO system within a trial environment will be further explored in our upcoming feasibility testing. Research nurses were also positive and found the clinical dashboard easy-to-use. Using ePROs in early phase trials is important in order to provide evidence of therapeutic responses and tolerability, increase the evidence based, and inform methodology development. TRIAL REGISTRATION: ISRCTN, ISRCTN80103507. Registered 01 April 2022, https://www.isrctn.com/ISRCTN80103507.

More and more patients tell clinicians how they feel by completing questionnaires electronically. Therefore, it is important to assess how easy it is for patients to do this. In this study, we describe how we developed an electronic platform for patients to report their symptoms and how we tested the usability of this platform with patient partners and research nurses. Once the electronic platform was developed, quality of life and symptoms questionnaires were programmed onto it. Alerts were sent to the clinical team if specific scores were obtained on the symptoms questionnaires. Although two patient partners were not able to finish the testing session because of technical issues, the ones who completed the session liked its simplicity and responsiveness. The research nurses also liked the system and only suggested minor modifications. Following this testing, we refined the electronic platform to test it further in a larger study which investigates the safety and use of a drug. We hope that thanks to this electronic platform, we will obtain useful information on the safety and efficacy of treatment.

Embedding patient-reported outcomes at the heart of artificial intelligence health-care technologies.

Integration of patient-reported outcome measures (PROMs) in artificial intelligence (AI) studies is a critical part of the humanisation of AI for health. It allows AI technologies to incorporate patients' own views of their symptoms and predict outcomes, reflecting a more holistic picture of health and wellbeing and ultimately helping patients and clinicians to make the best health-care decisions together. By positioning patient-reported outcomes (PROs) as a model input or output we propose a framework to embed PROMs within the function and evaluation of AI health care. However, the integration of PROs in AI systems presents several challenges. These challenges include (1) fragmentation of PRO data collection; (2) validation of AI systems trained and validated against clinician performance, rather than outcome data; (3) scarcity of large-scale PRO datasets; (4) inadequate selection of PROMs for the target population and inadequate infrastructure for collecting PROs; and (5) clinicians might not recognise the value of PROs and therefore not prioritise their adoption; and (6) studies involving PRO or AI frequently present suboptimal design. Notwithstanding these challenges, we propose considerations for the inclusion of PROs in AI health-care technologies to avoid promoting survival at the expense of wellbeing.