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Painter A, van Dael J, Neves A, et al., 2023, Identifying benefits and concerns with using digital health services during COVID-19: evidence from a hospital-based patient survey, Health Informatics Journal, Vol: 29, ISSN: 0965-8335
Despite large-scale adoption during COVID-19, patient perceptions on the benefits and potential risks with receiving care through digital technologies have remained largely unexplored. A quantitative content analysis of responses to a questionnaire (N = 6766) conducted at a multi-site acute trust in London (UK), was adopted to identify commonly reported benefits and concerns. Patients reported a range of promising benefits beyond immediate usage during COVID-19, including ease of access; support for disease and care management; improved timeliness of access and treatment; and better prioritisation of healthcare resources. However, in addition to known risks such as data security and inequity in access, our findings also illuminate some less studied concerns, including perceptions of compromised safety; negative impacts on patient-clinician relationships; and difficulties in interpreting health information provided through electronic health records and mHealth apps. Implications for future research and practice are discussed.
Gardner C, Wake D, Brodie D, et al., 2023, Evaluation of prototype risk prediction tools for clinicians and people living with type 2 diabetes in North West London using the think aloud method, Digital Health, Vol: 9, Pages: 1-11, ISSN: 2055-2076
The prevalence of type 2 diabetes in North West London (NWL) is relatively high compared to other parts of the United Kingdom with outcomes suboptimal. This presents a need for more effective strategies to identify people living with type 2 diabetes who need additional support. An emerging subset of web-based interventions for diabetes self-management and population management have used artificial intelligence and machine learning models to stratify the risk of complications from diabetes and identify patients in need of immediate support. In this study, two prototype risk prediction tools on the MyWay Diabetes and MyWay Clinical platforms were evaluated with six clinicians and six people living with type 2 diabetes in North West London using the think aloud method. The results of the sessions with people living with type 2 diabetes showed that the concept of the tool was intuitive, however more instruction on how to correctly use the risk prediction tool would be valuable. The feedback from the sessions with clinicians was that the data presented in the tool aligned with the key diabetes targets in NWL, and that this would be particularly useful for identifying and inviting patients to the practice who are overdue for tests and at-risk of complications. The findings of the evaluation have been used to support the development of the prototype risk predictions tools. This study demonstrates the value of conducting usability and user experience testing on web-based interventions designed to support for supporting the targeted management of type 2 diabetes in local communities.
Gardner C, Halligan J, Fontana G, et al., 2022, Evaluation of a clinical decision support tool for matching cancer patients to clinical trials using simulation-based research, Health Informatics Journal, Vol: 28, ISSN: 1460-4582
There is a growing need for alternative methodologies to evaluate digital health solutions in a short timeframe and at relatively low cost. Simulation-based research (SBR) methods have been proposed as an alternative methodology for evaluating digital health solutions; however, few studies have described the applicability of SBR methods to evaluate such solutions. This study used SBR to evaluate the feasibility and user experience of a clinical decision support (CDS) tool used for matching cancer patients to clinical trials. Twenty-five clinicians and research staff were recruited to match 10 synthetic patient cases to clinical trials using both the CDS tool and publicly available online trial databases. Participants were significantly more likely to report having sufficient time (p = 0.020) and to require less mental effort (p = 0.001) to complete trial matching with the CDS tool. Participants required less time for trial matching using the CDS tool, but the difference was not significant (p = 0.093). Most participants reported that they had sufficient guidance to participate in the simulations (96%). This study demonstrates the use of SBR methods is a feasible approach to evaluate digital health solutions and to collect valuable user feedback without the need for implementation in clinical practice. Further research is required to demonstrate the feasibility of using SBR to conduct remote evaluations of digital health solutions.
O'Brien N, van Dael J, Clarke J, et al., 2022, Addressing racial and ethnic inequities in data-driven health technologies, Publisher: Institute of Global Health Innovation, Imperial College London
Gardner C, Halligan J, Fontana G, et al., 2021, Evaluation of a clinical decision support tool for matching cancer patients to clinical trials using simulation-based research
<jats:title>Abstract</jats:title><jats:p>Simulation-based research (SBR) methods have been proposed as an alternative methodology for evaluating digital health solutions; however, applicability remains to be established. This study used SBR to evaluate a clinical decision support (CDS) tool used for matching cancer patients to clinical trials. 25 clinicians and research staff were recruited to match 10 synthetic patient cases to clinical trials using both the CDS tool and publicly available online trial databases. Participants were significantly more likely to report having sufficient time (<jats:italic>p</jats:italic> = 0.020) and to require less mental effort (<jats:italic>p</jats:italic> = 0.001) to complete trial matching with the CDS tool. Participants required less time for trial matching using the CDS tool, but the difference was not significant (<jats:italic>p</jats:italic> = 0.093). Most participants reported that they had sufficient guidance to participate in the simulations (96%). This study demonstrates the use of SBR methods is a feasible approach to evaluating digital health solutions.</jats:p>
Prime MS, Guo C, Fontana G, et al., 2021, An assessment of the NAVIFY clinical trial match application using clinical simulation-based research methods., Journal of Clinical Oncology, Vol: 39, ISSN: 0732-183X
Background: Cancer clinical trials require matching patients to strict, and sometimes lengthy, eligibility criteria. NAVIFY Clinical Trial Match (CTM) is a digital solution that uses data on an individual patient’s condition, genomic alterations and institution’s postal code to automatically find suitable clinical trials. We assessed the efficiency, accuracy and cognitive burden of NAVIFY CTM on matching patients to cancer clinical trials in the UK. Methods: 10 clinicians (8 medical doctors, 2 clinical trial practitioners) participated. Synthetic patient cases were developed with input from two oncologists, a histopathologist and a radiologist. Participants were instructed to identify appropriate trials for five patients using the NAVIFY CTM and five patients with the legacy approach (i.e. online trial databases) within one hour. For each method, participants were advised to approach the exercise with the level of scrutiny employed in a normal clinical setting. The efficiency, quality, and cognitive burden of trial matching was measured for each participant. The quality of trial matches was independently scored by an oncologist who did not participate in the simulations. The cognitive burden was measured subjectively, via a single-item questionnaire used to measure mental effort (Paas scale), and objectively, via Stroop test before and after each method. A survey was also conducted. Results: Efficiency: Participants completed the trial matching more efficiently using NAVIFY CTM, with trial matches completed on average one minute and 42 seconds faster using the digital solution (n = 73 matches) compared with the most commonly used online trial database, ClinicalTrials.gov (n = 52). Participants were more likely to ‘completely agree’ that they had enough time to complete the task using the NAVIFY CTM (70%) compared to online trial databases (40%). Quality of the matches: On the survey, more participants reported that trial suggestions were &lsq
van Dael J, Neves AL, Painter A, et al., 2021, Patient perspectives on the use of digital health services at a multi-site hospital in North-West London: a quantitative content analysis (Preprint), Journal of Medical Internet Research, ISSN: 1438-8871
Background:Following a large increase in the adoption of digital health amidst the COVID-19 crisis, there is increasing policy interest in the longer-term implementation of digital health services. Yet, there is still much unknown about the inherent quality of remote digital care, and research on patient perspectives remains comparatively small. Widespread usage amidst COVID-19 presents an important opportunity to better understand patients’ first-hand experiences with using these technologies.Objective:This study examined patients’ perspectives on main benefits and concerns with using digital health services in a large multi-site teaching hospital in North-West London during the COVID-19 crisis.Methods:Qualitative data was obtained from a larger questionnaire conducted during the COVID-19 pandemic on Care Information Exchange, which represents the largest patient-facing electronic health records in the English National Health Service. All responses were analysed using the framework analysis method. Quantitative content analysis was performed by mapping frequencies of reported themes across the respondent population.Results:Of all 6,766 respondents, 25.1% reported to have no concerns with digital health services, compared to 3.0% reporting no benefits. Reported benefits included: ease of access (37.1%), feeling empowered and informed (23.2%), improved timeliness of access and treatment (18.6%), healthcare capacity (11.5%), and care continuity amidst COVID-19 (7.4%). In contrast, reported concerns included issues around data security and privacy (17.5%), clinical uncertainty (17.0%), impact on patient-doctor relationship (11.9%), inequity in access and use (11.8%), misunderstanding health information (6.3%), and digital maturity (3.8%).Conclusions:Patients report many benefits with digital health services beyond immediate COVID-19 support, including improved access, timeliness, and enhanced healthcare capacity. Yet, some concerns remain, including some le
Gardner C, Halligan J, Ghafur S, 2021, P02.08 A UK Survey of Current Methods for Conducting Cancer Multidisciplinary Team Meetings and Opportunities for Digital Solutions., Journal of Thoracic Oncology, Vol: 16, Pages: S250-S250, ISSN: 1556-0864
Smalley KR, Lound A, Gardner C, et al., 2021, CO-DESIGNING A DIGITAL SELF-MANAGEMENT PLAN FOR BRONCHIECTASIS, Publisher: BMJ PUBLISHING GROUP, Pages: A170-A171, ISSN: 0040-6376
Guo C, Ashrafian H, Ghafur S, et al., 2020, Challenges for the evaluation of digital health solutions-A call for innovative evidence generation approaches, NPJ DIGITAL MEDICINE, Vol: 3, ISSN: 2398-6352
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Gardner C, Ghafur S, Fontana G, et al., 2020, A mixed methods study for the evaluation of a digital health solution for cancer multidisciplinary team meetings using simulation-based research methods., Journal of Clinical Oncology, Vol: 38, Pages: e14063-e14063, ISSN: 0732-183X
Background: Simulation-based research (SBR) methods involve setting up structured scenarios to replicate real-world situations, with the aim of eliciting real-world reactions and behaviours. SBR is useful for the evaluation of new healthcare solutions without compromising patient safety or navigating complex ethical review processes. However, there are few trials using SBR methods for the evaluation of digital health interventions (DHIs), the adoption of which has been hindered in the NHS due to a lack of evidence-base for their efficacy. SBR methods could be an appropriate tool for testing digital solutions. Methods: The Institute of Global Health Innovation (IGHI) developed a series of simulated lung cancer multidisciplinary team (MDT) meetings to test the NAVIFY Tumor Board solution by Roche Diagnostic Information Solutions, a digital solution for the preparation and conduct of cancer MDTs. To provide an environment for participants to evaluate the capabilities of the NAVIFY Tumor Board solution, 10 simulation sessions were organised in which groups of five to six clinicians were recruited to discuss up to 10 mock patient cases across two simulated MDTs, first using standard tools commonly used to conduct MDTs and then using the NAVIFY Tumor Board solution. The cases were developed by the study team at IGHI and consultants in respiratory medicine and oncology. 56 healthcare professionals (respiratory physicians, oncologists, radiologists, histopathologists, clinical nurse specialists and thoracic surgeons) were recruited. The sessions were video recorded and observations were noted by the study team, followed by a focus group in which participants provided feedback about their experience of the simulated MDTs. Results: Through this study we were able to generate evidence and multi-professional recommendations for Roche regarding the functionality, usability and applicability of the solution in the NHS, as well as beneficial features and those which could be impro
Gardner C, Ghafur S, Fontana G, et al., 2020, A mixed methods study for the evaluation of a digital health solution for cancer multidisciplinary team meetings using simulation-based research methods., Annual Meeting of the American-Society-of-Clinical-Oncology (ASCO), Publisher: LIPPINCOTT WILLIAMS & WILKINS, ISSN: 0732-183X
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