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Introduction: Digital health interventions may support physical activity among solid organ transplant recipients. These interventions should be designed with users in mind, including healthcare professionals who counsel transplant recipients on physical activity to ensure acceptance and to promote an optimal user experience. The purpose of this study was to explore the perspectives of health care providers on the features of digital health interventions that would be useful in the promotion, implementation, and maintenance of physical activity among solid organ transplant recipients. Methods: This qualitative, cross-sectional study used semistructured interviews that were conducted remotely, via videoconferencing software, with providers who worked with transplant recipients. Interviews were transcribed, and an iterative-inductive, thematic analysis was used to identify common themes. Data were coded using NVivo software. Findings: Thirteen providers participated in this study. Four main themes were identified: (a) physical activity and exercise features (eg, physical activity guidelines, and exercise instructions); (b) credibility; (c) self-management; and (d) user engagement. Potential barriers to using digital health interventions included staffing requirements, professional regulatory issues, cost, perceived low patient motivation to use, and lack of technological literacy or access. Discussion: Digital health interventions were perceived to be a potential adjunct to current physical activity counseling practices, and part of an innovative strategy to address identified barriers to physical activity participation in solid organ transplant recipients.

UNSTRUCTURED International deployment of remote monitoring and virtual care (RMVC) technologies would efficiently harness their positive impact on outcomes. Since Canada and the UK have similar populations, healthcare systems, and digital health landscapes, transferring digital health innovations between them should be relatively straightforward. Yet, examples of successful attempts are scarce. In a workshop, we identified six differences that may complicate RMVC transfer between Canada and the UK, and provide recommendations for addressing. These key differences include: 1) minority groups, (2) physical geography, (3) clinical pathways, (4) value propositions, (5) governmental priorities and support for digital innovation, (6) regulatory pathways. We detail four broad recommendations to plan for sustainability including: the need to formally consider how highlighted country-specific recommendations may impact RMVC and contingency planning to overcome challenges; the need to map which pathways are available as an innovator to support cross-country transfer; the need to report on and apply learnings from regulatory barriers and facilitators so that everyone may benefit; and explore existing guidance to successfully transfer digital health solutions while developing further guidance (e.g., extending the NASSS framework for cross-country transfer). Finally, we present an ecosystem readiness checklist. Considering these recommendations will contribute to successful international deployment and increased positive impact of RMVC technologies.

BACKGROUND Emerging adults living with type 1 diabetes (T1D) face a series of challenges with self-management and decreased health system engagement, leading to increased risk of acute complications and hospital admissions. Effective and scalable strategies are needed to support this population to transfer seamlessly from paediatric to adult care with sufficient self-management capability. While digital health interventions for T1D self-management are a promising strategy, it remains unclear which elements work, how, and for which group(s) of individuals. OBJECTIVE The present study aims to evaluate the design and implementation of a multi-component digital health intervention to support emerging adults living with T1D in real-world settings. Specifically, the objectives are to identify the intervention components and associated mechanisms that lead to improved user engagement and T1D healthcare transition experiences and determine the individual-level contextual factors that influence the implementation process. METHODS Embedded alongside a randomized controlled trial, this realist evaluation employs a sequential mixed-methods design to analyze data from multiple sources, including intervention usage data, patient-reported outcomes, and semi-structured interviews. In Step 1, we conducted a document analysis to develop a program theory that outlines the hypothesized relationships amongst individual-level contextual factors (C), intervention components and features (I), mechanisms (M), and target outcomes (O) with special attention paid to user engagement. In Step 2, we will conduct semi-structured interviews with the RCT intervention arm participants to validate the hypothesized C-I-M-O configurations. In Step 3, we will triangulate all sources of data using a Coincidence Analysis to identify the necessary combinations of conditions (i.e., factors, pathways, and context) that determine whether and how the desired outcomes are achieved and use these insights to refine the program theory. RESULTS For step 1 analysis, we have developed the initial program theory and the corresponding data collection plan. For step 2 analysis, participant enrollment for the randomized controlled trial started in January 2023. Participant enrollment for the present realist evaluation is anticipated to start in May 2023 and continue until we reach thematic saturation or achieve informational power. CONCLUSIONS Beyond contributing to knowledge on the multiple pathways that lead to successful engagement with a digital health intervention as well as target outcomes in T1D care transitions, embedding the realist evaluation alongside the trial may inform real-time intervention refinement to improve user engagement and transition experiences. The knowledge gained from this study may inform the design, implementation, and evaluation of future digital health interventions that aim to improve transition experiences.

BACKGROUND For individuals living with diabetes and its psychosocial comorbidities (eg, depression, anxiety, and distress), there remains limited access to interprofessional, integrated care that includes mental health support, education, and follow-up. Health technology, broadly defined as the application of organized knowledge or skill as software, devices, and systems to solve health problems and improve quality of life, is emerging as a means of addressing these gaps. There is thus a need to understand how such technologies are being used to support, educate, and help individuals living with co-occurring diabetes and mental health distress or disorder. OBJECTIVE The purpose of this scoping review was to (1) describe the literature on technology-enabled integrated interventions for diabetes and mental health; (2) apply frameworks from the Mental Health Commission of Canada and World Health Organization to elucidate the components, type, processes, and users of technology-enabled integrated interventions for diabetes and mental health; and (3) map the level of integration of interventions for diabetes and mental health. METHODS We searched 6 databases from inception to February 2022 for English-language, peer-reviewed studies of any design or type that used technology to actively support both diabetes and any mental health distress or disorder in succession or concurrently among people with diabetes (type 1 diabetes, type 2 diabetes, and gestational diabetes). Reviewers screened citations and extracted data including study characteristics and details about the technology and integration used. RESULTS We included 24 studies described in 38 publications. These studies were conducted in a range of settings and sites of care including both web-based and in-person settings. Studies were mostly website-based (n=13) and used technology for wellness and prevention (n=16) and intervention and treatment (n=15). The primary users of these technologies were clients and health care providers. All the included intervention studies (n=20) used technology for clinical integration, but only 7 studies also used the technology for professional integration. CONCLUSIONS The findings of this scoping review suggest that there is a growing body of literature on integrated care for diabetes and mental health enabled by technology. However, gaps still exist with how to best equip health care professionals with the knowledge and skills to offer integrated care. Future research is needed to continue to explore the purpose, level, and breadth of technology-enabled integration to facilitate an approach to overcome or address care fragmentation for diabetes and mental health and to understand how health technology can further drive the scale-up of innovative integrated interventions.

BACKGROUND Comprehensive models of survivorship care are necessary to improve access and coordination of care and to address the complexity of physical and psychosocial problems and long-term health needs experienced by patients following cancer treatment. Our group is building a nurse-led virtual clinic to support men living with prostate cancer (PCa) in the post-treatment follow-up phase of their survivorship journey. OBJECTIVE This paper presents our expert-informed, rules-based, survivorship algorithm to build a nurse-led model of survivorship care for prostate cancer survivors with “no evidence of disease” (Ned) to support more timely decision-making, enhanced safety and continuity of care. METHODS An initial rule-set was developed via a literature review and working groups with clinical experts across Canada (e.g., nurse experts, physician experts, scientists) (n=20), and patient partners (n=3). Algorithm priorities were defined through a multidisciplinary consensus meeting with clinical nurse specialists, nurse scientists, nurse practitioners, urologic oncologists, urologists, and radiation oncologists (n=17). The system was refined and validated using nominal group technique. RESULTS Four levels of alert classification were established, initiated by responses on the EPIC-CP survey, and mediated by changes in minimal clinically important different alert thresholds, alert history, clinical urgency with patient autonomy influencing clinical acuity. Patient autonomy was supported through tailored education as a first line of response, and alert escalation depending on a patient-initiated request for a nurse consultation. CONCLUSIONS The Ned algorithm is positioned to facilitate PCa nurse-led care models with a high nurse to patient ratio. This novel expert-informed PCa survivorship care algorithm contains a defined escalation pathway for clinically urgent symptoms while honoring patient preference. Though further validation is required through a pragmatic trial, we anticipate the Ned algorithm will support more timely decision-making, enhance continuity of care through automation of more frequent automated check points, while empowering patients to self-manage their symptoms more effectively than standard care. INTERNATIONAL REGISTERED REPORT RR2-10.1136/bmjopen-2020-045806

DailyDose is a decision support system developed at Oregon Health & Science University designed for people with T1D on MDI to improve glycemic control. It connects with Dexcom G6 and Medtronic's InPen. DailyDose runs on a smartphone and calculates insulin doses using CGM value and trend, IOB, carbohydrate amount, and exercise information. The system analyzes CGM and insulin data and automatically provides weekly recommendations on insulin settings, such as basal insulin dose and carbohydrate ratios, based on a k-nearest neighbors algorithm. Twenty-four adults with T1D used DailyDose for 8 weeks. The primary outcome was change in % time in range (TIR, 70-180 mg/dL) on CGM comparing the two week run-in period before starting DailyDose vs. final two weeks of DailyDose use. A mixed effects model was used to determine the impact of the % of accepted recommendations on change in % TIR. Users who accepted and followed recommendations showed a mean week-to-week improvement in TIR of 2.0% (Figure) . The mixed effects model shows week-by-week TIR increased by 7.8% when recommendations were accepted compared with not accepted (CI, 3-12%, P=.001) . Overall, there were no significant differences between TIR or time in hypoglycemia comparing the run-in period and the final two weeks of use. Further work is needed to encourage people using decision support systems to follow recommendations. Disclosure J.R.Castle: Advisory Panel; Insulet Corporation, Novo Nordisk, Zealand Pharma A/S, Stock/Shareholder; Pacific Diabetes Technologies. V.Gabo: None. J.H.Eom: None. J.El youssef: None. K.Ramsey: None. T.Kushner: Consultant; Tandem Diabetes Care, Inc. K.Winters-stone: None. J.A.Cafazzo: None. P.G.Jacobs: Other Relationship; Pacific Diabetes Technologies, Research Support; Dexcom, Inc. A.Z.Espinoza: None. N.S.Tyler: None. L.M.Wilson: n/a. C.M.Mosquera-lopez: None. J.Pinsonault: None. R.Dodier: None. S.M.Oganessian: None. D.Branigan: None. Funding The Leona M. and Harry B. Helmsley Charitable Trust (Grant 2018PG-T1D001) .

Background and objectives Patients with CKD are at risk for adverse drug reactions, but effective community-based preventive programs remain elusive. In this study, we compared the effectiveness of two digital applications designed to improve outpatient medication safety. Design, setting, participants, & measurements In a 1-year randomized controlled trial, 182 outpatients with advanced CKD were randomly assigned to receive a smartphone preloaded with either eKidneyCare (n=89) or MyMedRec (n=93). The experimental intervention, eKidneyCare, includes a medication feature that prompted patients to review medications monthly and report changes, additions, or medication problems to clinicians for reconciliation and early intervention. The active comparator was MyMedRec, a commercially available, standalone application for storing medication and other health information that can be shared with patients' providers. The primary outcome was the rate of medication discrepancy, defined as differences between the patient's reported history and the clinic's medication record, at exit. Results At exit, the eKidneyCare group had fewer total medication discrepancies compared with MyMedRec (median, 0.45; interquartile range, 0.33-0.63 versus 0.67; interquartile range, 0.40-1.00; P=0.001), and the change from baseline was 0.13±0.27 in eKidneyCare and 0.30±0.41 in MyMedRec (P=0.007). eKidneyCare use also reduced the severity of clinically relevant medication discrepancies in all categories, including those with the potential to cause serious harm (estimated rate ratio, 0.40; 95% confidence interval, 0.27 to 0.63). Usage data revealed that 72% of patients randomized to eKidneyCare completed one or more medication reviews per month, whereas only 30% of patients in the MyMedRec group (adjusted for dropouts) kept their medication profile on their phone. Conclusions In patients who are high risk and have CKD, eKidneyCare significantly reduced the rate and severity of medication discrepancies, the proximal cause of medication errors, compared with the active comparator. CLINICAL TRIAL REGISTRY NAME AND REGISTRATION NUMBER: www.clinicaltrials.gov, NCT:02905474.

IntroductionTransition from paediatric to adult care can be challenging for youth living with type 1 diabetes (T1D), as many youth feel unprepared to transfer to adult care and are at high risk for deterioration of glycaemic management and acute complications. Existing strategies to improve transition experience and outcomes are limited by cost, scalability, generalisability and youth engagement. Text messaging is an acceptable, accessible and cost-effective way of engaging youth. Together with adolescents and emerging adults and paediatric and adult T1D providers, we co-designed a text message-based intervention, Keeping in Touch (KiT), to deliver tailored transition support. Our primary objective is to test the effectiveness of KiT on diabetes self-efficacy in a randomised controlled trial.Methods and analysisWe will randomise 183 adolescents with T1D aged 17–18 years within 4 months of their final paediatric diabetes visit to the intervention or usual care. KiT will deliver tailored T1D transition support via text messages over 12 months based on a transition readiness assessment. The primary outcome, self-efficacy for diabetes self-management, will be measured 12 months after enrolment. Secondary outcomes, measured at 6 and 12 months, include transition readiness, perceived T1D-related stigma, time between final paediatric and first adult diabetes visits, haemoglobin A1c, and other glycaemia measures (for continuous glucose monitor users), diabetes-related hospitalisations and emergency department visits and the cost of implementing the intervention. The analysis will be intention-to-treat comparing diabetes self-efficacy at 12 months between groups. A process evaluation will be conducted to identify elements of the intervention and individual-level factors influencing implementation and outcomes.Ethics and disseminationThe study protocol version 7 July 2022 and accompanying documents were approved by Clinical Trials Ontario (Project ID: 3986) and the McGill University Health Centre (MP-37-2023-8823). Study findings will be presented at scientific conferences and in peer-reviewed publications.Trial registration numberNCT05434754.

There is a growing interest to investigate the feasibility of using voice user interfaces as a platform for digital therapeutics in chronic disease management. While mostly deployed as smartphone applications, some demographics struggle when using touch screens and often cannot complete tasks independently. This research aimed to evaluate how heart failure patients interacted with a voice app version of an already existing digital therapeutic, Medly, using a mixed-methods concurrent triangulation approach. The objective was to determine the acceptability and feasibility of the voice app by better understanding who this platform is be best suited for. Quantitative data included engagement levels and accuracy rates. Participants (n=20) used the voice app over a four week period and completed questionnaires and semi-structured interviews relating to acceptability, ease of use, and workload. The average engagement level was 73%, with a 14% decline between week one and four. The difference in engagement levels between the oldest and youngest demographic was the most significant, 84% and 43% respectively. The Medly voice app had an overall accuracy rate of 97.8% and was successful in sending data to the clinic. Users were accepting of the technology (ranking it in the 80th percentile) and felt it did not require a lot of work (2.1 on a 7-point Likert scale). However, 13% of users were less inclined to use the voice app at the end of the study. The following themes and subthemes emerged: (1) feasibility of clinical integration: user adaptation to voice app’s conversational style, device unreliability, and (2) voice app acceptability: good device integration within household, users blamed themselves for voice app problems, and voice app missing desirable user features. The voice app proved to be most beneficial to those who: are older, have flexible schedules, are confident with using technology, and are experiencing other medical conditions.

The use of digital therapeutics (DTx) in the prevention and management of medical conditions has increased through the years with an estimated 44 million people using one as part of their treatment plan in 2021, nearly double the amount from last year. DTx are commonly accessed through smartphone apps, but offering these treatments through an alternative input can improve the accessibility of these interventions. Voice apps are an emerging technology in the digital health field, and may be an appropriate alternative platform for some patients. This research aimed to identify the acceptability and feasibility of offering a voice app as an alternative input for a chronic disease self-management program. The objective of this project was to design, develop, and evaluate a voice app of an already existing smartphone-based heart failure self-management program, Medly, to be used as a case study. A voice app version of Medly was designed and developed through a user-centered design process. We conducted a usability study and semi-structured interviews with representative end users (n=8) at the Peter Munk Cardiac Clinic in Toronto General Hospital to better understand the user experience. A Medly voice app prototype was built using a software development kit in tandem with a cloud computing platform. Three out of the eight participants were successful in completing the usability session, while the rest of the participants were not due to various errors. Almost all (7 out of the 8) participants were satisfied with the voice app and felt confident using it. Half of the participants were unsure about using the voice app in the future, though. With these findings, design changes were made to better improve the user experience. With rapid advancements in voice user interfaces, we believe this technology will play an integral role when providing access to DTx for chronic disease management.

Background Complications due to type 2 diabetes (T2D) can be mitigated through proper self-management that can positively change health behaviors. Technological tools are available to help people living with, or at risk of developing, T2D to manage their condition, and such tools provide a large repository of patient-generated health data (PGHD). Analytics can provide insights into the health behaviors of people living with T2D. Objective The aim of this review is to investigate what can be learned about the health behaviors of those living with, or at risk of developing, T2D through analytics from PGHD. Methods A scoping review using the Arksey and O’Malley framework was conducted in which a comprehensive search of the literature was conducted by 2 reviewers. In all, 3 electronic databases (PubMed, IEEE Xplore, and ACM Digital Library) were searched using keywords associated with diabetes, behaviors, and analytics. Several rounds of screening using predetermined inclusion and exclusion criteria were conducted, after which studies were selected. Critical examination took place through a descriptive-analytical narrative method, and data extracted from the studies were classified into thematic categories. These categories reflect the findings of this study as per our objective. Results We identified 43 studies that met the inclusion criteria for this review. Although 70% (30/43) of the studies examined PGHD independently, 30% (13/43) combined PGHD with other data sources. Most of these studies used machine learning algorithms to perform their analysis. The themes identified through this review include predicting diabetes or obesity, deriving factors that contribute to diabetes or obesity, obtaining insights from social media or web-based forums, predicting glycemia, improving adherence and outcomes, analyzing sedentary behaviors, deriving behavior patterns, discovering clinical correlations from behaviors, and developing design principles. Conclusions The increased volume and availability of PGHD have the potential to derive analytical insights into the health behaviors of people living with T2D. From the literature, we determined that analytics can predict outcomes and identify granular behavior patterns from PGHD. This review determined the broad range of insights that can be examined through PGHD, which constitutes a unique source of data for these applications that would not be possible through the use of other data sources.

BACKGROUND Despite the growing prevalence of people with complex conditions and evidence of the positive impact of telemonitoring for single conditions, little research exists on telemonitoring for this population. OBJECTIVE This randomized controlled trial and embedded qualitative study aims to evaluate the impact on and experiences of patients and health care providers (HCPs) using a telemonitoring system with decision support to manage patients with complex conditions, including those with multiple chronic conditions, compared with the standard of care. METHODS A pragmatic, unblinded, 6-month randomized controlled trial sought to recruit 146 patients with ≥1 diagnosis of heart failure (HF), uncontrolled hypertension (HT), and insulin-requiring diabetes mellitus (DM) from outpatient specialty settings in Toronto, Ontario, Canada. Participants were randomized into the control and telemonitoring groups, with the latter being instructed to take readings relevant to their conditions. The telemonitoring system contained an algorithm that generated decision support in the form of actionable self-care directives to patients and alerts to HCPs. The primary outcome was health status (36-Item Short Form Health Survey questionnaire). Secondary outcomes included anxiety and depression, self-efficacy in chronic disease management, and self-reported health service use. HF-related quality of life and self-care measures were also collected from patients followed for HF. Within- and between-group change scores were analyzed for statistical significance (P RESULTS A total of 96 patients were recruited and randomized. Recruitment was terminated early because of implementation challenges and the onset of the COVID-19 pandemic. No significant within- and between-group differences were found for the main primary and secondary outcomes. However, a within-group analysis of patients with HF found improvements in self-care maintenance (P=.04) and physical quality of life (P=.046). Opinions expressed by the 5 HCPs and 13 patients who were interviewed differed based on the monitored conditions. Although patients with HF reported benefitting from actionable self-care guidance and meaningful interactions with their HCPs, patient and HCP users of the DM and HT modules did not think telemonitoring improved the clinical management of those conditions to the same degree. These differing experiences were largely attributed to the siloed nature of specialty care and the design of the decision support, whereby fluctuations in the status of HT and DM typically required less urgent interventions compared with patients with HF. CONCLUSIONS We recommend that future research conceive telemonitoring as a program and that self-management and clinical decision support are necessary but not sufficient components of such programs for patients with complex conditions and lower acuity. We conclude that telemonitoring for patients with complex conditions or within multidisciplinary care settings may be best operationalized through nurse-led models of care. CLINICALTRIAL ClinicalTrials.gov NCT03127852; https://clinicaltrials.gov/ct2/show/NCT03127852 INTERNATIONAL REGISTERED REPORT RR2-10.2196/resprot.8367

BackgroundDespite the growing prevalence of people with complex conditions and evidence of the positive impact of telemonitoring for single conditions, little research exists on telemonitoring for this population.ObjectiveThis randomized controlled trial and embedded qualitative study aims to evaluate the impact on and experiences of patients and health care providers (HCPs) using a telemonitoring system with decision support to manage patients with complex conditions, including those with multiple chronic conditions, compared with the standard of care.MethodsA pragmatic, unblinded, 6-month randomized controlled trial sought to recruit 146 patients with ≥1 diagnosis of heart failure (HF), uncontrolled hypertension (HT), and insulin-requiring diabetes mellitus (DM) from outpatient specialty settings in Toronto, Ontario, Canada. Participants were randomized into the control and telemonitoring groups, with the latter being instructed to take readings relevant to their conditions. The telemonitoring system contained an algorithm that generated decision support in the form of actionable self-care directives to patients and alerts to HCPs. The primary outcome was health status (36-Item Short Form Health Survey questionnaire). Secondary outcomes included anxiety and depression, self-efficacy in chronic disease management, and self-reported health service use. HF-related quality of life and self-care measures were also collected from patients followed for HF. Within- and between-group change scores were analyzed for statistical significance (PResultsA total of 96 patients were recruited and randomized. Recruitment was terminated early because of implementation challenges and the onset of the COVID-19 pandemic. No significant within- and between-group differences were found for the main primary and secondary outcomes. However, a within-group analysis of patients with HF found improvements in self-care maintenance (P=.04) and physical quality of life (P=.046). Opinions expressed by the 5 HCPs and 13 patients who were interviewed differed based on the monitored conditions. Although patients with HF reported benefitting from actionable self-care guidance and meaningful interactions with their HCPs, patient and HCP users of the DM and HT modules did not think telemonitoring improved the clinical management of those conditions to the same degree. These differing experiences were largely attributed to the siloed nature of specialty care and the design of the decision support, whereby fluctuations in the status of HT and DM typically required less urgent interventions compared with patients with HF.ConclusionsWe recommend that future research conceive telemonitoring as a program and that self-management and clinical decision support are necessary but not sufficient components of such programs for patients with complex conditions and lower acuity. We conclude that telemonitoring for patients with complex conditions or within multidisciplinary care settings may be best operationalized through nurse-led models of care.Trial RegistrationClinicalTrials.gov NCT03127852; https://clinicaltrials.gov/ct2/show/NCT03127852International Registered Report Identifier (IRRID)RR2-10.2196/resprot.8367

Introduction Digital health tools may be effective in engaging solid organ transplant (SOT) recipients in physical activity (PA). This study examined the perspectives of SOT recipients regarding PA, and desired features for digital health tools. Methods Semi-structured interviews were used to explore perspectives of SOT recipients about barriers and motivators to physical activity, and core features of a digital health tool to support PA. Interviews were analyzed via thematic analysis. Results Participants included 21 SOT recipients (11 men, 10 women, 21-78 years, 1.5-16 years post-transplant) from various organ groups (4 heart, 5 kidney, 5 liver, 3 lung, and 4 multi-organ). Barriers to PA included risk aversion, managing non-linear health trajectories, physical limitations and lack of access to appropriate fitness training. Facilitators of PA included desire to live long and healthy lives, renewed physical capabilities, access to appropriate fitness guidelines and facilities. Desired features of a digital health tool included a reward system, affordability, integration of multiple functions, and the ability to selectively share information with healthcare professionals and peers. Conclusions SOT recipients identified the desired features of a digital health tool, which may be incorporated into future designs of digital and mobile health applications to support PA in SOT recipients. This article is protected by copyright. All rights reserved.

IntroductionProstate cancer (PCa) is the most common cancer in Canadian men. Current models of survivorship care are no longer adequate to address the chronic and complex survivorship needs of patients today. Virtual care models for cancer survivorship have recently been associated with comparable clinical outcomes and lower costs to traditional follow-up care, with patients favouring off-site and on-demand visits. Building on their viability, our research group conceived the Ned Clinic—a virtual PCa survivorship model that provides patients with access to lab results, collects patient-reported outcomes, alerts clinicians to emerging issues, and promotes patient self-care. Despite the promise of the Ned Clinic, the model remains limited by its dependence on oncology specialists, lack of an autonomous triage algorithm, and has only been implemented among PCa survivors living in Ontario.Methods and analysisOur programme of research comprises two main research objectives: (1) to evaluate the process and cost of implementing and sustaining five nurse-led virtual PCa survivorship clinics in three provinces across Canada and identify barriers and facilitators to implementation success and (2) to assess the impact of these virtual clinics on implementation and effectiveness outcomes of enrolled PCa survivors. The design phase will involve developing an autonomous triage algorithm and redesigning the Ned Clinic towards a nurse-led service model. Site-specific implementation plans will be developed to deploy a localised nurse-led virtual clinic at each centre. Effectiveness will be evaluated using a historical control study comparing the survivorship outcomes of 300 PCa survivors enrolled in the Ned Clinic with 300 PCa survivors receiving traditional follow-up care.Ethics and disseminationAppropriate site-specific ethics approval will be secured prior to each research phase. Knowledge translation efforts will include diffusion, dissemination, and application approaches to ensure that knowledge is translated to both academic and lay audiences.

BACKGROUND Recent shifts to telemedicine and remote patient monitoring demonstrate the potential for new technology to transform health systems; yet, methods to design for inclusion and resilience are lacking. OBJECTIVE The aim of this study is to design and implement a participatory framework to produce effective health care solutions through co-design with diverse stakeholders. METHODS We developed a design framework to cocreate solutions to locally prioritized health and communication problems focused on cancer care. The framework is premised on the framing and discovery of problems through community engagement and lead-user innovation with the hypothesis that diversity and inclusion in the co-design process generate more innovative and resilient solutions. Discovery, design, and development were implemented through structured phases with design studios at various locations in urban and rural Kentucky, including Appalachia, each building from prior work. In the final design studio, working prototypes were developed and tested. Outputs were assessed using the System Usability Scale as well as semistructured user feedback. RESULTS We co-designed, developed, and tested a mobile app (myPath) and service model for distress surveillance and cancer care coordination following the LAUNCH (Linking and Amplifying User-Centered Networks through Connected Health) framework. The problem of awareness, navigation, and communication through cancer care was selected by the community after framing areas for opportunity based on significant geographic disparities in cancer and health burden resource and broadband access. The codeveloped digital myPath app showed the highest perceived combined usability (mean 81.9, SD 15.2) compared with the current gold standard of distress management for patients with cancer, the paper-based National Comprehensive Cancer Network Distress Thermometer (mean 74.2, SD 15.8). Testing of the System Usability Scale subscales showed that the myPath app had significantly better usability than the paper Distress Thermometer (t63=2.611; P=.01), whereas learnability did not differ between the instruments (t63=–0.311; P=.76). Notable differences by patient and provider scoring and feedback were found. CONCLUSIONS Participatory problem definition and community-based co-design, design-with methods, may produce more acceptable and effective solutions than traditional design-for approaches.

There is clear evidence to suggest that diabetes does not affect all populations equally. Among adults living with diabetes, those from ethnoracial minority communities—foreign-born, immigrant, refugee, and culturally marginalized—are at increased risk of poor health outcomes. Artificial intelligence (AI) is actively being researched as a means of improving diabetes management and care; however, several factors may predispose AI to ethnoracial bias. To better understand whether diabetes AI interventions are being designed in an ethnoracially equitable manner, we conducted a secondary analysis of 141 articles included in a 2018 review by Contreras and Vehi entitled “Artificial Intelligence for Diabetes Management and Decision Support: Literature Review.” Two members of our research team independently reviewed each article and selected those reporting ethnoracial data for further analysis. Only 10 articles (7.1%) were ultimately selected for secondary analysis in our case study. Of the 131 excluded articles, 118 (90.1%) failed to mention participants’ ethnic or racial backgrounds. The included articles reported ethnoracial data under various categories, including race (n=6), ethnicity (n=2), race/ethnicity (n=3), and percentage of Caucasian participants (n=1). Among articles specifically reporting race, the average distribution was 69.5% White, 17.1% Black, and 3.7% Asian. Only 2 articles reported inclusion of Native American participants. Given the clear ethnic and racial differences in diabetes biomarkers, prevalence, and outcomes, the inclusion of ethnoracial training data is likely to improve the accuracy of predictive models. Such considerations are imperative in AI-based tools, which are predisposed to negative biases due to their black-box nature and proneness to distributional shift. Based on our findings, we propose a short questionnaire to assess ethnoracial equity in research describing AI-based diabetes interventions. At this unprecedented time in history, AI can either mitigate or exacerbate disparities in health care. Future accounts of the infancy of diabetes AI must reflect our early and decisive action to confront ethnoracial inequities before they are coded into our systems and perpetuate the very biases we aim to eliminate. If we take deliberate and meaningful steps now toward training our algorithms to be ethnoracially inclusive, we can architect innovations in diabetes care that are bound by the diverse fabric of our society.

Key Points Question Can virtual care (VC) be rapidly implemented across a tertiary center during the coronavirus disease 2019 (COVID-19) pandemic, and what are service capacity and quality outcomes? Findings This cohort study of 22 085 VC visits at a single cancer center suggests feasibility of an agile service design process for implementation of VC at scale. This approach preserved outpatient caseloads and maintained care quality in all 6 care-quality domains of care quality laid out by the Institute of Medicine while rendering high patient and practitioner satisfaction. Meaning These data support the value proposition of VC to safeguard system capacity, while minimizing the disruption to patient care during a pandemic., Importance The coronavirus disease 2019 (COVID-19) pandemic has burdened health care resources and disrupted care of patients with cancer. Virtual care (VC) represents a potential solution. However, few quantitative data support its rapid implementation and positive associations with service capacity and quality. Objective To examine the outcomes of a cancer center–wide virtual care program in response to the COVID-19 pandemic. Design, Setting, and Participants This cohort study applied a hospitalwide agile service design to map gaps and develop a customized digital solution to enable at-scale VC across a publicly funded comprehensive cancer center. Data were collected from a high-volume cancer center in Ontario, Canada, from March 23 to May 22, 2020. Main Outcomes and Measures Outcome measures were care delivery volumes, quality of care, patient and practitioner experiences, and cost savings to patients. Results The VC solution was developed and launched 12 days after the declaration of the COVID-19 pandemic. A total of 22 085 VC visits (mean, 514 visits per day) were conducted, comprising 68.4% (range, 18.8%-100%) of daily visits compared with 0.8% before launch (P, This cohort study of a publicly funded comprehensive cancer center examines the outcomes of a cancer center–wide virtual care program in response to the COVID-19 pandemic.

Background Indigenous populations have remained strong and resilient in maintaining their unique culture and values, despite centuries of colonial oppression. Unfortunately, a consequential result of facing years of adversity has led Indigenous populations to experience a disproportionate level of poorer health outcomes compared to non-Indigenous populations. Specifically, the rate of Indigenous chronic disease prevalence has significantly increased in the last decade. Many of the unique issues Indigenous populations experience are deeply rooted in their colonial history and the intergenerational traumas that has subsequently impacted their physical, mental, emotional and spiritual well-being. With this, to better improve Indigenous health outcomes, understanding the local context of their challenges is key. Studies have begun to use modes of community engagement to initiate Indigenous partnerships and design chronic disease-based interventions. However, with the lack of a methodological guideline regarding the appropriate level of community engagement to be used, there is concern that many interventions will continue to fall short in meeting community needs. Objective The objective of this study was to investigate the how various community engagement strategies have been used to design and/or implement interventions for Indigenous populations with chronic disease. Methods A scoping review guided by the methods outlined by Arksey and O’Malley was conducted. A comprehensive search was completed by two reviewers in five electronic databases using keywords related to community engagement, Indigenous health and chronic disease. Studies were reviewed using a descriptive-analytical narrative method and data was categorized into thematic groups reflective of the main findings. Results We identified 23 articles that met the criteria for this scoping review. The majority of the studies included the use a participatory research model and the procurement of study approval. However, despite the claimed use of participatory research methods, only 6 studies had involved community members to identify the area of priority and only five had utilized Indigenous interview styles to promote meaningful feedback. Adapting for the local cultural context and the inclusion of community outreach were identified as the key themes from this review. Conclusion Many studies have begun to adopt community engagement strategies to better meet the needs of Indigenous Peoples. With the lack of a clear guideline to approach Indigenous-based participatory research, we recommend that researchers focus on 1) building partnerships, 2) obtaining study approval and 3) adapting interventions to the local context.

BACKGROUND The emergence of genetic and genomic sequencing approaches for pediatric patients has raised questions about the genomic health literacy levels, attitudes toward receiving genomic information, and use of this information to inform treatment decisions by pediatric patients and their parents. However, the methods to educate pediatric patients and their parents about genomic concepts through digital health interventions have not been well-established. OBJECTIVE The primary objective of this scoping review is to investigate the current levels of genomic health literacy and the attitudes toward receiving genomic information among pediatric patients and their parents. The secondary aim is to investigate patient education interventions that aim to measure and increase genomic health literacy among pediatric patients and their parents. The findings from this review will be used to inform future digital health interventions for patient education. METHODS A scoping review using PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines and protocols was completed using the following databases: MEDLINE, Embase, CINAHL, and Scopus. Our search strategy included genomic information inclusive of all genetic and genomic terms, pediatrics, and patient education. Inclusion criteria included the following: the study included genetic, genomic, or a combination of genetic and genomic information; the study population was pediatric (children and adolescents RESULTS Of the 4618 studies, 14 studies (n=6, 43% qualitative, n=6, 43% mixed methods, and n=2, 14% quantitative) were included. Key findings were based on the following 6 themes: knowledge of genomic concepts, use of the internet and social media for genomic information, use of genomic information for decision-making, hopes and attitudes toward receiving genomic information, experiences with genetic counseling, and interventions to improve genomic knowledge. CONCLUSIONS This review identified that older age is related to the capacity of understanding genomic concepts, increased genomic health literacy levels, and the perceived ability to participate in decision-making related to genomic information. In addition, internet-searching plays a major role in obtaining genomic information and filling gaps in communication with health care providers. However, little is known about the capacity of pediatric patients and their parents to understand genomic information and make informed decisions based on the genomic information obtained. More research is required to inform digital health interventions and to leverage the leading best practices to educate these genomic concepts.

Background Recent shifts to telemedicine and remote patient monitoring demonstrate the potential for new technology to transform health systems; yet, methods to design for inclusion and resilience are lacking. Objective The aim of this study is to design and implement a participatory framework to produce effective health care solutions through co-design with diverse stakeholders. Methods We developed a design framework to cocreate solutions to locally prioritized health and communication problems focused on cancer care. The framework is premised on the framing and discovery of problems through community engagement and lead-user innovation with the hypothesis that diversity and inclusion in the co-design process generate more innovative and resilient solutions. Discovery, design, and development were implemented through structured phases with design studios at various locations in urban and rural Kentucky, including Appalachia, each building from prior work. In the final design studio, working prototypes were developed and tested. Outputs were assessed using the System Usability Scale as well as semistructured user feedback. Results We co-designed, developed, and tested a mobile app (myPath) and service model for distress surveillance and cancer care coordination following the LAUNCH (Linking and Amplifying User-Centered Networks through Connected Health) framework. The problem of awareness, navigation, and communication through cancer care was selected by the community after framing areas for opportunity based on significant geographic disparities in cancer and health burden resource and broadband access. The codeveloped digital myPath app showed the highest perceived combined usability (mean 81.9, SD 15.2) compared with the current gold standard of distress management for patients with cancer, the paper-based National Comprehensive Cancer Network Distress Thermometer (mean 74.2, SD 15.8). Testing of the System Usability Scale subscales showed that the myPath app had significantly better usability than the paper Distress Thermometer (t63=2.611; P=.01), whereas learnability did not differ between the instruments (t63=–0.311; P=.76). Notable differences by patient and provider scoring and feedback were found. Conclusions Participatory problem definition and community-based co-design, design-with methods, may produce more acceptable and effective solutions than traditional design-for approaches.

UNSTRUCTURED There is clear evidence to suggest that diabetes does not affect all populations equally. Among adults living with diabetes, those from ethnoracial minority communities—foreign-born, immigrant, refugee, and culturally marginalized—are at increased risk of poor health outcomes. Artificial intelligence (AI) is actively being researched as a means of improving diabetes management and care; however, several factors may predispose AI to ethnoracial bias. To better understand whether diabetes AI interventions are being designed in an ethnoracially equitable manner, we conducted a secondary analysis of 141 articles included in a 2018 review by Contreras and Vehi entitled “Artificial Intelligence for Diabetes Management and Decision Support: Literature Review.” Two members of our research team independently reviewed each article and selected those reporting ethnoracial data for further analysis. Only 10 articles (7.1%) were ultimately selected for secondary analysis in our case study. Of the 131 excluded articles, 118 (90.1%) failed to mention participants’ ethnic or racial backgrounds. The included articles reported ethnoracial data under various categories, including race (n=6), ethnicity (n=2), race/ethnicity (n=3), and percentage of Caucasian participants (n=1). Among articles specifically reporting race, the average distribution was 69.5% White, 17.1% Black, and 3.7% Asian. Only 2 articles reported inclusion of Native American participants. Given the clear ethnic and racial differences in diabetes biomarkers, prevalence, and outcomes, the inclusion of ethnoracial training data is likely to improve the accuracy of predictive models. Such considerations are imperative in AI-based tools, which are predisposed to negative biases due to their black-box nature and proneness to distributional shift. Based on our findings, we propose a short questionnaire to assess ethnoracial equity in research describing AI-based diabetes interventions. At this unprecedented time in history, AI can either mitigate or exacerbate disparities in health care. Future accounts of the infancy of diabetes AI must reflect our early and decisive action to confront ethnoracial inequities before they are coded into our systems and perpetuate the very biases we aim to eliminate. If we take deliberate and meaningful steps now toward training our algorithms to be ethnoracially inclusive, we can architect innovations in diabetes care that are bound by the diverse fabric of our society.

Introduction: As we progress to an era when patient autonomy and shared decision-making are highly valued, there is a need to also have effective patient-centered communication tools. Radiology reports are designed for clinicians and can be very technical and difficult for patients to understand. It is important for patients to understand their magnetic resonance imaging (MRI) report in order to make an informed treatment decision with their physician. Therefore, we aimed to create a patient-centered prostate MRI report in order to give our patients a better understanding of their clinical condition. Methods: A prototype patient-centered radiology report (PACERR) was created by identifying items to include based on opinions sought from a group of patients undergoing prostate MRI and medical experts. Data was collected in semi-structured interviews using a salient belief question. A prototype PACERR was created in collaboration with human factors engineering and design, medical imaging, biomedical informatics, and cancer patient education groups. Results: Fifteen patients and eight experts from urology, radiation oncology, radiology, and nursing participated in this study. Patients were particularly interested to have a report with laymen terms, concise language, contextualization of values, definitions of medical terms, and next course of action. Everyone believed the report should include the risk of MRI findings actually being cancer in the subsequent biopsy. Conclusions: A prostate MRI PACERR has been developed to communicate the most important findings relevant to decision-making in prostate cancer using patient-oriented design principles. The ability of this tool to improve patient knowledge and communication will be explored.