Implementing and Evaluating a National Integrated Digital Registry and Clinical Decision Support System in Early Intervention in Psychosis Services (Early Psychosis Informatics Into Care): Co-Designed Protocol.

BACKGROUND: Early intervention in psychosis (EIP) services are nationally mandated in England to provide multidisciplinary care to people experiencing first-episode psychosis, which disproportionately affects deprived and ethnic minority youth. Quality of service provision varies by region, and people from historically underserved populations have unequal access. In other disease areas, including stroke and dementia, national digital registries coupled with clinical decision support systems (CDSSs) have revolutionized the delivery of equitable, evidence-based interventions to transform patient outcomes and reduce population-level disparities in care. Given psychosis is ranked the third most burdensome mental health condition by the World Health Organization, it is essential that we achieve the same parity of health improvements. OBJECTIVE: This paper reports the protocol for the program development phase of this study, in which we aimed to co-design and produce an evidence-based, stakeholder-informed framework for the building, implementation, piloting, and evaluation of a national integrated digital registry and CDSS for psychosis, known as EPICare (Early Psychosis Informatics into Care). METHODS: We conducted 3 concurrent work packages, with reciprocal knowledge exchange between each. In work package 1, using a participatory co-design framework, key stakeholders (clinicians, academics, policy makers, and patient and public contributors) engaged in 4 workshops to review, refine, and identify a core set of essential and desirable measures and features of the EPICare registry and CDSS. Using a modified Delphi approach, we then developed a consensus of data priorities. In work package 2, we collaborated with National Health Service (NHS) informatics teams to identify relevant data currently captured in electronic health records, understand data retrieval methods, and design the software architecture and data model to inform future implementation. In work package 3, observations of stakeholder workshops and individual interviews with representative stakeholders (n=10) were subject to interpretative qualitative analysis, guided by normalization process theory, to identify factors likely to influence the adoption and implementation of EPICare into routine practice. RESULTS: Stage 1 of the EPICare study took place between December 2021 and September 2022. The next steps include stage 2 building, piloting, implementation, and evaluation of EPICare in 5 demonstrator NHS Trusts serving underserved and diverse populations with substantial need for EIP care in England. If successful, this will be followed by stage 3, in which we will seek NHS adoption of EPICare for rollout to all EIP services in England. CONCLUSIONS: By establishing a multistakeholder network and engaging them in an iterative co-design process, we have identified essential and desirable elements of the EPICare registry and CDSS; proactively identified and minimized potential challenges and barriers to uptake and implementation; and addressed key questions related to informatics architecture, infrastructure, governance, and integration in diverse NHS Trusts, enabling us to proceed with the building, piloting, implementation, and evaluation of EPICare. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/50177.

User engagement in a randomised controlled trial for a digital health intervention for early psychosis (Actissist 2.0 trial).

Digital Health Interventions (DHIs) can help support people with mental health problems. Achieving satisfactory levels of patient engagement is a crucial, yet often underexplored, pre-requisite for health improvement. Actissist is a co-produced DHI delivered via a smartphone app for people with early psychosis, based on Cognitive Behaviour Therapy principles. This study describes and compares engagement patterns among participants in the two arms of the Actissist 2.0 randomised controlled trial. Engagement frequency and duration were measured among participants using the Actissist app in the intervention arm (n = 87) and the ClinTouch symptom monitoring only app used as the control condition (n = 81). Overall, 47.1 % of Actissist and 45.7 % of ClinTouch users completed at least a third of scheduled alerts while active in the study. The mean frequency (77.1 versus 60.2 total responses) and the median duration (80 versus 75 days until last response) of engagement were not significantly higher among Actissist users compared to ClinTouch users. Older age, White ethnicity, using their own smartphone device and, among Actissist users, an increased sense of therapeutic alliance were significantly associated with increased engagement. Through exploiting detailed usage data, this study identifies possible participant-level and DHI-level predictors of engagement to inform the practical implementation of future DHIs.

IMI-Management and Investigation of High Myopia in Infants and Young Children.

Purpose: The purpose of this study was to evaluate the epidemiology, etiology, clinical assessment, investigation, management, and visual consequences of high myopia (≤-6 diopters [D]) in infants and young children. Findings: High myopia is rare in pre-school children with a prevalence less than 1%. The etiology of myopia in such children is different than in older children, with a high rate of secondary myopia associated with prematurity or genetic causes. The priority following the diagnosis of high myopia in childhood is to determine whether there is an associated medical diagnosis that may be of greater overall importance to the health of the child through a clinical evaluation that targets the commonest features associated with syndromic forms of myopia. Biometric evaluation (including axial length and corneal curvature) is important to distinguishing axial myopia from refractive myopia associated with abnormal development of the anterior segment. Additional investigation includes ocular imaging, electrophysiological tests, genetic testing, and involvement of pediatricians and clinical geneticists is often warranted. Following investigation, optical correction is essential, but this may be more challenging and complex than in older children. Application of myopia control interventions in this group of children requires a case-by-case approach due to the lack of evidence of efficacy and clinical heterogeneity of high myopia in young children. Conclusions: High myopia in infants and young children is a rare condition with a different pattern of etiology to that seen in older children. The clinical management of such children, in terms of investigation, optical correction, and use of myopia control treatments, is a complex and often multidisciplinary process.

Effectiveness of Public Health Digital Surveillance Systems for Infectious Disease Prevention and Control at Mass Gatherings: Systematic Review.

BACKGROUND: Mass gatherings (MGs; eg, religious, sporting, musical, sociocultural, and other occasions that draw large crowds) pose public health challenges and concerns related to global health. A leading global concern regarding MGs is the possible importation and exportation of infectious diseases as they spread from the attendees to the general population, resulting in epidemic outbreaks. Governments and health authorities use technological interventions to support public health surveillance and prevent and control infectious diseases. OBJECTIVE: This study aims to review the evidence on the effectiveness of public health digital surveillance systems for infectious disease prevention and control at MG events. METHODS: A systematic literature search was conducted in January 2022 using the Ovid MEDLINE, Embase, CINAHL, and Scopus databases to examine relevant articles published in English up to January 2022. Interventional studies describing or evaluating the effectiveness of public health digital surveillance systems for infectious disease prevention and control at MGs were included in the analysis. Owing to the lack of appraisal tools for interventional studies describing and evaluating public health digital surveillance systems at MGs, a critical appraisal tool was developed and used to assess the quality of the included studies. RESULTS: In total, 8 articles were included in the review, and 3 types of MGs were identified: religious (the Hajj and Prayagraj Kumbh), sporting (the Olympic and Paralympic Games, the Federation International Football Association World Cup, and the Micronesian Games), and cultural (the Festival of Pacific Arts) events. In total, 88% (7/8) of the studies described surveillance systems implemented at MG events, and 12% (1/8) of the studies described and evaluated an enhanced surveillance system that was implemented for an event. In total, 4 studies reported the implementation of a surveillance system: 2 (50%) described the enhancement of the system that was implemented for an event, 1 (25%) reported a pilot implementation of a surveillance system, and 1 (25%) reported an evaluation of an enhanced system. The types of systems investigated were 2 syndromic, 1 participatory, 1 syndromic and event-based, 1 indicator- and event-based, and 1 event-based surveillance system. In total, 62% (5/8) of the studies reported timeliness as an outcome generated after implementing or enhancing the system without measuring its effectiveness. Only 12% (1/8) of the studies followed the Centers for Disease Control and Prevention guidelines for evaluating public health surveillance systems and the outcomes of enhanced systems based on the systems' attributes to measure their effectiveness. CONCLUSIONS: On the basis of the review of the literature and the analysis of the included studies, there is limited evidence of the effectiveness of public health digital surveillance systems for infectious disease prevention and control at MGs because of the absence of evaluation studies.

Examining public views on decentralised health data sharing.

In recent years, researchers have begun to explore the use of Distributed Ledger Technologies (DLT), also known as blockchain, in health data sharing contexts. However, there is a significant lack of research that examines public attitudes towards the use of this technology. In this paper, we begin to address this issue and present results from a series of focus groups which explored public views and concerns about engaging with new models of personal health data sharing in the UK. We found that participants were broadly in favour of a shift towards new decentralised models of data sharing. Retaining 'proof' of health information stored about patients and the capacity to provide permanent audit trails, enabled by immutable and transparent properties of DLT, were regarded as particularly valuable for our participants and prospective data custodians. Participants also identified other potential benefits such as supporting people to become more health data literate and enabling patients to make informed decisions about how their data was shared and with whom. However, participants also voiced concerns about the potential to further exacerbate existing health and digital inequalities. Participants were also apprehensive about the removal of intermediaries in the design of personal health informatics systems.

Interventions Aimed at Enhancing Health Care Providers' Behavior Toward the Prescription of Mobile Health Apps: Systematic Review.

BACKGROUND: Mobile health (mHealth) apps have great potential to support the management of chronic conditions. Despite widespread acceptance of mHealth apps by the public, health care providers (HCPs) are reluctant to prescribe or recommend such apps to their patients. OBJECTIVE: This study aimed to classify and evaluate interventions aimed at encouraging HCPs to prescribe mHealth apps. METHODS: A systematic literature search was conducted to identify studies published from January 1, 2008, to August 5, 2022, using 4 electronic databases: MEDLINE, Scopus, CINAHL, and PsycINFO. We included studies that evaluated interventions encouraging HCPs to prescribe mHealth apps. Two review authors independently assessed the eligibility of the studies. The "National Institute of Health's quality assessment tool for before-and-after (pretest-posttest design) studies with no control group" and "the mixed methods appraisal tool (MMAT)" were used to assess the methodological quality. Owing to high levels of heterogeneity between interventions, measures of practice change, specialties of HCPs, and modes of delivery, we conducted a qualitative analysis. We adopted the behavior change wheel as a framework for classifying the included interventions according to intervention functions. RESULTS: In total, 11 studies were included in this review. Most of the studies reported positive findings, with improvements in a number of outcomes, including increased knowledge of mHealth apps among clinicians, improved self-efficacy or confidence in prescribing, and an increased number of mHealth app prescriptions. On the basis of the behavior change wheel, 9 studies reported elements of environmental restructuring such as providing HCPs with lists of apps, technological systems, time, and resources. Furthermore, 9 studies included elements of education, particularly workshops, class lectures, individual sessions with HCPs, videos, or toolkits. Furthermore, training was incorporated in 8 studies using case studies or scenarios or app appraisal tools. Coercion and restriction were not reported in any of the interventions included. The quality of the studies was high in relation to the clarity of aims, interventions, and outcomes but weaker in terms of sample size, power calculations, and duration of follow-up. CONCLUSIONS: This study identified interventions to encourage app prescriptions by HCPs. Recommendations for future research should consider previously unexplored intervention functions such as restrictions and coercion. The findings of this review can help inform mHealth providers and policy makers regarding the key intervention strategies impacting mHealth prescriptions and assist them in making informed decisions to encourage this adoption.

Accuracy of a tool to prioritise patients awaiting elective surgery: an implementation report.

STUDY OBJECTIVE: The objective of this study was to evaluate the accuracy of a new elective surgery clinical decision support system, the 'Patient Tacking List' (PTL) tool (C2-Ai(c)) through receiver operating characteristic (ROC) analysis. METHODS: We constructed ROC curves based on risk predictions produced by the tool and compared these with actual patient outcomes on a retrospective cohort of patients awaiting elective surgery. RESULTS: A total of 11 837 patients were included across three National Health Service (NHS) hospitals in England. ROC analysis revealed an area under the curve of 0.95 (95% CI 0.92 to 0.98) for mortality and 0.8 (95% CI 0.78 to 0.82) for complications. DISCUSSION: The PTL tool was successfully integrated into existing data infrastructures, allowing real-time clinical decision support and a low barrier to implementation. ROC analysis demonstrated a high level of accuracy to predict the risk of mortality and complications after elective surgery. As such, it may be a valuable adjunct in prioritising patients on surgical waiting lists.Health systems, such as the NHS in England, must look at innovative methods to prioritise patients awaiting surgery in order to best use limited resources. Clinical decision support tools, such as the PTL tool, can improve prioritisation and thus positively impact clinical care and patient outcomes. CONCLUSIONS: The high level of accuracy for predicating mortality and complications after elective surgery using the PTL tool indicates the potential for clinical decision support tools to help tackle rising waiting lists and improve surgical planning.

Sepsis and Mortality Prediction in Very Low Birth Weight Infants: Analysis of HeRO and nSOFA.

OBJECTIVE: Scores to predict sepsis or define sepsis severity could improve care for very low birth weight (VLBW) infants. The heart rate characteristics (HRC) index (HeRO score) was developed as an early warning system for late-onset sepsis (LOS), and also rises before necrotizing enterocolitis (NEC). The neonatal sequential organ failure assessment (nSOFA) was developed to predict sepsis-associated mortality using respiratory, hemodynamic, and hematologic data. The aim of this study was to analyze the HRC index and nSOFA near blood cultures in VLBW infants relative to diagnosis and sepsis-associated mortality. STUDY DESIGN: Retrospective, single-center study of VLBW infants from 2011 to 2019. We analyzed HRC index and nSOFA around blood cultures diagnosed as LOS/NEC. In a subgroup of the cohort, we analyzed HRC and nSOFA near the first sepsis-like illness (SLI) or sepsis ruled-out (SRO) compared with LOS/NEC. We compared scores by diagnosis and mortality during treatment. RESULTS: We analyzed 179 LOS/NEC, 93 SLI, and 96 SRO blood culture events. In LOS/NEC, the HRC index increased before the blood culture, while nSOFA increased at the time of culture. Both scores were higher in nonsurvivors compared with survivors and in LOS/NEC compared with SRO. The nSOFA 12 hours after the time of blood culture predicted mortality during treatment better than any other time point analyzed (area under the curve 0.91). CONCLUSION: The HRC index provides earlier warning of imminent sepsis, whereas nSOFA after blood culture provides better prediction of mortality. KEY POINTS: · The HRC index and nSOFA provide complementary information on sepsis risk and sepsis-related mortality risk.. · This study adds to existing literature evaluating these risk scores independently by analyzing them together and in cases of not only proven but also suspected infections.. · The impact of combining risk models could be improved outcomes for premature infants..

KidneyCloud: A Clinically-Codesigned Solution to Support Kidney Services with Assessing Patients for Transplantation.

There is a need for IT systems that support the complex needs of data management in kidney transplantation. The KidneyCloud project aims to inform a transplant-specific digital solution by exploring patient pathways and data journeys. This paper reports on the early prototyping of the KidneyCloud clinician interface using an iterative codesign methodology. User workshops identified that for making clinical decisions and adding patients to the national waiting list transplant teams relied heavily on manual processes to access data across systems and organisations. Based on the requirements gathered, a prototype interface was designed to provide a unified view on the available patient data, which aligned with clinical workflows. Interactive prototype screens allowed users to gain hands-on experience and provide rich real-time feedback. This informed the necessary functionalities of the interface, but also helped us understand the capabilities required of the back-end solution.

Digital smartphone intervention to recognise and manage early warning signs in schizophrenia to prevent relapse: the EMPOWER feasibility cluster RCT.

BACKGROUND: Relapse is a major determinant of outcome for people with a diagnosis of schizophrenia. Early warning signs frequently precede relapse. A recent Cochrane Review found low-quality evidence to suggest a positive effect of early warning signs interventions on hospitalisation and relapse. OBJECTIVE: How feasible is a study to investigate the clinical effectiveness and cost-effectiveness of a digital intervention to recognise and promptly manage early warning signs of relapse in schizophrenia with the aim of preventing relapse? DESIGN: A multicentre, two-arm, parallel-group cluster randomised controlled trial involving eight community mental health services, with 12-month follow-up. SETTINGS: Glasgow, UK, and Melbourne, Australia. PARTICIPANTS: Service users were aged > 16 years and had a schizophrenia spectrum disorder with evidence of a relapse within the previous 2 years. Carers were eligible for inclusion if they were nominated by an eligible service user. INTERVENTIONS: The Early signs Monitoring to Prevent relapse in psychosis and prOmote Wellbeing, Engagement, and Recovery (EMPOWER) intervention was designed to enable participants to monitor changes in their well-being daily using a mobile phone, blended with peer support. Clinical triage of changes in well-being that were suggestive of early signs of relapse was enabled through an algorithm that triggered a check-in prompt that informed a relapse prevention pathway, if warranted. MAIN OUTCOME MEASURES: The main outcomes were feasibility of the trial and feasibility, acceptability and usability of the intervention, as well as safety and performance. Candidate co-primary outcomes were relapse and fear of relapse. RESULTS: We recruited 86 service users, of whom 73 were randomised (42 to EMPOWER and 31 to treatment as usual). Primary outcome data were collected for 84% of participants at 12 months. Feasibility data for people using the smartphone application (app) suggested that the app was easy to use and had a positive impact on motivations and intentions in relation to mental health. Actual app usage was high, with 91% of users who completed the baseline period meeting our a priori criterion of acceptable engagement (> 33%). The median time to discontinuation of > 33% app usage was 32 weeks (95% confidence interval 14 weeks to ∞). There were 8 out of 33 (24%) relapses in the EMPOWER arm and 13 out of 28 (46%) in the treatment-as-usual arm. Fewer participants in the EMPOWER arm had a relapse (relative risk 0.50, 95% confidence interval 0.26 to 0.98), and time to first relapse (hazard ratio 0.32, 95% confidence interval 0.14 to 0.74) was longer in the EMPOWER arm than in the treatment-as-usual group. At 12 months, EMPOWER participants were less fearful of having a relapse than those in the treatment-as-usual arm (mean difference -4.29, 95% confidence interval -7.29 to -1.28). EMPOWER was more costly and more effective, resulting in an incremental cost-effectiveness ratio of £3041. This incremental cost-effectiveness ratio would be considered cost-effective when using the National Institute for Health and Care Excellence threshold of £20,000 per quality-adjusted life-year gained. LIMITATIONS: This was a feasibility study and the outcomes detected cannot be taken as evidence of efficacy or effectiveness. CONCLUSIONS: A trial of digital technology to monitor early warning signs that blended with peer support and clinical triage to detect and prevent relapse is feasible. FUTURE WORK: A main trial with a sample size of 500 (assuming 90% power and 20% dropout) would detect a clinically meaningful reduction in relapse (relative risk 0.7) and improvement in other variables (effect sizes 0.3-0.4). TRIAL REGISTRATION: This trial is registered as ISRCTN99559262. FUNDING: This project was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 26, No. 27. See the NIHR Journals Library website for further project information. Funding in Australia was provided by the National Health and Medical Research Council (APP1095879).

WHAT WAS THE PROBLEM?: Relapse is a considerable problem for people with a diagnosis of schizophrenia. Relapse can be predicted by early warning signs that are unique to the person. They include withdrawal, fear and paranoia. WHAT WAS THE QUESTION?: Is it possible to investigate the effectiveness of an intervention to recognise and promptly manage early warning signs of relapse in schizophrenia with the aim of preventing relapse? WHAT DID WE DO?: We spoke with 88 mental health staff, 40 carers and 21 service users before we designed a system that used a mobile phone to help people monitor early warning signs. We included peer support to help people using the system reflect on their experiences. We hoped the overall system, called EMPOWER, would help people to be more in charge of their mental health. After consenting 86 people to the study, we were able to randomly assign 73 people either to use the EMPOWER system (42 people) or to receive their normal treatment alone (31 people). We used research measures over 1 year to help us better understand people's experiences. We also involved carers (for example family or friends) and mental health service providers in the research. WHAT DID WE FIND?: We found that it was possible to recruit people to the study and to gather research data. We also found that people used the EMPOWER system and found it acceptable. We found that those who used EMPOWER had a lower rate of relapse over 12 months than people who did not. They were also less likely to be fearful of relapse. We found that EMPOWER was likely to be cost-effective. WHAT DOES THIS MEAN?: This means that a study to investigate the effectiveness of a system to recognise and respond to early warning signs of relapse in schizophrenia is possible.

The evaluation of digital transformation in renal transplantation in the United Kingdom: A national interview study.

BACKGROUND: Care pathways in renal transplantation involve multi-speciality coordination and administration of clinical data across organisational boundaries. The potential for information technology (IT) to support the service through data management, communication and national registration has been reported. However, no previous national-level evaluation on the current state of digital transformation has been undertaken. METHODS: We undertook structured phone interviews with transplant coordinators at all 23 transplant centres in the United Kingdom (UK). The interview covered topics including clinical workflows during transplant referral and current data management processes. Based on established frameworks, we elicited IT capabilities, readiness and infrastructure to evaluate the digital maturity at each centre. We analysed interview data thematically and synthesised results across centres to identify common challenges and inform recommendations. RESULTS: Transplant coordinators across centres reported similar care pathways with patients being referred by to transplant centres from regional renal referral centres. Analysis revealed that a key challenge revolved around the inability to access data across organisational boundaries. This resulted in dependence on postal or electronic mail to transfer clinical data, such as blood results or medication lists. Most centres had a hospital-wide electronic medical record, which was unable to meet the specific workflow requirements of transplantation. This was primarily because implemented solutions were unable to provide a single unified view of transplant-related data. As a result, transplant coordinators reported several workarounds to manage clinical data, such as paper folders, Excel© sheets and scanned files on hospital shared drives. CONCLUSIONS: Existing front-line IT solutions and wider infrastructure did not support the requirements of care pathways in renal transplantation. Digital transformation should focus on the need to surface patient data across organisational boundaries and provide specific views of data that complement the clinical workflow. This study highlights how regional interoperability remains a major priority to support multi-centre specialist services.

The EMPOWER blended digital intervention for relapse prevention in schizophrenia: a feasibility cluster randomised controlled trial in Scotland and Australia.

BACKGROUND: Early warning signs monitoring by service users with schizophrenia has shown promise in preventing relapse but the quality of evidence is low. We aimed to establish the feasibility of undertaking a definitive randomised controlled trial to determine the effectiveness of a blended digital intervention for relapse prevention in schizophrenia. METHODS: This multicentre, feasibility, cluster randomised controlled trial aimed to compare Early signs Monitoring to Prevent relapse in psychosis and prOmote Well-being, Engagement, and Recovery (EMPOWER) with treatment as usual in community mental health services (CMHS) in Glasgow and Melbourne. CMHS were the unit of randomisation, selected on the basis of those that probably had five or more care coordinators willing to participate. Participants were eligible if they were older than 16 years, had a schizophrenia or related diagnosis confirmed via case records, were able to provide informed consent, had contact with CMHS, and had had a relapse within the previous 2 years. Participants were randomised within stratified clusters to EMPOWER or to continue their usual approach to care. EMPOWER blended a smartphone for active monitoring of early warning signs with peer support to promote self-management and clinical triage to promote access to relapse prevention. Main outcomes were feasibility, acceptability, usability, and safety, which was assessed through face-to-face interviews. App usage was assessed via the smartphone and self-report. Primary end point was 12 months. Participants, research assistants and other team members involved in delivering the intervention were not masked to treatment conditions. Assessment of relapse was done by an independent adjudication panel masked to randomisation group. The study is registered at ISRCTN (99559262). FINDINGS: We identified and randomised eight CMHS (six in Glasgow and two in Melbourne) comprising 47 care coordinators. We recruited 86 service users between Jan 19 and Aug 8, 2018; 73 were randomised (42 [58%] to EMPOWER and 31 [42%] to treatment as usual). There were 37 (51%) men and 36 (49%) women. At 12 months, main outcomes were collected for 32 (76%) of service users in the EMPOWER group and 30 (97%) of service users in the treatment as usual group. Of those randomised to EMPOWER, 30 (71%) met our a priori criterion of more than 33% adherence to daily monitoring that assumed feasibility. Median time to discontinuation of these participants was 31·5 weeks (SD 14·5). There were 29 adverse events in the EMPOWER group and 25 adverse events in the treatment as usual group. There were 13 app-related adverse events, affecting 11 people, one of which was serious. Fear of relapse was lower in the EMPOWER group than in the treatment as usual group at 12 months (mean difference -7·53 (95% CI -14·45 to 0·60; Cohen's d -0·53). INTERPRETATION: A trial of digital technology to monitor early warning signs blended with peer support and clinical triage to detect and prevent relapse appears to be feasible, safe, and acceptable. A further main trial is merited. FUNDING: UK National Institute for Health Research Health Technology Assessment programme and the Australian National Health and Medical Research Council.

Non-Fungible Tokens as a Mechanism for Representing Patient Consent.

In recent years we have seen the adoption of distributed ledger technology (DLT), originally the mechanism underpinning the operation of the Bitcoin crypto currency, across a wider range of technology sectors including healthcare. DLT allows for the design of informatics systems with the properties of immutability, security, and decentralization. One recent innovation in the space has been the specification and development of Non-Fungible Tokens (NFTs). NFTs are decentralized DLT-based records that represent ownership of a unique digital asset. The predominant current use case for NFTs has been in the representation and sale of digital artwork, however the features offered by NFTs, unique-ness, immutability, transferability, and verifiability, are directly applicable to the design of health informatics systems. In this paper we explore these properties and describe a reference architecture for using NFTs as a means of representing and transferring records of patient's consent for medical data use.

Modeling Data Journeys to Inform the Digital Transformation of Kidney Transplant Services: Observational Study.

BACKGROUND: Data journey modeling is a methodology used to establish a high-level overview of information technology (IT) infrastructure in health care systems. It allows a better understanding of sociotechnical barriers and thus informs meaningful digital transformation. Kidney transplantation is a complex clinical service involving multiple specialists and providers. The referral pathway for a transplant requires the centralization of patient data across multiple IT solutions and health care organizations. At present, there is a poor understanding of the role of IT in this process, specifically regarding the management of patient data, clinical communication, and workflow support. OBJECTIVE: To apply data journey modeling to better understand interoperability, data access, and workflow requirements of a regional multicenter kidney transplant service. METHODS: An incremental methodology was used to develop the data journey model. This included review of service documents, domain expert interviews, and iterative modeling sessions. Results were analyzed based on the LOAD (landscape, organizations, actors, and data) framework to provide a meaningful assessment of current data management challenges and inform ways for IT to overcome these challenges. RESULTS: Results were presented as a diagram of the organizations (n=4), IT systems (n>9), actors (n>4), and data journeys (n=0) involved in the transplant referral pathway. The diagram revealed that all movement of data was dependent on actor interaction with IT systems and manual transcription of data into Microsoft Word (Microsoft, Inc) documents. Each actor had between 2 and 5 interactions with IT systems to capture all relevant data, a process that was reported to be time consuming and error prone. There was no interoperability within or across organizations, which led to delays as clinical teams manually transferred data, such as medical history and test results, via post or email. CONCLUSIONS: Overall, data journey modeling demonstrated that human actors, rather than IT systems, formed the central focus of data movement. The IT landscape did not complement this workflow and exerted a significant administrative burden on clinical teams. Based on this study, future solutions must consider regional interoperability and specialty-specific views of data to support multi-organizational clinical services such as transplantation.

An integrated early care pathway for autism.

In this Viewpoint, we argue for the need to reconceptualise an integrated early-care provision for autistic children in the light of their enduring support needs and relevant new findings from developmental and intervention research. This model goes beyond short-term reactive care to outline an early proactive, evidenced, developmentally phased, and scalable programme of support for autistic children and their families from the earliest opportunity, with timely access to later step-up care when needed. We also integrate this model with emerging opportunities from data science and digital health technologies as a potential facilitator of such a pathway. Building on this work, we argue that the best current autism intervention evidence can be integrated with concepts and evidence gained in the management of other enduring health conditions to support an autistic child and their family through their early development. The aim is to improve those children's social communication abilities, expand their range and flexibility of interests, and mitigate any negative impacts of sensory difficulties and restricted, repetitive behaviours on the child and their family wellbeing. The pathway solutions described could also be adapted for older adolescents and adults and could be used within the health systems of different countries, including within low-income and middle-income contexts.

Self-management intervention to reduce pulmonary exacerbations by supporting treatment adherence in adults with cystic fibrosis: a randomised controlled trial.

INTRODUCTION: Recurrent pulmonary exacerbations lead to progressive lung damage in cystic fibrosis (CF). Inhaled medications (mucoactive agents and antibiotics) help prevent exacerbations, but objectively measured adherence is low. We investigated whether a multi-component (complex) self-management intervention to support adherence would reduce exacerbation rates over 12 months. METHODS: Between October 2017 and May 2018, adults with CF (aged ≥16 years; 19 UK centres) were randomised to the intervention (data-logging nebulisers, a digital platform and behavioural change sessions with trained clinical interventionists) or usual care (data-logging nebulisers). Outcomes included pulmonary exacerbations (primary outcome), objectively measured adherence, body mass index (BMI), lung function (FEV1) and Cystic Fibrosis Questionnaire-Revised (CFQ-R). Analyses were by intent to treat over 12 months. RESULTS: Among intervention (n=304) and usual care (n=303) participants (51% female, median age 31 years), 88% completed 12-month follow-up. Mean exacerbation rate was 1.63/year with intervention and 1.77/year with usual care (adjusted ratio 0.96; 95% CI 0.83 to 1.12; p=0.64). Adjusted mean differences (95% CI) were in favour of the intervention versus usual care for objectively measured adherence (9.5% (8.6% to 10.4%)) and BMI (0.3 (0.1 to 0.6) kg/m2), with no difference for %FEV1 (1.4 (-0.2 to 3.0)). Seven CFQ-R subscales showed no between-group difference, but treatment burden reduced for the intervention (3.9 (1.2 to 6.7) points). No intervention-related serious adverse events occurred. CONCLUSIONS: While pulmonary exacerbations and FEV1 did not show statistically significant differences, the intervention achieved higher objectively measured adherence versus usual care. The adherence difference might be inadequate to influence exacerbations, though higher BMI and lower perceived CF treatment burden were observed.

WFS1 protein expression correlates with clinical progression of optic atrophy in patients with Wolfram syndrome.

BACKGROUND: Wolfram syndrome (WFS) is a rare disorder characterised by childhood-onset diabetes mellitus and progressive optic atrophy. Most patients have variants in the WFS1 gene. We undertook functional studies of WFS1 variants and correlated these with WFS1 protein expression and phenotype. METHODS: 9 patients with a clinical diagnosis of WFS were studied with quantitative PCR for markers of endoplasmic reticulum (ER) stress and immunoblotting of fibroblast protein extracts for WFS1 protein expression. Luciferase reporter assay was used to assess ATF-6 dependent unfolded protein response (UPR) activation. RESULTS: 6 patients with compound heterozygous nonsense mutations in WFS1 had no detectable WFS1 protein expression; 3 patients with missense variants had 4%, 45% and 48% WFS1 protein expression. One of these also had an OPA1 mutation and was reclassified as autosomal dominant optic atrophy-plus syndrome. There were no correlations between ER stress marker mRNA and WFS1 protein expression. ERSE-luciferase reporter indicated activation of the ATF6 branch of UPR in two patients tested. Patients with partial WFS1 expression showed milder visual acuity impairment (asymptomatic or colour blind only), compared with those with absent expression (registered severe vision impaired) (p=0.04). These differences remained after adjusting for duration of optic atrophy. CONCLUSIONS: Patients with WFS who have partial WFS1 protein expression present with milder visual impairment. This suggests a protective effect of partial WFS1 protein expression on the severity and perhaps progression of vision impairment and that therapies to increase residual WFS1 protein expression may be beneficial.

Using a learning health system to understand the mismatch between medicines supply and actual medicines use among adults with cystic fibrosis.

BACKGROUND: Studies in separate cohorts suggest possible discrepancies between inhaled medicines supplied (median 50-60%) and medicines used (median 30-40%). We performed the first study that directly compares CF medicine supply against use to identify the cost of excess medicines supply. METHODS: This cross-sectional study included participants from 12 UK adult centres with ≥1 year of continuous adherence data from data-logging nebulisers. Medicine supply was measured as medication possession ratio (MPR) for a 1-year period from the first suitable supply date. Medicine use was measured as electronic data capture (EDC) adherence over the same period. The cost of excess medicines was calculated as whole excess box(es) supplied after accounting for the discrepancy between EDC adherence and MPR with 20% contingency. RESULTS: Among 275 participants, 133 (48.4%) were females and mean age was 30 years (95% CI 29-31 years). Median EDC adherence was 57% (IQR 23-86%), median MPR was 74% (IQR 46-96%) and the discrepancy between measures was median 14% (IQR 2-29%). Even with 20% contingency, mean potential cost of excess medicines was £1,124 (95% CI £855-1,394), ranging from £183 (95% CI £29-338) for EDC adherence ≥80% to £2,017 (95% CI £1,507-2,526) for EDC adherence <50%. CONCLUSIONS: This study provides a conservative estimate of excess inhaled medicines supply cost among adults with CF in the UK. The excess supply cost was highest among those with lowest EDC adherence, highlighting the importance of adherence support and supplying medicine according to actual use. MPR provides information about medicine supply but over-estimates actual medicine use.