BACKGROUND: Precision public health (PPH) can maximize impact by targeting surveillance and interventions by temporal, spatial, and epidemiological characteristics. Although rapid diagnostic tests (RDTs) have enabled ubiquitous point-of-care testing in low-resource settings, their impact has been less than anticipated, owing in part to lack of features to streamline data capture and analysis.
OBJECTIVE: We aimed to transform the RDT into a tool for PPH by defining information and data axioms and an information utilization index (IUI); identifying design features to maximize the IUI; and producing open guidelines (OGs) for modular RDT features that enable links with digital health tools to create an RDT-OG system.
METHODS: We reviewed published papers and conducted a survey with experts or users of RDTs in the sectors of technology, manufacturing, and deployment to define features and axioms for information utilization. We developed an IUI, ranging from 0% to 100%, and calculated this index for 33 World Health Organization-prequalified RDTs. RDT-OG specifications were developed to maximize the IUI; the feasibility and specifications were assessed through developing malaria and COVID-19 RDTs based on OGs for use in Kenya and Indonesia.
RESULTS: The survey respondents (n=33) included 16 researchers, 7 technologists, 3 manufacturers, 2 doctors or nurses, and 5 other users. They were most concerned about the proper use of RDTs (30/33, 91%), their interpretation (28/33, 85%), and reliability (26/33, 79%), and were confident that smartphone-based RDT readers could address some reliability concerns (28/33, 85%), and that readers were more important for complex or multiplex RDTs (33/33, 100%). The IUI of prequalified RDTs ranged from 13% to 75% (median 33%). In contrast, the IUI for an RDT-OG prototype was 91%. The RDT open guideline system that was developed was shown to be feasible by (1) creating a reference RDT-OG prototype; (2) implementing its features and capabilities on a smartphone RDT reader, cloud information system, and Fast Healthcare Interoperability Resources; and (3) analyzing the potential public health impact of RDT-OG integration with laboratory, surveillance, and vital statistics systems.
CONCLUSIONS: Policy makers and manufacturers can define, adopt, and synergize with RDT-OGs and digital health initiatives. The RDT-OG approach could enable real-time diagnostic and epidemiological monitoring with adaptive interventions to facilitate control or elimination of current and emerging diseases through PPH.

OBJECTIVE: Authors reported multiple definitions of e-oral health and related terms, and used several definitions interchangeably, like mhealth, teledentistry, teleoral medicine and telehealth. The International Association of Dental Research e-Oral Health Network (e-OHN) aimed to establish a consensus on terminology related to digital technologies used in oral healthcare.
METHODS: The Crowdsourcing Delphi method used in this study comprised of four main stages. In the first stage, the task force created a list of terms and definitions around digital health technologies based on the literature and established a panel of experts. Inclusion criteria for the panellists were: to be actively involved in either research and/or working in e-oral health fields; and willing to participate in the consensus process. In the second stage, an email-based consultation was organized with the panel of experts to confirm an initial set of terms. In the third stage, consisted of: a) an online meeting where the list of terms was presented and refined; and b) a presentation at the 2022-IADR annual meeting. The fourth stage consisted of two rounds of feedback to solicit experts\' opinion about the terminology and group discussion to reach consensus. A Delphi-questionnaire was sent online to all experts to independently assess a) the appropriateness of the terms, and b) the accompanying definitions, and vote on whether they agreed with them. In a second round, each expert received an individualised questionnaire, which presented the expert\'s own responses from the first round and the panellists\' overall response (% agreement/disagreement) to each term. It was decided that 70% or higher agreement among experts on the terms and definitions would represent consensus.
RESULTS: The study led to the identification of an initial set of 43 terms. The list of initial terms was refined to a core set of 37 terms. Initially, 34 experts took part in the consensus process about terms and definitions. From them, 27 experts completed the first rounds of consultations, and 15 the final round of consultations. All terms and definitions were confirmed via online voting (i.e., achieving above the agreed 70% threshold), which indicate their agreed recommendation for use in e-oral health research, dental public health, and clinical practice.
CONCLUSIONS: This is the first study in oral health organised to achieve consensus in e-oral health terminology. This terminology is presented as a resource for interested parties. These terms were also conceptualised to suit with the new healthcare ecosystem and the place of e-oral health within it. The universal use of this terminology to label interventions in future research will increase the homogeneity of future studies including systematic reviews.

With the rapid development of sleep medicine and digital technology, digital therapy for insomnia has been in creasingly used in the prevention, diagnosis, treatment, rehabilitation and management of insomnia in recent years. As a new medical technology, there is an urgent need for experts in the fields of clinical, scientific research, regulatory authorities and industry to work together to form recommendations for the application of digital therapy for insomnia. This expert consensus systematically reviews and evaluates the relevant research and application status of digital therapy for insomnia at home and abroad. Based on, the expert opinions in various fields, recommendations for the clinical application of digital therapy for insomnia and 13 opinions on the regulatory approach and direction of future development are proposed, providing references for the clinical diagnosis and treatment of insomnia.
得益于睡眠医学和数字技术的快速发展，近年来失眠症数字疗法越来越广泛地应用于失眠症的预防、诊断、治疗、康复和管理等各个环节。作为一种新型医疗技术，亟须临床、科研、监管部门及产业等领域的专家共同对失眠症数字疗法的应用形成推荐意见。本专家共识系统回顾和评价了国内外失眠症数字疗法的相关研究和应用现状，综合各领域专家意见，提出了失眠症数字疗法临床应用推荐及针对监管方式和未来发展方向的13条意见，为失眠症的临床诊疗提供参考。.

Guideline-directed medical therapy (GDMT) underuse is common in heart failure (HF) patients. Digital solutions have the potential to support medical professionals to optimize GDMT prescriptions in a growing HF population. We aimed to review current literature on the effectiveness of digital solutions on optimization of GDMT prescriptions in patients with HF.
We report on the efficacy, characteristics of the study, and population of published digital solutions for GDMT optimization. The following digital solutions are discussed: teleconsultation, telemonitoring, cardiac implantable electronic devices, clinical decision support embedded within electronic health records, and multifaceted interventions. Effect of digital solutions is reported in dedicated studies, retrospective studies, or larger studies with another focus that also commented on GDMT use. Overall, we see more studies on digital solutions that report a significant increase in GDMT use. However, there is a large heterogeneity in study design, outcomes used, and populations studied, which hampers comparison of the different digital solutions. Barriers, facilitators, study designs, and future directions are discussed. There remains a need for well-designed evaluation studies to determine safety and effectiveness of digital solutions for GDMT optimization in patients with HF. Based on this review, measuring and controlling vital signs in telemedicine studies should be encouraged, professionals should be actively alerted about suboptimal GDMT, the researchers should consider employing multifaceted digital solutions to optimize effectiveness, and use study designs that fit the unique sociotechnical aspects of digital solutions. Future directions are expected to include artificial intelligence solutions to handle larger datasets and relieve medical professional\'s workload.

New sleep technologies are being developed, refined and delivered at a fast pace. However, there are serious concerns about the validation and accuracy of new sleep-related technologies being made available, as many of them, especially consumer-sleep technologies, have not been tested in comparison with gold-standard methods or have been approved by health regulatory agencies. The importance of proper validation and performance evaluation of new sleep technologies has already been discussed in previous studies and some recommendations have already been published, but most of them do not employ standardized methodology and are not able to cover all aspects of new sleep technologies. The current protocol describes the methods of a Delphi consensus study to create guidelines for the development, performance evaluation and validation of new sleep devices and technologies. The resulting recommendations are not intended to be used as a quality assessment tool to evaluate individual articles, but rather to evaluate the overall procedures, studies and experiments performed to develop, evaluate performance and validate new technologies. We hope these guidelines can be helpful for researchers who work with new sleep technologies on the appraisal of their reliability and validation, for companies who are working on the development and refinement of new sleep technologies, and by regulatory agencies to evaluate new technologies that are looking for registration, approval or inclusion on health systems.

OBJECTIVE: Mobile Health (mHealth) refers to using mobile devices to support health. This study aimed to identify specific methodological challenges in systematic reviews (SRs) of mHealth interventions and to develop guidance for addressing selected challenges.
METHODS: Two-phase participatory research project. First, we sent an online survey to corresponding authors of SRs of mHealth interventions. On a five-category scale, survey respondents rated how challenging they found 24 methodological aspects in SRs of mHealth interventions compared to non-mHealth intervention SRs. Second, a subset of survey respondents participated in an online workshop to discuss recommendations to address the most challenging methodological aspects identified in the survey. Finally, consensus-based recommendations were developed based on the workshop discussion and subsequent interaction via email with the workshop participants and two external mHealth SR authors.
RESULTS: We contacted 953 corresponding authors of mHealth intervention SRs, of whom 50 (5 %) completed the survey. All the respondents identified at least one methodological aspect as more or much more challenging in mHealth intervention SRs than in non-mHealth SRs. A median of 11 (IQR 7.25-15) out of 24 aspects (46 %) were rated as more or much more challenging. Those most frequently reported were: defining intervention intensity and components (85 %), extracting mHealth intervention details (71 %), dealing with dynamic research with evolving interventions (70 %), assessing intervention integrity (69 %), defining the intervention (66 %) and maintaining an updated review (65 %). Eleven survey respondents participated in the workshop (five had authored more than three mHealth SRs). Eighteen consensus-based recommendations were developed to address issues related to mHealth intervention integrity and to keep mHealth SRs up to date.
CONCLUSIONS: mHealth SRs present specific methodological challenges compared to non-mHealth interventions, particularly related to intervention integrity and keeping SRs current. Our recommendations for addressing these challenges can improve mHealth SRs.

Describe the rationale for and design of Diabetes Remote Intervention to improVe use of Evidence-based medications (DRIVE), a remote medication management program designed to initiate and titrate guideline-directed medical therapy (GDMT) in patients with type 2 diabetes (T2D) at elevated cardiovascular (CV) and/or kidney risk by leveraging non-physician providers.
An electronic health record based algorithm is used to identify patients with T2D and either established atherosclerotic CV disease (ASCVD), high risk for ASCVD, chronic kidney disease, and/or heart failure within our health system. Patients are invited to participate and randomly assigned to either simultaneous education and medication management, or a period of education prior to medication management. Patient navigators (trained, non-licensed staff) are the primary points of contact while a pharmacist or nurse practitioner reviews and authorizes each medication initiation and titration under an institution-approved collaborative drug therapy management protocol with supervision from a cardiologist and/or endocrinologist. Patient engagement is managed through software to support communication, automation, workflow, and standardization.
We are testing a remote, navigator-driven, pharmacist-led, and physician-overseen management strategy to optimize GDMT for T2D as a population-level strategy to close the gap between guidelines and clinical practice for patients with T2D at elevated CV and/or kidney risk.

A foundation for digitally enabling healthier living is the safe development and use of technology. The practice of digital health safety has emerged from patient harm attributed to failing technologies. The study aimed to investigate how to adopt and implement digital health safety guidelines at scale. Data was collected through an online survey, semi-structured interviews, focus groups, document review, and data mining of artefacts. The findings of this study capture the emerging practice from Australia in a way that offers insights into the problem of practice, patient safety practice, safety culture, and socio-technical factors. The research findings contribute to better understanding of the complexities of balancing digital innovation with patient safety. The four recommendations from the study and the provision of a logic model will support the audience to implement actions toward a safer digital health ecology.

OBJECTIVE: Many heart failure (HF) patients do not receive optimal guideline-directed medical therapy (GDMT) despite clear benefit on morbidity and mortality outcomes. Digital consults (DCs) have the potential to improve efficiency on GDMT optimization to serve the growing HF population. The investigator-initiated ADMINISTER trial was designed as a pragmatic multicenter randomized controlled open-label trial to evaluate efficacy and safety of DC in patients on HF treatment.
RESULTS: Patients (n = 150) diagnosed with HF with a reduced ejection fraction will be randomized to DC or standard care (1:1). The intervention group receives multifaceted DCs including (i) digital data sharing (e.g. exchange of pharmacotherapy use and home-measured vital signs), (ii) patient education via an e-learning, and (iii) digital guideline recommendations to treating clinicians. The consults are performed remotely unless there is an indication to perform the consult physically. The primary outcome is the GDMT prescription rate score, and secondary outcomes include time till full GDMT optimization, patient and clinician satisfaction, time spent on healthcare, and Kansas City Cardiomyopathy Questionnaire. Results will be reported in accordance to the CONSORT statement.
CONCLUSIONS: The ADMINISTER trial will offer the first randomized controlled data on GDMT prescription rates, time till full GDMT optimization, time spent on healthcare, quality of life, and patient and clinician satisfaction of the multifaceted patient- and clinician-targeted DC for GDMT optimization.

Mental health Applications (Mhealth Apps) can change how healthcare is delivered. However, very little is known about the efficacy of Mhealth Apps. Currently, only minimum guidance is available in Assessment and Evaluation Tools (AETs). Therefore, this project aims to understand AET developers\' perspectives and end users\' experiences and opinions on \"how to choose a Mhealth App\".
The primary objectives were: (1) obtaining stakeholder\'s opinions and experiences of development and use of AETs for Mhealth Apps, their weaknesses and strengths, and barriers in their implementation of Mhealth Apps; (2) the experiences of App users, their analyzation and, obstacles in the use of apps; and (3) to quantify themes related to choosing a Mhealth App.
This qualitative study, used a sampling method to recruit six stakeholders (one App developer, two AET developers, an individual with lived experience of mental health illness, and two physicians) who were interviewed using a topic guide. These were examined by researchers (CT, WK, & FN) using thematic content analysis. Additionally, an anonymous online survey of 107 individuals was conducted.
Our analyses revealed six main themes: (a) needs and opportunities; (b) views on Mhealth apps; (c) views & opinions on AETs; (d) implementation barriers; (e) system of evaluation and; (f) future directions. The first key concept was, all stakeholders agreed that Apps could significantly impact mental health and that end-users were unaware of mental health AETs and Apps. Secondly, due to commercial interests, end-users reliability of App evaluations requires clear conflict-free guidelines. Thirdly, AETs should be evaluated and developed through a rigorous methodology. Finally, stakeholders shared insights into future developments for AETs and Mhealth Apps. Additionally, online survey respondents chose a \"health professional\" as their preferred source of guidance in selecting a Mhealth app (84%) and best suited to develop guidelines (70%).
The interviews and survey highlight the need for Mhealth Apps to be regulated and the importance of health professionals\' engagement in the implementation process. Similarly, without well-defined roles for App evaluations within the health care system, it is unlikely that AETs will have wider spread use and impact without risk.