Background Although well recognized for its scientific value, data sharing from clinical trials remains limited. Steps toward harmonization and standardization are increasing in various pockets of the global scientific community. This issue has gained salience during the COVID-19 pandemic. Even for agencies willing to share data, data exclusivity practices complicate matters; strict regulations by funders affect this even further. Finally, many low- and middle-income countries (LMICs) have weaker institutional mechanisms. This complex of factors hampers research and rapid response during public health emergencies. This drew our attention to the need for a review of the regulatory landscape governing clinical trial data sharing. Objective This review seeks to identify regulatory frameworks and policies that govern clinical trial data sharing and explore key elements of data-sharing mechanisms as outlined in existing regulatory documents. Following from, and based on, this empirical analysis of gaps in existing policy frameworks, we aimed to suggest focal areas for policy interventions on a systematic basis to facilitate clinical trial data sharing. Methods We followed the JBI scoping review approach. Our review covered electronic databases and relevant gray literature through a targeted web search. We included records (all publication types, except for conference abstracts) available in English that describe clinical trial data–sharing policies, guidelines, or standard operating procedures. Data extraction was performed independently by 2 authors, and findings were summarized using a narrative synthesis approach. Results We identified 4 articles and 13 policy documents; none originated from LMICs. Most (11/17, 65%) of the clinical trial agencies mandated a data-sharing agreement; 47% (8/17) of these policies required informed consent by trial participants; and 71% (12/17) outlined requirements for a data-sharing proposal review committee. Data-sharing policies have, a priori, milestone-based timelines when clinical trial data can be shared. We classify clinical trial agencies as following either controlled- or open-access data-sharing models. Incentives to promote data sharing and distinctions between mandated requirements and supportive requirements for informed consent during the data-sharing process remain gray areas, needing explication. To augment participant privacy and confidentiality, a neutral institutional mechanism to oversee dissemination of information from the appropriate data sets and more policy interventions led by LMICs to facilitate data sharing are strongly recommended. Conclusions Our review outlines the immediate need for developing a pragmatic data-sharing mechanism that aims to improve research and innovations as well as facilitate cross-border collaborations. Although a one-policy-fits-all approach would not account for regional and subnational legislation, we suggest that a focus on key elements of data-sharing mechanisms can be used to inform the development of flexible yet comprehensive data-sharing policies so that institutional mechanisms rather than disparate efforts guide data generation, which is the foundation of all scientific endeavor.

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The potential ability of unattended office blood pressure (AOBP) has been acknowledged worldwide, including Japan, although much resource consumption makes it less feasible to use AOBP in clinical practice. We reported that the three consecutive AOBP measurement values in each patient were almost identical, with high correlations (r ≥ 0.90), and the AOBP and conventional attended office blood pressure were moderate to highly correlated. We therefore interpret that AOBP can be an alternative that is more stable than the conventional attended blood pressure value despite with the average shifted to some extent, e.g., 10.4/4.2 mmHg based on the same study. In contrast, there is a fundamental discrepancy between the similarity in average values and the poor agreement in individuals when we compare AOBP versus self-measured home blood pressure, as the systolic blood pressure difference was 0.9 mmHg with a 95% agreement limit was -34.0 to + 35.8 mmHg. The vast wide range of difference indicates that we cannot estimate home as well as ambulatory blood pressure values by AOBP measurements in each patient, and vice versa. AOBP has another advantage regarding the elimination of white-coat effect by the presence of medical staff. Nevertheless, because AOBP measurement is performed at a clinic or in a screening setting where participants cannot be relaxed like at their own home, such a clinic effect still affects AOBP readings. In this session, the current evidence on AOBP based on our Japanese studies and others will be summarized and issues which remain to be investigated for the assessment of a variety of blood pressure conditions, unattended and attended office, and out-of-office blood pressures will be discussed.

ObjectiveTo identify and summarise the digital health interventions (DHIs) implemented for non-communicable disease (NCD) management for COVID-19.DesignRapid scoping review. Three reviewers jointly screened titles–abstracts and full texts. One reviewer screened all excluded records. Data were mapped to WHO DHI Classification and narratively summarised.Data sourcesPubMed, CENTRAL, CINAHL, EMBASE.Eligibility criteria for selecting studiesPeer-reviewed primary research published between 1 November 2019 and 19 September 2021 on DHI for NCD management during the COVID-19 pandemic. Reviews, editorials, letters, commentaries, opinions, conference abstracts and grey literature were excluded.ResultsEighty-three studies drawn from 5275 records were included. A majority of the studies were quantitative in design. Forty per cent of the DHIs were implemented in the Americas. Nearly half of these DHIs targeted mental health conditions. A majority of the interventions were delivered remotely and via telephones. Zoom (26.5%), email (17%) and WhatsApp (7.5%) were the top three platforms for care delivery. Telemedicine, targeted client interventions, personal health tracking and on-demand information services for clients were the most frequently implemented interventions. Details regarding associated costs, sustainability, scalability and data governance of the DHI implementations were not described in the majority of the studies.ConclusionWhile DHIs supported NCD management during the COVID-19 pandemic, their implementation has not been equitable across geographies or NCDs. While offering promise towards supporting the continuum of care during care delivery disruptions, DHIs need to be embedded into healthcare delivery settings towards strengthening health systems rather than standalone parallel efforts to overcome system level challenges.

BACKGROUND: To identify and summarize the global research literature on validation of automated noninvasive blood pressure measurement devices (BPMDs) with upper arm cuff, develop a repository of validated BPMDs in compliance with the 2020 World Health Organization technical specifications, and identify challenges and gaps in evidence base on validated BPMDs. METHODS: A scoping review was conducted. Primary research validating BPMDs complying with the 2020 World Health Organization technical specifications (ie, semiautomated/automated noninvasive devices with upper arm cuff), published in English between January 2000 and December 2021, was included. We searched MEDLINE, Web of Science, Scopus, EMBASE, CINAHL, CENTRAL, ProQuest and the dabl website. RESULTS: We included 269 studies validating 251 BPMDs across 89 manufacturers. Omron (29%), Microlife (10%), and A&D Company (8%) were the top 3 manufacturers. The 3 most frequently used validation protocols were the European Society of Hypertension-international protocol 2002 (27%), European Society of Hypertension-international protocol 2010 (25%), and modified British Hypertension Society protocol 1993 (16%), respectively. Nearly 45% of the validated BPMDs were intended for use in clinical settings, 38% were for home or self-measurement use, and 48% were for general adults. Most studies reported that BPMDs passed the validation criteria. There was inadequate reporting across studies, especially pertaining to validation settings. CONCLUSIONS: Most BPMDs fulfilled the validation criteria. However, there are considerable gaps in BPMD research in terms of geographical representation, including specific target populations and diseases/conditions, and a range of arm circumferences. Additionally, a potential strategy is required to accelerate the adoption of the Association for the Advancement of Medical Instrumentation (AAMI)/European Society of Hypertension/International Organization for Standardization Universal Standard (International Organization for Standardization 81060-2:2018) for BPMD validation.