Objective Cardiac rehabilitation (CR) is pivotal in preventing recurring events of myocardial infarction (MI). This study aims to investigate the effect of a smartphone-based home service delivery (Care Assessment Platform) of CR (CAP-CR) on CR use and health outcomes compared with a traditional, centre-based programme (TCR) in post-MI patients. Methods In this unblinded randomised controlled trial, post-MI patients were randomised to TCR (n=60; 55.7±10.4 years) and CAP-CR (n=60; 55.5±9.6 years) for a 6-week CR and 6-month self-maintenance period. CAP-CR, delivered in participants’ homes, included health and exercise monitoring, motivational and educational material delivery, and weekly mentoring consultations. CAP-CR uptake, adherence and completion rates were compared with TCR using intention-to-treat analyses. Changes in clinical outcomes (modifiable lifestyle factors, biomedical risk factors and health-related quality of life) across baseline, 6 weeks and 6 months were compared within, and between, groups using linear mixed model regression. Results CAP-CR had significantly higher uptake (80% vs 62%), adherence (94% vs 68%) and completion (80% vs 47%) rates than TCR (p<0.05). Both groups showed significant improvements in 6-minute walk test from baseline to 6 weeks (TCR: 537±86–584±99 m; CAP-CR: 510±77–570±80 m), which was maintained at 6 months. CAP-CR showed slight weight reduction (89±20–88±21 kg) and also demonstrated significant improvements in emotional state (K10: median (IQR) 14.6 (13.4–16.0) to 12.6 (11.5–13.8)), and quality of life (EQ5D-Index: median (IQR) 0.84 (0.8–0.9) to 0.92 (0.9–1.0)) at 6 weeks. Conclusions This smartphone-based home care CR programme improved post-MI CR uptake, adherence and completion. The home-based CR programme was as effective in improving physiological and psychological health outcomes as traditional CR. CAP-CR is a viable option towards optimising use of CR services. Trial registration number ANZCTR12609000251224.

Background: Gestational diabetes mellitus (GDM) is defined as glucose intolerance first identified during pregnancy. Delays in diagnosis and challenges in management can lead to serious adverse outcomes for the mother and child. As rates of GDM diagnosis increase worldwide, health systems and maternity services have become increasingly strained, especially with new restrictions around in-person care due to the current COVID-19 pandemic. Mobile health (mHealth) has increasingly shown promise for management of chronic disease, driven by smartphone adoption and increased internet connectivity. The aim of this work was to evaluate the adoption and multidisciplinary care coordination of an mHealth platform called M♡THer in a cohort of women with first-time diagnosis of GDM. Methods: The mHealth platform for GDM management was developed incorporating a smartphone application, clinician portal, and secure cloud data storage. Forty participants with a first-time diagnosis of GDM were recruited to use the app during their pregnancy. User attitudes from clinicians and women were captured through post-hoc surveys, and app-usage metrics. Results: Clinicians and women indicated satisfaction and ease of use of the mHealth platform, with some technological challenges around wireless connectivity. Blood glucose reviews and antenatal contact were higher with use of the M♡THer app compared with a matched historical sample. Conclusion: The M♡THer mHealth platform is a new comprehensive tool for health care of women with GDM, and may provide an effective new avenue to enhance multidisciplinary care in the face of COVID-19 disruptions and challenges to traditional care pathways.

Background: Clinical decision support systems (CDSS) have the potential to play a crucial role in enhancing health care quality by providing evidence-based information to clinicians at the point of care. Despite their increasing popularity, there is a lack of comprehensive research exploring their design characterization and trends. This limits our understanding and ability to optimize their functionality, usability, and adoption in health care settings. Objective: This systematic review examined the design characteristics of CDSS from a user-centered perspective, focusing on user-centered design (UCD), user experience (UX), and usability, to identify related design challenges and provide insights into the implications for future design of CDSS. Methods: This review followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) recommendations and used a grounded theory analytical approach to guide the conduct, data analysis, and synthesis. A search of 4 major electronic databases (PubMed, Web of Science, Scopus, and IEEE Xplore) was conducted for papers published between 2013 and 2023, using predefined design-focused keywords (design, UX, implementation, evaluation, usability, and architecture). Papers were included if they focused on a designed CDSS for a health condition and discussed the design and UX aspects (eg, design approach, architecture, or integration). Papers were excluded if they solely covered technical implementation or architecture (eg, machine learning methods) or were editorials, reviews, books, conference abstracts, or study protocols. Results: Out of 1905 initially identified papers, 40 passed screening and eligibility checks for a full review and analysis. Analysis of the studies revealed that UCD is the most widely adopted approach for designing CDSS, with all design processes incorporating functional or usability evaluation mechanisms. The CDSS reported were mainly clinician-facing and mostly stand-alone systems, with their design lacking consideration for integration with existing clinical information systems and workflows. Through a UCD lens, four key categories of challenges relevant to CDSS design were identified: (1) usability and UX, (2) validity and reliability, (3) data quality and assurance, and (4) design and integration complexities. Notably, a subset of studies incorporating Explainable artificial intelligence highlighted its emerging role in addressing key challenges related to validity and reliability by fostering explainability, transparency, and trust in CDSS recommendations, while also supporting collaborative validation with users. Conclusions: While CDSS show promise in enhancing health care delivery, identified challenges have implications for their future design, efficacy, and utilization. Adopting pragmatic UCD design approaches that actively involve users is essential for enhancing usability and addressing identified UX challenges. Integrating with clinical systems is crucial for interoperability and presents opportunities for AI-enabled CDSS that rely on large patient data. Incorporating emerging technologies such as Explainable Artificial Intelligence can boost trust and acceptance. Enabling functionality for CDSS to support both clinicians and patients can create opportunities for effective use in virtual care.

Clinical informatics, decision support for health professionals, electronic health records, and ehealth infrastructures.

Clinical informatics, decision support for health professionals, electronic health records, and ehealth infrastructures.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Mobile Health (mHealth) technologies, such as wearable devices and mobile applications have become popular for lifestyle and healthcare support. They have the potential to be beneficial for pregnancy monitoring, in the form of health and well-being tools to facilitate the tracking of health status changes, risks and complications of pregnant women. However, research on understanding clinicians’ and pregnant women’s interests, preferences and requirements for mHealth solutions tailored to pregnancy care is limited. Objective: This qualitative study aimed to understand clinicians’ and pregnant women’s perceptions on the potential use of mHealth to support the monitoring of health and well-being during pregnancy. Methods: Semi-structured interviews were conducted with four pregnant women, four postnatal women, and thirteen clinicians working in perinatal care. Results: Clinicians perceived the potential benefit of mHealth in supporting different levels of health and wellbeing monitoring, risk assessment and care provision in pregnancy care. The majority of women participants were open to the use of wearables and health monitoring devices and were more likely to use these technologies if they knew that clinicians can monitor the data. While some pregnancy-related medical conditions can be suitable for an mHealth model of remote monitoring, there are clinical and technical challenges for introducing mHealth in pregnancy care. Incorporating appropriate health and well-being measures, intelligent detection of abnormalities and tailored information for pregnant women were considered critical. Usability and data privacy were among the concerns of participants. The challenges of getting pregnant women engaged in longitudinal mHealth monitoring, the extra work required for clinicians in monitoring data, and the need for an evidence-based technical solution were highlighted. Conclusions: mHealth technologies, such as wearable sensors, smart health devices and mobile applications capable of supporting the pregnancy journey are emerging. Clinical, technical and practical factors associated with the use of mHealth technologies to monitor health and well-being, as well as strategies for motivating pregnant women and clinicians’ in the use of the technologies need to be carefully considered before the introduction of mHealth pregnancy care routine and practices.