UNASSIGNED: Digital health ecosystems may be the next revolution in improving citizens\' well-being, health delivery, data management, and health system processes, but solutions have not yet been broadly established. Reasons could be that health service-organizations have misaligned interests or lack capabilities. This study investigates reasons from a multi-health-service-organization perspective, differentiating between payers, insurers, healthcare providers, and innovators, detailing the expected value-adds, preferred participation roles, and required capabilities including a rating assessment.
UNASSIGNED: Findings are based on a taxonomy development methodology, which combines a literature review with semi-structured qualitative expert interviews, conducted using a modified Delphi approach. Interviews were thematically analysed.
UNASSIGNED: In total, 21 experts across the four health service-organization groups were interviewed. The capability taxonomy includes a total of 16 capabilities, categorized in three themes: \'Health market\', \'organizational\', and \'technology and informatic\'. Providers expect a value-add from strengthening their health process economics through efficiency gains but reveal the largest capability gaps, especially in \'interoperability\' and \'platform\'. Innovators\' \'technology and informatic\' capabilities complement well with those of payers for the \'health market\'.
UNASSIGNED: We present a health service-organization-specific three-stage approach for establishing digital health ecosystems. Payers and insurers should address their \'technology and informatic\' capability gaps, using technical enablers or forming new entities to reduce dependencies from legacy information technology systems. Innovators should clarify their monetization models and create positive awareness for their services, possibly entering the market directly. Providers must address interoperability issues and may require incentives to encourage their participation. Findings suggest governmental policymakers to prioritize three health policy initiatives.

The remote monitoring of vital signs via wearable devices holds significant potential for alleviating the strain on hospital resources and elder-care facilities. Among the various techniques available, photoplethysmography stands out as particularly promising for assessing vital signs such as heart rate, respiratory rate, oxygen saturation, and blood pressure. Despite the efficacy of this method, many commercially available wearables, bearing Conformité Européenne marks and the approval of the Food and Drug Administration, are often integrated within proprietary, closed data ecosystems and are very expensive. In an effort to democratize access to affordable wearable devices, our research endeavored to develop an open-source photoplethysmographic sensor utilizing off-the-shelf hardware and open-source software components. The primary aim of this investigation was to ascertain whether the combination of off-the-shelf hardware components and open-source software yielded vital-sign measurements (specifically heart rate and respiratory rate) comparable to those obtained from more expensive, commercially endorsed medical devices. Conducted as a prospective, single-center study, the research involved the assessment of fifteen participants for three minutes in four distinct positions, supine, seated, standing, and walking in place. The sensor consisted of four PulseSensors measuring photoplethysmographic signals with green light in reflection mode. Subsequent signal processing utilized various open-source Python packages. The heart rate assessment involved the comparison of three distinct methodologies, while the respiratory rate analysis entailed the evaluation of fifteen different algorithmic combinations. For one-minute average heart rates\' determination, the Neurokit process pipeline achieved the best results in a seated position with a Spearman\'s coefficient of 0.9 and a mean difference of 0.59 BPM. For the respiratory rate, the combined utilization of Neurokit and Charlton algorithms yielded the most favorable outcomes with a Spearman\'s coefficient of 0.82 and a mean difference of 1.90 BrPM. This research found that off-the-shelf components are able to produce comparable results for heart and respiratory rates to those of commercial and approved medical wearables.

UNASSIGNED: Patient-centred care and enhancing patient experience is a priority across Australia. Stroke rehabilitation has multiple consumer touchpoints that would benefit from a better understanding of customer journeys, subsequently impacting better patient-centred care, and contributing to process improvements and better patient outcomes. Customer journey mapping through process mining extracts process data from event logs in existing information systems discovering patient journeys, which can be utilized to monitor guideline compliance and uncover nonconformance.
UNASSIGNED: Utilizing process mining and variant analysis, customer journey maps were developed for 130 stroke rehabilitation patients from referral to discharge. In total, 168 cases from the Australasian Rehabilitation Outcomes Centre dataset were matched with 6291 cases from inpatient stroke data. Variants were explored for age, gender, outcome measures, length of stay and functional independence measure (FIM) change.
UNASSIGNED: The study illustrated the process, process variants and patient journey map in stroke rehabilitation. Process characteristics of stroke rehabilitation patients were extracted and represented utilizing process mining and results highlighted process variation, attributes, touchpoints and timestamps across stroke rehabilitation patient journeys categorized by patient demographics and outcome variables. Patients demonstrated a mean and median duration of 49.5 days and 44 days, respectively, across the patient journeys. Nine variants were discovered, with 78.46% (n = 102) of patients following the expected sequence of activities in their stroke rehabilitation patient journey. Relationships involving age, gender, length of stay and FIM change along the patient journeys were evident, with four cases experiencing stroke rehabilitation journeys of more than 100 days, warranting further investigation.
UNASSIGNED: Process mining can be utilized to visualize and analyse patient journeys and identify gaps in service quality, thus contributing to better patient-centred care and improved patient outcomes and experiences in stroke rehabilitation.

Background: Even before coronavirus disease 2019, integrating telemedicine into routine health care has become increasingly attractive. Evidence regarding the benefits of telemedicine in prenatal care is still inconclusive. As one of the largest sectors of preventive medicine with a relative paucity of specialists in maternal-fetal medicine (MFM), the implementation of telemedicine solutions into prenatal care is promising. Our objective aimed at establishing a telemedicine network of specialists in MFM for interprofessional exchange regarding high-risk pregnancies. Furthermore, the aims were to evaluate the providers\' attitude toward the telemedicine solutions and to quantify the number of inpatient appointments that were avoided through interprofessional video consultations. Methods: This prospective trial was part of a larger telemedicine project funded by the European Regional Development Fund. MFM experts were brought together using the ELVI software. A questionnaire was designed for the evaluation of video consultations. The responses were analyzed by the exact McNemar-Bowker test to compare planned procedures before and after video consultation. Results: An interprofessional network of specialists in prenatal ultrasound was established with a total of 140 evaluations for statistical analysis. Interprofessional video communication was viewed favorably by providers. Overall, 47% (33/70) of the scheduled visits were avoided after video consultation. The providers\' tendency to refrain from sending their patients to the University Hospital Münster was statistically noticeable (p = 0.048). Conclusions: Interprofessional exchange through video consultation holds great potential in the context of prenatal care. More prospective research is needed to clearly establish the most beneficial standard of care for both patients and providers. Clinical trial registration number: 2019-683-f-S.

UNASSIGNED: Due to the growing complexity in monitoring and treatment of many disorders, disease-specific care and research networks offer patients certified healthcare. However, the networks\' ability to provide health services close to patients\' homes usually remains vague. Digital Health Technologies (DHTs) help to provide better care, especially if implemented in a targeted manner in regions undersupplied by specialised networks. Therefore, we used a car travel time-based isochrone approach to identify care gaps using the example of the neuroinflammation-focused German healthcare and research networks for multiple sclerosis (MS), myasthenia gravis (MG), myositis and immune-mediated neuropathy.
UNASSIGNED: Excellence centres were mapped, and isochrones for 30, 60, 90 and 120 minutes were calculated. The resulting geometric figures were aggregated and used to mask the global human settlement population grid 2019 to estimate German inhabitants that can reach centres within the given periods.
UNASSIGNED: While 96.48% of Germans can drive to an MS-focused centre within one hour, coverage is lower for the rare disease networks for MG (48.3%), myositis (43.1%) and immune-mediated neuropathy (56.7%). Within 120 minutes, more than 80% of Germans can reach a centre of any network. Besides the generally worse covered rural regions such as North-Eastern Germany, the rare disease networks also show network-specific regional underrepresentation.
UNASSIGNED: An isochrone-based approach helps identify regions where specialised care is hard to reach, which might be especially troublesome in the case of an often disabled patient collective. Patient care could be improved by focusing deployments of disease-specific DHTs on these areas.

As medical science advances and the population ages, the prevalence of chronic conditions has also grown. The traditional model of care, with its focus on acute and episodic issues within the office visit, is not designed to meaningfully address long-term patient needs. With COVID-19 has come unprecedented digital adoption, bringing health care delivery to a critical juncture. While digital tools and technologies present vast opportunities for democratizing and decentralizing care experiences, their piecemeal application to the existing \"sick care\" model and its information technology infrastructure will not only limit their value, but will inevitably add cost, inefficiency, and burden to care teams. In order to build upon this momentum and reap the full benefits of practice digitization, care model transformation must occur. This entails holistically reexamining how every component of the health care experience, from the digital tools to visit interactions, synchronizes to address the full continuum of patient needs throughout the journey. By doing this, care shifts away from one-size-fits-all, fragmented strings of visits, toward seamless experiences that adapt to patients\' needs in real-time while integrating within their daily lives. Rather than acting as a substitute for care, technology instead is vital to promoting and amplifying the impact of all those involved. To achieve this, this paper outlines 10 principles for restructuring care to incorporate digital health capabilities. Each describes how all care model components work as a system that aligns with patient needs. By doing this, technology is now an integral in supporting relationships across the full continuum of care.

BACKGROUND: Steady Health\'s novel virtual care model incorporates continuous glucose monitoring (CGM) and a multidisciplinary approach to timely person-centered diabetes care.
OBJECTIVE: This real-world retrospective case series explores the early glycemic outcomes of its patients with uncontrolled diabetes.
METHODS: All patients of Steady Health who had an initial time in range (TIR) below 70% from their first 4 weeks of available CGM data and who had completed onboarding by February 2021 were included in this analysis. We compared the change in TIR, time below range, and average blood glucose from their first 4 weeks with their latest 4 weeks of available CGM data. Hemoglobin A1c (HbA1c) values at baseline and at the end of the study were also compared. Patients completed a questionnaire assessing their satisfaction with Steady Health\'s intervention.
RESULTS: A total of 53 patients (n=35, 66% with type 1 diabetes; n=44, 83% treated with insulin) were included in this analysis. This cohort had a median baseline TIR of 53.0% (IQR 40.9%, 61.7%) and saw a median change in TIR of +16.6% (IQR +6.0%, +27.9%; P<.001) over a median duration of care of 11 months, amounting to nearly 4 more hours spent between 70 to 180 mg/dL a day. Of the 27 patients who had both baseline and follow-up HbA1c results, their median baseline HbA1c was 8.6% (IQR 7.5%, 11.4%; 70 mmol/mol), while their median change in HbA1c was -1.2% (IQR -2.6%, -0.2%; P=.001). Importantly, these glycemic improvements were achieved with a median decrease in the time below range by -0.3% (IQR -1.1%, 0.0%; P<.001), regardless of whether patients were started on an automated insulin delivery system. A total of 40 (75.5%) patients improved TIR by ≥5%, and 27 (50.9%) achieved TIR≥70% by the end of the study. Glycemic improvements were greatest among patients with the lowest baseline TIR and those who collaborated most intensively with Steady Health\'s clinicians. A total of 25 of these patients responded to a questionnaire assessing levels of satisfaction with their care, and all of them agreed that Steady Health had a positive impact on their diabetes management.
CONCLUSIONS: Our findings suggest that patients with uncontrolled diabetes can achieve significant glycemic improvements by working with a virtual multidisciplinary care team that uses CGM to provide continuous clinical feedback and support.

Data has always been integral to modern medicine in almost all aspects of patient care and the recent proliferation of data has opened up innumerable opportunities for all the stakeholders in trying to improve the quality of care and health outcomes including quality of life and rehabilitation. Greater usage and adoption of digital technologies have led to the convergence of health data in different forms - clinical, self-reported, electronic health records social media, etc. The application and utilization of patient data set continue to get broadened each day with greater availability and access. These are empowering newer cutting-edge solutions such as connected care and artificial intelligence, 3D printing and real-life mimicking prosthetics. The availability of data at micro and macro levels has the potential to act as a catalyst for personalized care based on behavioral, cultural, genetic, and psychological needs for patients with musculoskeletal disorders. Realistic algorithms coupled with biomarkers which can identify relevant interventions and alert the care providers regarding any deterioration. Although in the nascent stage currently, 3D printing, exoskeletons, and virtual rehabilitation hold tremendous potential of cost-effective, precise interventions for the patients.

This paper presents results of a qualitative descriptive study conducted to understand parents\' experiences with digital technologies during their transition to parenting (i.e. the period from pre-conception through postpartum). Individuals in southwest Ontario who had become a new parent within the previous 24 months were recruited to participate in a focus group or individual interview. Participants were asked to describe the type of technologies they/their partner used during their transition to parenthood, and how such technologies were used to support their own and their family\'s health. Focus group and interview transcripts were then subjected to thematic analysis using inductive coding. Ten focus groups and three individual interviews were conducted with 26 heterosexual female participants. Participants primarily used digital technologies to: (1) seek health information for a variety of reproductive health issues, and (2) establish social and emotional connections. The nature of such health information work was markedly gendered and was categorized by 2 dominant themes. First, \"\'Let me know when I\'m needed\'\", characterizes fathers\' apparent avoidance of health information seeking and resultant creation of mothers as lay information mediaries. Second, \"Information Curation\", captures participants\' belief that gender biases built-in to popular parenting apps and resources reified the gendered nature of health and health information work during the transition to parenting. Overall, findings indicate that digital technology tailored to new and expecting parents actively reinforced gender norms regarding health information seeking, which creates undue burden on new mothers to become the sole health information seeker and interpreter for their family.

BACKGROUND: Italy was the first country to largely experience the COVID-19 epidemic among other Western countries during the so-called first wave of the COVID-19 pandemic. Proper management of an increasing number of home-quarantined individuals created a significant challenge for health care authorities and professionals. This was especially true when considering the importance of remote surveillance to detect signs of disease progression and consequently regulate access to hospitals and intensive care units on a priority basis.
OBJECTIVE: In this paper, we report on an initiative promoted to cope with the first wave of the COVID-19 epidemic in the Spring/Summer of 2020, in the Autonomous Province of Trento, Italy. A purposefully built app named TreCovid19 was designed to provide dedicated health care staff with a ready-to-use tool for remotely monitoring patients with progressive symptoms of COVID-19, who were home-quarantined during the first wave of the epidemic, and to focus on those patients who, based on their self-reported clinical data, required a quick response from health care professionals.
METHODS: TreCovid19 was rapidly developed to facilitate the monitoring of a selected number of home-quarantined patients with COVID-19 during the very first epidemic wave. The app was built on top of an existing eHealth platform, already in use by the local health authority to provide home care, with the following functionalities: (1) to securely collect and link demographic and clinical information related to the patients and (2) to provide a two-way communication between a multidisciplinary health care team and home-quarantined patients. The system supported patients to self-assess their condition and update the multidisciplinary team on their health status. The system was used between March and June 2020 in the province of Trento.
RESULTS: A dedicated multidisciplinary group of health care professionals adopted the platform over a period of approximately 3 months (from March-end to June 2020) to monitor a total of 170 patients with confirmed COVID-19 during home quarantine. All patients used the system until the end of the initiative. The TreCovid19 system has provided useful insights of possible viability and impact of a technological-organizational asset to manage a potentially critical workload for the health care staff involved in the periodic monitoring of a relevant number of quarantined patients, notwithstanding its limitations given the rapid implementation of the whole initiative.
CONCLUSIONS: The technological and organizational model adopted in response to the COVID-19 pandemic was developed and finalized in a relatively short period during the initial few weeks of the epidemic. The system successfully supported the health care staff involved in the periodic monitoring of an increasing number of home-quarantined patients and provided valuable data in terms of disease surveillance.