Aligning mission to digital health strategy in academic medical centers

Investigating drivers of telecare acceptance to improve healthcare quality for independently living older adults

Contemporary telecare systems facilitate the ability for older adults to age in place, keeping them out of residential care facilities and providing numerous quality-of-life advantages for both care receivers (CRs) and caregivers (CGs). However, despite the acceptance of digital health interventions among older adults and their CGs, telecare adoption has been slower than expected. This paper aimed to compare attitudes toward adopting telecare systems between CRs (aging adults) and their CGs (family/friends). Data were collected via an online survey. Respondents included aging adults concerned about their care (CRs) and older adults who cared for an aging loved one (CGs). Analysis of covariance and partial-least-squares techniques were used to examine the relationships between healthcare concerns for older adults, functional telecare benefits, and telecare acceptance. Concerns for healthcare status, mainly driven by CRs, positively impacted telecare acceptance. However, concerns for mental and physical stimulation had a negative relationship with telecare acceptance, while CGs showed a neutral relationship. Telecare's ability to improve healthcare quality and cognitive stimulation positively impacted its acceptance. CGs mainly drove the impact of healthcare quality on telecare acceptance, while the relationship was not significant for CRs. CRs' age reduced telecare acceptance, and higher educational levels of CGs increased telecare acceptance. We found significant differences in telecare acceptance and its drivers between CGs and CRs in the USA. In addition, we discerned that not all healthcare concerns or functional telecare characteristics influenced telecare acceptance equally between the two. Consequently, telecare providers must consider the different needs of constituencies interested in telecare to support the life quality of older adults.

Digital Health for Oncological Care

ABSTRACT

Digital health tools extend well beyond telemedicine, holding great potential to advance oncological care. We survey digital health and provide recommendations across the health continuum, tailoring them to oncology, including prevention, detection and diagnosis, and treatment and monitoring. Within the prevention realm, we review wellness technologies, cancer screening, mental health solutions, and digital biomarkers. For detection and diagnosis, we describe existing and emerging solutions for remote patient monitoring and various means to capture digital biomarkers, the "digital exam," and "digital outcomes." Treatment and monitoring solutions include telemedicine, chatbots, and digital therapeutics, which are also explored. We also discuss a host of technology enablers that are required for successful implementation and sustainment of digital health-enabled care. Our recommendations pertain to health care systems as well as companies that work with these systems or provide care to patients directly.

Digital Fellowships: Inspiring use of contemporary technologies in applied healthcare

The adoption of digital technologies in healthcare, accelerated by the COVID-19 pandemic, requires a well-prepared workforce capable of implementing those technologies. Here, we examine the role and impact of digital fellowships in facilitating digital transformation in healthcare systems. Digital fellowships are structured educational programmes designed to equip healthcare professionals with advanced digital skills. Focusing on UK-based initiatives like the Topol Digital Fellowship and the Fellowship in Clinical AI, we explore their efforts to prepare healthcare leaders for digital and AI adoption. Each fellowship programme provides participants with hands-on experience in digital healthcare projects and fosters interdisciplinary collaboration and post-fellowship support. We discuss how these fellowships contribute to staff retention by diversifying professional experiences and opportunities. We call for increased collaborations between universities, industry, and professional bodies to integrate lessons from digital fellowships into relevant curricula, acknowledging that digital fellowships are just one piece of the puzzle in bridging the digital skills gap in the healthcare workforce.

Mapping Factors That Affect the Uptake of Digital Therapeutics Within Health Systems: Scoping Review

BACKGROUND

Digital therapeutics are patient-facing digital health interventions that can significantly alter the health care landscape. Despite digital therapeutics being used to successfully treat a range of conditions, their uptake in health systems remains limited. Understanding the full spectrum of uptake factors is essential to identify ways in which policy makers and providers can facilitate the adoption of effective digital therapeutics within a health system, as well as the steps developers can take to assist in the deployment of products.

OBJECTIVE

In this review, we aimed to map the most frequently discussed factors that determine the integration of digital therapeutics into health systems and practical use of digital therapeutics by patients and professionals.

METHODS

A scoping review was conducted in MEDLINE, Web of Science, Cochrane Database of Systematic Reviews, and Google Scholar. Relevant data were extracted and synthesized using a thematic analysis.

RESULTS

We identified 35,541 academic and 221 gray literature reports, with 244 (0.69%) included in the review, covering 35 countries. Overall, 85 factors that can impact the uptake of digital therapeutics were extracted and pooled into 5 categories: policy and system, patient characteristics, properties of digital therapeutics, characteristics of health professionals, and outcomes. The need for a regulatory framework for digital therapeutics was the most stated factor at the policy level. Demographic characteristics formed the most iterated patient-related factor, whereas digital literacy was considered the most important factor for health professionals. Among the properties of digital therapeutics, their interoperability across the broader health system was most emphasized. Finally, the ability to expand access to health care was the most frequently stated outcome measure.

CONCLUSIONS

The map of factors developed in this review offers a multistakeholder approach to recognizing the uptake factors of digital therapeutics in the health care pathway and provides an analytical tool for policy makers to assess their health system's readiness for digital therapeutics.

Training Physicians in the Digital Health Era: How to Leverage the Residency Elective

Digital health is an expanding field and is fundamentally changing the ways health care can be delivered to patients. Despite the changing landscape of health care delivery, medical trainees are not routinely exposed to digital health during training. In this viewpoint, we argue that thoughtfully implemented immersive elective internships with digital health organizations, including start-ups, during residency are valuable for residents, residency programs, and digital health companies. This viewpoint represents the opinions of the authors based on their experience as resident physicians working as interns within a start-up health navigation and telehealth company. First, residents were able to apply their expertise beyond the traditional clinical environment, use creativity to solve health care problems, and learn from different disciplines not typically encountered by most physicians in traditional clinical practice. Second, residency programs were able to strengthen their program's educational offerings and better meet the needs of a heterogenous group of residents who are increasingly seeking nontraditional ways to learn more about care delivery transformation. Third, digital health companies were able to expand their clinical team and receive new insights from physicians in training. We believe that immersive elective internships for physicians in training provide opportunities for experiential learning in a fast-paced environment within a field that is rapidly evolving. By creating similar experiences for other resident physicians, residency programs and digital health companies have a key opportunity to influence future physician-leaders and health care innovators.

Exploring Stakeholder Requirements to enable research and development of AI algorithms in a hospital based generic infrastructure: Results of a Multi-step mixed-methods Study (Preprint)

BACKGROUND

Legal, controlled, and regulated access to high-quality data from academic hospitals currently poses a barrier to the development and testing of new artificial intelligence (AI) algorithms. To overcome this barrier, the German Federal Ministry of Health supports the "pAItient" (Protected Artificial Intelligence Innovation Environment for Patient Oriented Digital Health Solutions for developing, testing and evidence-based evaluation of clinical value) project, with the goal to establish an AI Innovation Environment at the Heidelberg University Hospital, Germany. It is designed as a proof-of-concept extension to the preexisting Medical Data Integration Center.

OBJECTIVE

The first part of the pAItient project aims to explore stakeholders' requirements for developing AI in partnership with an academic hospital and granting AI experts access to anonymized personal health data.

METHODS

We designed a multistep mixed methods approach. First, researchers and employees from stakeholder organizations were invited to participate in semistructured interviews. In the following step, questionnaires were developed based on the participants' answers and distributed among the stakeholders' organizations. In addition, patients and physicians were interviewed.

RESULTS

The identified requirements covered a wide range and were conflicting sometimes. Relevant patient requirements included adequate provision of necessary information for data use, clear medical objective of the research and development activities, trustworthiness of the organization collecting the patient data, and data should not be reidentifiable. Requirements of AI researchers and developers encompassed contact with clinical users, an acceptable user interface (UI) for shared data platforms, stable connection to the planned infrastructure, relevant use cases, and assistance in dealing with data privacy regulations. In a next step, a requirements model was developed, which depicts the identified requirements in different layers. This developed model will be used to communicate stakeholder requirements within the pAItient project consortium.

CONCLUSIONS

The study led to the identification of necessary requirements for the development, testing, and validation of AI applications within a hospital-based generic infrastructure. A requirements model was developed, which will inform the next steps in the development of an AI innovation environment at our institution. Results from our study replicate previous findings from other contexts and will add to the emerging discussion on the use of routine medical data for the development of AI applications.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/42208.