Advancing digital health applications: priorities for innovation in real-world evidence generation

Mobilizing data during a crisis: Building rapid evidence pipelines using multi-institutional real world data

The COVID-19 pandemic generated tremendous interest in using real world data (RWD). Many consortia across the public and private sectors formed in 2020 with the goal of rapidly producing high-quality evidence from RWD to guide medical decision-making, public health priorities, and more. Experiences were gathered from five large consortia on rapid multi-institutional evidence generation during the COVID-19 pandemic. Insights have been compiled across five dimensions: consortium composition, governance structure and alignment of priorities, data sharing, data analysis, and evidence dissemination. The purpose of this piece is to offer guidance on building large-scale multi-institutional RWD analysis pipelines for future public health issues. The composition of each consortium was largely influenced by existing collaborations. A central set of priorities for evidence generation guided each consortium, however different approaches to governance emerged. Challenges surrounding limited access to clinical data due to various contributors were overcome in unique ways. While all consortia used different methods to construct and analyze patient cohorts ranging from centralized to federated approaches, all proved effective for generating meaningful real-world evidence. Actionable recommendations for clinical practice and public health agencies were made from translating insights from consortium analyses. Each consortium was successful in rapidly answering questions about COVID-19 diagnosis and treatment despite all taking slightly different approaches to data sharing and analysis. Leveraging RWD, leveraged in a manner that applies scientific rigor and transparency, can complement higher-level evidence and serve as an important adjunct to clinical trials to quickly guide policy and critical care, especially for a pandemic response.

The three-year evolution of Germany's Digital Therapeutics reimbursement program and its path forward

The 2019 German Digital Healthcare Act introduced the Digital Health Application program, known in German as 'Digitale Gesundheitsanwendungen' (DiGA). The program has established a pioneering model for integrating Digital Therapeutics (DTx) into a healthcare system with scalable and effective reimbursement strategies. To date, the continuous upward trend enabled by this framework has resulted in more than 374,000 DiGA prescriptions, increasingly cementing its role in the German healthcare system. This perspective provides a synthesis of the DiGA program's evolution since its inception three years ago, highlighting trends regarding prescriptions and pricing as well as criticisms and identified shortcomings. It further discusses forthcoming legislative amendments, including the anticipated integration of higher-risk medical devices, which have the potential to significantly transform the program. Despite encountering challenges related to effectiveness, evidence requirements, and integration within the healthcare system, the DiGA program continues to evolve and serves as a seminal example for the integration of DTx, offering valuable insights for healthcare systems globally.

Digital wearable insole-based identification of knee arthropathies and gait signatures using machine learning

Gait is impaired in musculoskeletal conditions, such as knee arthropathy. Gait analysis is used in clinical practice to inform diagnosis and monitor disease progression or intervention response. However, clinical gait analysis relies on subjective visual observation of walking as objective gait analysis has not been possible within clinical settings due to the expensive equipment, large-scale facilities, and highly trained staff required. Relatively low-cost wearable digital insoles may offer a solution to these challenges. In this work, we demonstrate how a digital insole measuring osteoarthritis-specific gait signatures yields similar results to the clinical gait-lab standard. To achieve this, we constructed a machine learning model, trained on force plate data collected in participants with knee arthropathy and controls. This model was highly predictive of force plate data from a validation set (area under the receiver operating characteristics curve [auROC] = 0.86; area under the precision-recall curve [auPR] = 0.90) and of a separate, independent digital insole dataset containing control and knee osteoarthritis subjects (auROC = 0.83; auPR = 0.86). After showing that digital insole-derived gait characteristics are comparable to traditional gait measurements, we next showed that a single stride of raw sensor time-series data could be accurately assigned to each subject, highlighting that individuals using digital insoles can be identified by their gait characteristics. This work provides a framework for a promising alternative to traditional clinical gait analysis methods, adds to the growing body of knowledge regarding wearable technology analytical pipelines, and supports clinical development of at-home gait assessments, with the potential to improve the ease, frequency, and depth of patient monitoring.

Which behaviour change techniques work best for diabetes self-management mobile apps? Results from a systematic review and meta-analysis of randomised controlled trials

BACKGROUND

Self-management is pivotal in addressing noncommunicable diseases, such as diabetes. The increased availability of digital behaviour change interventions (DBCIs) delivered through mobile health apps offers unprecedented opportunities to enhance self-management and improve health outcomes. However, little is known about the characteristics of DBCIs for diabetes that significantly impact glycaemic control. Therefore, our systematic review with meta-analysis aimed to summarize characteristics and behaviour change components in DBCIs for diabetes self-management and explore potential associations with metabolic outcomes.

METHODS

A systematic search was conducted in PubMed, Embase, the Cochrane Central Register of Controlled Trials, and Scopus to identify randomized controlled trials published until November 2023. The main outcome variable was the change in the mean difference of HbA1c levels between baseline and follow-up across intervention and control groups. Random-effects meta-regression was used to explore variation in glycaemic control as a function of prespecified characteristics of study designs and app interventions.

FINDINGS

A total of 57 studies was included in the analysis, showing a statistically significant percentage point reduction in HbA1c for the intervention group compared to the control arm (-0.36, 95% CI = -0.46 to -0.26, p < 0.001). The inclusion of "self-monitoring of behaviour" as a behaviour change technique (β = -0.22, p = 0.04) and "taking medication" as a target behaviour (β = -0.20, p = 0.05) was associated with improved metabolic outcomes.

INTERPRETATION

Our analyses endorse the use of diabetes self-management apps, highlighting characteristics statistically associated with intervention effectiveness and guiding the design of more effective DBCIs.

FUNDING

This project received funding from the European Union's Horizon 2020 programme.

Tracing Digital Therapeutics Research Across Medical Specialties: Evidence from ClinicalTrails.gov

Digital therapeutics (DTx), evidence-based software interventions for preventing, managing, or treating medical disorders, have rapidly evolved with healthcare's shift toward online, patient-centric solutions. This study scrutinizes DTx clinical trials from 2005 to 2022, analyzing their growth, funding, underlying medical specialties, and other R&D characteristics, using ClinicalTrials.gov data. Our analysis includes trials categorized via the ICD-11 system, covering active, recruiting, or completed studies and considering trials listing multiple conditions. In analyzing 5,889 registered DTx trials, we document a more than five-fold increase in such trials since 2011, and a compound annual growth rate of 22.82% since 2005. While most trials were single-center, the median number of study subjects increased in recent years, driven by larger interventional trials. The key disciplines driving this growth were psychiatry, neurology, oncology, and endocrinology. Mental health dominated DTx trials in recent years, led by neurocognitive disorders, substance abuse disorders, and mood disorders. Industry funding varied across disciplines and was particularly high in visual system diseases and dermatology. DTx trials have surged since 2005, accelerated by recent growth in mental health trials. These trends mirror developments toward remote healthcare delivery, amplified by digital health investments during the COVID-19 pandemic. Growing numbers of participants in DTx trials point to increased demand for more robust trials. However, because most trials are single-center and country-specific, more international cooperation and harmonized evaluation standards will be essential for DTx trials to become more efficient and provide validation across countries, health systems, and groups of individuals.

The German Fast Track Toward Reimbursement of Digital Health Applications: Opportunities and Challenges for Manufacturers, Healthcare Providers, and People With Diabetes

BACKGROUND

Digital health applications (DiGA) supporting the management of diabetes are among the most commonly available digital health technologies. However, transparent quality assurance of DiGA and clinical proof of a positive healthcare effect is often missing, which creates skepticism of some stakeholders regarding the usage and reimbursement of these applications.

METHODS

This article reviews the recently established fast-track integration of DiGA in the German reimbursement market, with emphasis on the current impact for manufacturers, healthcare providers, and people with diabetes. The German DiGA fast track is contextualised with corresponding initiatives in Europe.

RESULTS

The option of a provisional prescription and reimbursement of DiGA while proving a positive healthcare effect in parallel may expedite the adoption of DiGA in Germany and beyond. However, hurdles for a permanent prescription and reimbursement of DiGA are high and only one of 12 that have achieved this status specifically addresses people with diabetes.

CONCLUSION

The DiGA fast track needs to be further enhanced to cope with remaining skepticism and contribute even more to a value-based diabetes care.

[Digital medicine in neurological research-Between hype and evidence]

BACKGROUND

The rapid advancement of digital medicine and health technologies in neurology offers both significant potential and challenges. This article outlines fundamental aspects of digital medicine related to neurological research and highlights application examples of digital technologies in neurological research.

AIM

To provide a comprehensive overview of current digital developments in neurology and their impact on neurological research.

MATERIAL AND METHODS

In this narrative review articles from various sources and references related to digital medicine and health technologies in neurology were compiled and analyzed.

RESULTS AND DISCUSSION

The data presented indicate that digital health technologies and digital therapeutics have the potential to decisively shape neurological care and research; however, it is emphasized that a critical evaluation and evidence-based approach to these technologies are essential to determine their actual value in neurology.

Digital Transformation of Public Health for Noncommunicable Diseases: Narrative Viewpoint of Challenges and Opportunities

The recent SARS-CoV-2 pandemic underscored the effectiveness and rapid deployment of digital public health interventions, notably the digital proximity tracing apps, leveraging Bluetooth capabilities to trace and notify users about potential infection exposures. Backed by renowned organizations such as the World Health Organization and the European Union, digital proximity tracings showcased the promise of digital public health. As the world pivots from pandemic responses, it becomes imperative to address noncommunicable diseases (NCDs) that account for a vast majority of health care expenses and premature disability-adjusted life years lost. The narrative of digital transformation in the realm of NCD public health is distinct from infectious diseases. Public health, with its multifaceted approach from disciplines such as medicine, epidemiology, and psychology, focuses on promoting healthy living and choices through functions categorized as "Assessment," "Policy Development," "Resource Allocation," "Assurance," and "Access." The power of artificial intelligence (AI) in this digital transformation is noteworthy. AI can automate repetitive tasks, facilitating health care providers to prioritize personal interactions, especially those that cannot be digitalized like emotional support. Moreover, AI presents tools for individuals to be proactive in their health management. However, the human touch remains irreplaceable; AI serves as a companion guiding through the health care landscape. Digital evolution, while revolutionary, poses its own set of challenges. Issues of equity and access are at the forefront. Vulnerable populations, whether due to economic constraints, geographical barriers, or digital illiteracy, face the threat of being marginalized further. This transformation mandates an inclusive strategy, focusing on not amplifying existing health disparities but eliminating them. Population-level digital interventions in NCD prevention demand societal agreement. Policies, like smoking bans or sugar taxes, though effective, might affect those not directly benefiting. Hence, all involved parties, from policy makers to the public, should have a balanced perspective on the advantages, risks, and expenses of these digital shifts. For a successful digital shift in public health, especially concerning NCDs, AI's potential to enhance efficiency, effectiveness, user experience, and equity-the "quadruple aim"-is undeniable. However, it is vital that AI-driven initiatives in public health domains remain purposeful, offering improvements without compromising other objectives. The broader success of digital public health hinges on transparent benchmarks and criteria, ensuring maximum benefits without sidelining minorities or vulnerable groups. Especially in population-centric decisions, like resource allocation, AI's ability to avoid bias is paramount. Therefore, the continuous involvement of stakeholders, including patients and minority groups, remains pivotal in the progression of AI-integrated digital public health.

An intriguing vision for transatlantic collaborative health data use and artificial intelligence development

Our traditional approach to diagnosis, prognosis, and treatment, can no longer process and transform the enormous volume of information into therapeutic success, innovative discovery, and health economic performance. Precision health, i.e., the right treatment, for the right person, at the right time in the right place, is enabled through a learning health system, in which medicine and multidisciplinary science, economic viability, diverse culture, and empowered patient's preferences are digitally integrated and conceptually aligned for continuous improvement and maintenance of health, wellbeing, and equity. Artificial intelligence (AI) has been successfully evaluated in risk stratification, accurate diagnosis, and treatment allocation, and to prevent health disparities. There is one caveat though: dependable AI models need to be trained on population-representative, large and deep data sets by multidisciplinary and multinational teams to avoid developer, statistical and social bias. Such applications and models can neither be created nor validated with data at the country, let alone institutional level and require a new dimension of collaboration, a cultural change with the establishment of trust in a precompetitive space. The Data for Health (#DFH23) conference in Berlin and the Follow-Up Workshop at Harvard University in Boston hosted a representative group of stakeholders in society, academia, industry, and government. With the momentum #DFH23 created, the European Health Data Space (EHDS) as a solid and safe foundation for consented collaborative health data use and the G7 Hiroshima AI process in place, we call on citizens and their governments to fully support digital transformation of medicine, research and innovation including AI.

The value of using real-world evidence as a source of clinical evidence in the European medical device regulations: a mixed methods study

OBJECTIVES

This study investigates the benefits, limitations and awareness of using Real World Evidence and Real World Data for post-market clinical follow-up studies and clinical evaluation reports in the European Medical Device Regulations.

METHODOLOGY

A mixed methods study was utilized with qualitative interviews and a quantitative survey.

RESULTS

The findings from the study demonstrate that in the case of the Medical Device Regulations, opportunities exist for manufacturers of legacy devices to conduct Real World Evidence studies to bridge gaps in clinical evidence. The primary value of Real World Evidence lies in its ability to provide an accurate and, therefore, more reliable measure of device safety and performance. As a measure of safety and performance, it supplements clinical evidence generated from pre and post-market clinical investigations, reducing the costs associated with these studies and supporting the manufacturer's benefit: risk conclusion.

CONCLUSION

This study provides insight into how the medical device industry could utilize Real World Evidence and have an initiative in the EU similar to the FDA-sponsored NESTcc partnership. This would aid medical device manufacturers in transitioning to the MDR clinical evaluation requirements and mitigate the impact on medical device availability in the EU.

Developing an Artificial Intelligence-Driven Nudge Intervention to Improve Medication Adherence: A Human-Centred Design Approach

To improve medication adherence, we co-developed a digital, artificial intelligence (AI)-driven nudge intervention with stakeholders (patients, providers, and technologists). We used a human-centred design approach to incorporate user needs in creating an AI-driven nudge tool. We report the findings of the first stage of a multi-phase project: understanding user needs and ideating solutions. We interviewed healthcare providers (n = 10) and patients (n = 10). Providers also rated example nudge interventions in a survey. Stakeholders felt the intervention could address existing deficits in medication adherence tracking and were optimistic about the solution. Participants identified flexibility of the intervention, including mode of delivery, intervention intensity, and the ability to stratify to user ability and needs, as critical success factors. Reminder nudges and provision of healthcare worker contact were rated highly by all. Conversely, patients perceived incentive-based nudges poorly. Finally, participants suggested that user burden could be minimised by leveraging existing software (rather than creating a new App) and simplifying or automating the data entry requirements where feasible. Stakeholder interviews generated in-depth data on the perspectives and requirements for the proposed solution. The participatory approach will enable us to incorporate user needs into the design and improve the utility of the intervention. Our findings show that an AI-driven nudge tool is an acceptable and appropriate solution, assuming it is flexible to user requirements.

Two years of approved digital health applications in Germany - Perspectives and experiences of general practitioners with an affinity for their use

BACKGROUND

Since 2020, physicians in Germany can prescribe approved digital health applications (DHAs) with the costs covered by the health system. There has so far been a lack of studies on attitudes and experiences amongst GPs in using DHAs.

OBJECTIVES

The aim was to elucidate the experiences and observations of GPs that have used DHAs in health care and to examine the conditions necessary for DHAs to gain a foothold in primary care according to the GPs.

METHODS

In 2022, 96 qualitative semi-standardised interviews were conducted with German GPs with experience in prescribing DHAs. The GPs were all organised in digitalisation-oriented physicians' associations. Fifty-four interviews were carried out in person and 42 by phone. The data were analysed according to qualitative content analysis.

RESULTS

Unlike health apps, the interviewees saw DHAs as reliable tools for enhancing the relationship between GPs and their patients. They saw the DHAs they had been prescribing as useful and reported various benefits, including improvements in compliance, mobility, information for patients and weight reduction. The physicians also saw room for further improvement (usability, gamification, training, information sources). Interviewees saw the inclusion of DHAs in evidence-based guidelines as a major step forward.

CONCLUSION

The interviewees rated DHAs favourably regarding healthcare potential and as safer and more reliable than conventional health apps. Many saw benefits to healthcare from using such applications. From the interviewees' point of view, DHAs can be integrated more effectively into patient care.

Dynamic HTA for digital health solutions: opportunities and challenges for patient-centered evaluation

OBJECTIVES

Germany's 2019 Digital Healthcare Act (Digitale-Versorgung-Gesetz, or DVG) created a number of opportunities for the digital transformation of the healthcare delivery system. Key among these was the creation of a reimbursement pathway for patient-centered digital health applications (digitale Gesundheitsanwendungen, or DiGA). Worldwide, this is the first structured pathway for "prescribable" health applications at scale. As of October 10, 2023, 49 DiGA were listed in the official directory maintained by Germany's Federal Institute for Drugs and Medical Devices (BfArM); these are prescribable by physicians and psychotherapists and reimbursed by the German statutory health insurance system for all its 73 million beneficiaries. Looking ahead, a major challenge facing DiGA manufacturers will be the generation of the evidence required for ongoing price negotiations and reimbursement. Current health technology assessment (HTA) methods will need to be adapted for DiGA.

METHODS

We describe the core issues that distinguish HTA in this setting: (i) explicit allowance for more flexible research designs, (ii) the nature of initial evidence generation, which can be delivered (in its final form) up to one year after becoming reimbursable, and (iii) the dynamic nature of both product development and product evaluation. We present the digital health applications in the German DiGA scheme as a case study and highlight the role of RWE in the successful evaluation of DiGA on an ongoing basis.

RESULTS

When a DiGA is likely to be updated and assessed regularly, full-scale RCTs are infeasible; we therefore make the case for using real-world data and real-world evidence (RWE) for dynamic HTAs.

CONCLUSIONS

Continous evaluation using RWD is a regulatory innovation that can help improve the quality of DiGAs on the market.

Proposing a health-specific organizational impact framework to evaluate organizational impacts in health technology assessments

OBJECTIVES

Health technology assessments (HTAs) have traditionally included clinical and cost-effectiveness evaluation of new health technologies (HTs). However, new HTs can generate important organizational impacts (OIs) that influence their overall value. OIs are currently not clearly identified and evaluated in HTA procedures and tools are limited. To address this issue, a comprehensive framework that allows to assess OIs of new HTs in HTAs is proposed.

METHODS

A working and methodological group identified the Oslo Manual 2018, 4th edition, OECD/Eurostat, on the objectives and outcomes of commercial innovations as the basis for the OIs framework for HTAs. The Oslo Manual was translated to the healthcare sector and adapted to HTA procedures through a three-step process.

RESULTS

The framework is composed of three main parts. Part I tackles the context of the evaluation, Part II the categories of impacts and the specific impacts - in total, 16 OIs were identified - and Part III the stakeholders involved. The central part of the framework is Part II, and consists of three categories of impacts: (i) on the care process, (ii) on the stakeholders' capabilities and skills, and (iii) on society or the community.

CONCLUSIONS

This framework provides a comprehensive and structured basis to document OIs of new HTs. It thus contributes to the extension of HTA evaluation criteria to other dimensions than clinical and economic aspects, that is, organizational aspects. Some of its intrinsic limitations and the questions they raise in the field for policy-makers, practitioners, and researchers are discussed.

Management of multiple sclerosis fatigue in the digital age: from assessment to treatment

Fatigue is one of the most disabling symptoms of Multiple Sclerosis (MS), affecting more than 80% of patients over the disease course. Nevertheless, it has a multi-faceted and complex nature, making its diagnosis, evaluation, and treatment extremely challenging in clinical practice. In the last years, digital supporting tools have emerged to support the care of people with MS. These include not only smartphone or table-based apps, but also wearable devices or novel techniques such as virtual reality. Furthermore, an additional effective and cost-efficient tool for the therapeutic management of people with fatigue is becoming increasingly available. Virtual reality and e-Health are viable and modern tools to both assess and treat fatigue, with a variety of applications and adaptability to patient needs and disability levels. Most importantly, they can be employed in the patient's home setting and can not only bridge clinic visits but also be complementary to the monitoring and treatment means for those MS patients who live far away from healthcare structures. In this narrative review, we discuss the current knowledge and future perspectives in the digital management of fatigue in MS. These may also serve as sources for research of novel digital biomarkers in the identification of disease activity and progression.

Promoting the systematic use of real-world data and real-world evidence for digital health technologies across Europe: a consensus framework

Despite the acceleration in the use of digital health technologies across different aspects of the healthcare system, the full potential of real-world data (RWD) and real-world evidence (RWE) arising from the technologies is not being utilised in decision-making. We examine current national efforts and future opportunities to systematically use RWD and RWE in decision-making in five countries (Estonia, Finland, Germany, Italy and the United Kingdom), and then develop a framework for promotion of the systematic use of RWD and RWE. A review assesses current national efforts, complemented with a three-round consensus-building exercise among an international group of experts (n1 = 44, n2 = 24, n3 = 24) to derive key principles. We find that Estonia and Finland have invested and developed digital health-related policies for several years; Germany and Italy are the more recent arrivals, while the United Kingdom falls somewhere in the middle. Opportunities to promote the systematic use of RWD and RWE were identified for each country. Eight building blocks principles were agreed through consensus, relating to policy scope, institutional role and data collection. Promoting post-market surveillance and digital health technology vigilance ought to rely on clarity in scope and data collection with consensus reached on eight principles to leverage RWD and RWE.

Hybrid Controlled Clinical Trials Using Concurrent Registries in Amyotrophic Lateral Sclerosis: A Feasibility Study

Hybrid designs with both randomized arms and an external control cohort preserve key features of randomization and utilize external information to augment clinical trials. In this study, we propose to leverage high-quality, patient-level concurrent registries to enhance clinical trials and illustrate the impact on trial design for amyotrophic lateral sclerosis. The proposed methodology was evaluated in a randomized, placebo-controlled clinical trial. We used patient-level information from a well-defined, population-based registry, that was running parallel to the randomized clinical trial, to identify concurrently nonparticipating, eligible patients who could be matched with trial participants, and integrate them into the statistical analysis. We assessed the impact of the addition of the external controls on the treatment effect estimate, precision, and time to reach a conclusion. During the runtime of the trial, a total of 1,141 registry patients were alive; 473 (41.5%) of them fulfilled the eligibility criteria and 133 (11.7%) were enrolled in the study. A matched control population could be identified among the nonparticipating patients. Augmenting the randomized controls with matched external controls could have avoided unnecessary randomization of 17 patients (-12.8%) as well as reducing the study duration from 30.1 months to 22.6 months (-25.0%). Matching eligible external controls from a different calendar period led to bias in the treatment effect estimate. Hybrid trial designs utilizing a concurrent registry with rigorous matching can minimize bias due to a mismatch in calendar time and differences in standard of care, and may accelerate the development of new treatments.

Pain experience of lung cancer patients during home recovery after surgery: A qualitative descriptive study

BACKGROUND

Patients with lung cancer surgery often suffer pain after discharge. However, there is limited evidence to describe the pain experience from the qualitative investigation. This study was designed to describe the pain experience of lung cancer patients during home recovery after surgery and to provide evidence for developing pain management strategies.

METHODS

This qualitative descriptive study recruited 35 patients who had received lung resection and were discharged by purposive sampling from May to July 2022. Mobile phone interviews were conducted to collect views on patients' pain experience after discharge. The interviews were audio-recorded and converted verbatim into standard text, and the data were iteratively thematic analyzed.

RESULTS

A thematic framework was identified for three themes: perception and impact of pain, coping styles for pain, and unmet needs for pain. Whether short or long-term after discharge, patients complain that they suffer from different degrees and types of pain, causing them a "double burden" physically and mentally. The lack of knowledge about pain may lead them to adopt very different coping styles and desire professional continuous pain management.

CONCLUSIONS

This study may help clarify the status of pain problems that patients face after lung cancer surgery and provides multiple dimensions of pain assessment and management objectives for quantitative research. We call on medical staff to pay attention to patients' perspectives and related needs after discharge and formulate targeted management strategies to reduce pain and improve their quality of life.

Digital Health Reimbursement Strategies of 8 European Countries and Israel: Scoping Review and Policy Mapping

BACKGROUND

The adoption of digital health care within health systems is determined by various factors, including pricing and reimbursement. The reimbursement landscape for digital health in Europe remains underresearched. Although various emergency reimbursement decisions were made during the COVID-19 pandemic to enable health care delivery through videoconferencing and asynchronous care (eg, digital apps), research so far has primarily focused on the policy innovations that facilitated this outside of Europe.

OBJECTIVE

This study examines the digital health reimbursement strategies in 8 European countries (Belgium, France, Germany, Italy, the Netherlands, Poland, Sweden, and the United Kingdom) and Israel.

METHODS

We mapped available digital health reimbursement strategies using a scoping review and policy mapping framework. We reviewed the literature on the MEDLINE, Embase, Global Health, and Web of Science databases. Supplementary records were identified through Google Scholar and country experts.

RESULTS

Our search strategy yielded a total of 1559 records, of which 40 (2.57%) were ultimately included in this study. As of August 2023, digital health solutions are reimbursable to some extent in all studied countries except Poland, although the mechanism of reimbursement differs significantly across countries. At the time of writing, the pricing of digital health solutions was mostly determined through discussions between national or regional committees and the manufacturers of digital health solutions in the absence of value-based assessment mechanisms. Financing digital health solutions outside traditional reimbursement schemes was possible in all studied countries except Poland and typically occurs via health innovation or digital health-specific funding schemes. European countries have value-based pricing frameworks that range from nonexistent to embryonic.

CONCLUSIONS

Studied countries show divergent approaches to the reimbursement of digital health solutions. These differences may complicate the ability of patients to seek cross-country health care in another country, even if a digital health app is available in both countries. Furthermore, the fragmented environment will present challenges for developers of such solutions, as they look to expand their impact across countries and health systems. An increased emphasis on developing a clear conceptualization of digital health, as well as value-based pricing and reimbursement mechanisms, is needed for the sustainable integration of digital health. This study can therein serve as a basis for further, more detailed research as the field of digital health reimbursement evolves.

Non-pharmaceutical interventions to optimize cancer immunotherapy

The traditional picture of cancer patients as weak individuals requiring maximum rest and protection is beginning to dissolve. Too much focus on the medical side and one's own vulnerability and mortality might be counterproductive and not doing justice to the complexity of human nature. Unlike cytotoxic and lympho-depleting treatments, immune-engaging therapies strengthen the immune system and are typically less harmful for patients. Thus, cancer patients receiving checkpoint inhibitors are not viewed as being vulnerable per se, at least not in immunological and physical terms. This perspective article advocates a holistic approach to cancer immunotherapy, with an empowered patient in the center, focusing on personal resources and receiving domain-specific support from healthcare professionals. It summarizes recent evidence on non-pharmaceutical interventions to enhance the efficacy of immune checkpoint blockade and improve quality of life. These interventions target behavioral factors such as diet, physical activity, stress management, circadian timing of checkpoint inhibitor infusion, and waiving unnecessary co-medication curtailing immunotherapy efficacy. Non-pharmaceutical interventions are universally accessible, broadly applicable, instantly actionable, scalable, and economically sustainable, creating value for all stakeholders involved. Most importantly, this holistic framework re-emphasizes the patient as a whole and harnesses the full potential of anticancer immunity and checkpoint blockade, potentially leading to survival benefits. Digital therapeutics are proposed to accompany the patients on their mission toward change in lifestyle-related behaviors for creating optimal conditions for treatment efficacy and personal growth.

Digital tool to identify and monitor regorafenib-associated hand-foot skin reactions: A proof-of-concept study protocol

BACKGROUND

The FACET study is a prospective, open-label, low risk interventional clinical trial aiming at exploring the fitness-for-purpose and usability of an electronic device suite for the detection of hand-foot skin reaction symptoms in patients with metastatic colorectal cancer treated with regorafenib.

METHODS

38 patients with metastatic colorectal cancer are being selected in 6 centers in France, and will be followed for 2 regorafenib treatment cycles, or for approximately 56 days. The electronic device suite includes connected insoles and a mobile device equipped with a camera and a companion application with electronic patient-reported outcomes questionnaires and educational material. The FACET study is intended to provide information useful for the improvement of the electronic device suite and its usability before the testing of its robustness in a larger follow-up study. This paper describes the protocol of the FACET study and discusses the limitations to consider for the implementation of digital devices in real-life practice.

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.

Association of digital measures and self-reported fatigue: a remote observational study in healthy participants and participants with chronic inflammatory rheumatic disease

Background

Fatigue is a subjective, complex and multi-faceted phenomenon, commonly experienced as tiredness. However, pathological fatigue is a major debilitating symptom associated with overwhelming feelings of physical and mental exhaustion. It is a well-recognized manifestation in chronic inflammatory rheumatic diseases, such as Sjögren's Syndrome and Systemic Lupus Erythematosus and an important predictor of patient's health-related quality of life (HRQoL). Patient reported outcome questions are the key instruments to assess fatigue. To date, there is no consensus about reliable quantitative assessments of fatigue.

Method

Observational data for a period of one month were collected from 296 participants in the United States. Data comprised continuous multimodal digital data from Fitbit, including heart rate, physical activity and sleep features, and app-based daily and weekly questions covering various HRQoL factors including pain, mood, general physical activity and fatigue. Descriptive statistics and hierarchical clustering of digital data were used to describe behavioural phenotypes. Gradient boosting classifiers were trained to classify participant-reported weekly fatigue and daily tiredness from multi-sensor and other participant-reported data, and extract a set of key predictive features.

Results

Cluster analysis of Fitbit parameters highlighted multiple digital phenotypes, including sleep-affected, fatigued and healthy phenotypes. Features from participant-reported data and Fitbit data both contributed as key predictive features of weekly physical and mental fatigue and daily tiredness. Participant answers to pain and depressed mood-related daily questions contributed the most as top features for predicting physical and mental fatigue, respectively. To classify daily tiredness, participant answers to questions on pain, mood and ability to perform daily activities contributed the most. Features related to daily resting heart rate and step counts and bouts were overall the most important Fitbit features for the classification models.

Conclusion

These results demonstrate that multimodal digital data can be used to quantitatively and more frequently augment pathological and non-pathological participant-reported fatigue.

Methods for Navigating the Mobile Mental Health App Landscape for Clinical Use

There are over 10,000 mental health and wellness apps on the market. Apps offer the opportunity to increase access to mental health care. However, with many apps to choose from and an app landscape that is largely unregulated, it can be difficult to incorporate this technology into clinical practice. The first step towards achieving this goal is to identify clinically relevant and appropriate apps. The purpose of this review is to discuss app evaluation, raise awareness of considerations involved in implementing mental health apps into clinical care, and provide an example of how apps can be used effectively in the clinical space. We discuss the current regulatory environment for health apps, how to evaluate apps, and implement them into clinical practice. We also showcase a digital clinic where apps are integrated into the clinical workflow and discuss barriers to app implementation. Mental health apps have the potential to increase access to care if they are clinically effective, easy to use, and protect patient privacy. Learning how to find, evaluate, and implement quality apps into practice is key in harnessing this technology for the benefit of patients.

Evidence requirements of permanently listed digital health applications (DiGA) and their implementation in the German DiGA directory: an analysis

BACKGROUND

With its digital health application (DiGA)-system, Germany is considered one of Europe's pioneers in the field of evidence-based digital health. Incorporating DiGA into standard medical care must be based on evidence-based success factors; however, a comprehensive overview of the evidence required of scientific studies for their approval is lacking.

OBJECTIVE

The study aims to, (1) identify specific requirements defined by the Federal Institute for Drugs and Medical Devices (German: Bundesinstitut für Arzneimittel- und Medizinprodukte; BfArM) to design adequate studies, proving a positive healthcare effect, and (2) to assess the evidence given for applications permanently listed in the DiGA directory.

METHODS

A multi-step approach was used: (1) identification of the evidence requirements for applications permanently listed in the DiGA directory, (2) identification of the evidence available supporting them.

RESULTS

All DiGA permanently listed in the DiGA directory (13 applications) are included in the formal analysis. Most DiGA addressed mental health (n = 7), and can be prescribed for one or two indications (n = 10). All permanently listed DiGA have demonstrated their positive healthcare effect through a medical benefit, and most of them provide evidence for one defined primary endpoint. All DiGA manufacturers conducted a randomized controlled trial.

DISCUSSION

It is striking that- although patient-relevant structural and procedural improvements show high potential for improving care, especially in terms of processes - all DiGA have provided a positive care effect via a medical benefit. Although BfArM accepts study designs with a lower level of evidence for the proof of a positive healthcare effect, all manufacturers conducted a study with a high level of evidence.

CONCLUSION

The results of this analysis indicate that permanently listed DiGA meet higher standards than required by the guideline.

Increasing digitalization is associated with anxiety and depression: A Google Ngram analysis

The prevalence of anxiety disorders and depression are rising worldwide. Studies investigating risk factors on a societal level leading to these rises are so far limited to social-economic status, social capital, and unemployment, while most such studies rely on self-reports to investigate these factors. Therefore, our study aims to evaluate the impact of an additional factor on a societal level, namely digitalization, by using a linguistic big data approach. We extend related work by using the Google Books Ngram Viewer (Google Ngram) to retrieve and adjust word frequencies from a large corpus of books (8 million books or 6 percent of all books ever published) and to subsequently investigate word changes in terms of anxiety disorders, depression, and digitalization. Our analyses comprise and compare data from six languages, British English, German, Spanish, Russian, French, and Italian. We also retrieved word frequencies for the control construct "religion". Our results show an increase in word frequency for anxiety, depression, and digitalization over the last 50 years (r = .79 to .89, p < .001), a significant correlation between the frequency of anxiety and depression words (r = .98, p < .001), a significant correlation between the frequency of anxiety and digitalization words (r = .81, p < .001), and a significant correlation between the frequency of depression and anxiety words (r = .81, p < .001). For the control construct religion, we found no significant correlations for word frequency over the last 50 years and no significant correlation between the frequency of anxiety and depression words. Our results showed a negative correlation between the frequency of depression and religion words (r = -.25, p < .05). We also improved the method by excluding terms with double meanings detected by 73 independent native speakers. Implications for future research and professional and clinical implications of these findings are discussed.

Postmarketing Follow-Up of a Digital Home Exercise Program for Back, Hip, and Knee Pain: Retrospective Observational Study With a Time-Series and Matched-Pair Analysis

BACKGROUND

Musculoskeletal conditions are the main drivers of global disease burden and cause significant direct and indirect health care costs. Digital health applications improve the availability of and access to adequate care. The German health care system established a pathway for the approval of "Digitale Gesundheitsanwendungen" (DiGAs; Digital Health Applications) as collectively funded medical services through the "Digitale-Versorgung-Gesetz" (Digital Health Care Act) in 2019.

OBJECTIVE

This article presents real-world prescription data collected through the smartphone-based home exercise program "Vivira," a fully approved DiGA, regarding its effect on self-reported pain intensity and physical inability in patients with unspecific and degenerative pain in the back, hip, and knee.

METHODS

This study included 3629 patients (71.8% [2607/3629] female; mean age 47 years, SD 14.2 years). The primary outcome was the self-reported pain score, which was assessed with a verbal numerical rating scale. The secondary outcomes were self-reported function scores. To analyze the primary outcome, we used a 2-sided Skillings-Mack test. For function scores, a time analysis was not feasible; therefore, we calculated matched pairs using the Wilcoxon signed-rank test.

RESULTS

Our results showed significant reductions in self-reported pain intensity after 2, 4, 8, and 12 weeks in the Skillings-Mack test (T₃₆₂₈=5308; P<.001). The changes were within the range of a clinically relevant improvement. Function scores showed a generally positive yet more variable response across the pain areas (back, hip, and knee).

CONCLUSIONS

This study presents postmarketing observational data from one of the first DiGAs for unspecific and degenerative musculoskeletal pain. We noted significant improvements in self-reported pain intensity throughout the observation period of 12 weeks, which reached clinical relevance. Additionally, we identified a complex response pattern of the function scores assessed. Lastly, we highlighted the challenges of relevant attrition at follow-up and the potential opportunities for evaluating digital health applications. Although our findings do not have confirmatory power, they illustrate the potential benefits of digital health applications to improve the availability of and access to medical care.

TRIAL REGISTRATION

German Clinical Trials Register DRKS00024051; https://drks.de/search/en/trial/DRKS00024051.

[Digitalization in healthcare: today and in the future]

Although Germany continues to struggle with the digital transformation of healthcare, there is reason for optimism. The political will to improve healthcare with digital technologies has been underpinned by numerous legal initiatives since 2018. In addition, there is growing acceptance among healthcare providers and the population. The latter has clearly been driven by the corona pandemic, which underscored the need for more digitized care.Digitalization in healthcare has three key drivers: the rapid technological development in data processing, the ever-improving understanding of the biological basis of human life, and growing patient sovereignty coupled with a growing desire for transparency. Prerequisites for digital medicine are data interoperability and the establishment of a networking (telematics) infrastructure (TI). The status of the most important digital TI applications affecting German healthcare are described: the electronic patient record (ePA) as its core as well as electronic prescriptions, medication plans, and communication tools such as Communication in Medicine (KIM) and TI Messenger (TIM). In addition, various telemedical offerings are discussed as well as the introduction of digital health applications (DiGA) into the statutory healthcare system, which Germany has pioneered. Furthermore, the use of medical data as the basis for artificial intelligence (AI) algorithms is discussed. While helpful and capable of improving diagnostics as well as medical therapy, such AI tools will not replace doctors and nurses.

Reverse Engineering of Digital Measures: Inviting Patients to the Conversation

Background

Digital measures offer an unparalleled opportunity to create a more holistic picture of how people who are patients behave in their real-world environments, thereby establishing a better connection between patients, caregivers, and the clinical evidence used to drive drug development and disease management. Reaching this vision will require achieving a new level of co-creation between the stakeholders who design, develop, use, and make decisions using evidence from digital measures.

Summary

In September 2022, the second in a series of meetings hosted by the Swiss Federal Institute of Technology in Zürich, the Foundation for the National Institutes of Health Biomarkers Consortium, and sponsored by Wellcome Trust, entitled "Reverse Engineering of Digital Measures," was held in Zurich, Switzerland, with a broad range of stakeholders sharing their experience across four case studies to examine how patient centricity is essential in shaping development and validation of digital evidence generation tools.

Key Messages

In this paper, we discuss progress and the remaining barriers to widespread use of digital measures for evidence generation in clinical development and care delivery. We also present key discussion points and takeaways in order to continue discourse and provide a basis for dissemination and outreach to the wider community and other stakeholders. The work presented here shows us a blueprint for how and why the patient voice can be thoughtfully integrated into digital measure development and that continued multistakeholder engagement is critical for further progress.

Current challenges for evaluating mobile health applications

As mobile health applications continue to proliferate without clear regulation, the need for app evaluation frameworks to offer guidance to patients and clinicians also expands. However, this expanding number of app evaluation frameworks itself can be a source of confusion and often contradictory recommendations. In pursuit of better frameworks that offer innovation for app evaluation, we present 4 challenges that app evaluation frameworks must overcome as well as examples from our own experience toward overcoming them. The recommendations are applicable to all health apps from any field of medicine, although we use examples from mental health as they are illustrative.

[Evidence of positive care effects by digital health apps-methodological challenges and approaches]

Since 2020, digital health applications (DiGA) can be prescribed at the expense of the German statutory health insurance (SHI) system after undergoing an approval procedure by the Federal Institute for Drugs and Medical Devices (BfArM). DiGA can be approved provisionally for 1 year (with the option of extension) or permanently. The latter is dependent on scientific evidence of a positive effect on care, which can be a medical benefit or a patient-relevant structural and procedural improvement in care. However, it is apparent that the investigation of DiGA in scientific studies is challenging, as they are often complex interventions whose success also includes user and prescriber factors. In addition, health services research data underpinning the benefits of DiGA are lacking to date. In the current article, methodological considerations for DiGA research are presented, and a selection of internal medicine DiGAs is used to critically discuss current research practice.

Digital health applications and the fast-track pathway to public health coverage in Germany: challenges and opportunities based on first results

Objectives

Evidence-based decision-making is the sine qua non for safe and effective patient care and the long-term functioning of health systems. Since 2020 Digital Health Applications (DiHA) in Germany have been undergoing a systematic pathway to be reimbursed by statutory health insurance (SHI) which is attracting attention in other European countries. We therefore investigate coverage decisions on DiHA and the underlying evidence on health care effects, which legally include both medical outcomes and patient-centred structural and procedural outcomes.

Methods

Based on publicly available data of the Institute for Medicines and Medical Devices searched between 08/2021 and 02/2022, all DiHA listed in the corresponding registry and thus reimbursable by the SHI were systematically investigated and presented descriptively on the basis of predefined criteria, such as clinical condition, and costs. The clinical trials on DiHA permanently included in the registry were reviewed with regard to their study design, endpoints investigated, the survey instruments used, and whether an intention-to-treat analysis was performed. Risk of bias was assessed using the ROB II tool.

Results

By February 2022, 30 DiHA had been included in the DiHA registry, one third of them permanently and two thirds conditionally. Most DiHA were therapeutic applications for mental illness based on cognitive behavioural therapy. For all permanently included DiHA, randomised controlled trials were conducted to demonstrate the impact on health care effects. While medical outcomes were investigated for all of these DiHA, patient-centred structural and procedural outcomes were rarely investigated. The majority of clinical trials showed a high risk of bias, mainly due to insufficient reporting quality. Overall, the prices for DiHA covered by SHI are on average around € 150 per month (min. € 40; max. € 248).

Conclusions

Evidence-based decision-making on coverage of DiHA leaves room for improvements both in terms of reporting-quality and the use of patient-centred structural and procedural outcomes in addition to medical outcomes. With appropriate evidence, DiHA can offer an opportunity as an adjunct to existing therapy while currently the high risk of bias of the trials raises doubts about the justification of its high costs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-08500-6.

Regulatory considerations to keep pace with innovation in digital health products

Rapid innovation and proliferation of software as a medical device have accelerated the clinical use of digital technologies across a wide array of medical conditions. Current regulatory pathways were developed for traditional (hardware) medical devices and offer a useful structure, but the evolution of digital devices requires concomitant innovation in regulatory approaches to maximize the potential benefits of these emerging technologies. A number of specific adaptations could strengthen current regulatory oversight while promoting ongoing innovation.

What Intervention Elements Drive Weight Loss in Blended-Care Behavior Change Interventions? A Real-World Data Analysis with 25,706 Patients

Background: Blended-care behavior change interventions (BBCI) are a combination of digital care and coaching by health care professionals (HCP), which are proven effective for weight loss. However, it remains unclear what specific elements of BBCI drive weight loss. Objectives: This study aims to identify the distinct impact of HCP-elements (coaching) and digital elements (self-monitoring, self-management, and education) for weight loss in BBCI. Methods: Long-term data from 25,706 patients treated at a digital behavior change provider were analyzed retrospectively using a ridge regression model to predict weight loss at 3, 6, and 12 months. Results: Overall relative weight loss was −1.63 kg at 1 month, −3.61 kg at 3 months, −5.28 kg at 6 months, and −6.55 kg at 12 months. The four factors of BBCI analyzed here (coaching, self-monitoring, self-management, and education) predict weight loss with varying accuracy and degree. Coaching, self-monitoring, and self-management are positively correlated with weight losses at 3 and 6 months. Learn time (i.e., self-guided education) is clearly associated with a higher degree of weight loss. Number of appointments outside of app coaching with a dietitian (coach) was negatively associated with weight loss. Conclusions: The results testify to the efficacy of BBCI for weight loss-with particular positive associations per time point-and add to a growing body of research that characterizes the distinct impact of intervention elements in real-world settings, aiming to inform the design of future interventions for weight management.