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.

Differences in Care Team Response to Patient Portal Messages by Patient Race and Ethnicity.

Importance: The COVID-19 pandemic was associated with substantial growth in patient portal messaging. Higher message volumes have largely persisted, reflecting a new normal. Prior work has documented lower message use by patients who belong to minoritized racial and ethnic groups, but research has not examined differences in care team response to messages. Both have substantial ramifications on resource allocation and care access under a new care paradigm with portal messaging as a central channel for patient-care team communication. Objective: To examine differences in how care teams respond to patient portal messages sent by patients from different racial and ethnic groups. Design, Setting, and Participants: In a cross-sectional design in a large safety-net health system, response outcomes from medical advice message threads sent from January 1, 2021, through November 24, 2021, from Asian, Black, Hispanic, and White patients were compared, controlling for patient and message thread characteristics. Asian, Black, Hispanic, and White patients with 1 or more adult primary care visits at Boston Medical Center in calendar year 2020 were included. Data analysis was conducted from June 23, 2022, through December 21, 2023. Exposure: Patient race and ethnicity. Main Outcomes and Measures: Rates at which medical advice request messages were responded to by care teams and the types of health care professionals that responded. Results: A total of 39 043 patients were included in the sample: 2006 were Asian, 21 600 were Black, 7185 were Hispanic, and 8252 were White. A total of 22 744 (58.3%) patients were women and mean (SD) age was 50.4 (16.7) years. In 2021, these patients initiated 57 704 medical advice request message threads. When patients who belong to minoritized racial and ethnic groups sent these messages, the likelihood of receiving any care team response was similar, but the types of health care professionals that responded differed. Black patients were 3.95 percentage points (pp) less likely (95% CI, -5.34 to -2.57 pp; P < .001) to receive a response from an attending physician, and 3.01 pp more likely (95% CI, 1.76-4.27 pp; P < .001) to receive a response from a registered nurse, corresponding to a 17.4% lower attending response rate. Similar, but smaller, differences were observed for Asian and Hispanic patients. Conclusions and Relevance: The findings of this study suggest lower prioritization of patients who belong to minoritized racial and ethnic groups during triaging. Understanding and addressing these disparities will be important for improving care equity and informing health care delivery support algorithms.

Tepid Uptake of Digital Health Technologies in Clinical Trials by Pharmaceutical and Medical Device Firms.

Digital health technologies (DHTs) can enable more patient-centric therapeutic development by generating evidence that captures how patients feel and function, enabling decentralized trial designs that increase participant inclusivity and convenience, and collecting and structuring patient-generated data for regulators to use in approval decisions alongside traditional clinical outcomes. Although a growing body of evidence has documented increasing use of DHTs in clinical trials overall, the use of DHTs in clinical trials supporting medical product development is unclear; here, we quantify the use of DHTs in clinical trials sponsored by pharmaceutical and medical device firms. Despite interest from pharmaceutical and medical device manufacturers in DHTs, we find tepid uptake of DHTs in trials by these sponsor types over time. Further, to date, these sponsors have most frequently used conventional, hardware-based technologies that have been available for many years (e.g., Holter monitors and glucose meters) rather than newer activity monitors, mobile apps, and other online-based tools that are frequently used by non-industry sponsors. Considering the recent and evolving nature of regulatory guidance around DHT use in clinical trials, our findings suggest that organizations pursuing product development still appear hesitant to incorporate DHTs in trials that provide the most critical evidence for regulatory review and impact how new products are used. This suggests there are likely additional opportunities for sponsors of regulated trials to incorporate (more) DHTs and patient-centric endpoints into product development clinical trials. However, additional regulatory clarity and efforts to reduce operational barriers may be needed in order to more fully capture these opportunities.

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.

Effects of Remote Patient Monitoring Use on Care Outcomes Among Medicare Patients With Hypertension : An Observational Study.

BACKGROUND: Remote patient monitoring (RPM) is a promising tool for improving chronic disease management. Use of RPM for hypertension monitoring is growing rapidly, raising concerns about increased spending. However, the effects of RPM are still unclear. OBJECTIVE: To estimate RPM's effect on hypertension care and spending. DESIGN: Matched observational study emulating a longitudinal, cluster randomized trial. After matching, effect estimates were derived from a regression analysis comparing changes in outcomes from 2019 to 2021 for patients with hypertension at high-RPM practices versus those at matched control practices with little RPM use. SETTING: Traditional Medicare. PATIENTS: Patients with hypertension. INTERVENTION: Receipt of care at a high-RPM practice. MEASUREMENTS: Primary outcomes included hypertension medication use (medication fills, adherence, and unique medications received), outpatient visit use, testing and imaging use, hypertension-related acute care use, and total hypertension-related spending. RESULTS: 192 high-RPM practices (with 19 978 patients with hypertension) were matched to 942 low-RPM control practices (with 95 029 patients with hypertension). Compared with patients with hypertension at matched low-RPM practices, patients with hypertension at high-RPM practices had a 3.3% (95% CI, 1.9% to 4.8%) relative increase in hypertension medication fills, a 1.6% (CI, 0.7% to 2.5%) increase in days' supply, and a 1.3% (CI, 0.2% to 2.4%) increase in unique medications received. Patients at high-RPM practices also had fewer hypertension-related acute care encounters (-9.3% [CI, -20.6% to 2.1%]) and reduced testing use (-5.9% [CI, -11.9% to 0.0%]). However, these patients also saw increases in primary care physician outpatient visits (7.2% [CI, -0.1% to 14.6%]) and a $274 [CI, $165 to $384]) increase in total hypertension-related spending. LIMITATION: Lacked blood pressure data; residual confounding. CONCLUSION: Patients in high-RPM practices had improved hypertension care outcomes but increased spending. PRIMARY FUNDING SOURCE: National Institute of Neurological Disorders and Stroke.

Federated electronic health records for the European Health Data Space.

The European Commission's draft for the European Health Data Space (EHDS) aims to empower citizens to access their personal health data and share it with physicians and other health-care providers. It further defines procedures for the secondary use of electronic health data for research and development. Although this planned legislation is undoubtedly a step in the right direction, implementation approaches could potentially result in centralised data silos that pose data privacy and security risks for individuals. To address this concern, we propose federated personal health data spaces, a novel architecture for storing, managing, and sharing personal electronic health records that puts citizens at the centre-both conceptually and technologically. The proposed architecture puts citizens in control by storing personal health data on a combination of personal devices rather than in centralised data silos. We describe how this federated architecture fits within the EHDS and can enable the same features as centralised systems while protecting the privacy of citizens. We further argue that increased privacy and control do not contradict the use of electronic health data for research and development. Instead, data sovereignty and transparency encourage active participation in studies and data sharing. This combination of privacy-by-design and transparent, privacy-preserving data sharing can enable health-care leaders to break the privacy-exploitation barrier, which currently limits the secondary use of health data in many cases.

Evidence from ClinicalTrials.gov on the growth of Digital Health Technologies in neurology trials.

Digital Health Technologies (DHTs) such as connected sensors offer particular promise for improving data collection and patient empowerment in neurology research and care. This study analyzed the recent evolution of the use of DHTs in trials registered on ClinicalTrials.gov for four chronic neurological disorders: epilepsy, multiple sclerosis, Alzheimer's, and Parkinson's disease. We document growth in the collection of both more established digital measures (e.g., motor function) and more novel digital measures (e.g., speech) over recent years, highlighting contexts of use and key trends.

Association Between Regulatory Submission Characteristics and Recalls of Medical Devices Receiving 510(k) Clearance.

Importance: Most regulated medical devices enter the US market via the 510(k) regulatory submission pathway, wherein manufacturers demonstrate that applicant devices are "substantially equivalent" to 1 or more "predicate" devices (legally marketed medical devices with similar intended use). Most recalled medical devices are 510(k) devices. Objective: To examine the association between characteristics of predicate medical devices and recall probability for 510(k) devices. Design, Setting, and Participants: In this exploratory cross-sectional analysis of medical devices cleared by the US Food and Drug Administration (FDA) between 2003 and 2018 via the 510(k) regulatory submission pathway, linear probability models were used to examine associations between a 510(k) device's recall status and characteristics of its predicate medical devices. Public documents for the 510(k) medical devices were collected using FDA databases. A text extraction algorithm was applied to identify predicate medical devices cited in 510(k) regulatory submissions. Algorithm-derived metadata were combined with 2003-2020 FDA recall data. Exposures: Citation of predicate medical devices with certain characteristics in 510(k) regulatory submissions, including the total number of predicate medical devices cited by the applicant device, the age of the predicate medical devices, the lack of similarity of the predicate medical devices to the applicant device, and the recall status of the predicate medical devices. Main Outcomes and Measures: Class I or class II recall of a 510(k) medical device between its FDA regulatory clearance date and December 31, 2020. Results: The sample included 35 176 medical devices, of which 4007 (11.4%) were recalled. The applicant devices cited a mean of 2.6 predicate medical devices, with mean ages of 3.6 years and 7.4 years for the newest and oldest, respectively, predicate medical devices. Of the applicant devices, 93.9% cited predicate medical devices with no ongoing recalls, 4.3% cited predicate medical devices with 1 ongoing class I or class II recall, 1.0% cited predicate medical devices with 2 ongoing recalls, and 0.8% cited predicate medical devices with 3 or more ongoing recalls. Applicant devices citing predicate medical devices with 3 or more ongoing recalls were significantly associated with a 9.31-percentage-point increase (95% CI, 2.84-15.77 percentage points) in recall probability compared with devices without ongoing recalls of predicate medical devices, or an 81.2% increase in recall probability relative to the mean recall probability. A 1-SD increase in the total number of predicate medical devices cited by the applicant device was significantly associated with a 1.25-percentage-point increase (95% CI, 0.62-1.87 percentage points) in recall probability, or an 11.0% increase in recall probability relative to the mean recall probability. A 1-SD increase in the newest age of a predicate medical device was significantly associated with a 0.78-percentage-point decrease (95% CI, 1.29-0.30 percentage points) in recall probability, or a 6.8% decrease in recall probability relative to the mean recall probability. Conclusions and Relevance: This exploratory cross-sectional study of 510(k) medical devices cleared by the FDA between 2003 and 2018 demonstrated significant associations between 510(k) submission characteristics and recalls of medical devices. Further research is needed to understand the implications of these associations.

Rapid Growth Of Remote Patient Monitoring Is Driven By A Small Number Of Primary Care Providers.

Growing enthusiasm for remote patient monitoring has been motivated by the hope that it can improve care for patients with poorly controlled chronic illness. In a national commercially insured population in the US, we found that billing for remote patient monitoring increased more than fourfold during the first year of the COVID-19 pandemic. Most of this growth was driven by a small number of primary care providers. Among the patients of these providers with a high volume of remote patient monitoring, we did not observe substantial targeting of remote patient monitoring to people with greater disease burden or worse disease control. Further research is needed to identify which patients benefit from remote patient monitoring, to inform evidence-based use and coverage decisions. In the meantime, payers and policy makers should closely monitor remote patient monitoring use and spending.

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.

Health app policy: international comparison of nine countries' approaches.

An abundant and growing supply of digital health applications (apps) exists in the commercial tech-sector, which can be bewildering for clinicians, patients, and payers. A growing challenge for the health care system is therefore to facilitate the identification of safe and effective apps for health care practitioners and patients to generate the most health benefit as well as guide payer coverage decisions. Nearly all developed countries are attempting to define policy frameworks to improve decision-making, patient care, and health outcomes in this context. This study compares the national policy approaches currently in development/use for health apps in nine countries. We used secondary data, combined with a detailed review of policy and regulatory documents, and interviews with key individuals and experts in the field of digital health policy to collect data about implemented and planned policies and initiatives. We found that most approaches aim for centralized pipelines for health app approvals, although some countries are adding decentralized elements. While the countries studied are taking diverse paths, there is nevertheless broad, international convergence in terms of requirements in the areas of transparency, health content, interoperability, and privacy and security. The sheer number of apps on the market in most countries represents a challenge for clinicians and patients. Our analyses of the relevant policies identified challenges in areas such as reimbursement, safety, and privacy and suggest that more regulatory work is needed in the areas of operationalization, implementation and international transferability of approvals. Cross-national efforts are needed around regulation and for countries to realize the benefits of these technologies.

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

In 2019, Germany passed the Digital Healthcare Act, which, among other things, created a "Fast-Track" regulatory and reimbursement pathway for digital health applications in the German market. The pathway explicitly provides for flexibility in how researchers can present evidence for new digital products, including the use of real-world data and real-world evidence. Against this backdrop, the Digital Medicine Society and the Health Innovation Hub of the German Federal Ministry of Health convened a set of roundtable discussions to bring together international experts in evidence generation for digital medicine products. This Viewpoint highlights findings from these discussions with the aims of (1) accelerating and stimulating innovative approaches to digital medical product evaluation, and (2) promoting international harmonisation of best evidentiary practices. Advancing these topics and fostering international agreement on evaluation approaches will be vital to the safe, effective, and evidence-based deployment and acceptance of digital health applications globally.

Artificial Intelligence and Clinical Decision Making: The New Nature of Medical Uncertainty.

Estimates in a 1989 study indicated that physicians in the United States were unable to reach a diagnosis that accounted for their patient's symptoms in up to 90% of outpatient patient encounters. Many proponents of artificial intelligence (AI) see the current process of moving from clinical data gathering to medical diagnosis as being limited by human analytic capability and expect AI to be a valuable tool to refine this process. The use of AI fundamentally calls into question the extent to which uncertainty in medical decision making is tolerated. Uncertainty is perceived by some as fundamentally undesirable and thus, for them, optimal decision making should be based on minimizing uncertainty. However, uncertainty cannot be reduced to zero; thus, relative uncertainty can be used as a metric to weigh the likelihood of various diagnoses being correct and the appropriateness of treatments. Here, the authors make the argument, using as examples the experiences of 2 AI systems, IBM Watson on Jeopardy and Watson for Oncology, that medical decision making based on relative uncertainty provides a better lens for understanding the application of AI to medicine than one that minimizes uncertainty. This approach to uncertainty has significant implications for how health care leaders consider the benefits and trade-offs of AI-assisted and AI-driven decision tools and ultimately integrate AI into medical practice.

Lessons From The Impact Of Price Regulation On The Pricing Of Anticancer Drugs In Germany.

Worldwide spending on prescription drugs has increased dramatically in recent years. Although this increase has been particularly pronounced in the US, it remains largely unaddressed there. In Europe, however, different approaches to regulating drug prices have been implemented. Under the 2011 German Pharmaceutical Market Restructuring Act (Arzneimittelmarktneuordnungsgesetz, or AMNOG), for example, manufacturers freely set the prices of newly authorized drugs during their first year on the market. Benefit assessments are carried out during this year and then used in price negotiations between manufacturers and representatives of the country's statutory health insurers. Using data on fifty-seven anticancer drugs launched in Germany from 2002 to 2017, we found that implementation of AMNOG was associated with drug prices being more closely aligned with clinical benefit. Introducing price negotiations led to a 24.5 percent decrease in negotiated prices relative to launch prices. We did not find evidence that manufacturers responded by setting higher launch prices. AMNOG is an example of how government price negotiation can be designed to better align prices with clinical benefit without delaying patient access.