"What Goes Around Comes Around": Lessons Learned from Economic Evaluations of Personalized Medicine Applied to Digital Medicine

Definitions of digital biomarkers: a systematic mapping of the biomedical literature

BACKGROUND

Technological devices such as smartphones, wearables and virtual assistants enable health data collection, serving as digital alternatives to conventional biomarkers. We aimed to provide a systematic overview of emerging literature on 'digital biomarkers,' covering definitions, features and citations in biomedical research.

METHODS

We analysed all articles in PubMed that used 'digital biomarker(s)' in title or abstract, considering any study involving humans and any review, editorial, perspective or opinion-based articles up to 8 March 2023. We systematically extracted characteristics of publications and research studies, and any definitions and features of 'digital biomarkers' mentioned. We described the most influential literature on digital biomarkers and their definitions using thematic categorisations of definitions considering the Food and Drug Administration Biomarkers, EndpointS and other Tools framework (ie, data type, data collection method, purpose of biomarker), analysing structural similarity of definitions by performing text and citation analyses.

RESULTS

We identified 415 articles using 'digital biomarker' between 2014 and 2023 (median 2021). The majority (283 articles; 68%) were primary research. Notably, 287 articles (69%) did not provide a definition of digital biomarkers. Among the 128 articles with definitions, there were 127 different ones. Of these, 78 considered data collection, 56 data type, 50 purpose and 23 included all three components. Those 128 articles with a definition had a median of 6 citations, with the top 10 each presenting distinct definitions.

CONCLUSIONS

The definitions of digital biomarkers vary significantly, indicating a lack of consensus in this emerging field. Our overview highlights key defining characteristics, which could guide the development of a more harmonised accepted definition.

Telehealth utilization barriers among Alabama parents of pediatric patients during COVID-19 outbreak

BACKGROUND

Telehealth can improve access to evidence-based care at a lower cost for patients, especially those living in underserved and remote areas. The barriers to the widespread adoption of telehealth have been well documented in the literature. However, the barriers may not be the same for pediatric patients, who must rely on their parents or guardians to make healthcare decisions. This paper presents some of the leading barriers parents or guardians of pediatric patients report in using telehealth to meet their children's healthcare needs.

METHODS

This cross-sectional survey was conducted in a tertiary care pediatric Emergency Department (ED) at a children's hospital in Alabama between September 2020 to December 2020. The parents or guardians of pediatric patients were asked about their reasons for not using telehealth despite having healthcare needs for their children, whether they canceled or rescheduled healthcare provider visits and facility visits, and whether the child's health conditions changed over the past three months. Descriptive analyses were conducted that explored the distribution of telehealth use across the variables listed above.

RESULTS

Five hundred ninety-seven parents or guardians of pediatric patients participated in the survey, and 578 answered the question of whether they used telehealth or not over the past three months. Of them, 33.1% used telehealth, 54.3% did not, and 12.6% did not have healthcare needs for their child. The leading reason for not using telehealth was that the doctor or health provider did not give them a telehealth option, the second main reason was that they did not know what telehealth is, and the third leading reason was that the parents did not think telehealth would help meet healthcare needs for their child.

CONCLUSIONS

This study highlights the telehealth utilization barriers among underserved pediatric populations, including the need for physicians to proactively offer telehealth options to parents or guardians of pediatric patients. Improving health literacy is of paramount importance, given that a substantial proportion of parents were not familiar with telehealth. Policymakers and healthcare organizations should raise awareness about the benefits of telehealth which can improve healthcare access for underserved pediatric patients.

Economic evaluation of genomic/genetic tests: a review and future directions

It has been suggested that health economists need to improve their methods in order to meet the challenges of evaluating genomic/genetic tests. In this article, we set out twelve challenges identified from a rapid review of the literature and suggest solutions to the challenges identified. Two challenges were common to all economic evaluations: choice of perspective and time-horizon. Five challenges were relevant for all diagnostic technologies: complexity of analysis; range of costs; under-developed evidence base; behavioral aspects; and choice of outcome metrics. The final five challenges were pertinent for genomic tests and only these may require methodological development: heterogeneity of tests and platforms, increasing stratification, capturing personal utility; incidental findings; and spillover effects. Current methods of economic evaluation are generally able to cope with genomic/genetic tests, although a renewed focus on specific decision-makers’ needs and a willingness to move away from cost-utility analysis may be required. Certain analysts may be constrained by reference cases developed primarily for the assessment of pharmaceuticals. The combined impact of multiple challenges may require analysts to be particularly careful in setting the scope of their analysis in order to ensure that feasibility is balanced with usefulness to the decision maker. A key issue is the under-developed evidence-base and it may be necessary to rethink translation processes to ensure sufficient, relevant evidence is available to support economic evaluation and adoption of genomic/genetic tests.

Health Technology Assessment for Cardiovascular Digital Health Technologies and Artificial Intelligence: Why Is It Different?

Innovations in health care are growing exponentially, resulting in improved quality of and access to care, as well as rising societal costs of care and variable reimbursement. In recent years, digital health technologies and artificial intelligence have become of increasing interest in cardiovascular medicine owing to their unique ability to empower patients and to use increasing quantities of data for moving toward personalised and precision medicine. Health technology assessment agencies evaluate the money spent on a health care intervention or technology to attain a given clinical impact and make recommendations for reimbursement considerations. However, there is a scarcity of economic evaluations of cardiovascular digital health technologies and artificial intelligence. The current health technology assessment framework is not equipped to address the unique, dynamic, and unpredictable value considerations of these technologies and highlight the need to better approach the digital health technologies and artificial intelligence health technology assessment process. In this review, we compare digital health technologies and artificial intelligence with traditional health care technologies, review existing health technology assessment frameworks, and discuss challenges and opportunities related to cardiovascular digital health technologies and artificial intelligence health technology assessment. Specifically, we argue that health technology assessments for digital health technologies and artificial intelligence applications must allow for a much shorter device life cycle, given the rapid and even potentially continuously iterative nature of this technology, and thus an evidence base that maybe less mature, compared with traditional health technologies and interventions.

Internet of Things, Digital Biomarker, and Artificial Intelligence in Spine: Current and Future Perspectives

Recent interest in medical artificial intelligence (AI) has increased with onset of the fourth industrial revolution. Real-time monitoring of patients is an important research area of medical AI. The medical AI is very closely related to the Internet of Things (IoT), a core element of the fourth industrial revolution. Attempts to diagnose and treat patients using IoT have been already applied to patients with chronic disease such as hypertension and arrhythmia. However, in the spine, research on IoT and digital biomarkers are still in the early stages. The digital biomarker obtained by IoT devices is objective and could represent real-time, real-world, and abundant data. Based on its characteristics, IoT and digital biomarkers can also be useful in the spine. Currently, research on real-time monitoring of physical activity or spinal posture is ongoing. Therefore, the authors introduce the basic concepts of IoT and digital biomarkers, their relationship to AI, and recent trends. Current and future perspectives of IoT and digital biomarker in spine are also discussed. In the future, it is expected that IoT, digital biomarkers, and AI will lead to a paradigm shift in the diagnosis and treatment of spinal diseases.

Personalized medicine: motivation, challenges, and progress

There is a great deal of hype surrounding the concept of personalized medicine. Personalized medicine is rooted in the belief that since individuals possess nuanced and unique characteristics at the molecular, physiological, environmental exposure, and behavioral levels, they may need to have interventions provided to them for diseases they possess that are tailored to these nuanced and unique characteristics. This belief has been verified to some degree through the application of emerging technologies such as DNA sequencing, proteomics, imaging protocols, and wireless health monitoring devices, which have revealed great inter-individual variation in disease processes. In this review, we consider the motivation for personalized medicine, its historical precedents, the emerging technologies that are enabling it, some recent experiences including successes and setbacks, ways of vetting and deploying personalized medicines, and future directions, including potential ways of treating individuals with fertility and sterility issues. We also consider current limitations of personalized medicine. We ultimately argue that since aspects of personalized medicine are rooted in biological realities, personalized medicine practices in certain contexts are likely to be inevitable, especially as relevant assays and deployment strategies become more efficient and cost-effective.

The Future of Precision Medicine: Potential Impacts for Health Technology Assessment

OBJECTIVE

Precision medicine allows healthcare interventions to be tailored to groups of patients based on their disease susceptibility, diagnostic or prognostic information, or treatment response. We analysed what developments are expected in precision medicine over the next decade and considered the implications for health technology assessment (HTA) agencies.

METHODS

We performed a pragmatic literature search to account for the large size and wide scope of the precision medicine literature. We refined and enriched these results with a series of expert interviews up to 1 h in length, including representatives from HTA agencies, research councils and researchers designed to cover a wide spectrum of precision medicine applications and research.

RESULTS

We identified 31 relevant papers and interviewed 13 experts. We found that three types of precision medicine are expected to emerge in clinical practice: complex algorithms, digital health applications and 'omics'-based tests. These are expected to impact upon each stage of the HTA process, from scoping and modelling through to decision-making and review. The complex and uncertain treatment pathways associated with patient stratification and fast-paced technological innovation are central to these effects.

DISCUSSION

Innovation in precision medicine promises substantial benefits but will change the way in which some health services are delivered and evaluated. The shelf life of guidance may decrease, structural uncertainty may increase and new equity considerations will emerge. As biomarker discovery accelerates and artificial intelligence-based technologies emerge, refinements to the methods and processes of evidence assessments will help to adapt and maintain the objective of investing in healthcare that is value for money.

Translational Radiomics: Defining the Strategy Pipeline and Considerations for Application-Part 2: From Clinical Implementation to Enterprise

Enterprise imaging has channeled various technological innovations to the field of clinical radiology, ranging from advanced imaging equipment and postacquisition iterative reconstruction tools to image analysis and computer-aided detection tools. More recently, the advancement in the field of quantitative image analysis coupled with machine learning-based data analytics, classification, and integration has ushered in the era of radiomics, a paradigm shift that holds tremendous potential in clinical decision support as well as drug discovery. However, there are important issues to consider to incorporate radiomics into a clinically applicable system and a commercially viable solution. In this two-part series, we offer insights into the development of the translational pipeline for radiomics from methodology to clinical implementation (Part 1) and from that point to enterprise development (Part 2). In Part 2 of this two-part series, we study the components of the strategy pipeline, from clinical implementation to building enterprise solutions.