Precision medicine in 2030-seven ways to transform healthcare.

Precision medicine promises improved health by accounting for individual variability in genes, environment, and lifestyle. Precision medicine will continue to transform healthcare in the coming decade as it expands in key areas: huge cohorts, artificial intelligence (AI), routine clinical genomics, phenomics and environment, and returning value across diverse populations.

Biomedical Research Goes Viral: Dangers and Opportunities.

Researchers around the globe have been mounting, accelerating, and redeploying efforts across disciplines and organizations to tackle the SARS-CoV-2 outbreak. However, humankind continues to be afflicted by numerous other devastating diseases in increasing numbers. Here, we outline considerations and opportunities toward striking a good balance between maintaining and redefining research priorities.

American Cancer Society's report on the status of cancer disparities in the United States, 2023.

In 2021, the American Cancer Society published its first biennial report on the status of cancer disparities in the United States. In this second report, the authors provide updated data on racial, ethnic, socioeconomic (educational attainment as a marker), and geographic (metropolitan status) disparities in cancer occurrence and outcomes and contributing factors to these disparities in the country. The authors also review programs that have reduced cancer disparities and provide policy recommendations to further mitigate these inequalities. There are substantial variations in risk factors, stage at diagnosis, receipt of care, survival, and mortality for many cancers by race/ethnicity, educational attainment, and metropolitan status. During 2016 through 2020, Black and American Indian/Alaska Native people continued to bear a disproportionately higher burden of cancer deaths, both overall and from major cancers. By educational attainment, overall cancer mortality rates were about 1.6-2.8 times higher in individuals with ≤12 years of education than in those with ≥16 years of education among Black and White men and women. These disparities by educational attainment within each race were considerably larger than the Black-White disparities in overall cancer mortality within each educational attainment, ranging from 1.03 to 1.5 times higher among Black people, suggesting a major role for socioeconomic status disparities in racial disparities in cancer mortality given the disproportionally larger representation of Black people in lower socioeconomic status groups. Of note, the largest Black-White disparities in overall cancer mortality were among those who had ≥16 years of education. By area of residence, mortality from all cancer and from leading causes of cancer death were substantially higher in nonmetropolitan areas than in large metropolitan areas. For colorectal cancer, for example, mortality rates in nonmetropolitan areas versus large metropolitan areas were 23% higher among males and 21% higher among females. By age group, the racial and geographic disparities in cancer mortality were greater among individuals younger than 65 years than among those aged 65 years and older. Many of the observed racial, socioeconomic, and geographic disparities in cancer mortality align with disparities in exposure to risk factors and access to cancer prevention, early detection, and treatment, which are largely rooted in fundamental inequities in social determinants of health. Equitable policies at all levels of government, broad interdisciplinary engagement to address these inequities, and equitable implementation of evidence-based interventions, such as increasing health insurance coverage, are needed to reduce cancer disparities.

Leveraging physiology and artificial intelligence to deliver advancements in health care.

Artificial intelligence in health care has experienced remarkable innovation and progress in the last decade. Significant advancements can be attributed to the utilization of artificial intelligence to transform physiology data to advance health care. In this review, we explore how past work has shaped the field and defined future challenges and directions. In particular, we focus on three areas of development. First, we give an overview of artificial intelligence, with special attention to the most relevant artificial intelligence models. We then detail how physiology data have been harnessed by artificial intelligence to advance the main areas of health care: automating existing health care tasks, increasing access to care, and augmenting health care capabilities. Finally, we discuss emerging concerns surrounding the use of individual physiology data and detail an increasingly important consideration for the field, namely the challenges of deploying artificial intelligence models to achieve meaningful clinical impact.

Clinical practice guideline and expert consensus recommendations for rehabilitation among children with cancer: A systematic review.

Increased attention to the rehabilitation needs of children with cancer is vital to enhance health, quality-of-life, and productivity outcomes. Among adults with cancer, rehabilitation recommendations are frequently incorporated into guidelines, but the extent to which recommendations exist for children is unknown. Reports included in this systematic review are guideline or expert consensus reports containing recommendations related to rehabilitation referral, evaluation, and/or intervention for individuals diagnosed with cancer during childhood (younger than 18 years). Eligible reports were published in English from January 2000 to August 2022. Through database searches, 42,982 records were identified; 62 records were identified through citation and website searching. Twenty-eight reports were included in the review: 18 guidelines and 10 expert consensus reports. Rehabilitation recommendations were identified in disease-specific (e.g., acute lymphoblastic leukemia), impairment-specific (e.g., fatigue, neurocognition, pain), adolescent and young adult, and long-term follow-up reports. Example recommendations included physical activity and energy-conservation techniques to address fatigue, referral to physical therapy for chronic pain management, ongoing psychosocial surveillance, and referral to speech-language pathology for those with hearing loss. High-level evidence supported rehabilitation recommendations for long-term follow-up care, fatigue, and psychosocial/mental health screening. Few intervention recommendations were included in guideline and consensus reports. In this developing field, it is critical to include pediatric oncology rehabilitation providers in guideline and consensus development initiatives. This review enhances the availability and clarity of rehabilitation-relevant guidelines that can help prevent and mitigate cancer-related disability among children by supporting access to rehabilitation services.

Integrative oncology: Addressing the global challenges of cancer prevention and treatment.

The increase in cancer incidence and mortality is challenging current cancer care delivery globally, disproportionally affecting low- and middle-income countries (LMICs) when it comes to receiving evidence-based cancer prevention, treatment, and palliative and survivorship care. Patients in LMICs often rely on traditional, complementary, and integrative medicine (TCIM) that is more familiar, less costly, and widely available. However, spheres of influence and tensions between conventional medicine and TCIM can further disrupt efforts in evidence-based cancer care. Integrative oncology provides a framework to research and integrate safe, effective TCIM alongside conventional cancer treatment and can help bridge health care gaps in delivering evidence-informed, patient-centered care. This growing field uses lifestyle modifications, mind and body therapies (eg, acupuncture, massage, meditation, and yoga), and natural products to improve symptom management and quality of life among patients with cancer. On the basis of this review of the global challenges of cancer control and the current status of integrative oncology, the authors recommend: 1) educating and integrating TCIM providers into the cancer control workforce to promote risk reduction and culturally salient healthy life styles; 2) developing and testing TCIM interventions to address cancer symptoms or treatment-related adverse effects (eg, pain, insomnia, fatigue); and 3) disseminating and implementing evidence-based TCIM interventions as part of comprehensive palliative and survivorship care so patients from all cultures can live with or beyond cancer with respect, dignity, and vitality. With conventional medicine and TCIM united under a cohesive framework, integrative oncology may provide citizens of the world with access to safe, effective, evidence-informed, and culturally sensitive cancer care.

Addressing distress management challenges: Recommendations from the consensus panel of the American Psychosocial Oncology Society and the Association of Oncology Social Work.

Distress management (DM) (screening and response) is an essential component of cancer care across the treatment trajectory. Effective DM has many benefits, including improving patients' quality of life; reducing distress, anxiety, and depression; contributing to medical cost offsets; and reducing emergency department visits and hospitalizations. Unfortunately, many distressed patients do not receive needed services. There are several multilevel barriers that represent key challenges to DM and affect its implementation. The Consolidated Framework for Implementation Research was used as an organizational structure to outline the barriers and facilitators to implementation of DM, including: 1) individual characteristics (individual patient characteristics with a focus on groups who may face unique barriers to distress screening and linkage to services), 2) intervention (unique aspects of DM intervention, including specific challenges in screening and psychosocial intervention, with recommendations for resolving these challenges), 3) processes for implementation of DM (modality and timing of screening, the challenge of triage for urgent needs, and incorporation of patient-reported outcomes and quality measures), 4) organization-inner setting (the context of the clinic, hospital, or health care system); and 5) organization-outer setting (including reimbursement strategies and health-care policy). Specific recommendations for evidence-based strategies and interventions for each of the domains of the Consolidated Framework for Implementation Research are also included to address barriers and challenges.

Planning for post-pandemic cancer care delivery: Recovery or opportunity for redesign?

The delivery of cancer care has never changed as rapidly and dramatically as we have seen with the coronavirus disease 2019 (COVID-19) pandemic. During the early phase of the pandemic, recommendations for the management of oncology patients issued by various professional societies and government agencies did not recognize the significant regional differences in the impact of the pandemic. California initially experienced lower than expected numbers of cases, and the health care system did not experience the same degree of the burden that had been the case in other parts of the country. In light of promising trends in COVID-19 infections and mortality in California, by late April 2020, discussions were initiated for a phased recovery of full-scale cancer services. However, by July 2020, a surge of cases was reported across the nation, including in California. In this review, the authors share the response and recovery planning experience of the University of California (UC) Cancer Consortium in an effort to provide guidance to oncology practices. The UC Cancer Consortium was established in 2017 to bring together 5 UC Comprehensive Cancer Centers: UC Davis Comprehensive Cancer Center, UC Los Angeles Jonsson Comprehensive Cancer Center, UC Irvine Chao Family Comprehensive Cancer Center, UC San Diego Moores Cancer Center, and the UC San Francisco Helen Diller Family Comprehensive Cancer Center. The interventions implemented in each of these cancer centers are highlighted, with a focus on opportunities for a redesign in care delivery models. The authors propose that their experiences gained during this pandemic will enhance pre-pandemic cancer care delivery.

Health Digital Twins in Life Science and Health Care Innovation.

Health digital twins (HDTs) are virtual representations of real individuals that can be used to simulate human physiology, disease, and drug effects. HDTs can be used to improve drug discovery and development by providing a data-driven approach to inform target selection, drug delivery, and design of clinical trials. HDTs also offer new applications into precision therapies and clinical decision making. The deployment of HDTs at scale could bring a precision approach to public health monitoring and intervention. Next steps include challenges such as addressing socioeconomic barriers and ensuring the representativeness of the technology based on the training and validation data sets. Governance and regulation of HDT technology are still in the early stages.

Innovations in research and clinical care using patient-generated health data.

Patient-generated health data (PGHD), or health-related data gathered from patients to help address a health concern, are used increasingly in oncology to make regulatory decisions and evaluate quality of care. PGHD include self-reported health and treatment histories, patient-reported outcomes (PROs), and biometric sensor data. Advances in wireless technology, smartphones, and the Internet of Things have facilitated new ways to collect PGHD during clinic visits and in daily life. The goal of the current review was to provide an overview of the current clinical, regulatory, technological, and analytic landscape as it relates to PGHD in oncology research and care. The review begins with a rationale for PGHD as described by the US Food and Drug Administration, the Institute of Medicine, and other regulatory and scientific organizations. The evidence base for clinic-based and remote symptom monitoring using PGHD is described, with an emphasis on PROs. An overview is presented of current approaches to digital phenotyping or device-based, real-time assessment of biometric, behavioral, self-report, and performance data. Analytic opportunities regarding PGHD are envisioned in the context of big data and artificial intelligence in medicine. Finally, challenges and solutions for the integration of PGHD into clinical care are presented. The challenges include electronic medical record integration of PROs and biometric data, analysis of large and complex biometric data sets, and potential clinic workflow redesign. In addition, there is currently more limited evidence for the use of biometric data relative to PROs. Despite these challenges, the potential benefits of PGHD make them increasingly likely to be integrated into oncology research and clinical care.

A network frame offers a promising transdisciplinary tool for understanding complex health and health care system problems like suicide.

As health and health care systems continue to face massive challenges from local to global well-being, understanding the processes that lead to improvement or deterioration in human health has embraced a broad range of forces from genes to national cultures. Despite the many efforts to deploy a common framework that captures diverse drivers at scale, the common missing element is the absence of a flexible mechanism that can guide research within and across levels. This hinders both the cumulation of knowledge and the development of a scientific foundation for multiplex interventions. However, studies across disciplines using a wide variety of methods and measures have converged on "connectedness" as crucial to understanding how factors operate in the health space. More formally, a focus on the critical role of the network structure and content of key elements and how they interact, rather than just on the elements themselves, offers both a generalized theory of active factors within levels and the potential to theorize interactions across levels. One critical contemporary health crisis, suicide, is deployed to illustrate the Network Embedded Symbiome Framework. The wide range of health and health care research where networks have been implicated supports its potential but also cautions against inevitable limits that will require creative theorizing and data harmonization to move forward.

Wearable Devices: Implications for Precision Medicine and the Future of Health Care.

Wearable devices are integrated analytical units equipped with sensitive physical, chemical, and biological sensors capable of noninvasive and continuous monitoring of vital physiological parameters. Recent advances in disciplines including electronics, computation, and material science have resulted in affordable and highly sensitive wearable devices that are routinely used for tracking and managing health and well-being. Combined with longitudinal monitoring of physiological parameters, wearables are poised to transform the early detection, diagnosis, and treatment/management of a range of clinical conditions. Smartwatches are the most commonly used wearable devices and have already demonstrated valuable biomedical potential in detecting clinical conditions such as arrhythmias, Lyme disease, inflammation, and, more recently, COVID-19 infection. Despite significant clinical promise shown in research settings, there remain major hurdles in translating the medical uses of wearables to the clinic. There is a clear need for more effective collaboration among stakeholders, including users, data scientists, clinicians, payers, and governments, to improve device security, user privacy, data standardization, regulatory approval, and clinical validity. This review examines the potential of wearables to offer affordable and reliable measures of physiological status that are on par with FDA-approved specialized medical devices. We briefly examine studies where wearables proved critical for the early detection of acute and chronic clinical conditions with a particular focus on cardiovascular disease, viral infections, and mental health. Finally, we discuss current obstacles to the clinical implementation of wearables and provide perspectives on their potential to deliver increasingly personalized proactive health care across a wide variety of conditions.

Australian Genomics: Outcomes of a 5-year national program to accelerate the integration of genomics in healthcare.

Australian Genomics is a national collaborative partnership of more than 100 organizations piloting a whole-of-system approach to integrating genomics into healthcare, based on federation principles. In the first five years of operation, Australian Genomics has evaluated the outcomes of genomic testing in more than 5,200 individuals across 19 rare disease and cancer flagship studies. Comprehensive analyses of the health economic, policy, ethical, legal, implementation and workforce implications of incorporating genomics in the Australian context have informed evidence-based change in policy and practice, resulting in national government funding and equity of access for a range of genomic tests. Simultaneously, Australian Genomics has built national skills, infrastructure, policy, and data resources to enable effective data sharing to drive discovery research and support improvements in clinical genomic delivery.

The Safety of Inpatient Health Care.

BACKGROUND: Adverse events during hospitalization are a major cause of patient harm, as documented in the 1991 Harvard Medical Practice Study. Patient safety has changed substantially in the decades since that study was conducted, and a more current assessment of harm during hospitalization is warranted. METHODS: We conducted a retrospective cohort study to assess the frequency, preventability, and severity of patient harm in a random sample of admissions from 11 Massachusetts hospitals during the 2018 calendar year. The occurrence of adverse events was assessed with the use of a trigger method (identification of information in a medical record that was previously shown to be associated with adverse events) and from review of medical records. Trained nurses reviewed records and identified admissions with possible adverse events that were then adjudicated by physicians, who confirmed the presence and characteristics of the adverse events. RESULTS: In a random sample of 2809 admissions, we identified at least one adverse event in 23.6%. Among 978 adverse events, 222 (22.7%) were judged to be preventable and 316 (32.3%) had a severity level of serious (i.e., caused harm that resulted in substantial intervention or prolonged recovery) or higher. A preventable adverse event occurred in 191 (6.8%) of all admissions, and a preventable adverse event with a severity level of serious or higher occurred in 29 (1.0%). There were seven deaths, one of which was deemed to be preventable. Adverse drug events were the most common adverse events (accounting for 39.0% of all events), followed by surgical or other procedural events (30.4%), patient-care events (which were defined as events associated with nursing care, including falls and pressure ulcers) (15.0%), and health care-associated infections (11.9%). CONCLUSIONS: Adverse events were identified in nearly one in four admissions, and approximately one fourth of the events were preventable. These findings underscore the importance of patient safety and the need for continuing improvement. (Funded by the Controlled Risk Insurance Company and the Risk Management Foundation of the Harvard Medical Institutions.).

Standardized indolent systemic mastocytosis evaluations across a health care system: implications for screening accuracy.

ABSTRACT: Timely diagnosis of systemic mastocytosis (SM) remains challenging because of care heterogeneity. We implemented a standardized approach for SM screening and diagnosis using a novel health care system-wide international screening registry. A retrospective analysis assessed rates of SM, cutaneous mastocytosis (CM), and molecular diagnoses before and 2 years after care standardization. The accuracy of individual and combined SM screening tests, basal serum tryptase (BST) ≥11.5 and ≥20.0 ng/mL, REMA ≥2, monomorphic maculopapular CM (MPCM), and elevated BST based upon tryptase genotype, was analyzed. Tryptase genotyping and high-sensitivity KIT p.D816V testing increased substantially 2 years after care standardization. SM diagnoses doubled from 47 to 94, and KIT p.D816V molecular diagnoses increased from 24 to 79. Mean BST and KIT p.D816V variant allele frequency values were significantly lower in patients diagnosed after standardization. Hereditary-alpha tryptasemia prevalence was increased in SM before care standardization (4/30 [13.3%]) but reflected the general population prevalence 2 years later at (5/76 [6.6%]). Elevated BST based upon genotype and BST ≥11.5 ng/mL had the highest sensitivities at 84.2% and 88.3%, respectively. The presence of monomorphic MPCM, elevated BST based upon tryptase genotype, and the combination of REMA ≥2 with elevated BST based upon tryptase genotype had specificities >90%. BST >20.0 ng/mL had low sensitivity and specificity and was not required to establish any indolent SM (ISM) diagnosis. Care standardization increased SM diagnosis rates, particularly in patients with low BSTs. Stratifying BST based upon genotype had the best overall sensitivity and specificity of any ISM screening test and improved the REMA score specificity.

Materials-Driven Soft Wearable Bioelectronics for Connected Healthcare.

In the era of Internet-of-things, many things can stay connected; however, biological systems, including those necessary for human health, remain unable to stay connected to the global Internet due to the lack of soft conformal biosensors. The fundamental challenge lies in the fact that electronics and biology are distinct and incompatible, as they are based on different materials via different functioning principles. In particular, the human body is soft and curvilinear, yet electronics are typically rigid and planar. Recent advances in materials and materials design have generated tremendous opportunities to design soft wearable bioelectronics, which may bridge the gap, enabling the ultimate dream of connected healthcare for anyone, anytime, and anywhere. We begin with a review of the historical development of healthcare, indicating the significant trend of connected healthcare. This is followed by the focal point of discussion about new materials and materials design, particularly low-dimensional nanomaterials. We summarize material types and their attributes for designing soft bioelectronic sensors; we also cover their synthesis and fabrication methods, including top-down, bottom-up, and their combined approaches. Next, we discuss the wearable energy challenges and progress made to date. In addition to front-end wearable devices, we also describe back-end machine learning algorithms, artificial intelligence, telecommunication, and software. Afterward, we describe the integration of soft wearable bioelectronic systems which have been applied in various testbeds in real-world settings, including laboratories that are preclinical and clinical environments. Finally, we narrate the remaining challenges and opportunities in conjunction with our perspectives.

LifeTime and improving European healthcare through cell-based interceptive medicine.

Here we describe the LifeTime Initiative, which aims to track, understand and target human cells during the onset and progression of complex diseases, and to analyse their response to therapy at single-cell resolution. This mission will be implemented through the development, integration and application of single-cell multi-omics and imaging, artificial intelligence and patient-derived experimental disease models during the progression from health to disease. The analysis of large molecular and clinical datasets will identify molecular mechanisms, create predictive computational models of disease progression, and reveal new drug targets and therapies. The timely detection and interception of disease embedded in an ethical and patient-centred vision will be achieved through interactions across academia, hospitals, patient associations, health data management systems and industry. The application of this strategy to key medical challenges in cancer, neurological and neuropsychiatric disorders, and infectious, chronic inflammatory and cardiovascular diseases at the single-cell level will usher in cell-based interceptive medicine in Europe over the next decade.

Illuminating the dark spaces of healthcare with ambient intelligence.

Advances in machine learning and contactless sensors have given rise to ambient intelligence-physical spaces that are sensitive and responsive to the presence of humans. Here we review how this technology could improve our understanding of the metaphorically dark, unobserved spaces of healthcare. In hospital spaces, early applications could soon enable more efficient clinical workflows and improved patient safety in intensive care units and operating rooms. In daily living spaces, ambient intelligence could prolong the independence of older individuals and improve the management of individuals with a chronic disease by understanding everyday behaviour. Similar to other technologies, transformation into clinical applications at scale must overcome challenges such as rigorous clinical validation, appropriate data privacy and model transparency. Thoughtful use of this technology would enable us to understand the complex interplay between the physical environment and health-critical human behaviours.

Evidence for 28 genetic disorders discovered by combining healthcare and research data.

De novo mutations in protein-coding genes are a well-established cause of developmental disorders1. However, genes known to be associated with developmental disorders account for only a minority of the observed excess of such de novo mutations1,2. Here, to identify previously undescribed genes associated with developmental disorders, we integrate healthcare and research exome-sequence data from 31,058 parent-offspring trios of individuals with developmental disorders, and develop a simulation-based statistical test to identify gene-specific enrichment of de novo mutations. We identified 285 genes that were significantly associated with developmental disorders, including 28 that had not previously been robustly associated with developmental disorders. Although we detected more genes associated with developmental disorders, much of the excess of de novo mutations in protein-coding genes remains unaccounted for. Modelling suggests that more than 1,000 genes associated with developmental disorders have not yet been described, many of which are likely to be less penetrant than the currently known genes. Research access to clinical diagnostic datasets will be critical for completing the map of genes associated with developmental disorders.