Damion Nero, Director of HEOR Research Analytics, Cardinal Health
Computational health combines availability of more data and advances in software/ hardware technologies to solve problems in healthcare with computation-based approaches. The explosion in volume of various kinds of data — genomic, transcriptomic, proteomic, epigenetic, metabolomic, microbiome, clinical, and behavioral — is driven by the lowering cost of data acquisition and storage. For example, sequencing a human genome used to cost around $3 billion in the 90’s. Today it only costs a few thousand dollars — a faster decline than what we observed in computing cost depicted by Moore’s Law. In addition, advances in software and hardware technologies are rapidly accelerating, particularly around artificial intelligence.
The confluence of these trends is transforming healthcare, and companies are harnessing data and applying AI to solve meaningful problems in diagnostics, therapeutics, treatment & care, and clinical & administrative workflows. In diagnostics, researchers are applying deep learning to ultrasound imaging, to help with both acquisition and interpretation of echocardiograms. Other groups are developing blood screening tests and novel computation methods to detect cancer early. In therapeutics, researchers have developed a computational platform that characterizes disease heterogeneity and identifies compounds that will be effective for specific patient sub-populations. Several research groups are also building a number of machine learning modules to interpret genetic variations and how they impact various biological processes, such as splicing, in the body, discovering new drug targets for nucleic acid therapeutics. Further several companies are using predictive algorithms and machine learning to understand their vastly growing databasesof integrated data such as administrative claims and electronic medical records.
As multi-morbid patients continue to grow in volume and make up ever more of the cost of care provided, hospitals are increasingly forced to seek cost-effective, proactive, multi-touch methods to manage these patients.
Several companiesare offering services that help Medicare Advantage plans to more accurately adjust risk based on patient records, and other companies are enabling payors to speed up important decisions such as prior authorizations to reduce unnecessary services. Several groups are currently working to fuse multiple data sources to reveal drivers of cost and quality so that clinical teams can deliver the best possible care at the lowest cost. Outside the hospital, we see smart care coordination platforms prevent costly acute care readmissions which account for the bulk of healthcare cost. Companies are using these platforms to help care coordinators detect signs of mental disorders such as depression through automated patient voice analysis, enabling the clinician to kick-off depression protocols potentially even before patients themselves are aware of their depression. Other companies are taking this further, transforming care coordination by taking on risks themselves to provide social services (for example, food, transportation) to Medicare and Medicaid patients in a patient’s community.
The influx of data from the molecular to behavioral level will provide unprecedented insight into diagnosis and treatment of diseases. The interdisciplinary nature of computational health presents innovation and partnership opportunities for startups and established organizations. We are now at the early stage of data collection and discovery: We are still discovering new insights about our genome every day and we still know very little about our epigenome and proteome. Advances in data analysis may one day enable us to create a detailed molecular atlas of our body that simulates changes based on various diseases and changes in the environment (Virtual Human). In addition, there are many opportunities in technologies that help hospitals effectively deploy increasingly costly labor resources and meaningfully reduce supply cost, predict acute events, ensure delivery of care in the most appropriate setting, and enhance patient experience and health outcomes for an ever older, sicker, and more complex population. The challenges facing healthcare providers and payers are significant and so are the opportunities for innovative companies with effective solutions. By computing health, providers can design treatments that are targeted, precise, and uniquely suited for individuals. One area where the applications of these advances have clear potential is in digital therapeutics.
Digital therapeutics, a subset of digital health, is a health discipline and treatment option that utilizes a digital and often online health technologies to treat patients.The treatment relies on behavioral and lifestyle changes usually spurred by a collection of digital impetuses. Because of the digital nature of the methodology, data can be collected and analyzed as both a progress report and a preventative measure. Treatments are being developed for the prevention and management of a wide variety of diseases and conditions, including type II diabetes, congestive heart failure, obesity, Alzheimer's disease, dementia, asthma, substance abuse, ADHD, anxiety, depression, and several others.
Digital therapeutics may provide information on mental health issues affecting the quality of life of patients with various disease states and chronic conditions which are not often captured by providers or in survey based research. Further incorporating successful techniques into long term treatment plans may improve patient outcomes and reduce costs to offset treatment and therapy options currently being offered in oncology and other disease areas. Currently several companies are offering portals for patients to access digital therapies and other companies are offering specific software/devices or online resources for digital therapy. The potential for this technology is to provide real time health and preventative care that is supported by integrated patient data and can improve patient outcomes while reducing costs.