Digital health is unquestionably becoming part of healthcare lexicon and fabric. Electronic health records (EHRs) and personal fitness trackers have helped create awareness through use.  The entrepreneurial enthusiasm for the healthcare space is evident by the volume of digital health incubators, medical school innovation centers,  and angel investors.  Though there has been significant sector investment, the road to success of adoption in the healthcare enterprise has been challenging.  I’d like to discuss what I believe are five areas of significant opportunity for quality technologies.

1. EHRs. According to most recent statistics from the Office of the National Coordinator, use of EHRs has increased from 20% in 2004 to 87% in 2015. EHRs were designed as documentation centers for billing and regulatory purposes. Relevant clinical patient management data workflow was not a priority and remains a major pain point for clinicians today. According to a study in the American Journal of Emergency Medicine ER physicians spend only 28% of their time in direct face to face patient contact and can go through 4000 computer mouse clicks in one shift.  From a provider standpoint. the regulatory and billing data entry should be performed by someone else and relegated to an (almost) invisible part of the EHR.  We need EHRs which are clinically oriented with good user interfaces. Interoperability [defined by the federal Office of the National Coordinator for health information technology (HIT) as the ability of information systems to exchange patients’ electronic health information and use information from other EHR systems without any special effort from the user] is another major pain point that needs to be addressed. .Six years into Meaningful Use we have yet to achieve any significant interoperability of EHRs. There are hospitals within the same healthcare system in many places with disparate EHRs which do not talk to each other or exchange information.  Increasing healthcare consolidation of hospitals has exacerbated the problem of lack of interoperability. Health Information Exchanges (HIEs) have been woefully underfunded and have fallen short of their vision. There remain many opportunities for technologies to assist in achieving true interoperability.
2. Clinical trials. CIOs are constantly inundated with requests to purchase new technologies which will “save money, improve patient satisfaction and outcomes and decrease readmissions.” What is in fact lacking in most cases is evidence for these claims.  The hesitation of many entrepreneurs to embrace the intuitive adoption requirement of proof of claim (which needs to be said should not differ from the adoption of product in any field of endeavor making claims) is the misconception that time-consuming large costly randomized clinical trials are what I am referring to. This should not however translate to “take my word for it” is all you need. I agree that traditional trials are neither practical nor necessary for most tools. Even the FDA has now recognized with thoughtful and cautious restraint a role for ‘real world evidence’ (defined by the legislation as “data regarding the usage, or the potential benefits or risks, of a drug derived from sources other than randomized clinical trials,” including sources such as “ongoing safety surveillance, observational studies, registries, claims, and patient-centered outcomes research activities.” in the approval process of drugs. Thus, the opportunity for trials utilizing digital registries, mobile clinical trial platforms, quality communications and analytics tools is significant.
3. Artificial Intelligence (AI). One early definition of Artificial Intelligence (AI) in medicine (1984) was “…the construction of AI programs that perform diagnosis and make therapy recommendations. Unlike medical applications based on other programming methods, such as purely statistical and probabilistic methods, medical AI programs are based on symbolic models of disease entities and their relationship to patient factors and clinical manifestations.” Today a broader definition may be applied: “the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using the rules to reach approximate or definite conclusions), and self-correction.” The use of artificial intelligence in medicine has been the subject of intense and rapidly growing interest in medical, computer science, and business arenas.  The market growth of AI is based on its projected impact on both technology and non-technology sectors. There have been arguments for and against the inevitability of replacement of physicians by AI technologies for a while now. The debate continues. BASF declared “We don’t make the household product, we make the product better.” An analogy can surely be made with AI. It runs in the background of technologies already in use but will make them run faster and more importantly will add a dimension of relevance of incoming data.
4. Personalized medicine. The National Cancer Institute’s definition of personalized medicine is “…a form of medicine that uses information about a person’s genes, proteins, and environment to prevent, diagnose, and treat disease…” Personalized medicine is medical care directed in whole or part from information specific to an individual.  Discoveries in the area of the genetics of cancer have resulted in the development of drugs no longer targeted towards an anatomical location but a specific genetic marker. A landmark clinical trial in which drugs are given solely on the basis of genetic markers identified in the cancer tissue itself is the NCI-MATCH Trial (Molecular Analysis for Therapy Choice). “Patients with advanced solid tumors, lymphomas, or myeloma may be eligible for MATCH, once they have progressed on standard treatment for their cancer or if they have a rare cancer for which there is no standard treatment.” The role of personally derived connected data (from sensors external or internal to the body) will also facilitate personalized medical care. Opportunities thus exist for life sciences and technology companies to develop products for this new therapeutic approach.
5. Social Media. An early observational study of synergistic impacts of healthcare and social media demonstrated that personal experiences and not data drive social media healthcare discussions. One early survey of physicians on their use of social media found that “85% of oncologists and primary care physicians use social media at least once a week or once a day to scan or explore health information. Sixty percent said social media improves the care they deliver.” The potential for social media to disseminate information from published clinical trials, the exchange of professional education among peers, and discussions surrounding disease states is invaluable.  To be sure there exist professional and regulatory guidelines for the use of social media for providers, vendors and other healthcare stakeholders.  Social media open platforms in healthcare have proven successful for patients, caregivers and others.  Examples areTreatment Diaries, patientslikeme, and WEGOHEALTH.  Potential opportunities here involve recruitment of patients for clinical trials, gleaning real world evidence data from discussions.

By no means is this a complete discussion of opportunities for digital health. These are what I consider the ‘biggest bang for the buck’ ones doable today. I look forward to comments and the sharing of experiences from others. As a consultant I am amazed on a daily basis at the high quality clinical, financial and personal experience energies devoted to the development and advocacy for digital health tools. Bring it!