The adoption of digital health technologies is rising, propelled by the spiralling cost of healthcare provision and drug development. Digital solutions are already having a major impact on almost every aspect of healthcare, from molecular drug discovery to clinical decision support and population health. In our comprehensive Digital Health Sector Note, we provide a breakdown of the digital health landscape into four identifiable segments: Patient-Doctor Interaction, Patient Management, Data Analytics and Drug Development.
In our report, we detail 17 UK-based companies with substantial and representative exposure to digital health trends, illustrating our market-leading coverage of this exciting and rapidly developing sub-sector.
The Quadrants of Digital Health
We have divided the digital health landscape into four broad categories, depending on the specific area of focus. Ultimately, the unifying characteristic across all four categories is the use of technology, specifically digital information supported by specialised software, to provide better prevention, diagnosis and treatment at lower cost.
- Patient-Doctor Interaction – tools to improve communication between patients and physicians, including online/video physician consultations, mental health consultations, chatbots, and sophisticated clinical decision support tools;
- Patient Management – electronic health records, digital diagnosis, remote monitoring, efficiency tools, triage tools and wearables;
- Data Analytics – providing better insights into complex datasets, often identifying digital biomarkers from disparate sources to identify trends in behaviour or disease expression, simplifying decision making in areas such as population health, or improve patient stratification into clinical drug trials; and
- Drug Development – applying new technologies, principally AI / machine learning, to streamline the drug discovery and development process, and identify more promising drug candidates.
Quadrant 1: Patient Doctor Interaction
A core theme in digital health is enabling improved communication between patients and their physicians. This is effectively an extension of the telehealth initiatives that have been in gestation for years, but which have not had the technical wherewithal to be truly effective. Now, with smartphones and tablets being almost ubiquitous, online, virtual and video consultations are possible and gaining prominence.
Practical considerations, especially in the NHS, are all too clear. Concerns abound that outdated IT systems are not fit for purpose – slow to log in, clunky to use and unreliable in moments of crisis. There are signs that these issues are now finally being seriously addressed, giving health and care professionals the tools they need to efficiently deliver safe and effective patient care, and requiring vendors to meet usability standards to match those in other fields. As an example, the NHS Long Term Plan, published earlier this year, includes a chapter dedicated to its ambitions in relation to digital technology. It is largely a reiteration of goals around digitisation of patient records and processes, sharing of information via the NHS app, and completing the work started by the Global Digital Exemplar program prompted by the Wachter Review.
Quadrant 2: Patient Management
Evolving best practice and confidentiality issues have held back broad adoption…
Standardisation, the starting point for digitalisation, is a well-known driver of industrial success, but only once best practice has been established: this has held true from T-Ford to T-Cell manufacturing. However, in healthcare, best practice is constantly evolving as a result of a rapidly expanding understanding of human biology, and increasingly astute, often payer-led monitoring of the impact of intervention. In our view, this has represented a major hurdle for wholesale adoption of digital technology, restricting its use to distinct operations such as imaging, maintenance of patient records and laboratory automation. An additional hurdle is the regulatory challenge of integrating and analysing a diverse mix of personal and generalised data without breaching patient confidentiality.
… but the opportunity for cost reductions and improved care can no longer be ignored
The previously patchy pattern of digital technology adoption is now changing rapidly, primarily driven by the rising cost of healthcare provision, and enabled by i) increasing computational power; ii) cloud-based solutions that eliminate the need for local infrastructure; iii) open-source software that facilitates systems integration; and iv) handheld devices that provide sophisticated decision support to the end-user, whether he or she is a hospital specialist, a community nurse or an individual engaged in maintaining good health.
In our view, the positive impact of digital adoption in patient management mainly stems from: i) cross-functional integration, and ii) devolved decision-making: the spiralling cost of healthcare provision cannot be curtailed unless more people are empowered to make the right decisions at the right time.
Quadrant 3: Data Analytics
We believe the collection and analysis of digital biomarkers (physiological and behavioural data collected by exclusively digital devices1 e.g. wearables) will play an increasingly important role in several areas, enabled by the more proactive regulatory environment.
- In drug development, the use of digital biomarkers allows for the cost-efficient collection of vast amounts of longitudinal data, providing in-depth and potentially new insights into the safety and real-world efficacy of investigational drugs;
- In medical practice, the longitudinal data provided by digital biomarkers can be used alongside point-of-care measurements and analyses of biological samples to enhance diagnostic accuracy and improve the management of chronic diseases;
- In an increasingly payer-led environment, the additional evidence provided by digital biomarkers can be used to establish appropriate reimbursement rates for new and existing drugs & medical devices; and
- Digital biomarkers can empower patients and healthy individuals to make better healthcare-related decisions (from self- medication to prevention-by-lifestyle).
Quadrant 4: Drug Development
Potential for large efficiency gains in preclinical and clinical drug development.
Preclinical development (from target identification to non-human preclinical models) represents a critical but time-consuming and often iterative process, which intuitively seems ripe for digitalisation. In addition, the underlying core technologies (e.g. molecular imaging, structure-based chemistry, gene sequencing and PCR) have all been digitised for many years, providing excellent scope for data integration.
As a result, AI-enabled deep learning networks (trained on large data sets) are currently being developed to improve new molecular design and predict drug reactions. The early results are encouraging, with similar or better outcomes than rule-based methods. Another area where AI is making an early contribution is drug target validation, based on the integration and analysis of disparate ‘omics’ data (e.g. epigenomics, genomics, transcriptomics and proteomics).
The clinical development process is also being targeted for efficiency gains, by means of machine learning algorithms developed within Big Pharma to track and improve patient recruitment, monitor trial progression and reduce the substantial cost of operating global, multi-centre clinical trials that at any given point in time involve many thousands of patients.
Regulatory change to stimulate innovation, but so far only in the US
The FDA has opened the door to digital health medicines and software, embracing this evolution through regulatory change and approving the first wave of clinically trialled digital health products. A key measure is allowing for low-to-moderate risk digital health products to be classified as Class I/II devices, avoiding an initial 510(k) submission in favour of a less stringent De Novo approval pathway (which enables regulatory clearance of digital health products in the absence of an existing reference product with which to determine substantial equivalence).
In addition, the FDA has introduced a Software Precertification Pilot Program for healthcare software products. This pilot promises to facilitate a more streamlined regulatory process by basing a review primarily on the software developer’s regulatory status rather than the product itself, whilst maintaining stringent standards with regards to maintaining patient safety. Over 100 companies are involved in the scheme including Apple, Fitbit, and many Big Pharma companies.
In Europe, less regulatory progress has been made: no digital-focused approval pathway has so far been established, which unless addressed could temper innovation in the digital health space.
To receive the full version of the Digital Health Note, please contact Jens Lindqvist or email Research Entitlement.