Opportunities and Challenges in Digital Health (Part I)

Photo by National Cancer Institute on Unsplash

Introduction

Huge strides have been made in human health since the foundation of modern health services at the end of WW2 with dramatic increases in human health and life expectancy. A time transported doctor from the 1940’s would be amazed at modern technology and our ability to keep people alive through management of disease and better ER and intensive care. Surgical techniques and pharmacology, the use of antibiotics and the development of vaccination against childhood disease and public health measures have dramatically increased average human life expectancy.

However, while medicine develops all the time, modern healthcare services are hitting something of a plateau in terms of big transformative gains. Heart disease, chronic obstructive pulmonary disease (COPD), cancer, dementia, and diabetes are the major causes of death. While smoking as a major cause of preventable ill health has reduced, obesity has increased.

In living longer, modern medicine has introduced something of a dilemma. Although life expectancy has increased dramatically, the proportion of time we spend in good health has not increased by a similar amount. On average, we can currently expect to live out the last quarter of our life with one or more chronic conditions.

All of this, and an increasing awareness of the importance of mental health, is causing significant strain on healthcare systems around the world, irrespective of the method of funding. The costs of providing that care are huge. Planned spending for the Department of Health and Social Care in England alone is £180.2 billion in 2022/23.

Digital Health, in all its forms, is therefore one of the most exciting areas of technology. As health is our most important asset and the world market is 8 billion people, then it’s a hugely attractive market opportunity offering both the possibilities of better healthcare for patients and making inroads into the cost of modern health and social care. It also allows us to start to make inroads into what has been an illusive area of medicine to date i.e. prevention.

Part I covers the opportunities in Digital Health and Part II next week will cover some of the challenges to growth for companies in this space.

Digital Health

The Digital Health sector (also known as ‘HealthTech’) is focused on the prevention and management of disease, while MedTech provides treatment support through diagnosis, patient care, and treatment tools. Many of the existing MedTech tools are developed by industry experts and researchers through years of research and clinical trials.

Prevention is Better Than Cure

It may be true but prevention in human health turns out to be a whole lot more complex than prevention of accidents or manufacturing defects. In healthcare, prevention is ‘celebrated in principle, resisted in practice’ as Harvey V. Fineberg aptly describes it.

In reality we currently spend far more time and money on treatment of illness rather than prevention and some of those barriers will become apparent in PartII. However, this is why Digital Health offers so many opportunities in a number of broad areas.

Wellness

Definitions of ‘wellness’ vary. Typically those within the medical profession have tended to define wellness as the act of practicing healthy habits to attain better physical and mental health outcomes in a medical sense e.g. preventing obesity, mental illness and suicide. This is typically covered under public health. However, an increasing number would also include wider spiritual and emotional wellness.

We know that exercise, healthy diet, sleep etc are important to human health but measuring the individual effect is difficult enough. As a society, we think nothing of managing the cost/benefits of treating depression and diabetes through drugs, but many would think it ridiculous to pay for someone’s gym membership or a Hello Fresh subscription.

People who have sufficient time and money can afford to explore these options for themselves. The ‘worried well’ and ‘biohackers’ can work through different types of wellness options and, if they find it helpful, incorporate it into their lifestyle. However, for poorer people, who typically have less time and less money, these options become far more limited but using affordable mobile and wearable technology, we’re now starting to get more continuous measurement to be able to look at helping people improve their wellness.

While GPs would typically tell people to stop smoking, lose weight and get more exercise, people are essentially left to get on with it unaided. If it proves beneficial compared to the cost of illness, that advice may start to become more specific and we may have a more tailored and assisted approach to wellness at a population level. To do that, we need to better understand what works and what doesn’t and luckily that technology is emerging.

Data Analysis / Predictive Analytics

We have increasing capability to evaluate data and determine what works best in preventing the onset of morbidities (chronic conditions) and, for older people, prevent accidents and falls through predictive analytics. Using real world data is much easier to manage and quicker than longitudinal studies which are expensive, take years to perform and often give poor results.

Over time we may come to better understand the economics of prevention over treatment 5, 10, 20 years down the road in the same way that we understand the cost benefits for drugs. This opens up the possibility of later life lived in better health. Not only do data analysis and predictive analytics work for ‘wellness’, they also work within diagnostics.

Diagnostics

We encounter diagnostics (typically included in MedTech) usually when we are ill e.g. the doctor orders blood tests or a MRI scan or being invited to limited testing as we get older e.g. breast screening or colon cancer testing. Treatment is more effective and less invasive the earlier it is detected e.g. pancreatic cancer is often discovered far too late and survival rates are terrible.

The problem of diagnostics is cost, both in terms of capital equipment and time to do the test, analyse and feed back the results. So we’re limited in the amount of people and the tests we can do. There’s also the problem of misdiagnosis - false negatives and false positives. Furthermore, hospital testing is inconvenient for patients. They don’t want to live their lives at a hospital being tested for numerous things they’ll probably never get.

Innovation in diagnostics is working in two ways. MedTech is inventing new diagnostic tests and making the cost of testing less expensive and less invasive e.g. they can be done at home in private vs in a hospital setting increasing participation rates and enabling more testing.

In digital technology, two main technologies are coming into play. AI is increasingly being applied, along with automation, to reduce the time taken to analyse the results. Data analysis and predictive analytics enables clinicians to better understand the propensity to risk of a disease, increasingly in combination with genomic profiling.

Genomics

This is an area of huge interest and investment. By studying our genes, we can detect genetic diseases and potentially treat them using technologies such as CRISPR even before a baby is born.

At a wider level of health, it enables us to identify the genes which are associated with particular illnesses and assign a risk score for diseases according to an individual’s profile. Hence you may be tested more often and earlier in life for prostate cancer but less for colon cancer. The scope and cost of this technology is shooting down and it’s likely to be standard to do this kind of profiling at a very early age in the future.

Telemedicine

Up until COVID, one of the things that our time transported 1940’s doctor would recognise is the model of delivery. A sick patient would physically attend primary care (a General Practitioner in the UK), then be referred to secondary care in a hospital or local health centre.The need for social distancing not only accelerated the trend to remote appointments but also the concept of virtual wards where patients during the recuperative phase are discharged earlier from hospital to a home setting but are monitored remotely. This has significant potential to improve both ‘throughput’ of hospitals but also reduce the risk to the patient of hospital acquired infections. This is particularly important for geriatric patients.

Data Management and Workflow

Another huge area of potential improvement is in the area of data management e.g. patient records and workflows. The introduction of electronic patient records has been painful and expensive and there are issues around how data is recorded and classified.

As most of you will recognise from experience, the whole process of getting appointments (let alone at a convenient time) , referrals via letters.emails, reminders etc is antediluvian in ​​comparison to modern day companies like Tesco or Amazon.

And while medicine itself is not comparable to these companies (as we’ll discover in Part II), there is a huge opportunity to use digital technology to improve what are essentially workflows of people. Reducing missed appointments, the need to chase up missing information, less dispensing errors and a better patient experience are all huge benefits in both patient experience and cost savings.

Huge Opportunities Big Challenges

Healthcare is bursting with huge opportunities to improve life for both clinicians and patients both in terms of improving human health and the whole health experience. At the same time, there are big systemic challenges for companies looking to play in this space.

In Part 2, we’ll look at some of the challenges they face and why digital health companies are facing stormy waters in the next few years.

Until Next Time

Pete