The growing number of digital health companies that have reached unicorn status in the past two years would lead many to believe that this has finally become a mature, well established space. However, when it comes to the application of digital health in real world clinical settings, we still have a long way to go.
We have some unforgettable examples in the archives to prove growth hacks are not sustainable in healthcare. Aggressiveness for disruption by softwares in other industries cannot be replicated in healthcare. We need to take the time to establish a solid evidence base to support their claims before going gung-ho with the marketing and partnerships.
Given that the environment in which these digital health technologies are being funded and developed is not comparable to that in which pharmaceuticals are being developed, we are walking into our report and analysis with the assumption that there is not as much evidence out there in terms of rigor, size, validated endpoints, validated digital trial protocol, validated placebo, widespread geography, but are open to being proven wrong.
HealthXLs Digital Health Evidence Review 2019. This report aims to identify, categorize, and summarize all existing, relevant studies in digital health. Through this report, we want to establish a clear understanding of the existing body of clinical evidence for digital health, its maturity, current gaps and needs.
Hypothesis - What do we expect to find in the universe of digital health publications?
Some of the hypotheses we are gunning to decode this report include the following:
- We suspect a large proportion of digital health publications are not in the highest impact factor journals
- We would expect there to be a growing maturity over time in the data in terms of presence of interventional studies and gold-standard RCTs with larger sample sizes
- We expect to see greater content in more frequently occuring/ high disease burden conditions such as cardiometabolic disease, cancer, etc.
- We expect to see greater content in earlier ‘digital’ initiatives such as telemedicine and mHealth (as opposed to newer digital therapeutics or AI)
- Additionally, we hypothesise a direct correlation between the most funded companies in the past decade and those who are producing research publications
Methodology - What’s driving the data?
The HealthXL Research and Platform teams have joined forces to collate thousands of digital health related publications in order to decode our hypothesis and uncover hidden insights - we are using a number of digital and clinical terms to slice the Everest of information we have at hand. Here is an overview of some of the sources we will be pulling from to access this information.
Q2 Report incorporates research data from:
- PubMed digital health studies
- Digital health company websites
- Leading healthcare journals
- Emerging digital health journals
In addition to the research collected we will be cross referencing other data points including:
- Regulatory approvals of solutions
- Company investment information
- Journal impact factors
- Top publishing health systems and institutions
- Leading disease burden areas
- And more...
In addition to the data insights gathered, we will be nuancing our findings with expert input from clinicians, investors and industry executives and triangulating with our own insights gathered from the thousands of hours of digital health research we already have under our belts.
User Stories - What value will these insights provide and to whom?
Throughout this report are peppered user stories - you will probably be able to associate with one or more. Below is how we intend to answer and address these user stories through our investigation.
User Story 1 - As a HealthXL member, I want to be able to see if digital health solutions are producing the same rigor of evidence as drugs, and if money going into the sector matches evidence generation and subsequent regulatory approval and commercial partnerships.
This will involve mapping HealthXLs research data with data on investment, IP, regulatory status, commercial partnerships, location.
User Story 2 - As a Therapeutic Area (TA) head, I want to understand a snapshot of my TA maturity in the form of published evidence for digital solutions.
Fields of Study -
Digital Areas: We want to identify the digital areas with the most evidence generated to date - is it telemedicine, or mHealth, or Digital Therapeutics? It may help answer the elusive question of maturity, and help us understand, as an industry, which areas are more ripe for adoption.
Therapeutic Areas: As a first step, we have identified the top disease areas by burden, globally.
What we are now attempting to do is map the digital studies captured above, to these areas by burden and identify commonalities or gaps. Shouldn’t new solutions address conditions that have the greatest morbidity and mortality to really help populations live healthier and longer?
User Story 3 - As a Senior Healthcare Executive, I want to be able to understand who the front-runners are for running research in digital health (universities, hospitals and start-ups), who are worth their dime in proving their technology, efficacy and efficiency.
Centers of Study -
We will map the digital studies captured back to the academic or research centers and hospitals where they have been conducted. This will not only tell us who the most active researchers are in digital health, but also help us identify hubs and hotspots for innovation in health technology. We will map this to university/ hospital and also to geographical region. Looking for your next big investment or partnerships - you will know where the foundations are being laid!
Journals of Reverence -
We all know of the gurus of medical and scientific journals - the Natures and NEJMs of the world. What we’d like to see is how many of these journals are publishing studies on digital health. If studies and trials in this space are not featured in these hallowed journals, it is very likely that they will not grab the attention of the scientific community. We want to call out this gap, if it exists.
User Story 4 - As a pharma innovator/ strategic investor, I want to understand competitive landscape from a clinical evidence perspective to help me make partner decisions.
We will use additional data from the HealthXL platform on digital health companies and identify correlations (if any) between strong clinical evidence and
- investment received: top funded in a specific TA = top rigor in evidence generation?
- regulatory approval received: more evidence = higher the opportunity to gain regulatory approval?
- partnerships engaged in: more evidence = more commercial partnerships?
We are super excited (and quite overwhelmed) about our Q2 Report (coming this July to your inbox). We want this report to be your reference and guide to mapping digital health studies and generating evidence. We want us, as an industry, to be thinking about what the methodologies should look like when it comes to evaluating digital health innovations, and ultimately inform the creation of validated, robust companies, guidelines and partnerships.