Dan Vahdat is the CEO of Medopad, a company that uses artificial intelligence to analyze patients’ data in order to make life easier for patients with rare and chronic diseases, while giving the healthcare system a way to better understand and treat these conditions.
In this interview, Mr. Vahdat shares insights on how AI can be used to improve the way patients are cared for from disease prediction to early-stage drug discovery.
What is your background and how did you start Medopad?
Medopad started in 2011 when I was researching the intersection of technology, biology and medicine. Working on part of my Johns Hopkins PhD research at the University of Oxford exposed me to the UK and the UK healthcare system where I saw a need for clinicians to have fast and reliable access to medical imaging data. I set out to research ways in which other technologies could assist clinicians and patients.
By spending time with clinicians and patients, I realised that when people leave the hospital, their data leaves with them. All of the information about their condition and how they’re feeling walks out the door. People with chronic, rare, and complex diseases are the most expensive cohort to treat and they typically spend 95% of their time outside the hospital, making the vast majority of their health data virtually invisible. Yet, it is out in the real world, outside the hospital, where most health problems occur.
As a result of those learnings and the opportunity to potentially create a new category in medicine to make the invisible, visible… I decided to leave my PhD and start Medopad (which of course caused my dad to be rather upset at me!)
For the next several years, Medopad experimented with the best ways to collect and understand patient data remotely. We worked closely with partners like Apple to accelerate our product development and test our assumptions. By 2017 our product had progressed to become fully modular which meant we were disease agnostic and that our app could be configured to meet the needs of almost any patient cohort that can benefit from the technologies we developed.
People with chronic, rare, and complex diseases are the most expensive cohort to treat and they typically spend 95% of their time outside the hospital, making the vast majority of their health data virtually invisible. Yet, it is out in the real world, outside the hospital, where most health problems occur.
How is your product improving patient experience?
Digital health has the opportunity to revolutionise the patient experience by supporting them in healthy decision-making, identifying signs of early deterioration or even treating certain conditions through digital means. At Medopad, our goal is to combine the best features of digital health into one centralised, tailored solution – meaning we allow patients to benefit in a way that’s targeted to their situation and condition. Our new solution delivers activities, tasks and education on a timed basis to support their journey through treatment. We hope that by providing this solution we can simplify digital health in order to better treat, manage or diagnose conditions.
The primary focal point for the industry at this stage, however, should be ensuring we collect the appropriate data in the best way possible. Only by using clean data with right information governance can we enable the Healthcare of tomorrow.
What are the primary issues in healthcare that AI can help to solve?
AI has been used as a blanket term for a huge area of digital health involving data and technology. As we see it, advanced data analytics has the largest applicability in identifying specific digital signatures for disease existence or advancement in an individual, in order to appropriately provide treatment. For example, by analysing gait data within an individual, studies have shown that you can diagnose Parkinson’s disease or the potential for a tremor. By allowing the patient access to this data, we can empower them to take control of their care and maximise the opportunity for better outcomes. Beyond patient-facing applications, AI also has a lot of applicability in early-stage drug discovery through either InSilico Patients for randomised control trials, or molecule analysis to identify novel therapeutic applications. The primary focal point for the industry at this stage, however, should be ensuring we collect the appropriate data in the best way possible. Only by using clean data with right information governance can we enable the Healthcare of tomorrow.
AI is there to support the physician in what they do best – make decisions on treatment, rather than replace them.
How can doctors prepare for AI-powered healthcare?
Much of the healthcare industry worries about AI potentially replacing the physician. As we see it, AI is there to support the physician in what they do best – make decisions on treatment, rather than replace them. The foremost application of AI should be in removing the need for physicians to sort through basal information on the patient and provide them with actionable insights. A good example is our work with Parkinson’s together with Tencent, which aims to automate the assignment of a UPDRS score, so physicians can focus on the patients treatment rather than monitoring them visually doing an exercise. Physicians can best prepare for AI by supporting it’s advance and working with innovators to help them understand which parts of their role can be automated, and where they believe there is the most value for focus.
AI is already changing the way in which patients are cared for, and if we reach the best possible outcome, the only difference they will notice is an improvement.
Do you think that AI will drastically change the way patients are cared for?
AI will certainly impact the way in which patients interact with the healthcare industry, whether it’s the way in which they access care or even how they are treated. However, the hope is that we will be able to retain the human interaction and decision-making that a physician provides, whilst perfecting the administrative elements. AI is already changing the way in which patients are cared for, and if we reach the best possible outcome, the only difference they will notice is an improvement.
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