In our ‘Disruptors’ webinar series, we look at industries undergoing major changes, inviting experts to explain key trends and what insights and intelligence professionals can do to tackle them. Here, we concentrate on the healthcare industry.
The webinar on disruption in the healthcare industry brought together industry experts Jo Appleton, Head of Clients & Global Therapy Centres of Excellence, Ipsos Healthcare; Jackie Ilacqua, Global Head of Syndicated Services and President, Global Oncology, Ipsos; and Martin Rückert, Chief A.I. Officer at Market Logic.
Jo Appleton opened with a presentation on the forces disrupting the healthcare industry today. While our ability to treat disease has drastically improved over the last few decades, it’s brought a much longer-lived population, which increases the cost-of-care burden.
This also means greater commercial and ethical pressure on pharmaceutical companies: new medicines need to prove their value to policymakers, payers, and patients alike.
Technological disruption in the healthcare industry
Technology plays a huge part in this: advances are leading to the creation of precisely targeted medicine, where patient outcomes can be predicted by matching the genetic makeup of a disease with a specific treatment.
Developments in A.I. are also transforming clinical trials: it’s now technically possible to run a clinical trial by identifying patterns in data and creating models that can sometimes predict outcomes in virtual patients.
Technology is also increasing the cost efficiency of real clinical trials, from more efficient recruiting to better outpatient monitoring. Ingestible smart pills assist in diagnosis and monitoring, reducing the need for invasive procedures.
Jo predicts that digital therapeutics (a discipline that uses digital and often online methods to change patient behaviour) will be one of the biggest disruptors in the coming years: from software and phone apps to virtual reality, this field is already redefining medicine. Whether traditional healthcare will compete with or absorb this new area remains to be seen.
For healthcare companies, unlocking the power of data to delve deeper into insights is essential; to do this, technology must be incorporated as a partner. The companies that deliver their own disruption while embracing technology and putting customers at the centre of their business model will be the market leaders of the future.
Jackie Ilacqua then addressed the power of real-world evidence. In the healthcare industry, there’s a constant demand for data to prove that a drug is effective. But the amount needed to look at medicine, from trials to medical devices, is a mountain of data that could overwhelm the most skilled data scientist.
Any data that’s readily available—for example, patient charts, pragmatic trial data, registries, patient surveys, biometric and government—is all real-world data. It’s important to remember that real-world data isn’t real-world evidence until the appropriate analytics are applied: multiple data sets are needed to get to the real evidence.
Although there have been a few rare disease products approved based solely off of real-world evidence, it isn’t typically used to substitute evidence generated through randomized controlled trials. However, Jackie predicts that the need to collect new data will diminish as the analytics necessary to analyze and extract value from existing data will increase. Data will support or be created from every other disrupter that Jo mentioned previously—knowing all of this, you need to ask yourself how you will get ahead of the curve.
Dealing with data
Which leads us perfectly into our next point: how to get faster speed to insight when there’s too much data. Martin Rückert explained that by blending structured and unstructured data, a knowledge graph that connects every source of input is created. This knowledge graph makes it easier to understand and anticipate patterns, augmenting the abilities of researchers to answer difficult questions and deal with mountains of data.
The panel then took questions from the audience. The first question was, “How is disruption changing the role of the insights manager in healthcare today?” Jo answered that there’s a great need to get more out of existing data sources by working with analysts and data scientists, as well as gain insights from different stakeholder groups.
Under increasing regulation, privacy concerns, and challenged budgets, the role of the insights manager is more complex than ever before. GDPR has also caused huge disruption recently: there’s a lot of nervousness in the industry around lawsuits and data privacy.
To the question, “How is the role of the real world evidence changing the role of the insights manager today?” Jackie answered that, years ago, you’d conduct primary research to answer questions.
But now, there are overwhelming amounts of data, which is changing the people that we need to interact with in order to gain insights, and the understanding of different data sources: not every source is going to give you the kind of answer that you need. It’s certainly getting harder for professionals in the healthcare industry.
How insights managers can stay on top
The next question from the audience was “What advice would you give an insights manager to stay on top of disruption?” Jackie noted that there are holes within data sources, and you need to know how to merge the right ones together to get your answers.
You have to partner with people who understand different sources and the best way to use and access them, in order to answer commercial questions that clients have.
“Is data the greatest disruptor?” is a tough question because data is linked to every disruptor. They’re all connected—it’s hard to pull the disruptors apart. We’ve moved from having limited data to having too much data.
Jo also noted that technology is a great facilitator, from the consumerization of health and the way that consumers are demanding more involvement in our healthcare to the treatment decision process.
Martin was asked, “A.I. promises to bring all of this together. But is it democratizing the way to be a data scientist?” He said that A.I. can take away the need to be a data scientist when data is connected to a platform.
The platform certainly makes data science techniques easier, as it converts data into statistical properties in the back end so the user doesn’t have to. It also keeps up with what’s changing, so that newer information is prioritized over older information.
Better healthcare solutions
In closing remarks, Jo said that we need to continue to challenge and disrupt the norm, no matter what area of healthcare we’re in. She believes that this will continue to lead to better healthcare solutions and improved outcomes, which can only be a good thing.
Jackie agreed: she said that we need to look at all the information available to help us make better decisions and to help our clients make better decisions for patients. Martin, meanwhile, wants to provide better outcomes to researchers and marketers: not just answers to questions, but what those answers mean for the business itself.