Using data and technology to improve healthcare ecosystems
A Verily Life Sciences executive explains how the company targets better patient outcomes by harnessing analytics, machine learning, and other digital tools.
Patient outcomes are taking over from products and services as the focus of healthcare. But reorienting away from product development toward a holistic approach to patients demands the convergence of data from every part of the healthcare system. In this interview, part of our Biopharma Frontiers series on how the pharmaceutical industry is evolving, Jared Josleyn, global head of corporate development at Alphabet-owned Verily Life Sciences, talks with McKinsey’s Michele Raviscioni about the need to integrate health data and apply it to patients’ lives in ways that achieve enduring impact.
Jared Josleyn: Verily is a data healthcare company that extracts high-fidelity data from the healthcare ecosystem and applies it to patients’ lives to improve human health. Everybody today talks about the need to focus on patient outcomes, but a lot of those conversations break down because of a lack of high-quality, longitudinal data—because we don’t know how well people manage their diseases on a daily basis, or we don’t understand comorbidities across different chronic diseases well enough, and so we can’t predict the effect a treatment will have on a patient population. Right now, data sets, whether from pharmaceutical companies, hardware companies, clinical workflows, or patients, sit separately within the ecosystem, which doesn’t effectively enable a true outcomes-based model that properly aligns incentives for all parties so that patients arrive at optimal outcomes. Verily’s purpose is to collect and integrate these massive and disparate data sets, observe new patterns, extract insights, and provide those insights to clinicians and patients to enable better management of health and disease.
Take medical-device hardware. Verily’s goal isn’t to create the next incremental invention in hardware: it’s to ask what exists in a particular space and whether it’s sufficient to extract the highest-quality data to enable better outcomes. For example, we looked at continuous glucose Using data and technology to improve healthcare ecosystems monitoring for patients who are diabetic. After doing an assessment, we didn’t think the applications currently available were wholly effective for patients with type 2 diabetes because they are not user-friendly, they are too narrowly focused, or they overlooked other important behavioral aspects of diabetes management. So we entered that space. We start with the problem first, and if an available wearable or other sensor doesn’t collect the right data so we can provide inputs back to the patient, the providers, and the clinicians, we want to create a solution.
The approach is equally applicable to pharmaceutical companies. We look at how we can improve a company’s ability to predict whether a particular combination therapy will be precise enough to be effective for a given patient population.
On the provider side, we look at how to create tools providers can use to create recommendation engines, to improve clinical workflows, to improve clinical outputs—and to offer doctors all the tools and data so they can make the best clinical decision possible and do what they went to medical school to do, which is to focus on the patient, not spend an inordinate amount of time entering information into systems.
McKinsey: What do you see as the short-term and longer-term opportunities for impact in the way healthcare is delivered?
Jared Josleyn: To create short-term impact in people’s lives, you need to focus on the delivery of certain applications. This can include the continuous glucose monitor, as I described before, or the diabetic-retinopathy screening tool that we’re developing with Nikon, the goal of which is to improve the speed, accuracy, and accessibility of diabetic-retinopathy screening as a way to prevent blindness.
