Lidia Fonseca Explains Ways Data Analytics Improves Patient Outcomes

The integration of data analytics into everyday use has allowed physicians to better engage in the patients care by intervening and taking action early, which ultimately improves quality of life and outcomes, said Lidia Fonseca, senior vice president and chief information officer of Quest Diagnostics.

Transcript (slightly modified)

How can the use of data analytics improve patient outcomes?

I think a couple of ways actually. One, by bringing the information together, by making it actionable. There’s a couple of major outcomes that are going to result from this. Number 1, I spoke about that shift from treating the sick to keeping people well, it’ll enable us actually by running those data diagnostics that we can intervene sooner. If you think about employers that insure their employees and if you look at their metrics, it tends to be that a small percentage of their employees with chronic conditions are the ones that drive the line share of health care spending.

So, 1 of the long-term outcomes of this data diagnostics is that we can identify risk sooner. So for example, if somebody is diabetic or pre-diabetic, the fact that we can stratify their risk because if you’re pre-diabetic, you take certain actions versus when you’re diabetic or if you’re in a late stage of diabetes. And so, by being able to intervene sooner, number 1 we can improve the quality of life of patients because we actually have the ability to intervene and stave off chronic conditions. So the 1 long-term effect is that we can improve the quality of life for the individual.

The second effect is that we identify risk and we can intervene and we can actually take actions to keep a patient on track and manage their health over time. And then I think the other major long-term effect is by doing this and intervening and managing risk and actually taking action sooner, it will take costs out of the healthcare system as well. But again, more importantly, improving the quality of life for the patient, number 2 improving the outcomes themselves because we made better clinical decisions and then number 3 really taking costs out of the system, becoming more efficient.