Why is Population Health Management Important?

Guest post by Abhinav Shashank, CEO and co-founder, Innovaccer.

Abhinav Shashank
Abhinav Shashank

The way we see healthcare today is very different from what it was a couple of decades ago. Back then, we did not have the technology to capture the best practices. But, today we have the capability to use medical data as a source of innovation and create impact at scale. But the question is are we capitalizing on it? Have we made the lives easier for both patients and care teams? Are we close to the goals we started chasing ten years ago?

When we talk about innovation in healthcare, we stumble across intuition. The intuition of care teams enhanced by data-driven approaches. It is not just limited providing connectivity to healthcare organizations; it is also about providing advanced analytics and reducing the cumbersome, tedious work! Like deep diving for hours on Excel or making quality tracking and reporting easier.

The concept of population health management is a new one. It has evolved from an idea to become a clinical discipline that works on developing and continually refining measures to improve the health status of populations. A successful population health management program thrives on the vision to deliver robust and coordinated care through a well-managed partnership network. This said, there is no one definition of Population Health Management, fifty different CIOs in an interview gave different definitions to this term. It is a broad concept and covers a lot under its umbrella.

What does an ordinary health IT setup lack?

True, the healthcare systems are working on building the skills to interact and develop well-planned health intervention strategies to move away from the traditional fee-for-service model to value-based reimbursements and incorporating value, but they are falling short in many areas:

Limited EHR capability: EHRs played a pivotal role in digitizing health care, but with EHR technology many restrictions came along. Today, only a few are equipped to support the necessary interoperable standards. To deliver better clinical outcomes, it is of paramount importance that we have the data and right analytics to ensure improvements; something healthcare organizations lack even today.

Integrating data sources: A patient who is being relocated to a new state and will have a new PCP and Care Coordinator. Can we say with confidence that the patient’s information will be available to the new PCP? In a large healthcare network, there is labs, pharmacy, clinical, claims, and operational data, but the capability to integrate it into a single source of truth is still a challenge for many! This has limited the potential of care teams and made them communicate in a disconnected ecosystem.

Risk Stratification: 50 percent of expenditure in healthcare is on 5 percent patient population. Wouldn’t it be great if we could find these patients and cure them before any acute episode? Back in 2012, about 117 million Americans had one or more chronic conditions, and account for 86 percent of the entire healthcare spending. The road to population health management will require care teams to recognize at-risk population timely to reduce cost and improve outcomes!

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