Expanding Non-traditional Data into Healthcare Analytics

Posted on June 14, 2016

Jay Kleinman CentraForce Health

Jay Kleinman, Managing Director and Chief Revenue Officer at CentraForce Health, sat down with the team to provide his perspective on how non-traditional intelligence is shaking up healthcare analytics and what we can look forward to as he moves into his new role at CentraForce Health. 

What are some of your plans for expanding CentraForce Health’s presence?

We’re looking to provide Healthcare Strategists with the non-traditional data that allows them to understand the context of their patients outside the walls of a healthcare setting. Our population-centric intelligence gives our clients a holistic view of their populations — everything from health attitudes to social determinants/behaviors to which modality to best engage can be found within our Platform. Whether the client is a payer, provider or employer; if they have an ACO, Medicare Shared Savings program or other value-based arrangement, we can offer intelligence on the on the community as a whole down to a single person in an attributed population. It’s a powerful capability.

Why will non-traditional data/intelligence be a key player in the future of healthcare?

Non-traditional datasets, like ours, capture patient populations in their everyday lives; away from the healthcare setting. We’re hearing more and more from Healthcare Strategists (such as CMOs, CIOs, etc) that clinical and utilization data, solely, is not enough to have a meaningful impact on the engagement and socio-behavioral changes a population needs in order to have a real opportunity to improve the quality and value of their care. It’s the non-traditional datasets that provide the “how” and “why” of patients as “consumers” that are going to be critical in closing the gap to holistically manage care for populations.

As we move toward the consumerization of healthcare, what can organizations do to be more customer-centric?

The patient as a consumer has a multitude of meanings in healthcare today.  But in all definitions it’s about outreach, engagement and interventions. Organizations can capitalize on the ability to know who their customer is before they even become a customer. Every provider and payer knows who their current patients are and how they utilize (or consume) health services. What’s lacking is their knowledge of who has the propensity or added risk of needing health services. With predictive analytics they can create actionable insights to reach these populations who may not even know they need the support services of a healthcare organization, or the intervention of care management. The ability to supercharge clinical analytics, care management plans, market development efforts and patient outreach and engagement will be the separator between those who will struggle as they react to the needs of their patients and those who will flourish as they proactively engage theirs.

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