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The Two Faces of Population Health Management

by corasharma | December 13, 2013

As we head into the New Year, we at Chilmark Research have been thinking a lot about how we will approach Population Health Management (PHM) in 2014, and beyond.

PHM is actually a pretty unfortunate term for the data-driven business processes and associated tech stack that HCOs must adopt as they head towards value-based reimbursement. But, the term is here to stay and therefore we must embrace it (besides, does anyone have a better term that does not include “Big Data” or “Accountable Care”?)

In August, we released our first market trends report addressing one aspect of enabling PHM: 2013 Clinical Analytics for Population Health Management Report. We are now working on the next iteration of this seminal research report, and as the market evolves, we must continually ask ourselves: “What does Population Health Management mean today?”

In public health circles, the concept of PHM is simple: increase a set of quality KPIs across a population that includes both low and high-risk groups.

In the real world, PHM is what is happening as providers move from FFS to value-based payment models — effectively forcing them to adopt HIT to (1) improve and report on ever proliferating quality metrics, and (2) move from a “cost plus” business model to one of cost containment.

Currently, we see PHM divided into two main categories that were previously, by and large, the responsibility of payers and vertically integrated HCOs: Care Management, and Performance Management. Below is a tech stack figure that I am using to visualize these two categories:

Care Management involves managing patients –both during and between visits– according to standardized protocols. The hope is that by identifying sources of patient health risk and through clinician intervention, costly utilization can be prevented and/or quality measures attained. Analytics and associated content are required to build out the necessary quality measures, care gaps, predictive models, etc. Workflow tools are needed so that clinical and care management teams can take timely action.

Care Management solutions on the market today are incredibly heterogeneous, ranging from basic disease registry dashboards to full-fledged care coordination workflows that can span an exceedingly wide range of care venues.

Performance Management is the domain of the Chief Medical Officer (CMO), CMIO, CFO and department leaders. This category of tools is informed by analytics and is meant to identify opportunities for care delivery process improvement across the HCO’s network. The emphasis is on turning the HCO into an efficient and cost effective organization (improving the health of a population might be a side effect).

For example, consider how important it is to identify which orthopedic surgeons are responsible for the highest variation in length-of-stay (LOS) and cost:

Yes, there is overlap between these two categories. For example, a physician leader might want a dashboard to view aggregate quality measures for different cohort populations, as well as have the ability to slice and dice and drill down to specific patient outliers. In addition, utilization and cost metrics are increasingly being used within care management tools as a way to identify high-risk patients.

One thing we at Chilmark Research continue to debate is how the definition of PHM might keep expanding. It is easy to define certain boundaries. We do see PHM as care delivery and care management centric – it is not about optimizing all HCO operations. Therefore, Chilmark will not wade not wading into RCM or supply chain/staffing territory when it conducts research on PHM.

Other boundaries, however, are not as easy to define. For example, what about  data mining tools that monitor inpatient vital signs in real time to predict sepsis? What about treatment pathways and the data-driven AI tools of the future that are meant to replace doctors? These should all have tremendous impact on patient health, right? Not to mention how activity-based costing systems (ABC) will eventually integrate with PHM systems (e.g., Intermountain’s relationship with Cerner).

The bottom line in my research that I will keep coming back to is the concept of driving care delivery efficiencies under value-based reimbursement, and the current separation between performance management and care management. Having said that, I look forward to 2014 where we will see if the term PHM will stand the test of time, or go the way of ACO-enablement.

Lastly, I invite our readers to chime in or contact me directly with their thoughts on PHM. Do you agree with how we have scoped out our PHM research? Is there anything that is currently a prioritization  at your organization that I have overlooked? I look forward to hearing from you.

 

 

4 responses to “The Two Faces of Population Health Management”

  1. […] As we head into the New Year, we at Chilmark Research have been thinking a lot about how we will approach Population Health Management (PHM) in 2014, and beyond. PHM is actually a pretty unfortunate term for the data-driven business … Continue reading → […]

  2. What about remote patient monitoring systems that track and manage patients either in between visits or help patients manage their ranges or disease. Our platform can say contact a patient on a specific schedule or period of time and determine if they status is a potential risk and then triage these patients around severity. Analytics is the first step but managing patients is another. Many systems in population health management help determine high risk patients then allow hospitals to export this data for “preventive USA mail letter generation ” is this a strategy ? The next wave will be symptom and recovery management of patients in near real time.

    • corasharma says:

      Hi Charles, yes user generated data/remote monitoring is the future. In the tech stack diagram I would put user generated data as another data source. Analytics is run on this data and insight provided to the caregiver team & the patient. However it is slow-going when it comes to providers ingesting this data. There remain many (non-technical) challenges.

  3. EHR vendors will have to partner….

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