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Avoiding the Noise—Making Sense of Population Health Management Data

Analyzing population health management (PHM) efforts is complicated. Many of the measures that are top-of-mind for health systems and other organizations are centered around the need to report on their population health management efforts so they can get paid. These requirements are unavoidable, but are “noise” in the big picture of population health management data—because what you’re being asked to report on is not the set of things that will necessarily make you better as an organization . Or even if it is, the measure is an absolute outcome measurement, not something that helps you understand how to improve what you do. Many measures also only assess the clinical services delivered, ignoring the social and behavioral factors negatively impacting patients that may need to be addressed before any improvement from clinical care can be realized.

PHM Data Graphic

It is incumbent on you to dig into and find information that will tell you how to treat the patient in a holistic way—what specifically to do, how to do it, and what you should improve upon to meet the test of this broader, less specific outcome. That signal in the midst of all the noise is critical, and you will need to analyze, measure, report, and act on that signal if you hope to make a difference for these less specific outcomes.

For example, a key measure for a diabetic population is a standard HEDIS measurement for controlling HbA1c levels. This measure helps you understand whether the portion of your diabetic population able to keep their levels under control is growing or shrinking, but it doesn’t give you any insight into how diabetics can best control their HbA1c levels or what other factors may be causing the issue so you can develop the right treatment to improve outcomes.

Just taking a measurement doesn’t tell you anything about the population you’re serving or the techniques needed to help those patients adhere to their care plans. It offers no insight into how often and how intensely you need to interact with the patients so their conditions remain under control. You’ll need to figure out these factors on your own—by measuring, analyzing, and improving the specific techniques you use to manage care for the population. These factors are totally missed if you jump straight to a specific health outcome.

Health systems will need to cut through the noise and dig deeper to move beyond the set of measures required for outcomes and payment to measures that will help you to become a better provider of care—and to build a better system of care among you and the partners required to impact your population in a significant way. For organizations with care management programs, changing how you think about population health management data and analytics will put you on the right path:

  • Insist upon process measures—those that measure the efficacy of care coordination actions you choose to do and the interventions you employ.
  • Insist upon measures that assess the effectiveness of the care teams you put together and the different components of care that that team represents in the lives of your patients and populations.
  • Insist upon measures you can trend over time to understand if the composition of care delivery methods, care partners, and patient interactions are leading to better health outcomes in aggregate or not.

These measures will enable you to perform population health management analytics and draw insights from your results so that you can take your best practices and deploy them as real protocols. This will help you bring predictability and assurance to your value-based care efforts so that the care you deliver will improve outcomes for the next set of patients that cross your threshold.

To move the needle on population health, you have to look for those things that are going to make you better, not just the things that will tell you if you’re good enough.

 

Why Is Interoperability Important?

Interoperability is the most persistent and fundamental challenge the healthcare industry faces today—and the industry spends tremendous energy trying to solve it. But interoperability discussions that focus solely on how to connect system A to system B miss the point. The real challenge is not just creating a free flow of data between systems, but figuring out how to move information in a meaningful way so that it is useful in a different context, and merging workflows so that people can do their jobs more efficiently.

Interoperability requires providers and managed care organizations to share information with multiple systems—all with different owners, different processes, and different underlying methods of assembling data. This data needs to be normalized to support the population health management goals, and delivered to the right people at the right time in the right setting so they can take the right actions. Any friction that prevents information sharing among these disparate systems and settings means that critical data doesn’t get to the people who need it in time to make decisions that will efficiently affect care.

True interoperability means not just focusing on data exchange, but on creating interoperable workflows, so that the act of participating in new activities is not disruptive. This means that the workflows must be harmonized so that users avoid inefficiencies such as double data entry when participating in broader population health management activities that require collaboration with organizations outside their four walls. It means making the user experience better, finding ways to notify users of key information to improve their ability to follow through on the care delivered in time to make a difference, and even blending the functionality of disparate systems at appropriate junctures. If we do it right, teams can efficiently work together to achieve their mutual goals and we’ll be a step closer to solving healthcare.

As a provider of care management software-as-a-service, we encounter the challenges of interoperability every day. Integrating care management tools with critical systems such as EHRs, HIEs, data warehouses, external analytics and business intelligence tools, Direct HISPs, and claims and billing systems—and minimizing friction by focusing on how the information is integrated into the workflow—is critical to successful population health management. We believe that data sharing for transparency alone is not sufficient and that the exchange of data should not just be ubiquitous, but also be harnessed to improve the quality of care that is delivered. We’ve found that when this more comprehensive approach is taken, more interoperability goals are achieved, and population health management just works better.

Our industry has made progress in developing interoperability guidelines to facilitate data exchange, but previous failures have lowered our standards. It is time to raise the interoperability bar and move beyond rhetoric to embrace a more open data exchange mentality and make a commitment to workflow harmony, which better supports our ability to manage population health. Our patients deserve better.

Download Interoperabilty Solution Brief

Healthcare Solved.

When people need healthcare, they need to receive it in a way that is optimized. Optimization encompasses many things—not only delivering the appropriate care to help patients get healthy, but also finding the organizations and care providers that will provide the shortest path to success for the desired patient outcomes. When there is an intersection between the right care at the right time with the right organizations reaching the right patients, the experience and efficiency of care is optimized, and you take a major step toward Healthcare Solved.

Read more “Healthcare Solved.” >

Beyond the EHR—Creating an Integrated Population Health Management Strategy

In recent years, the industry has focused a lot of attention on using the EHR as the center of today’s healthcare delivery. While EHRs add value at the point of care, enabling caregivers within a care setting to chart and manage patient information and to administer organizational operation, we can’t stop there. Extending the applicability of the EHR through other population health management solutions will help us look beyond the point of care to get to the real goal—improving how we manage patients—by focusing on the between-care activities and settings to significantly impact patient outcomes. This approach will help us bridge the gaps and pull the maximum value from the EHR in the larger picture of longitudinal care.

Read more “Beyond the EHR—Creating an Integrated Population Health Management Strategy” >

At-Risk Populations—Understanding Who We Serve

Delivering effective care to high-risk populations is challenging. As the costliest patients to treat, at-risk patients—typically those with some combination of tough chronic diseases, complicated behavioral health issues, and adverse social conditions—strain the entire healthcare system, requiring treatment from many different providers and a large investment of time and resources. If patients are unemployed, uninsured, or uneducated, the impact of their conditions is magnified. These forces result in an epidemic of poor health in our disadvantaged communities.

Read more “At-Risk Populations—Understanding Who We Serve” >

Developing Evidence-Based Care for Social Determinants

While we know that outcomes can be materially impacted by non-clinical factors like social determinants of health, the industry’s strong focus on medical factors have long pushed social determinants to the backseat. It is clear that population health management is most effective when it is comprehensive and community-based, extending beyond the walls of a single care establishment to encompass all relevant services, including medical, behavioral, and socioeconomic factors. But what will truly make a difference to patients is being able to prescribe how to address the social determinants in a normalized manner that will consistently improve patient outcomes.

Read more “Developing Evidence-Based Care for Social Determinants” >

Addressing the Healthcare Crisis in Philadelphia’s Poorest Neighborhoods

How the Digital Health Initiative of Philadelphia Began

Named the “poorest big city in America,” Philadelphia has plenty of challenges, and one of the most damaging is the impact on our poor communities in the area of healthcare. Philadelphia County has more than 500,000 Medicaid enrollees, and care for these vulnerable populations strains the entire healthcare system, diverting resources from other areas of investment that would otherwise benefit our region. Poverty costs us jobs, new business development, tourism, and other growth opportunities.

Read more “Addressing the Healthcare Crisis in Philadelphia’s Poorest Neighborhoods” >

Value-Based Care—The Future of Health Care: Part 2 of 2

This blog is part 2 of a discussion of value-based care—the new paradigm in which care is no longer delivered only by doctors and nurses, but by an entire community of providers that treat the “whole” patient rather than just treating the disease. The focus is on treating the entirety of a patient’s needs to bring about better health outcomes—which means that communication and care plans no long reside solely within a doctor’s office. To achieve this objective, the industry is migrating to a de facto set of standards that it is believed will take us down the right path. Read more “Value-Based Care—The Future of Health Care: Part 2 of 2” >

Value-Based Care—The Future of Health Care: Part 1 of 2

Value-based care creates a new paradigm—one in which care is no longer delivered only by doctors and nurses, but by an entire community of providers that treat the “whole” patient rather than just treating the disease. Communication and care plans can no longer live inside the four walls of a doctor’s office, but must integrate information from the community to fully address the needs of the patient and of the population. Further, those members of a patient’s care team must work together to deliver an effective and coordinated treatment experience. This blog—part 1 of a 2-part series—introduces the idea of value-based care, and discusses how integrating care coordination with robust analytics into a single platform provides the big picture of patient care, enabling efficient, collaborative care for diverse teams to treat complex populations. Part 1 is an introduction, intended for those starting to explore the idea of value-based care. Stay tuned for Part 2, which will be a deeper dive into some of the key issues facing the industry.

Read more “Value-Based Care—The Future of Health Care: Part 1 of 2” >

Care Coordination and Analytics Together

Remember the days when you had to use two different platforms for phone calls and for calendaring and task management? In today’s iPhone/Android laden world, such a separation seems heretical. Yet in healthcare’s hot new niche of population health management, we see that same heresy in the artificial, and suboptimal divide between care coordination/management software and analytic software. Read more “Care Coordination and Analytics Together” >

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