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In Pursuit of the Patient Stratification Gold Standard:
Getting There with Healthcare Analytics ̶ Maggie O'Keefe
© 2016 Health Catalyst
Proprietary. Feel free to share but we would appreciate a Health Catalyst citation.
Care Management...
© 2016 Health Catalyst
Proprietary. Feel free to share but we would appreciate a Health Catalyst citation.
Care Management...
© 2016 Health Catalyst
Proprietary. Feel free to share but we would appreciate a Health Catalyst citation.
Care Management...
© 2016 Health Catalyst
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Care Management...
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Problems with t...
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Problems with t...
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How to Improve ...
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How to Improve ...
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How to Improve ...
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How to Improve ...
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Why Healthcare ...
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Why Healthcare ...
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Healthcare Anal...
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Healthcare Anal...
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Healthcare Anal...
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Healthcare Anal...
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The Analytics-D...
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The Analytics-D...
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In Pursuit of the Patient Stratification Gold Standard: Getting There with Healthcare Analytics

Even the healthiest among us would benefit from some level of care management, but resources are limited and patients must be stratified to facilitate prioritized enrollment into care management programs. Therefore, health systems need to identify not only high-cost, high-risk, and rising-risk patients, but also patients who are truly impactable.

This article explains how systems can use healthcare analytics, at varying levels of maturity, to improve patient stratification and, ultimately, achieve the gold standard:

Level 1 (where to start): use healthcare analytics to identify high-cost, high-risk patients in a population.
Level 2: use healthcare analytics to identify patients with rising-risk profiles.
Level 3 (highest level of maturity): use healthcare analytics to identify patients who are truly impactable (the patient stratification gold standard).

Analytics is key to achieving the patient stratification gold standard, but should enhance (not replace) clinical judgement. Stratification lists need to go through workflows in which clinicians remove patients that aren’t appropriate for enrollment.

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In Pursuit of the Patient Stratification Gold Standard: Getting There with Healthcare Analytics

  1. 1. In Pursuit of the Patient Stratification Gold Standard: Getting There with Healthcare Analytics ̶ Maggie O'Keefe
  2. 2. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Care Management for Patient Populations As health systems take on risk and shift to value-based payment models, providing effective care for a population of patients is imperative. Care Management is a pillar of population health management strategies—succeeding in this arena is increasingly important to thriving in this risk-based industry. Care management is costly and requires significant investments in infrastructure and expenditure of resources to achieve targeted clinical and financial outcomes.
  3. 3. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Care Management for Patient Populations Even the healthiest among us benefits from some degree of care management, but limited resources lead to an unfortunate reality. Patients must be stratified in ways that facilitate prioritized enrollment into care management programs.
  4. 4. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Care Management for Patient Populations This presentation explains why identifying patients who are truly impactable is key to maximizing cost-effectiveness and sustainability of care management programs. And why leveraging analytics and clinical judgement will help systems achieve the patient stratification gold standard.
  5. 5. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Care Management for Patient Populations This presentation explains why identifying patients who are truly impactable is key to maximizing cost-effectiveness and sustainability of care management programs. And why leveraging analytics and clinical judgement will help systems achieve the patient stratification gold standard.
  6. 6. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Problems with the Common Care Management Approach Today, many health systems rely on qualitative assessments to identify and enroll patients in care management programs. Some systems identify patients by calling every individual within two days of discharge. At other systems, primary care providers are responsible for refer- ring patients to care management.
  7. 7. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Problems with the Common Care Management Approach Although there is value in using qualitative means (clinical judgement) to determine which patients need care management, relying solely on such mechanisms isn’t likely to create the optimal patient panels for two key reasons: 1: Patients who are part of an at-risk population, but aren’t receiving all necessary care within the health system, are likely to be missed. This may be due to not qualifying for any single provider’s patient panel, or because their frag- mented records make it difficult for a provider to appropriately ascertain the full continuum and complexity of their needs. 2: A myriad of biases and heuristics are at play when systems rely entirely on qualitative inputs. For example, patients asking for more attention may get enrolled instead of those who are reticent to engage independently, but who would benefit more from care management.
  8. 8. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. How to Improve Patient Stratification with Healthcare Analytics: Three Levels of Maturity Health systems can use healthcare analytics for incorporating quantitative information to more effectively stratify patients into the appropriate care management program: Level 1: Identify high-cost, high-risk patients Level 2: Identify patients with rising-risk profiles Level 3: Identify patients who are truly impactable
  9. 9. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. How to Improve Patient Stratification with Healthcare Analytics: Three Levels of Maturity LEVEL 1 The first level of maturity in using healthcare analytics to improve patient stratification is identifying high-cost, high-risk patients in a population. With the top five percent of patients responsible for nearly half of healthcare dollars spent, and patients with multiple chronic conditions costing up to seven times those patients with only one, focusing care management here is a logical way to leverage an analytics system.
  10. 10. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. How to Improve Patient Stratification with Healthcare Analytics: Three Levels of Maturity LEVEL 2 The next level is identifying patients with rising-risk profiles. If systems can recognize these individuals earlier, then it may be possible to intervene before their health status worsens and they become part of the high-cost, high- risk group.
  11. 11. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. How to Improve Patient Stratification with Healthcare Analytics: Three Levels of Maturity LEVEL 3 The highest level of maturity in using analytics to improve patient stratification, is identifying those patients who are truly impactable. This is the primary goal of patient stratification—the gold standard. Achieving this gold standard requires more than simply identifying patients with a high-cost or rising-risk status.
  12. 12. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. How to Improve Patient Stratification with Healthcare Analytics: Three Levels of Maturity LEVEL 3 Many of the highest cost patients will remain extraordinarily expensive regardless of intervention. Others with high costs in a given time frame will regress to the mean without any additional care management. The gold-standard patient stratification process identifies patients for whom care management support results in improved clinical and financial outcomes that would have otherwise not occurred.
  13. 13. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Why Healthcare Analytics Is Key to Achieving the Patient Stratification Gold Standard Achieving the gold standard of patient stratification capabilities, in which impactable patients are effectively identified, relies on a hybrid quantitative/qualitative approach. Analytics can provide visibility into the full continuum of care by drawing from disparate healthcare data sources. Combining claims data with clinical records greatly enhances the precision with which patient profiles can be created. Stratification algorithms can bring in other data such as patient socioeconomic, if available.
  14. 14. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Why Healthcare Analytics Is Key to Achieving the Patient Stratification Gold Standard While data is imperative, a key method to quantitatively derive impactability is employing analytics to illuminate trends of patients care management programs have successfully impacted in the past. By creating this learning system, common traits among patients who respond to intervention begin to emerge: Clinical similarities (e.g., conditions or treatments). Programmatic strengths (e.g., specific care plans or care managers with community ties who connect with patients) Social factors (e.g., IMPACT score or demographic characteristics) > > >
  15. 15. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Healthcare Analytics Should Enhance (not Replace) Clinician Judgement There is no question that clinician knowledge is a critical component of any successful patient stratification program. Many health systems are not going after the entire high-cost or rising-risk population—instead, they’re using their own prioritization based on experience and understanding of their market to further segment that population.
  16. 16. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Healthcare Analytics Should Enhance (not Replace) Clinician Judgement For example, a care management program may be targeted at the highest cost diabetics with several co-morbid conditions, excluding cancer or end-stage renal disease. Stratification algorithms may soon do more to drive these targeted decisions, but in the short-term, qualitative determination of where to begin remains important.
  17. 17. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Healthcare Analytics Should Enhance (not Replace) Clinician Judgement Qualitative determination (clinical judgement) is key because any stratific- ation algorithm is ultimately no more than a highly refined assumption about who the most impactable patients are. There are many nonclinical, nuanced factors that influence clinician-led enrollment today that are unlikely to become standard data elements, either because of privacy concerns, limited relevance to standard clinical care, or items not easily quantifiable.
  18. 18. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Healthcare Analytics Should Enhance (not Replace) Clinician Judgement While some cutting-edge health systems are using creative proxies for these factors— identifying patients with addresses that change often, for example—many of these determinations will happen on a case-by- case basis. Any stratification list needs to go through a workflow in which individuals, such as care managers, can remove patients they know are not appropriate for enrollment, and add patients the algorithm has missed.
  19. 19. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. The Analytics-Driven Pursuit of Patient Stratification Will Improve Outcomes Identifying patients who will benefit most from care management—achieving the patient stratification gold standard—is an iterative process. Although there is incredible value in health systems’ current strategies, creating the most effective patient stratification process requires employing healthcare analytics in an increasingly sophisticated fashion.
  20. 20. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. The Analytics-Driven Pursuit of Patient Stratification Will Improve Outcomes Health systems can start by using analytics to identify high-cost, high-risk, and rising-risk patients fairly quickly. Ultimately, however, health systems must work toward employing a learning system— in tandem with qualitative information—to best deduce where the opportunities lie as they pursue patient stratification that truly improves health outcomes
  21. 21. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. For more information: “This book is a fantastic piece of work” – Robert Lindeman MD, FAAP, Chief Physician Quality Officer
  22. 22. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. More about this topic Link to original article for a more in-depth discussion. In Pursuit of the Patient Stratification Gold Standard: Getting There with Healthcare Analytics Understanding Risk Stratification, Comorbidities, and the Future of Healthcare Eric Just, Technology, VP Defining Patient Populations Using Analytical Tools Kathleen Merkley, DNP, APRN, Sr. VP, Clinical Improvement Line Introducing the Breakthrough Health Catalyst Care Management Product Suite Paul Horstmeier, Senior VP The Six Care Management Challenges Healthcare Must Overcome Bobbi Weber, Product Manager Care Management and Patient Relationship How Care Management Will Save Richard’s Life—and Billions in Healthcare Costs Dr. John Haughom, Senior Advisor
  23. 23. © 2016 Health Catalyst Proprietary. Feel free to share but we would appreciate a Health Catalyst citation. Maggie O'Keefe joined Health Catalyst in July 2015 as Associate Director, Accountable Care. Prior to coming to Health Catalyst, she worked for CCNC Services as a Clinical Data Analyst. Maggie has a Master’s degree in Social and Behavioral Sciences from the Harvard School of Public Health and a Bachelor’s degree in Religious Studies from Yale University. Other Clinical Quality Improvement Resources Click to read additional information at www.healthcatalyst.com

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