The influence of impactability on patients, providers and population health results: Part II

This is the second in a series of case stories examining why population health results vary.

Earlier, Becker’s shared the story of Jane, a 66-year-old woman with multiple factors that suggested that typical population health interventions delivered by current-state programs would have limited impact on her health outcomes. Part II follows the journey of an Accountable Care Organization (ACO) in the Midwest. The ACO is led by a six-facility health system with participating providers that include both employed and independent physicians across a wide regional area, enrolled in the CMS Next Generation ACO program (Next Gen). It sheds light on the positive effects that the integration of a best practice approach has on provider’s clinical and financial performances.

ACO Performance Before Impactability
Prior to the focus on impactability, the ACO had a different method for identifying at-risk patients. It developed patient rosters based on high-cost claims data, rather than prediction of future avoidable events. This approach did not result in better patient outcomes. In fact, providers became frustrated because their time and resources were wasted on patients whose health and medical journey would stay the same, even with proper care management intervention. Overall, the ACO was being reactive, rather than proactive, which affected their success.

ACO Performance After Impactability
To optimize performance, the ACO decided to apply a best practice approach and identify impactable patients using robust predictive factors besides high-cost. The analytics-driven implementation of the best practice model incorporated administrative, clinical and social data. As a result, physicians were able to engage their patients in effective, evidence-based health programs, before adverse events occurred. Not only did patient outcomes improve, but physicians became more engaged in the new approach because their efforts were leading to positive results.

The ACO used this set of predictive analytics to further transform their engagement approach, segmenting patients based on their likelihood to engage. Primary care physicians began to personally contact patients with low engagement levels, which led to greater patient enrollment in the program.

Lastly, with the right infrastructure in place, the organization set out to measure and manage their ongoing performance. To accomplish this, a team of clinical experts and data scientists identified the activities and interventions that consistently resulted in positive outcomes for particular segments of the patient population. The outputs were then used as performance indicators to ensure those activities were regularly performed. A review of this approach uncovered a subset of top performing nurses that consistently engaged their patients in the best interventions. To spread this knowledge throughout the ACO, a mentorship program was created so other nurses and physicians could learn how to improve engagement, program adherence and patient outcomes.

The financial and clinical results of the best practice model were astounding, with the organization experiencing a 48 percent reduction in medical spend per member per month, a 66 percent reduction in patient admissions, a 51 percent reduction in emergency department visits and $4.6 million in total annual avoided costs. It is evident that each dimension of impactability played a critical part in the successful transformation of this ACO.

Olivia C. Tran, MPH, is the Director of Health Outcomes Research at Evolent Health. She can be reached at For more detailed insights on best practices across the dimensions of impactability, download “Why Do Population Health Results Vary? An Introduction to “Impactability” at [].

Anita Cattrell is the Senior Vice President of Research and Development at Evolent Health. She can be reached at

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