Setting Performance Expectations in Population Health Care Programs

J Clin Pathways. 2022;8(2):22-23. doi:10.25270/jcp.2022.03.2

Success is often defined based on expectations. This is a critical lesson for health systems leaders and organizations seeking to use as care pathways and other population health care programs to improve health outcomes.¹ 

Even if not explicitly stated, these initiatives often are launched with high expectations of cost savings, quality gains, and improved outcomes. It is easy to understand why. Many leaders have internalized the message that health care is beset on all sides by immense waste—and in turn, incredible improvement opportunities. Given widespread recognition of the Triple Aim, many organizations are also energized to achieve three-pronged goal of improving the health of populations, reducing health care costs, improving patient experience.²

To be clear, many parts of the US health care system need to be changed. There is also value in trying to reduce waste, provide high quality, cost-efficient care, and improve of entire populations. But these laudable concepts often belie much more complex realities. For instance, it is hard to argue the merit of improving the health of entire populations. But health care only contributes to a portion of individuals’ health outcomes, and providers are only able to affect individuals who seek care from them—a subset of actual populations. 

As another example, waste is bad, but certain types of care can be both wasteful in some circumstances or populations and yet underused in others. Because underuse can occur among historically marginalized populations that already face limited health care access, broad efforts to reduce utilization could exacerbate outcomes and/or disparities. The corollary: increased utilization of certain types of care may be desirable if it reverses underuse or promotes equity. As my prior work in orthopedic bundled payments demonstrates, more care does not necessarily equal failure, even in programs trying to reduce unnecessary health care utilization.³

In the face of these complexities, the solution is not to give up on population health care initiatives, but rather to frame them within appropriate expectations. Even otherwise promising programs can be hampered by unrealistic expectations if they create unattainable goals, disappointing results, and distorted perceptions of program failure. Instead, health systems leaders can take three steps to set clear-eyed performance expectations for population health care programs.

First, leaders targeting pathways and population-based programs toward high-risk patients can use insights from preventive medicine theory to level set expectations of benefit. The theory posits that “a large number of people exposed to a small risk may generate many more cases than a smaller number exposed to a high risk.”⁴ As I have noted previously, one implication for population health care programs is that to achieve a certain level of improvement across an entire group, programs that target a smaller number of high-risk people must achieve much larger changes per person than programs that target and achieve smaller changes in a larger number of low-risk people.⁵ Leaders should recognize that many small gains may add up to a bigger impact than fewer large gains. 

Second, organizational leaders pursuing broader population health care initiatives can embrace a “miss rate” when setting performance expectations. While no programs are completely effective, this is particularly salient for broad clinical pathways and initiatives aimed at improving care for all patients—those at low, moderate, and high risk for adverse outcomes—in a population. For one, it can be difficult for pathways to meet all the needs of low versus high-risk patients, which can differ in fundamental ways. For another, some individuals do not have intervenable needs—that is, their outcomes are difficult to improve despite multiple strategies and interventions. A reasonable “miss rate” may indicate meaningful efforts to address different types and degrees of care needs, not failure to address enough.

A third way for leaders to calibrate program performance expectations is to acknowledge that improvements can occur in the even in the absence of certain assumptions. For example, a core principle for clinical pathways is variation reduction—the logic being that poor outcomes are rooted in unwarranted variation, and that reducing it can stamp out waste and low-quality processes. While pathways can certainly improve care by reducing variation, that is not a requisite. In fact, my work evaluating organizational performance in bundled payment arrangements suggests that significant improvements can occur even in the presence of continue physician variation.⁶

Ultimately, it is encouraging to observe continued enthusiasm for using clinical pathways and other population health care initiatives to improve outcomes. However, success is often defined by expectations, and otherwise promising programs can be hampered by unrealistic ones. Three ways to calibrate expectations are to acknowledge the challenges of narrow initiatives targeted at high-risk individuals, embrace miss rates in broader population-wide initiatives, and recognize that improvements can occur even when certain assumptions are not met. Leaders can use these insights to set performance expectations and gain clearer understanding of true population health care initiative success. 

References

1. Liao JM. The Opportunity for Providers to Adopt the Concept of Population Health Care. J Clin Pathways. 2021;7(10):18-19.

2. Berwick DM, Nolan TW, Whittington J. The Triple Aim: Care, Health, and Cost. Health Affairs. 2008;27(3):759-769.

3. Navathe AS, Liao JM, Emanuel EJ. Volume Increases and Shared Decision-Making in Joint Replacement Bundles. Ann Surg. 2018;267(1):35-36.

4. Rose GA, Khaw K-T, Marmot MG. Rose’s Strategy of Preventive Medicine: The Complete Original Text. Oxford: Oxford University Press; 2008.

5. Marcotte LM, Reddy A, Liao J. Addressing Avoidable Healthcare costs: Time to Cool Off on Hotspotting in Primary Care? J Gen Intern Med. 2019;34(11):2634-2636.

6. Liao JM, Emanuel EJ, Whittington GL, et al. Physician Practice Variation Under Orthopedic Bundled Payment. Am J Manag Care. 2018;24(6):287-293.

Author Information

Author: Joshua M. Liao, MD, MSc^1,2

Affiliation: ¹Value & Systems Science Lab, Seattle, WA
²Health Systems Collective, Department of Medicine, University of Washington School of Medicine, Seattle, WA

Disclosures: Dr Liao has no disclosure to report.