A Quick Summary: Pay for Performance
- Has failed to deliver on promised improvements in health outcomes (strong evidence including major reviews)
- Has been costly (EHR, digitalization, management, administration, maintenance, and security for data collection)
- Has consumed delivery personnel workforce (nurses for example) with conversion to non-delivery personnel
- Has resulted in further discrimination against the providers where health care delivery is most needed and is already least supported (evidence consistent in dozens of studies)
- Has distracted health care from the most important area - support of the team members to actually deliver health care and caring
- Results in disparities in health care dollar distributions and distribution of health care workforce and can worsen health care outcomes because scarce health care dollars are stolen from lowest concentration settings to go to higher concentration settings to pay for the costs of Pay for Performance.
Failure to deliver on promises, increased costs, increased distractions of team members, and two forms of discrimination against places and populations most behind should be a reason to move to real reforms rather than reforms of failed reforms.
P4P Has Been Critically Reviewed and Is Not Evidence-Based for Patient Outcomes
Pay-for-performance programs may be associated with improved processes of care in ambulatory settings, but consistently positive associations with improved health outcomes have not been demonstrated in any setting. “In summary, we found low-strength, contradictory evidence that P4P programs could improve processes of care, but we found no clear evidence to suggest that they improve patient outcomes.” from The Effects of Pay-for-Performance Programs on Health, Health Care Use, and Processes of Care: A Systematic Review, Annals of Internal Medicine 1/10/17.
Our findings raise questions about whether pay-for-performance strategies that reward improvement can generate greater improvement among lower performing providers. They also cast some doubt on the extent to which hospitals respond to the specific structure of economic incentives in pay-for-performance programs.
P4P - Theoretical But Not Practical or Relevant
In the minds of those who speculate about health care from far above, it is possible to micromanage health care delivery. Over the last few decades, control has been shifted away from those who provide care to those who manage and administrate and design health care policies. Even worse are those who continue to blame and shame providers, without understanding the complexity of personal care delivery to a wide range of different people in a wide variety of settings with substantial variations in other determinants of health outcomes.
Managed care proponents, stung by defeats in the 1990s, returned with passion for measurement, micromanagement, and shifting risks to providers - but passion won out over evidence basis. The Passionate Assumptions that Conceived ACA
For those far above immersed in top concentrations, it appears possible to control many things. In the office or hospital working with patients, there are many areas that are impossible to control. Many years or decades have shaped the current presentation. Many of the important interventions take many days or months or even years. Often the framework for health outcomes improvement needs to be completely changed.
Where policies are formed, various leaders are prominent. US health care leaders are groomed by institutions, associations, foundations, and corporations that preach and teach control - a level of control that is not possible in complex human interactions shaped by other complex interactions before and after an encounter or hospital stay.
From the perspective of those delivering care at the community and local level, there are numerous dimensions that are out of the control of health care delivery.
People are far more complex than the ability to compile numerous dimensions of variables and parse out the important interactions and the types of interactions (dichotomous, continuous, conditional) and how these result in outcomes.
Instead of phasing out due to lack of evidence basis, Pay for Performance has multiplied to include Readmissions Penalties, Value Based Payments, and MACRA. MACRA actually arose from the ashes of previous meaningless costly attempts.
The Wrong Directions - Known To Those Who Deliver But Escape Those Who Do Not
- Process over Performance
- Form Over Function,
- Digitalization/documentation Over Relationship and Outcome
- Marginalization of Health Personnel
Readmissions Penalties Costly, Fail in Outcomes Improvements, and Discriminate
Once again we see the themes of minimal relationship of readmissions metrics to outcomes, discrimination against critically needed providers, and outcomes shaped by factors outside of provider control.
My analysis of Readmissions Penalties in the second year of operation indicated top penalties of 1 - 2% levied against 14% of hospitals in the lowest physician concentration counties and against 9% of rural hospitals as compared to 5% average and 3% for urban hospitals. The hospitals in places with more challenging patient situations, complexities, social determinants, local resources, and concentrations of workforce faced greater discrimination.
From the National Cardiovascular Data Registry Study April 26, 2017 - The performance metric for risk-standardized 30-day readmission rates for MI is not associated with quality of care, long-term mortality risk, or long-term readmission risk beyond the first 30 days following discharge.
ACA Proponents including former Presidente Obama fed CMS data and graphics, have indicated improvements in readmissions. Unfortunately these studies fail to consider that readmissions improvements are small change and may have improved because DRGs were a part of the reason for Readmissions issues and other problems. This illustrates the problems of designs focused upon cost cutting with consequences that can be seen decades later in many areas.
From What Obamacare’s Pay-For Performance Programs Mean for Health Care Quality By Kathryn Nix
- Readmission penalties discriminate against providers that care for those who are sicker, poorer, older, or have more complex conditions.
- Readmission improvement attempts can backfire with increases in readmissions for certain conditions.
- Readmissions rates also have a questionable relationship with other quality measures, varying by condition.
- Readmission rates are not always preventable. Even if a hospital does succeed in providing the highest quality of care, some readmissions simply are not preventable. Researchers estimate that 23.1 percent of 30-day unplanned readmissions are potentially unavoidable. Meanwhile, the CMS goal for the Hospital Readmissions Reduction Program is to reduce 30-day readmission rates by 20 percent by the end of 2013. This would require a 91 percent reduction among those readmissions that are avoidable, which may be unrealistic.
- Readmission rates often reflect the community and patient factors, not hospital care. Readmission rates reflect lack of local health resources, lack of local primary care access, and poorly coordinated care. Insurance design may contribute to poor coordination.
- Incentives that distract providers can actually distract from care – by more dollars spent elsewhere, by attention of care givers directed elsewhere, by lower productivity, by financial compromise of the provider, by marginalization of patient needs.
- There are two intractable impediments: Determining which doctor patients “belong” to (the attribution problem); and adjusting measures of physician cost and quality for factors outside of physician control such as patient health status (the risk-adjustment problem). The attribution and risk-adjustment methods used today are crude even for large groups; with the possible exception of a few of the simplest process measures, they are worthless at the individual physician level.
- The Medicare Payment Advisory Committee (MedPAC) questions whether MACRA can work and raised concerns that it would likely be too complex for individual providers and for CMS.
- Concerns about MACRA were also raised due to ACOs and primary care home efforts that failed to work out also due to vague definitions, confusion, and burdensome regulation.
- Outside the bubble where Congress and CMS live, there is a widespread recognition that CMS cannot measure physician “performance” accurately. Citations from NEJM, MedPAC, and JAMA indicate the major measurement and attribution issues. "In a world where evidence guides policy-making rather than groupthink, CMS would acknowledge this fact. But CMS refuses to do that."
- Too much noise (other factors) and not enough signal (consistent data, controls)
- Chaos in patient continuity and difficulties assigning a physician to a patient make measurement impossible. A medical home is not really a home if half of the patients are gone in a 3 year period.
Some small practices were excluded for the obvious reason that measurements fail for individual physicians and smaller numbers as noted by the RAND consultant. More options were given for MACRA, but no change other than termination of aberrant Pay for Performance designs can stop the discrimination against those providing more care for those most complex with inherently poor outcomes at higher rates.
The entire concept of ACA was misguided from the start.
- Universal adoption of electronic medical records;
- shifting insurance risk to providers with payments for “bundled services” and “accountable care organizations” (ACOs) so that providers would have an incentive to offer fewer services
- various pay-for-performance schemes (such as punishing hospitals for “excessive” readmissions).
Reasons for Pay for Performance Failure
- Health care outcomes are substantially not about clinical interventions
- Health care outcomes are about the patient, their situation, their environment, their behaviors and other personal, local, and community factors shaped since birth
- Too many assumptions have been made with vague definitions, failure to consider alternative hypotheses, grossly insufficient controls, far too few limitations, and publications that have made it to distribution more because they were timely and fit within the current bandwagon.
In the quest for the perfect,
the result has been marginalization of support
for those who deliver the care.
the result has been marginalization of support
for those who deliver the care.
Any real improvements in health care must pass the test of application specific to the team members who perform the functions associated with health care delivery.
There has been an incredible emphasis placed upon measurement with rapid increases in administrative costs. This has also occurred during the current Era of Cost Cutting focus - which has also been an era of rapid chaotic change. The impact upon delivery team members has been predictable as has been confirmed.
- Damage to morale and motivation
- Burnout
- Decreased productivity
In typical fashion, the leaders of health care have continued to support designs that attempt to fix health care from far above while failing to realize the most basic fact that health care is grassroots, local, personal, and community-based.
The literature regarding health care outcomes has major issues. Many of the findings can be explained by differences in the places of care, the populations, the resources, the level of organization, and the situations and complexity differences.
Be sure to review The Tyranny of Health Care Research and read some of the listed material from Dr. Saurabh Jha and others to see if science has advanced much in the past 100 years since the flawed race vs intelligence studies. See if the lazy generalizations or the Tyranny of the Aggregate strikes a chord. Does it make sense to pay attention to the mean that reflects so few that were studied?
For a critical review of any research involving quality or costs. Consider the following
- Health care outcomes are substantially not about clinical interventions that only shape 10 to 15% of outcomes
- Health care outcomes are about the patient, their situation, their environment, their behaviors and other personal, local, and community factors shaped since birth (Over 60%) that impact outcomes before, during, and after an encounter, procedure, or hospital stay.
- Too many assumptions
- Too few controls, usually convenience variables
- Lack of consideration of alternative hypotheses
- Too few limitations expressed
- That shape most of outcomes
- That are basically at the screening stage with support services limited
- That are limited because of so much consumed by health care delivery impacting few at high costs resulting in little funding left to address support services, local resources, jobs, child well being, nutrition, housing, etc.
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