The message comes in over the office slack line at 1:05 pm. There are four patients in rooms, one new, 3 patients in the waiting room. Really, not an ideal time to deal with this particular message.
“Kathy the home care nurse for Mrs. C called and said her weight yesterday was 185, today it is 194, she has +4 pitting edema, heart rate 120, BP 140/70 standing, 120/64 sitting”
I know Mrs. C well. She has severe COPD from smoking for 45 of the last 55 years. Every breath looks like an effort because it is. The worst part of it all is that Mrs. C just returned home from the hospital just days ago.
The day after NBC releases a story on a ‘ground-breaking’ observational study demonstrating caramel macchiatas reduce the risk of death, everyone expects physicians to be experts on the subject. The truth is that most of us hope John Mandrola has written a smart blog on the topic so we know intelligent things to tell patients and family members.
A minority of physicians actually read the original study, and of those who read the study, even fewer have any real idea of the statistical ingredients used to make the study. Imagine not knowing whether the sausage you just ate contained rat droppings. At least there is some hope the tongue may provide some objective measure of the horror within.
Data that emerges from statistical black boxes typically have no neutral arbiter of truth. The process is designed to reveal from complex data sets, that which cannot be readily seen. The crisis created is self-evident: With no objective way of recognizing reality, it is entirely possible and inevitable for illusions to proliferate.
Historically, the Centers for Medicare & Medicaid Services’ (CMS) stance on the influence that social determinants of health (SDOH) have on health outcomes has been equal parts signal and noise. In April 2016, the agency announced it would begin adjusting the Medicare Advantage star ratings for dual-eligibility and other social factors. This was amid calls for increased equity in the performance determinations from the managed care industry. At the same time, CMS continued to refuse risk-adjustment for SDOH in the Hospital Readmissions Reduction Program (HRRP) despite the research supporting the influence of these factors on the HRRP.
It wasn’t until Congress interceded with the 21st Century Cures Act that CMS conceded to adjusting for dual-eligibility under the new stratified approach to determining HRRP penalties beginning in fiscal year 2019. The new methodology compares hospital readmission performance to peers within the same quintile of dual-eligible payer mix. The debate surrounding the adjustment of incentive-based performance metrics for SDOH likely is to continue, as many feel stratification is a step in the right direction, albeit a small one. And importantly, the Cures Act includes the option of direct risk-adjustment for SDOH, as deemed necessary by the Secretary of Health and Humans Services.
SDOH are defined as “the conditions in which people are born, grow, live, work and age.” The multidimensional nature of SDOH reach far beyond poverty, requiring a systemic approach to effectively moderate their effects on health outcomes. The criteria used to identify SDOH include factors that have a defined association with health, exist before the delivery of care, are not determined by the quality of care received and are not readily modifiable by health care providers.
The question of modifiability is central to the debate. In the absence of reimbursement for treating SDOH, providers lack the resources to modify health outcomes attributable to social complexities. Therefore, statistical adjustments are needed to account for differences in these complexities to ensure risk-adjusted performance comparisons of hospitals are accurate.
The Hospital Readmissions Reduction Program (HRRP), one of numerous pay-for-performance (P4P) schemes authorized by the Affordable Care Act, was sprung on the Medicare fee-for-service population on October 1, 2012 without being pre-tested and with no other evidence indicating what it is hospitals are supposed to do to reduce readmissions. Research on the impact of the HRRP conducted since 2012 is limited even at this late date , but the research suggests the HRRP has harmed patients, especially those with congestive heart failure (CHF) (CHF, heart attack, and pneumonia were the first three conditions covered by the HRRP). The Medicare Payment Advisory Commission (MedPAC) disagrees. MedPAC would have us believe the HRRP has done what MedPAC hoped it would do when they recommended it in their June 2007 report to Congress (see discussion of that report in Part I of this two-part series). In Chapter 1 of their June 2018 report to Congress, MedPAC claimed the HRRP has reduced 30-day readmissions of targeted patients without raising the mortality rate.
MedPAC is almost certainly wrong about that. What is indisputable is that MedPAC’s defense of the HRRP in that report was inexcusably sloppy and, therefore, not credible. To illustrate what is wrong with the MedPAC study, I will compare it with an excellent study published by Ankur Gupta et al. in JAMA Cardiology in November 2017. Like MedPAC, Gupta et al. reported that 30-day CHF readmission rates dropped after the HRRP went into effect. Unlike MedPAC, Gupta et al. reported an increase in mortality rates among CHF patients. 
We will see that the study by Gupta et al. is more credible than MedPAC’s for several reasons, the most important of which are: (1) Gupta et al. separated in-patient from post-discharge mortality, while MedPAC collapsed those two measures into one, thus disguising any increase in mortality during the 30 days after discharge; (2) Gupta et al.’s method of controlling for differences in patient health was superior to MedPAC’s because they used medical records data plus claims data, while MedPAC used only claims data.
I will discuss as well research demonstrating that readmission rates have not fallen when the increase in observation stays and readmissions following observations stays are taken into account, and that some hospitals are more willing to substitute observation stays for admissions than others and thereby escape the HRRP penalties.
All this research taken together indicates the HRRP has given CHF patients the worst of all worlds: No reduction in readmissions but an increase in mortality, and possibly higher out-of-pocket costs for those who should have been admitted but were assigned to observation status instead.
One of the main goals of the Affordable Care Act (ACA), perhaps second only to improving access, was to improve the quality of care in our health system. Now several years out, we are at a point where we can ask some difficult questions as they relate to value and equity. Did the ACA improve quality of care in the ways it intended to? Did it do so for some people, or hospitals, more than others?
How did the ACA Attempt to Improve Quality?
Three particular programs created by the ACA are worthy to note in this regard. The Hospital Acquired Condition Reduction Program (HACRP) took effect on October 1, 2014 and was created to penalize hospitals scoring in the worst quartile for rates of hospital-acquired conditions outlined by the CMS. The Hospital Readmissions Reduction Program (HRRP), which began for patients discharged on October 1, 2012, required CMS to reduce payments to short-term, acute-care hospitals for readmissions within 30 days for specific conditions, including acute myocardial infarction, pneumonia, and heart failure.The Medicare Hospital Value-Based Purchasing Program (HVBP) started in FY2013, was built to improve quality of care for Medicare patients by rewarding acute-care hospitals with incentive payments for improvements on a number of established quality measures related to clinical processes and outcomes, efficiency, safety, and patient experience.