A Dangerous Malfunction in the Measure of Readmission Reduction

By Joanne Lynn and Steve Jencks

Work to reduce readmissions has started to yield remarkable improvements in integration of care for frail elderly people – by prompting hospital personnel to talk with community-based service providers, by teaching patients and families how to manage conditions and navigate the health care system more easily, and by paying more attention to trying to fill gaps in the community’s services. But the measure being used to track improvement is seriously misfiring in some settings, and if CMS does not mitigate the adverse impacts, they may become destructive to the momentum and the good that has been done. This is much more than an issue of imperfect risk adjustment or inadequate identification of planned readmissions: it is a punitive error that undermines program goals.

Since CMS mostly aims to assign responsibility for readmissions to the discharging hospital, the key metric has been the risk of readmission for the average person discharged, which is the number of readmissions, divided by the number of live discharges. Any time outcomes are monitored with a ratio, one has to watch out for whether interventions that affect the numerator also affect the denominator. Here, that’s happening enough to completely obliterate the usefulness of the metric – at least in some circumstances.

Here’s a quick hypothetical example: At baseline, a hospital has 1,000 Medicare fee-for-service (FFS) discharges per quarter, with 200 of them back within 30 days. Subsequently, the hospital team and various community-based providers work together and drop the readmissions to 160 per quarter. Does the readmission rate go down to 16% under the metric? No. First, they no longer have the 40 readmissions that are also admissions and in the denominator. But more important – the very things that are reducing the readmission rate also affect the likelihood of coming back in 45 days, or 6 months, or ever! Patients are supported in learning to take care of themselves and to advocate for themselves in the care system, they make good care plans (including advance care plans), and they encounter a more supportive care system in the community. These things are still affecting the patient many months after the hospitalization. Indeed, as the care system learns how to support fragile people in the community better, fewer patients will need to come to the hospital in the first place. The result for our hypothetical hospital is that it ends up with 800 discharges per quarter, and it has not budged its readmission rate! Officially, it has not improved, even though the work done by the hospital, by patients and families, and by community-based providers has improved care substantially, and has saved millions of dollars for Medicare. Yet, using the current flawed metric, the hospital is still likely to be penalized for having a high rate of readmissions!

This is not a new observation. The first sizable pilot project that CMS sponsored involved 14 communities, and the readmissions/discharges metric functioned so poorly that the outcome measure was changed during the project to a population-based measure: readmissions per 1,000 Medicare FFS beneficiaries in the geographic community [See: http://jama.jamanetwork.com/article.aspx?articleid=1558278]. That measure works to track changes in the experience of those living in a community, but it does not help in assigning credit or blame to particular providers (unless there is only one provider in the area). It is intrinsically community-anchored. The rub is that while good care of frail, chronically ill persons is at heart a community endeavor, Medicare has few tools to incentivize or penalize communities.

Furthermore, it is not clear what the “right rate” of readmissions should be. Very little work has been published on how well the various metrics perform in various circumstances, though NQF has a score of new ones under consideration [See: http://www.qualityforum.org/ProjectDescription.aspx?projectID=73619]. The hospital penalty measure has a very complicated risk adjustment, but should the population-based measure also be risk-adjusted (perhaps at least for the population age structure and whether the person is in Medicare due to disability or age)?

The problem here is more urgent than other controversies regarding the Medicare readmission measure such as higher readmission rates in disadvantaged populations and whether communities with low total hospital utilization should be expected to have higher readmission rates. In the case of measuring change, the measurement flaw directly punishes hospitals and communities for doing what the Affordable Care Act and the Medicare Readmissions Reduction Program otherwise encourage them to do: reduce preventable hospitalizations.

What should a responsible system manager like Medicare do? Below are some suggestions.

In the short-term:

1. Quickly sort out how to exclude certain contexts, perhaps as part of risk adjustment – e.g., whether CMS is authorized to limit application of the readmissions/discharges metric through regulation, or whether the issue has to go back to Congress.
1. For safety net hospitals – don’t penalize hospitals primarily serving poor beneficiaries.
2. For reducing admissions – see which of these approaches works best (or combine them)
1. Hospitals with declining admissions (and the same bed size), when the decline is at roughly the same rate (or more) than declining readmissions
2. Hospitals with >50% of their Medicare FFS utilization in counties with admission rates in the lowest quartile in the nation
2. Allow hospitals in a particular geographic area to propose accountability for a population – jointly or singly – so long as they together supply more than, for example, 70% of the hospital use for that population. Then measure their success on a population basis (readmissions/1,000 relevant people living in the area/quarter, and admissions/1,000/quarter)

In the longer-term:

1. Develop useful metrics for continuity and quality of care, especially for:
   1. Reliability, patient/family sense of trustworthiness/preparation; and
   2. Patient/family driven care plans, evaluated for quality with feedback
2. Develop useful metrics for the global costs of care, including private and Medicaid costs, for longer terms of illness, not depending upon hospitalization as the trigger, and including long-term services and supports.

What Can You Do Now?

If you agree, let’s talk about how to make improvements to the metric with the National Quality Forum, CMS, hospitals, and other interested organizations and colleagues. Feel free to add comments and suggestions here, too. Let’s build a commitment to evolving toward measures that really reflect optimal care, rather than staying with the under-performing and often misleading ones we have.

Want to know more?

Jencks et al.’s New England Journal of Medicine article on readmission statistics:
http://www.nejm.org/doi/full/10.1056/NEJMsa0803563

The Hospital Readmissions Reduction Program:
http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Readmissions-Reduction-Program.html

The Community-based Care Transitions Program:
http://innovation.cms.gov/initiatives/CCTP/