A Dangerous Malfunction in the Measure of Readmission Reduction

 Posted by on August 26, 2014  No Responses »  Tagged with: , , , , , ,
Aug 262014
 

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/

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An Eye to 2020: Where Will Health Care Reform Lead?

 Posted by on April 18, 2013  No Responses »  Tagged with: , , , ,
Apr 182013
 

By Anne Montgomery

Call Ezekiel (“Zeke”) Emanuel an optimist. Currently serving as Vice Provost and professor of bioethics and health policy at the University of Pennsylvania, much of his career has been about bucking mainstream medical thinking.  These days, Emanuel is using his background in medicine and ethics to lead conversations among health care policymakers and stakeholders in directions they must take: the impact of multiple, simultaneous delivery system reforms on costs.

“Keep an eye on 2020,” Emanuel told a crowd gathered by  Disruptive Women in Health Care (http://www.disruptivewomen.net)  at a March  briefing in Washington, D.C.  It will take that long, Emanuel suggests, to determine whether costs will begin to drop on a sustained basis.

Although critics continue to pound against the Affordable Care Act ceaselessly, Emanuel said, health care reform law is only now starting to unfurl its sails. To assign the law a grade at this point is “far too early. We’re not even close to the midterm yet.” But by 2016, state exchanges will be up and running, and other game-changing developments are likely to be on the horizon, including the possibility of “interoperable health records” created by “two young kids in a garage somewhere.”

By the end of the decade, “we’ll have better quality measures,” Emanuel continued, and “lower rates of infection in hospitals.” Such developments can help the U.S. health care system “get off fee-for-service” medicine, and chart a course toward other delivery system reforms and payment reforms. Whether these are Accountable Care Organizations, bundled payments, or global capitation — “whatever mix is fine,” he said. At the same time, Emanuel acknowledged that success “won’t happen overnight,” and “a lot of different payment models” will need to be tried.

“The problem is that fee-for-service and delivery system changes do not line up,” Emanuel said.  For example, marketing and advertising for costly procedures and treatments influence patient decision making.  More important, he observed, health care providers, many of whom are not primarily focused on delivering the best possible care for the most efficient price, follow entrenched patterns of practice. The result is that “rising [health care] costs are threatening wage growth and all of the other things we human beings care about.”

Despite the large challenges inherent in bending the health care cost growth curve, Emanuel does not advocate abandoning U.S. social insurance programs. Instead, he advocates serial systemic reforms.  For example, he notes that although “we don’t have a good alternative to peer review” (which some critics call a bottleneck to rapid reform) he believes it is feasible and imperative to develop new protocols for more rapid testing and dissemination of pilots, demonstrations, and other types of initiatives. “We need a frame shift to look at multiple factors at the same time,” he said. “We need to evaluate differently – with different standards and perhaps larger numbers.”

It is within this broader measurement context that Zeke Emanuel believes transparency will be an essential driver of change. “Doctors are highly competitive,” Emanuel told the crowd of Disruptive Women. “They are trained to want to be number one.” The current dilemma, he says, is that “the driven nature [inherent in] training physicians goes out the window when they start practicing.” But as quality measures increasingly become public, spotlighting how good processes of care and delivery are, along with patient outcomes and patient experience, “the big push for change” will come from providers, he predicted.

Emanuel also acknowledged that the quest to coordinate services and drive down costs must involve and engage individual patients. “Right now [patients] are not focused on costs,” he said. “They are not going through websites” to compare the costs of various procedures and treatments.  But if metrics of cost and quality can be “arrayed in a simple way” and if a “selection among them” can be developed to include price, this could help to drive costs “to a more reasonable level,” he said.  To that end, Emanuel is currently writing a concept paper on shared savings that discusses the possibility of sharing savings not only between health care providers, but also with patients.  If there is a choice between treatments that are clinically equivalent,” he reasoned, “why shouldn’t patients get part of the savings?”

Why not indeed?

Anne Montgomery is a Senior Policy Analyst for the Center for Elder Care and Advanced Illness at Altarum Institute. 

 

 

 

 

 

 

 

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Tips on blended rate for 3026 applicants

 Posted by on July 11, 2011  No Responses »  Tagged with: , , , , , , , , ,
Jul 112011
 

Since many potential applicants are now figuring out how to use the financial template for Community-Based Care Transitions Program (CCTP) funding (as mentioned in our previous blog at: https://medicaring.org/2011/07/08/community-based-care-transitions-program-%e2%80%93-section-3026-funding/), here are some suggestions on mapping out a successful care transition model utilizing blended rate.  First, realize that all payments are to the Community-Based Organization, and must be paid “per eligible beneficiary.” Second, the worksheet provided by CMS must be used to convey the proposed blended rate. You’ll need to have enough experience in providing care transition services to estimate your population and costs in order to be successful in getting the funding.

Some applicants might want to focus on a particular illness or transition type (e.g., to Skilled Nursing Facilities), but we would encourage you to consider taking all Medicare fee-for-service discharges, but then using a stratified model to deliver services and estimate financials. Using just one intervention on all patients (e.g., the Care Transitions Intervention at Dr. Coleman’s site at: http://www.caretransitions.org) will meet the terms of the solicitation. However, a more sustainable model seems to have you divide the target population into three groups: low-complexity transitions, medium-complexity transitions and high-complexity transitions. Then, estimate the N, the acceptance rate, and the total costs for each of the three populations over a year.  Remember that CMS has said that initial training of staff and trips to meetings in Baltimore are not included in the budget (they must be covered from other funds or from indirects).

If a community finds it appealing to stratify as we suggest, then the blended rate is set by the number of people in the population segment, the likely complete refusal rate, and the costs of serving this population. In order to be effective, you will want to drive down the refusal rate wherever possible, and again, experience will be helpful.

One possibility for increasing patient compliance is by creating a patient-centered and patient-friendly intervention by improving cultural competency of all staff workers. Getting endorsement of relevant community leaders could also help mitigate refusal rate. We also recommend incorporating maximum family input to optimize care transitions, and thereby, reducing not only avoidable hospital readmissions but also generating Medicare savings.

This piece was written in collaboration with Dr. Joanne Lynn.

 

We are very interested in your experience and thoughts – and in some real examples to share.  Please respond to this blog, or send along info to [email protected].

Key words: care transitions, blended rate, Medicare savings, 3026, Coleman model, hospital readmissions

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Community-Based Care Transitions Program – Section 3026 funding

 Posted by on July 8, 2011  No Responses »  Tagged with: , , , , , , , , , , , ,
Jul 082011
 

Despite widespread interest in the $500 million budget allotted for Community-Based Care Transitions Program (CCTP) under the Affordable Care Act, many stakeholders are confused about the exact nature of the program. What does it aim to do? Who is eligible to apply for the funds?

Aim: CCTP aims to improve the reliability and effectiveness of care transitions as evidenced by reducing hospital readmissions. CCTP participants are paid to improve services targeted fee-for-service Medicare beneficiaries, the population requiring the most frequent care transitions. The backbone of the program in most places will be cooperation of service providers in a geographic community, since the participation and engagement of many stakeholders who share in the care of the area’s patients appears to be essential for sustained excellence.

Eligibility: To be eligible for funding, every applicant must have a minimum of one Community-Based Organization (CBO) and one hospital. While a hospital on CMS’s list of high readmission hospitals by state can lead a proposal, the payment will still go to the CBO, making lead authorship rather trivial. Priority will be given to eligible entities participating in programs run by the Administration on Aging (AoA), or that serve the medically underserved, small communities, or rural areas.

Financing: Foremost, this is not a grant! Payment is based on a blended rate proposed in the response to the solicitation, paid “per eligible discharge” and heavily based on the type of intervention. The blended rate can reflect different costs for different categories of patients and can include such elements as ongoing supervision, monitoring, administrative costs, and so on. Most important, however, it does not include initial training: Sites must have some previous experience with care transitions, so they must have paid for initial training. CMS payment also cannot directly support travel expenses for attending the required meetings in Baltimore (the cost of this must come from some other source).

Applicants are required to use the worksheet provided by CMS. No payments will be made more than once in 6 months for each beneficiary. In other words, CMS will not pay for re-treatment of patients for whom first efforts to prevent rehospitalization failed. Keep in mind that, although the program will run for 5 years, the initial award is only for 2 years, with possibility of renewal annually thereafter.

Intervention: CCTP interventions must target Medicare beneficiaries who are at high-risk for readmissions, based on criteria provided by HHS, or for substandard care post-hospitalization. Interventions cannot duplicate already required services. You must be willing to participate in collaborative learning and redesign (including data collection). Finally, and not surprisingly, your intervention must save money overall, and show savings within two years.

CMS’s measures so far include:

Outcome measures

  1. 30-d Risk-adjusted all-cause readmission rate (currently under development)
  2. 30-d unadjusted all cause readmission rate
  3. 30-d risk-adjusted AMI, HF, and Pneu readmissions

Process measures

  1. PCP follow-up within 7 days of hospital discharge
  2. PCP follow-up within 30 days of hospital discharge

“HCAHP items” – (note – includes more than HCAHPS)

  1. HCAHPS on medication info
  2. HCAHPS on discharge info
  3. Care Transitions Measure (3 – item)
  4. Patient Activation Measure (13-item, see:    http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1361231/table/tbl1/)

Note: There are some areas where the solicitation is unclear or internally inconsistent.

Key words: hospital readmission, care transitions, 3026 funding, evidence-based intervenitons, patient activation measure, budget worksheet, financing, medicare beneficiaries, payment rate, CMS

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