[Skip to Content]
Access to paid content on this site is currently suspended due to excessive activity being detected from your IP address 35.171.146.16. Please contact the publisher to request reinstatement.
[Skip to Content Landing]
Views 709
Invited Commentary
Surgery
April 19, 2019

Clinical Accountability and Measuring Surgical Readmissions

Author Affiliations
  • 1National Clinician Scholars Program, Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor
  • 2Department of Surgery, Brigham and Women’s Hospital, Boston, Massachusetts
  • 3Division of General Internal Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia
  • 4Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania
  • 5Center for Healthcare Outcomes and Policy, University of Michigan, Ann Arbor
  • 6Department of Surgery, University of Michigan, Ann Arbor
JAMA Netw Open. 2019;2(4):e191301. doi:10.1001/jamanetworkopen.2019.1301

Medicare’s Hospital Readmissions Reduction Program, established in 2010, penalizes hospitals that have higher-than-expected readmission rates after discharge for select medical and surgical conditions. The policy has been controversial from its inception. Recent research has shown that it disproportionately affects safety-net hospitals and that it may have inadvertently increased mortality among certain patients who were not readmitted.1,2 Graham et al3 report on their development of a new readmission metric for surgical procedures, focused only on readmissions related to surgical quality rather than on readmissions for any unplanned reason. Using a Veterans Affairs surgical registry, they found that their surgical quality–associated readmission metric was more highly correlated with surgical complications than the broader unplanned readmission metric currently used by Medicare. In addition, Graham et al3 report that this metric would have changed penalties for up to 30% of hospitals.

To fully understand their approach, it is useful to draw on the terms of measurement theory. To ensure that the measure reflected the universe in which they were interested, Graham et al3 first established their metric’s content validity4 through an interdisciplinary Delphi panel of readmission experts. In this study, the universe of interest was the number of readmissions related only to surgical quality, and the Delphi process served to delineate which readmission diagnosis codes reflected surgical quality (eg, infection, bleeding, device complications) and which codes did not reflect surgical quality (eg, postoperative pain, chronic obstructive pulmonary disease exacerbation, intestinal obstruction).

The authors then tested their metric to establish construct validity, ie, the metric’s ability to measure a phenomenon without a gold-standard definition—in this case, readmissions that are primarily due to poor surgical quality.4 Graham et al3 used the Veterans Affairs Surgical Quality Improvement Program’s nurse-identified postdischarge complications as their criterion, ie, their surrogate for readmission due to poor surgical quality. They found that their metric generally identified postdischarge complications better than the US Centers for Medicare & Medicaid Services’ existing unplanned readmission metric, although the differences between the metrics’ ρ coefficients did not achieve statistical significance (Figure 1 in the article by Graham et al3).

Choosing the right quality metrics requires considering these aspects of validity as well as the goals of the measurement program more broadly. For instance, if the Centers for Medicare & Medicaid Services’ current unplanned readmission metric has no measurable association with surgical complications, would that justify abandoning it? Unplanned readmissions after surgery have at least 3 drivers: (1) complications of surgery, (2) complications of medical care and comorbidities, and (3) complications of care coordination and social support. Moreover, these factors can interact and even multiply—for instance, a surgical complication (eg, anastomotic leak) can provoke a medical condition (eg, atrial fibrillation), which can then create new challenges in care coordination (eg, managing anticoagulation). If readmission penalties were to focus on surgical quality alone, that would imply that the quality of medical care and care coordination are separate and unimportant.

This is a subjective judgment that depends on one’s perspective, and the premise of the study by Graham et al3 is that a surgical department should not be responsible if a patient is readmitted with pneumonia. However, it does not matter to patients whether their complication is medical or surgical. Hospitals and physicians must take care of the whole patient, regardless of whether they are admitted to a medical or surgical service. And policymakers increasingly believe that it is a hospital’s responsibility to ensure a good outcome after a patient has left its 4 walls—even when outcomes are outside the hospital’s control. For instance, bundled payment programs hold hospitals and physicians accountable by making a single payment for the entire continuum of care around an inpatient admission, including postacute care and readmissions. These programs discourage excessive postacute care utilization and also penalize hospitals and physicians for poor outcomes. Accountable care organizations put hospitals at risk for an entire population’s total costs of care, allowing them to share in the savings when the population’s costs are lower than expected—and in some cases, imposing a penalty when costs are higher. The Hospital Readmissions Reduction Program is thus part of a broader trend toward demanding better coordination, integration, and transitions of care. Although it is easier to respond to a metric that is directly within one’s control (eg, surgical quality–associated readmissions), such metrics narrow the perspective of those facing the penalty. And they do not align with the direction of today’s payment reforms.

The article by Graham et al3 is a useful example of how to evaluate the validity of a new quality measure. It also offers an opportunity to reflect on whether surgery should be viewed as an isolated fragment of a patient’s care or as an integrated aspect of the care continuum. But before their findings translate into policy changes, the clinical and policy communities need to define the scope of hospitals’ responsibilities to surgical patients. If we are truly aiming to incentivize comprehensive, coordinated care for surgical patients, we may need to look beyond strictly surgical complications.

Back to top
Article Information

Published: April 19, 2019. doi:10.1001/jamanetworkopen.2019.1301

Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2019 Chhabra KR et al. JAMA Network Open.

Corresponding Author: Karan R. Chhabra, MD, National Clinician Scholars Program, Institute for Healthcare Policy and Innovation, University of Michigan, 2800 Plymouth Rd, Bldg 14, Room G100, Ann Arbor, MI 48109 (kachhabr@umich.edu).

Conflict of Interest Disclosures: Dr Chhabra has received funding from the University of Michigan Institute for Healthcare Policy and Innovation Clinician Scholars Program, the Agency for Healthcare Research and Quality (grant AHRQ T32HS000053), and the National Institutes of Health’s Division of Loan Repayment. Dr Werner has received funding from Agency for Healthcare Research and Quality and the National Institutes of Health National Institute on Aging. Dr Dimick has received grant funding from the National Institutes of Health, the Agency for Healthcare Research and Quality, and BlueCross BlueShield of Michigan Foundation, and he is a cofounder of ArborMetrix, Inc, a company that makes software for profiling hospital quality and efficiency, which had no role in the work herein.

References
1.
Wadhera  RK, Joynt Maddox  KE, Wasfy  JH, Haneuse  S, Shen  C, Yeh  RW.  Association of the Hospital Readmissions Reduction Program with mortality among Medicare beneficiaries hospitalized for heart failure, acute myocardial infarction, and pneumonia.  JAMA. 2018;320(24):2542-2552. doi:10.1001/jama.2018.19232PubMedGoogle ScholarCrossref
2.
Chaiyachati  KH, Qi  M, Werner  RM.  Changes to racial disparities in readmission rates after Medicare’s Hospital Readmissions Reduction Program within safety-net and non–safety-net hospitals.  JAMA Netw Open. 2018;1(7):e184154. doi:10.1001/jamanetworkopen.2018.4154PubMedGoogle ScholarCrossref
3.
Graham  LA, Mull  HJ, Wagner  TH,  et al.  Comparison of a potential hospital quality metric with existing metrics for surgical quality–associated readmission.  JAMA Netw Open. 2019;2(4):e191313. doi:10.1001/jamanetworkopen.2019.1313Google Scholar
4.
Cronbach  LJ, Meehl  PE.  Construct validity in psychological tests.  Psychol Bull. 1955;52(4):281-302. doi:10.1037/h0040957PubMedGoogle ScholarCrossref
Limit 200 characters
Limit 25 characters
Conflicts of Interest Disclosure

Identify all potential conflicts of interest that might be relevant to your comment.

Conflicts of interest comprise financial interests, activities, and relationships within the past 3 years including but not limited to employment, affiliation, grants or funding, consultancies, honoraria or payment, speaker's bureaus, stock ownership or options, expert testimony, royalties, donation of medical equipment, or patents planned, pending, or issued.

Err on the side of full disclosure.

If you have no conflicts of interest, check "No potential conflicts of interest" in the box below. The information will be posted with your response.

Not all submitted comments are published. Please see our commenting policy for details.

Limit 140 characters
Limit 3600 characters or approximately 600 words
    ×