Health Services Research & Development

Veterans Crisis Line Badge
Go to the ORD website
Go to the QUERI website

Management eBrief no. 68

» Back to list of all Management eBriefs


Management eBriefs
Issue 68June 2013

New Articles Highlight Readmission Rates and Hospital Quality of Care


Recent national policies have used risk-adjusted hospital readmission rates as a measure of hospital quality, with mandatory reporting and financial penalties for hospitals with high rates, on the assumption that improving quality of inpatient care and the discharge process can lower rates of readmission. However, this approach remains controversial in light of conflicting evidence on the relationship between readmission and quality of care, the poor predictive ability of most readmission risk models, and the potential for negative unintended consequences on hospitals caring for vulnerable patients. Two recently published studies highlight the relationship between readmission rate measures and hospital quality of care.

Readmission Rates Limited in Measuring Hospital Quality
This study assessed readmission rates as a hospital quality measure.1 Using Centers for Medicare and Medicaid Services' (CMS) Hospital Compare data from 2009 and 2011 on hospitals' performance on process and outcomes measures for myocardial infarction (MI), congestive heart failure (CHF), and pneumonia, investigators sought to answer three specific questions:

  • How much do quartile rankings of hospitals based on readmission rates change over a two-year period?
  • Do changes occur in a pattern that suggests changes in quality or random variation?
  • Are readmission rates correlated with commonly used indicators of hospital quality, including mortality, volume, teaching status, and performance on process measures?

Data used in this study represent 2,247 hospitals for MI, 3,758 hospitals for CHF, and 3,940 hospitals for pneumonia. Hospitals were ranked from lowest readmission rate (quartile 1) to highest readmission rate (quartile 4), separately for each year.

Findings
Results show that the change in readmission rates between 2009 and 2011 was inversely related to readmission rates in 2009: hospitals with higher readmission rates in 2009 tended to improve by 2011, while hospitals with lower readmission rates in 2009 tended to worsen by 2011. On average, readmission rates for hospitals in quartile 4 ("worst" performers) in 2009 decreased over time between 2% and 4%, depending on the conditions, while readmission rates for hospitals in quartile 1 ("best" performers) in 2009 increased between 3% and 7%.

Implications
Results suggest that policymakers should consider augmenting the use of readmission rates with other measures of hospital performance during care transitions, and should build on current efforts that take a community-wide approach to the readmissions issue.

Comparing Two Methods of Assessing 30-Day VA Readmission Rates
Expanding upon the research discussed above, this study compared the CMS readmission measure with the 3M Health Information System Division Potentially Preventable Readmissions (PPR) measure.2 Both measures are used for public reporting. Specifically, investigators examined how consistently the CMS and PPR methods identify performance outliers in a national sample of VA hospitals. Using VA data from FY06 to FY10, they examined 30-day readmission rates for three conditions among Veterans: MI, heart failure, and pneumonia. A total of 1,445,221 acute admissions were used to identify cohorts by condition.

Findings
Results show that there are discrepancies in CMS-generated and PPR-generated hospital profiles. For example, when investigators held everything constant except preventability, they found that <7% of the hospitals in each cohort would have had different outlier status for public reporting, but 30% of the hospitals would have had different payment penalties.

Implications
The discrepancies in hospital profiling for reporting and pay-for-performance between the CMS and PPR methods have important policy implications both within and outside VA. The implications of potentially contradictory hospital readmission profiles on quality improvement initiatives and subsequent patient care are not yet well understood.

Additional Resources
The following cyberseminar will be presented by Dr. William O'Brien on 7/17/13: "Estimating Readmission Rates Using Incomplete Data: Implications for Two Methods of Hospital Profiling." To register, visit HSR&D's cyberseminar website.

In addition, the following archived cyberseminars are available online: "Hospital Readmission: A Measure of Hospital Quality?," presented by Dr. Peter Kaboli on 2/20/13, and "Facility Variation in Hospital Readmissions for Heart Failure Patients," presented by Dr. Chuan-Fen Liu on 1/16/13.

Also see "Risk Prediction Models for Hospitals Readmission: A Systematic Review."




References

1. Press M, Scanlon D, Ryan A, Zhu J, Navathe A, Mittler J, and Volpp K. Limits of Readmission Rates in Measuring Hospital Quality Suggest the Need for Added Metrics. Health Affairs June 2013;32(6):1083-1091.

2. Mull H, Chen Q, O'Brien W, Shwartz M, Borzecki A, Hanchate A, and Rosen A. Comparing Two Methods of Assessing 30-Day Readmission: What is the Impact on Hospital Profiling in the Veterans Health Administration? Medical Care July 2013;51(7):589-596.

Please feel free to forward this information to others!

Read past HSR&D Management e-Briefs on the HSR&D website.





This Management e-Brief is provided to inform you about recent HSR&D findings that may be of interest. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs. If you have any questions or comments about this Brief, please email CIDER. The Center for Information Dissemination and Education Resources (CIDER) is a VA HSR&D Resource Center charged with disseminating important HSR&D findings and information to policy makers, managers, clinicians, and researchers working to improve the health and care of Veterans.

See all reports online.