Thirty-day readmission rates as a measure of quality: causes of readmission after orthopedic surgeries and accuracy of administrative data

J Healthc Manag. 2013 Jan-Feb;58(1):64-76; discussion 76-7.

Abstract

The rate of unplanned 30-day readmissions to the hospital after discharge is being used as a marker to compare the quality of care across hospitals and to set reimbursement levels for care. While the readmission rate can be reported using administrative data, the accuracy of these data is variable, and defining which readmissions are unplanned and preventable is often difficult. The purpose of this study was to review readmissions to a single orthopedic hospital to identify the causes for readmission and, in particular, which readmissions are planned versus unplanned. Using that hospital's administrative database of patient records from 2007 to 2009, we identified all patients who were readmitted to the hospital within 30 days of a previous hospitalization for a procedure. Readmissions were broadly categorized as planned (a staged or rescheduled procedure or a direct transfer) or unplanned. Unplanned readmissions were defined as either surgical or nonsurgical complications (medical conditions not directly related to the procedure). Almost 30 percent of readmissions were planned. Of the unplanned readmissions, close to 60 percent were triggered by an infection or a concern for an infection. Nonsurgical complications accounted for 18.2 percent of unplanned readmissions. This study highlights the importance of careful data collection and abstraction when calculating early readmission rates. Preventing surgical site infection and better coordinating care between orthopedic surgeons and primary care and medical subspecialty physicians may significantly reduce readmission rates.

MeSH terms

  • Databases, Factual
  • Hospitals, University / standards
  • Humans
  • Medical Records / standards*
  • New York / epidemiology
  • Orthopedics*
  • Patient Readmission* / statistics & numerical data
  • Postoperative Complications / epidemiology
  • Quality Indicators, Health Care* / statistics & numerical data
  • Time Factors