527 30 Day Readmissions Rate- How Many Ways Can We Calculate Thee?

Track: Poster Abstracts
Saturday, February 14, 2015, 6:45 PM-7:45 PM
Grand Hall CD (Manchester Grand Hyatt)
Sheila Serafino, MT(ASCP), MBA , Blood & Marrow Transplant, Cleveland Clinic, Cleveland, OH
Julie Curtis, RN, BSN , Blood & Marrow Transplant, The Cleveland Clinic, Cleveland, OH
Laura Bernhard, RN BSN , Blood & Marrow Transplant Program, Cleveland Clinic Foundation, Cleveland, OH
Navneet S. Majhail, MD, MS , Blood & Marrow Transplant Program, Cleveland Clinic, Cleveland, OH
Ronald Sobecks, MD , Hematologic Oncology and Blood Disorders, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH
Presentation recording not available for download or distribution as requested by the presenting author.
Purpose: To create a process/method for monitoring the 30 day readmission rate for BMT patients. Our program has been active in attempting to reduce the 30 day readmission rate since 2011.  Initial reported metrics were available at the Cancer Center level.  Initiatives were undertaken to drill down to only BMT readmissions enabling us to ascertain a relevant rate for our program.

 Methods: Data from 2009 & 2010 were analyzed to determine the 30 day readmission base rate.  Data was categorized according to autologous, allogeneic inpatient and allogeneic outpatient transplants. Only readmissions occurring after index transplant hospitalization were included.  Also included were readmissions to other services (ICU, leukemia unit etc.).  30 day readmission numbers (numerator) were easily obtained through a hospital quality outcomes database; however, determining the denominator necessitated a manual analysis from 2 years’ worth of weekly meeting minutes. Readmission rates were monitored monthly at the BMT Quality Assurance meeting.  We have experienced many limitations in calculating and maintaining readmission rates including:

  • Data pulled from the BMT database for monthly reporting proved prohibitive due to time needed to clean up data

  • Different reporting platforms at the hospital level for both discharges and readmissions

  • Time lag in data availability for discharged patients from the hospital database

  • Gaps in data posting to hospital database, results in multiple data pulls

  • Necessity to reconcile/double check data monthly

There are many variables to consider when determining which readmissions/discharges to include (small changes in either category can reflect a large change in rate):

  • Pre transplant admit/discharge within 30 days of transplant admission (eg, BMT admit within 30 days of discharge after leukemia induction therapy)

  • Hospital metrics are unit based and may not include BMT patients cared for outside the BMT unit

  • ED admits

  • Admissions for Observation only

  • Admission/discharge from an outside hospital

  • Weighing the difference between the hospital calculated readmission rate and that which is beneficial from a BMT quality/patient safety perspective

Fields analyzed monthly include: number of days between admissions, readmission length of stay (LOS), index admission LOS; readmission reason, comorbidity score, location admitted from etc., we are always attempting to identify a focal point to direct efforts to reduce the readmission rate.

 Conclusion: Determine which calculation factors are most meaningful for your BMT program. Develop a system which is easy to maintain on a routine basis and in as real-time as possible.  Engage as many disciplines within your program to contribute input for readmission impact projects.  Resolve the fact that it may be necessary to sustain a hospital metric and a BMT metric.

Disclosures:
Nothing To Disclose