MedicalResearch.com Interview with:
Jeffrey C. Schneider, M.D.
Medical Director, Trauma, Burn & Orthopedic Program
Assistant Professor, Dept. of Physical Medicine and Rehabilitation
Harvard Medical School
Spaulding Rehabilitation Hospital
Boston, MA 02129
Medical Research: What is the background for this study? What are the main findings?
Response: Hospitalizations account for the largest share of healthcare costs in the U.S., comprising nearly one-third of all healthcare expenditures. In 2011, readmissions within 30 days of hospital discharge represented more than $41 billion in hospital costs. Financial penalties for excess 30-day hospital readmissions were instituted by the Centers for Medicare and Medicaid Services in 20124; more than 2,200 hospitals were fined a total of $280 million in reduced Medicare payments in fiscal year 2013.
Most readmission risk prediction models have targeted specific medical diagnoses and have utilized comorbidities and demographic data as the central risk factors for hospital readmission. Yet, large U.S. administrative datasets have demonstrated poor discriminative ability (c-statistics: 0.55-0.65) in predicting readmissions. However, few studies have considered functional status as potential readmission risk factors.
There is increasing evidence that functional status is a good predictor of other health outcomes. To date, acute care hospital administrative databases do not routinely include functional status measures. Therefore, inpatient rehabilitation setting is an ideal population in which to examine the impact of functional status on readmission risk, because:
(1) inpatient rehabilitation patients often have complex care transitions after acute care discharge, and represent a significant proportion of total readmissions;
2) inpatient rehabilitation facilities routinely document functional status using a valid instrument—the FIM®; and
(3) a majority of U.S. IRFs participate in one of the only national datasets that contain standardized functional data—the Uniform Data System for Medical Rehabilitation.
Limitations of prior work include small and single-center study designs, narrowly defined patient populations, and defining readmissions beyond the 30-day period. Overall, there is a lack of literature on the utility of function as a readmission predictor in a large population of medical patients. Moreover, function is a modifiable risk factor with potential to impact readmission outcomes if function-based interventions are instituted early. Therefore, the objective of this study was to compare functional status with medical comorbidities as predictors of acute care readmissions in the medically complex rehabilitation population. We hypothesized that acute care readmission prediction models based on functional status would outperform models based on comorbidities,and that the addition of comorbidity variables to function-based models would not significantly enhance predictive performance.