Risk stratification tools can identify patients at risk for 30-day readmission, but available tools lack predictive strength. One of these tools is the Better Outcomes by Optimizing Safe Transitions (BOOST) 8 P's tool.
The primary objective of this study was to validate the 8 P's tool as well as measure the predictive strength of variables within this tool.
This was a quantitative study that included 1 year of hospitalized elderly patients (n = 6849). Odds ratios were used to determine the strength of the association between variables individually with readmission. Multivariable logistic regression was used to evaluate the predictive strength of the BOOST risk stratification tool.
This study demonstrated that 5 of the 8 variables in the BOOST risk stratification tool showed significant association with 30-day readmission including the variables of health literacy (P = .030), depression (P = .003), problem medications (P = .001), physical limitations (P ≤ .001), and prior hospitalization (P ≤ .001). Combining variables using multivariable logistic regression, the BOOST 8 P's tool had limited predictive capability with a C-statistic of 0.631.
This study was the first attempt to validate the BOOST 8 P's tool and to utilize nursing documentation within an electronic medical record to capture social determinants of health.
American Society of Plastic Surgeons, Arlington Heights, Illinois (Dr Sieck); and Loyola University Health System, Loyola University of Chicago, Maywood, Illinois (Drs Adams and Burkhart); Center of Innovation for Complex Chronic Healthcare, Hines VA Hospital, Hines, Illinois (Dr Burkhart).
Correspondence: Carol Sieck, PhD, RN, American Society of Plastic Surgeons, 444 E Algonquin Rd, Arlington Heights, IL 60005 (email@example.com).
The authors declare no conflicts of interest.