Patrick T Delaplain1, Yigit S Guner2, William Feaster3, Elizabeth Wallace4, David Gibbs2, Maryam Gholizadeh2, Troy Reyna2, Louis Ehwerhemuepha3. 1. Department of Surgery, University of California, Irvine, Orange, California. Electronic address: pdelapla@uci.edu. 2. Department of Surgery, University of California, Irvine, Orange, California; Division of Pediatric Surgery, Children's Hospital of Orange County, Orange, California. 3. Information Systems, Children's Hospital of Orange County, Orange, California. 4. Research Institute, Children's Hospital of Orange County, Orange, California.
Abstract
BACKGROUND: Pediatric patients admitted for trauma may have unique risk factors of unplanned readmission and require condition-specific models to maximize accuracy of prediction. We used a multicenter data set on trauma admissions to study risk factors and predict unplanned 7-day readmissions with comparison to the 30-day metric. METHODS: Data from 28 hospitals in the United States consisting of 82,532 patients (95,158 encounters) were retrieved, and 75% of the data were used for building a random intercept, mixed-effects regression model, whereas the remaining were used for evaluating model performance. The variables included were demographics, payer, current and past health care utilization, trauma-related and other diagnoses, medications, and surgical procedures. RESULTS: Certain conditions such as poisoning and medical/surgical complications during treatment of traumatic injuries are associated with increased odds of unplanned readmission. Conversely, trauma-related conditions, such as trauma to the thorax, knee, lower leg, hip/thigh, elbow/forearm, and shoulder/upper arm, are associated with reduced odds of readmission. Additional predictors include the current and past health care utilization and the number of medications. The corresponding 7-day model achieved an area under the receiver operator characteristic curve of 0.737 (0.716, 0.757) on an independent test set and shared similar risk factors with the 30-day version. CONCLUSIONS: Patients with trauma-related conditions have risk of readmission modified by the type of trauma. As a result, additional quality of care measures may be required for patients with trauma-related conditions that elevate their risk of readmission.
BACKGROUND: Pediatric patients admitted for trauma may have unique risk factors of unplanned readmission and require condition-specific models to maximize accuracy of prediction. We used a multicenter data set on trauma admissions to study risk factors and predict unplanned 7-day readmissions with comparison to the 30-day metric. METHODS: Data from 28 hospitals in the United States consisting of 82,532 patients (95,158 encounters) were retrieved, and 75% of the data were used for building a random intercept, mixed-effects regression model, whereas the remaining were used for evaluating model performance. The variables included were demographics, payer, current and past health care utilization, trauma-related and other diagnoses, medications, and surgical procedures. RESULTS: Certain conditions such as poisoning and medical/surgical complications during treatment of traumatic injuries are associated with increased odds of unplanned readmission. Conversely, trauma-related conditions, such as trauma to the thorax, knee, lower leg, hip/thigh, elbow/forearm, and shoulder/upper arm, are associated with reduced odds of readmission. Additional predictors include the current and past health care utilization and the number of medications. The corresponding 7-day model achieved an area under the receiver operator characteristic curve of 0.737 (0.716, 0.757) on an independent test set and shared similar risk factors with the 30-day version. CONCLUSIONS:Patients with trauma-related conditions have risk of readmission modified by the type of trauma. As a result, additional quality of care measures may be required for patients with trauma-related conditions that elevate their risk of readmission.
Authors: Louis Ehwerhemuepha; Gary Gasperino; Nathaniel Bischoff; Sharief Taraman; Anthony Chang; William Feaster Journal: BMC Med Inform Decis Mak Date: 2020-06-19 Impact factor: 2.796
Authors: Kamila Hoenk; Lilibeth Torno; William Feaster; Sharief Taraman; Anthony Chang; Michael Weiss; Karen Pugh; Brittney Anderson; Louis Ehwerhemuepha Journal: Cancer Rep (Hoboken) Date: 2021-02-02