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1.
J Surg Res ; 207: 27-32, 2017 01.
Article in English | MEDLINE | ID: mdl-27979485

ABSTRACT

BACKGROUND: In older trauma patients, the impact of discharge destination on readmission rates is not known. The objective of this study was to evaluate the association between the discharge destination and the 30-day readmission rate in older trauma patients. MATERIALS AND METHODS: A previously validated database of all patients aged 45 years or older undergoing trauma evaluation at our level 1 trauma center between January 1, 2008 and December 31, 2008 was analyzed to retrospectively compare the incidences of 30-day readmission between patients discharged to home, to inpatient rehabilitation facilities, and to other extended care facilities (ECFs). Demographic information including age and gender and potentially confounding factors including injury severity, trauma activation level, comorbidities, medications, and preinjury functional status were included. Univariate analysis was undertaken using chi-square testing. Multiple logistic regression was performed with potential confounding variables to evaluate for independent contribution to readmission risk. RESULTS: A total of 960 patients were evaluated; 81 patients (8.4%) were excluded, leaving 879 patients included in the analysis. Seventy-six patients (8.6%) were readmitted within 30 d of discharge. Overall, 6% of those discharged to home, 13% of those discharged to ECF, and 16% of those discharged to rehabilitation were readmitted (P < 0.01 on univariate analysis). Overall, 866 (98.5%) patients had data recorded for all variables analyzed using multiple logistic regression; among these, only discharge destination was independently associated with the rate of readmission (P < 0.01). CONCLUSIONS: Discharge to ECFs and inpatient rehabilitation facilities appear to be an independent risk factor for hospital readmissions in this population despite controlling for injury severity and comorbidities. Recognition of this risk factor may aid in the disposition planning of these patients and suggests the need for further evaluation of this correlation at other US medical centers.


Subject(s)
Patient Discharge/statistics & numerical data , Patient Readmission/statistics & numerical data , Wounds and Injuries/therapy , Aged , Aged, 80 and over , Databases, Factual , Female , Humans , Logistic Models , Long-Term Care , Male , Middle Aged , Nursing Homes , Outcome Assessment, Health Care , Rehabilitation Centers , Retrospective Studies , Risk Factors , United States
2.
J Surg Res ; 199(1): 237-43, 2015 Nov.
Article in English | MEDLINE | ID: mdl-26163329

ABSTRACT

BACKGROUND: Hospital readmissions are considered to be a measure of quality of care, correlate with worse outcomes, and may soon lead to decreased reimbursement. The comorbidity-polypharmacy score (CPS) is the sum of the number of preinjury medications and comorbidities, and may estimate patient frailty more effectively than patient age. This study evaluates the association between CPS and readmission. METHODS: Medical records for trauma patients ≥45 y evaluated between January 1 and December 31, 2008, at our American College of Surgeons-verified level 1 trauma center were reviewed to obtain information on demographics, injuries, preinjury comorbidities, and medications, and occurrences of readmission to our facility within 30 d of discharge. Chi-square and Kruskal-Wallis testing was used to evaluate differences between readmitted and nonreadmitted patients, with multiple logistic regression used to evaluate the contribution of independent risk factors for readmission. RESULTS: A total of 879 patients were included; their ages ranged from 45-103 y (median 58), injury severity scores from 0-50 y (median 5), and CPS from 0-39 y (median 7). A total of 76 patients (8.6%) were readmitted to our facility within 30 d of discharge. The readmitted cohort had higher CPS (median, 9.5, range 0-32, P = 0.031) and injury severity score (median, 9, range 1-38, P = 0.045), but no difference in age (median, 59.5, range 47-99, P = 0.646). Logistic regression demonstrated independent association of higher CPS with increased risk of readmission, with each CPS point increasing readmission likelihood by 3.5% (P = 0.03). CONCLUSIONS: CPS appears to correlate well with readmissions within 30 d. Frailty defined by CPS was a significantly stronger predictor of readmission than was patient age. Early recognition of elevated CPS may improve discharge planning and help guide interventions to decrease readmission rates in older trauma patients.


Subject(s)
Decision Support Techniques , Frail Elderly , Patient Readmission/statistics & numerical data , Polypharmacy , Wounds and Injuries/therapy , Aged , Aged, 80 and over , Comorbidity , Female , Humans , Injury Severity Score , Logistic Models , Male , Middle Aged , Ohio/epidemiology , Retrospective Studies , Risk Assessment , Risk Factors , Wounds and Injuries/epidemiology
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