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. 2016 Oct;22(10):1204-1215.
doi: 10.4158/E161391.OR.

DEVELOPMENT AND VALIDATION OF A NOVEL TOOL TO PREDICT HOSPITAL READMISSION RISK AMONG PATIENTS WITH DIABETES

Daniel J Rubin, Elizabeth A Handorf, Sherita Hill Golden, Deborah B Nelson, Marie E McDonnell, Huaqing Zhao

DEVELOPMENT AND VALIDATION OF A NOVEL TOOL TO PREDICT HOSPITAL READMISSION RISK AMONG PATIENTS WITH DIABETES

Daniel J Rubin et al. Endocr Pract. 2016 Oct.

Abstract

Objective: To develop and validate a tool to predict the risk of all-cause readmission within 30 days (30-d readmission) among hospitalized patients with diabetes.

Methods: A cohort of 44,203 discharges was retrospectively selected from the electronic records of adult patients with diabetes hospitalized at an urban academic medical center. Discharges of 60% of the patients (n = 26,402) were randomly selected as a training sample to develop the index. The remaining 40% (n = 17,801) were selected as a validation sample. Multivariable logistic regression with generalized estimating equations was used to develop the Diabetes Early Readmission Risk Indicator (DERRI™).

Results: Ten statistically significant predictors were identified: employment status; living within 5 miles of the hospital; preadmission insulin use; burden of macrovascular diabetes complications; admission serum hematocrit, creatinine, and sodium; having a hospital discharge within 90 days before admission; most recent discharge status up to 1 year before admission; and a diagnosis of anemia. Discrimination of the model was acceptable (C statistic 0.70), and calibration was good. Characteristics of the validation and training samples were similar. Performance of the DERRI™ in the validation sample was essentially unchanged (C statistic 0.69). Mean predicted 30-d readmission risks were also similar between the training and validation samples (39.3% and 38.7% in the highest quintiles).

Conclusion: The DERRI™ was found to be a valid tool to predict all-cause 30-d readmission risk of individual patients with diabetes. The identification of high-risk patients may encourage the use of interventions targeting those at greatest risk, potentially leading to better outcomes and lower healthcare costs.

Abbreviations: DERRI™ = Diabetes Early Readmission Risk Indicator ICD-9-CM = International Classification of Diseases, Ninth Revision, Clinical Modification GEE = generalized estimating equations ROC = receiver operating characteristic.

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Figures

Fig. 1
Fig. 1
Quintiles of all-cause 30-d readmission risk predicted by the Diabetes Early Readmission Risk Indicator™ in training and validation samples.
See this image and copyright information in PMC

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