Methods: This retrospective descriptive correlational study involves abstracting 500 samples from the 2014-2015 electronic health records (EHRs) located in a Southern California urban hospital. Inclusion criteria are as follows: (1) hospitalized patients and who are at least 65 years and older; (2) discharged from the acute inpatient setting with a type II diabetes regardless of their admitting diagnosis; and (3) were readmitted within 30 days. Exclusion criteria include: (1) patients who were admitted and discharged in less than 24 hours; (2) patients who were admitted due to trauma; and (3) patients readmitted within 24 hours post discharge.
Data abstracted from the EHRs include demographic characteristics (age, gender, and race); hospital discharge disposition (home, skilled nursing facility, or rehabilitation center); clinical biomarker (Hemoglobin A1C), diabetes medications (oral versus insulin therapy); disease management (whether the patient received diabetes education or was seen by an Endocrinologist); length of stay; and comorbidities. Descriptive statistics will be used to describe the characteristics of the population. Correlation statistics will be employed and multivariate analysis using logistic regression will be performed in order to determine if the data fit a model that will explain the variance in readmission.
Results: The study is currenntly in data collection phase, but it is expected to be completed in May 2017; results should be available for dissemination at the time of the conference.
Conclusion: Understanding the factors associated with hospital readmissions among older patients with type II diabetes will assist healthcare organizations to create and implement targeted protocols that could prevent these costly, and potentially harmful readmissions. In addition, if the factors are identified and interventions are made, there is the potential for reduced morbidity and mortality rates in patients with type II diabetes.
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