DA04
Derivation and Validation of a Predictive Model for 30-Day Readmission Risk in Patients with Multiple Sclerosis

Friday, June 1, 2018: 2:45 PM
104 C-E (Nashville Music City Center)
Kanika Sharma, MD , Neurology, University of Iowa, Iowa City, IA
Yubo Gao, PhD , Medicine, University of Iowa, Iowa City, IA
Junlin Liao, PhD , Surgery, University of Iowa, Iowa City, IA
John A Kamholz, MD, PhD , Neurology, University of Iowa, Iowa City, IA
Frank R Bittner, DO , Neurology, University of Iowa, Iowa City, IA
Piyush Kalakoti, MD , University of Iowa, Iowa City, IA


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Background:

Recent healthcare reforms impose financial penalties on hospitals based on their performances that includes assessment of readmission rates. To optimize outcomes and enhance quality of care delivered to patients with multiple sclerosis(MS), identifying inherent risks associated with readmissions to implement appropriate preventive measures for modifiable risk-factors is warranted.

Objectives:

The current study seeks to develop and validate a predictive model of 30-day readmission risk in MS patients.

Methods:

Utilizing the National Readmission Database, adult patients discharged following index hospitalization with MS(ICD-9-CM 340) were tracked to identify 30-day readmission status. Multivariable regression techniques (generalized estimating equations to control clustering of outcomes by hospital) were employed to create a predictive model identifying factors independently associated with 30-day readmission risk. Model validation was performed by evaluating the impact on c-statistics (area under curves) using 50-bootstrapped replacement samples.

Results:

Of 15,687 patients (median age: 44 years; 73% female) with MS, 1624 (10.4%) were readmitted within 30-days. Most common causes for readmissions were exacerbation of MS(44.5%), urinary tract infection(5.6%), ear related issues(5.23%), respiratory(4.68%) and gastrointestinal(3.82%) diseases, psychiatric disorders (3.69%).

Factors associated with lower odds of readmission include female gender(OR:0.8;p=0.002), private insurance(OR:0.7;p<0.001), private hospitals and those receiving steroids(OR:0.7;p=0.03). Comorbidities [morbid obesity(OR:1.2; p=0.036), hypothyroidism(OR:1.2; p=0.045), diabetes (OR:1.3;p=0.003), fluid/electrolyte disorder(OR:1.3;p<0.001), hypertension(OR:1.2;p=0.001), arthritis(OR:2.0;p<0.001), depression (OR:1.2;p=0.025), psychosis(OR:1.3;p=0.002), bowel/bladder dysfunction(OR:1.4;p<0.001)], complications[venous thromboembolism(OR:1.9;p=<0.001), acute renal failure (OR:1.5;p=0.015)], patients leaving against medical advice(OR:2.2;p<0.001) and those on intravenous immunoglobulins(OR:1.6;p=0.002), were associated with higher odds of readmission.

Conclusions:

The study quantifies estimates associated with the risk of 30-day readmission in patients with MS. The proposed validated model can potentially be utilized by patients, providers, stakeholders and policy makers to assess individualized risks, shared decision making and guiding the process of patient counselling and informed consent.