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Abstract Number: 708

Determining Risk Factors That Increase Hospitalizations in Patients with Systemic Lupus Erythematosis

Hareth M. Madhoun1, Wael N. Jarjour2, Peter J. Embi3, Erinn M. Hade4 and W Neal Roberts Jr5, 1Rheumatology/Immunology, The Ohio State University Wexner Medical Center, Columbus, OH, 2Dept of Rheumatology/Medicine, The Ohio State University Wexner Medical Center, Columbus, OH, 3Biomedical Informatics & Internal Medicine, The Ohio State University, Columbus, OH, 4College of Medicine Department of Biomedical Informatics, The Ohio State University Wexner Medical Center, Columbus, OH, 5Dept of Internal Medicine, Division of Rheumatology, University of Louisville, Louisville, KY

Meeting: 2014 ACR/ARHP Annual Meeting

Keywords: Electronic Health Record, risk and systemic lupus erythematosus (SLE)

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Session Information

Title: Systemic Lupus Erythematosus - Clinical Aspects and Treatment: Treatment and Management Studies

Session Type: Abstract Submissions (ACR)

Background/Purpose

Systemic lupus erythematosis (SLE) is a complex heterogeneous disease which can be associated with significant morbidity and mortality. Hospitalization and readmissions have garnered significant attention in recent years through Medicare reimbursement adjustments. The aim of this study was to determine what factors may increase the risk of hospitalization in patients with SLE. The goal of this project is to develop a lupus specific computerized decision support prompt to improve care and reduce hospitalizations.  

Methods

Between 2006–2011, patients with an ICD-9 code of SLE were selected. Additional information that could be relevant to risk profiling were extracted, including: laboratory results, medications, appointments (scheduled and/or kept), and hospitalizations. Patients were divided into two groups: hospitalized and non-hospitalized. Hospitalized patients selected for chart review and inclusion in the cohort, included any with an ICD-9 diagnosis of lupus as the primary reason for admission to the hospital. The non-hospitalized patients included any with an ICD-9 code for lupus who were seen by rheumatology. Patients were selected randomly from among all who met inclusion criteria. The risks associated with hypothesized risk factors, including proportion of missed appointments and creatinine levels, were estimated through weighted Cox regression models to account for patient selection into the study.  

Results

29 patients were selected who met the above lupus hospitalization criteria and 37 patients were randomly selected as non-hospitalized lupus controls. Patients were categorized into three groups based on the percentage of missed appointments (0% missed, >0%-33% missed, 33%-100% missed). Of the 60 patients with appointment data, 12 had no missed appointments, 27 (0-33%), 21 (33-100%). There was a trend toward an elevated risk of hospitalization for those with missed appointments and an elevated creatinine at their last appointment. In a multivariable model accounting for age and last creatinine measurement, patients who missed up to 33% of appointments, were estimated to have 2.92 (95% CI: 0.54-15.76) times the risk of patients who did not miss any appointments. Patients who missed between 33% and 100% of their appointments, the risk was 3.30 (95% CI: 0.52-20.96) times. The estimated risk of hospitalization associated with creatinine measure over 1.25 ml/dl at their last appointment was 4.72 (95% CI: 1.22-18.27) times the risk of those with with lower creatinine.

Conclusion

Patients with SLE appear to have an elevated risk of hospitalization with an increase in missed appointments and higher creatinine. Data about proportion of missed appointments or elevated creatinine might be used to trigger electronic health record-based decision support alerts about such risk that could lead to clinical interventions to help avoid hospitalizations. Further study with larger cohort samples is needed to confirm these findings and potentially identify other risk factors. Ongoing work will incorporate elements from the Systemic Lupus International Correlation Clinics damage index to enhance the predictive value of this model with the goal of helping to reduce hospitalization and readmission.


Disclosure:

H. M. Madhoun,
None;

W. N. Jarjour,
None;

P. J. Embi,
None;

E. M. Hade,
None;

W. N. Roberts Jr,
None.

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