Su1119 Hospital Readmissions of Inflammatory Bowel Disease: Developing a High-Dimensional Predictive Model Using Administrative Claims Data

2014 ◽  
Vol 146 (5) ◽  
pp. S-380
Author(s):  
Berkeley N. Limketkai ◽  
Danning He ◽  
Susan Hutfless
Keyword(s):  
Inflammatory Bowel Disease ◽  
Predictive Model ◽  
Bowel Disease ◽  
Claims Data ◽  
Hospital Readmissions ◽  
High Dimensional ◽  
Administrative Claims ◽  
Administrative Claims Data ◽  
Inflammatory Bowel

scholarly journals Development and Validation of an Inflammatory Bowel Disease Severity Index Using US Administrative Claims Data: A Retrospective Cohort Study

2020 ◽  
Author(s):  
Grace Chen ◽  
Trevor Lissoos ◽  
Christopher Dieyi ◽  
Kyle D Null
Keyword(s):  
Inflammatory Bowel Disease ◽  
Emergency Department ◽  
Disease Severity ◽  
Emergency Department Visit ◽  
Bowel Disease ◽  
Claims Data ◽  
Administrative Claims ◽  
Total Cost ◽  
Administrative Claims Data ◽  
Inflammatory Bowel

Abstract Background Clinical indices to characterize the severity of inflammatory bowel disease (IBD) are widely used in clinical trials and real-world practice. However, there are few validated instruments for assessing IBD severity in administrative claims-based studies. Methods Patients (18–89 years) diagnosed with ulcerative colitis (UC) or Crohn’s disease (CD) and receiving ≥1 prescription claim for IBD therapy were identified using administrative claims data from the Optum Clinformatics, IMS PharMetrics, and Truven MarketScan databases (January 1, 2013–September 30, 2017). Regression modeling identified independent predictors of IBD-related hospitalization (inpatient stay or emergency department visit resulting in hospitalization), which were used to develop IBD severity indices. The index was validated against all-cause hospitalization and total cost and IBD-related hospitalization and total cost. Results There were 51,767 patients diagnosed with UC (n = 30,993) or CD (n = 20,774) who were initiated treatment with IBD therapy. Independent predictors of IBD-related hospitalization were Charlson Comorbidity Index score >1, anemia, weight loss, intravenous corticosteroid use, prior gastrointestinal-related emergency department visit and hospitalization, and unspecified disease location or more extensive disease. Female sex, renal comorbidities, intestinal fistula, and stricture were additional risk factors for patients with CD, whereas age <40 years was a UC-specific risk factor. Median IBD severity scores were 8 and 13 for UC and CD, respectively, from possible total scores of 51 and 37. Inflammatory bowel disease severity score correlated with significantly higher all-cause hospitalization and cost, all-cause total cost, IBD-related hospitalization cost, and total cost. Conclusions These validated UC and CD severity indices can be used to predict IBD-related outcomes using administrative claims databases.

scholarly journals Mental Health Costs of Inflammatory Bowel Diseases

2020 ◽  
Vol 27 (1) ◽  
pp. 40-48 ◽  
Author(s):  
Eva Szigethy ◽  
Sean M Murphy ◽  
Orna G Ehrlich ◽  
Nicole M Engel-Nitz ◽  
Caren A Heller ◽  
...  
Keyword(s):  
Mental Health ◽  
Inflammatory Bowel Disease ◽  
Bowel Disease ◽  
Claims Data ◽  
The United States ◽  
Cost Of Care ◽  
Medical Utilization ◽  
Administrative Claims ◽  
Inflammatory Bowel ◽  
Ed Visits

Abstract Background Mental health diagnoses (MHDs) were identified as significant drivers of inflammatory bowel disease (IBD)-related costs in an analysis titled “Cost of Care Initiative” supported by the Crohn’s & Colitis Foundation. In this subanalysis, we sought to characterize and compare IBD patients with and without MHDs based on insurance claims data in terms of demographic traits, medical utilization, and annualized costs of care. Methods We analyzed the Optum Research Database of administrative claims from years 2007 to 2016 representing commercially insured and Medicare Advantage insured IBD patients in the United States. Inflammatory bowel disease patients with and without an MHD were compared in terms of demographics (age, gender, race), insurance type, IBD-related medical utilization (ambulatory visits, emergency department [ED] visits, and inpatient hospitalizations), and total IBD-related costs. Only patients with costs >$0 in each of the utilization categories were included in the cost estimates. Results Of the total IBD study cohort of 52,782 patients representing 179,314 person-years of data, 22,483 (42.6%) patients had at least 1 MHD coded in their claims data with a total of 46,510 person-years in which a patient had a coded MHD. The most commonly coded diagnostic categories were depressive disorders, anxiety disorders, adjustment disorders, substance use disorders, and bipolar and related disorders. Compared with patients without an MHD, a significantly greater percentage of IBD patients with MHDs were female (61.59% vs 48.63%), older than 75 years of age (9.59% vs 6.32%), white (73.80% vs 70.17%), and significantly less likely to be younger than 25 years of age (9.18% vs 11.39%) compared with those without mental illness (P < 0.001). Patients with MHDs had significantly more ED visits (14.34% vs 7.62%, P < 0.001) and inpatient stays (19.65% vs 8.63%, P < 0.001) compared with those without an MHD. Concomitantly, patients with MHDs had significantly higher ED costs ($970 vs $754, P < 0.001) and inpatient costs ($39,205 vs $29,550, P < 0.001) compared with IBD patients without MHDs. Patients with MHDs also had significantly higher total annual IBD-related surgical costs ($55,693 vs $40,486, P < 0.001) and nonsurgical costs (medical and pharmacy) ($17,220 vs $11,073, P < 0.001), and paid a larger portion of the total out-of-pocket cost for IBD services ($1017 vs $905, P < 0.001). Conclusion Patients whose claims data contained both IBD-related and MHD-related diagnoses generated significantly higher costs compared with IBD patients without an MHD diagnosis. Based on these data, we speculate that health care costs might be reduced and the course of patients IBD might be improved if the IBD-treating provider recognized this link and implemented effective behavioral health screening and intervention as soon as an MHD was suspected during management of IBD patients. Studies investigating best screening and intervention strategies for MHDs are needed.

scholarly journals A predictive model to identify Parkinson disease from administrative claims data

Neurology ◽  
2017 ◽  
Vol 89 (14) ◽  
pp. 1448-1456 ◽  
Author(s):  
Susan Searles Nielsen ◽  
Mark N. Warden ◽  
Alejandra Camacho-Soto ◽  
Allison W. Willis ◽  
Brenton A. Wright ◽  
...  
Keyword(s):  
Parkinson Disease ◽  
Predictive Model ◽  
Claims Data ◽  
Demographic Data ◽  
Area Under The Curve ◽  
Rem Sleep Behavior Disorder ◽  
Administrative Claims ◽  
Sleep Behavior ◽  
Administrative Claims Data ◽  
Procedure Codes

Objective:To use administrative medical claims data to identify patients with incident Parkinson disease (PD) prior to diagnosis.Methods:Using a population-based case-control study of incident PD in 2009 among Medicare beneficiaries aged 66–90 years (89,790 cases, 118,095 controls) and the elastic net algorithm, we developed a cross-validated model for predicting PD using only demographic data and 2004–2009 Medicare claims data. We then compared this model to more basic models containing only demographic data and diagnosis codes for constipation, taste/smell disturbance, and REM sleep behavior disorder, using each model's receiver operator characteristic area under the curve (AUC).Results:We observed all established associations between PD and age, sex, race/ethnicity, tobacco smoking, and the above medical conditions. A model with those predictors had an AUC of only 0.670 (95% confidence interval [CI] 0.668–0.673). In contrast, the AUC for a predictive model with 536 diagnosis and procedure codes was 0.857 (95% CI 0.855–0.859). At the optimal cut point, sensitivity was 73.5% and specificity was 83.2%.Conclusions:Using only demographic data and selected diagnosis and procedure codes readily available in administrative claims data, it is possible to identify individuals with a high probability of eventually being diagnosed with PD.

P123 THIRTY DAY READMISSIONS AMONG PATIENTS WITH COMPLICATED INFLAMMATORY BOWEL DISEASE AND EFFECTS ON OUTCOMES: RESULTS OF ANALYSIS OF 2016 NATIONWIDE READMISSION DATABASE

2020 ◽  
Vol 26 (Supplement_1) ◽  
pp. S46-S46
Author(s):  
Sachit Sharma ◽  
Zubair Khan ◽  
Muhammad Aziz ◽  
Ishaan Vohra ◽  
Ashu Acharya
Keyword(s):  
Inflammatory Bowel Disease ◽  
Resource Use ◽  
Bowel Disease ◽  
Hospital Readmissions ◽  
Index Admission ◽  
Insurance Status ◽  
Lower Income ◽  
Comorbidity Score ◽  
Inflammatory Bowel ◽  
Nationwide Readmission Database

Abstract Objective To determine the rate of hospital readmissions within 30 days of discharge in patients with complicated Inflammatory Bowel Disease (IBD) and its impact on mortality, morbidity, and health care cost in the United States. Methods We performed a retrospective study using the Nationwide Readmission Database(NRD) for the year 2016 (Data on 35.6 million discharges). We collected data on hospital readmissions of 29,356 adults who were hospitalized for complicated Inflammatory Bowel Disease(Crohn’s disease and Ulcerative Colitis) and discharged. Complications were defined using ICD 10 codes. Patients with age less than 18, elective admission and admission during December month were excluded. The primary outcome was rate of all-cause readmission within 30 days of discharge. Secondary outcomes were reasons for readmission, readmission mortality rate, morbidity and resource use. Multivariate regression analysis was used to determine the independent predictors of 30-day readmission. Results Among patients admitted to US hospitals with complicated IBD, the total time at risk was 407,983 days, with the first readmission occurring at day 1 and the last readmission at day 30. The 30-day rate of readmission was 17.6%, with the most common cause of readmission being Crohn’s disease of small intestine with intestinal obstruction (9%). The mortality rate among patients readmitted to the hospital (0.6%), was higher than that for index admissions (0.3%) (P < .01). Mean length of stay was 5.5 days for index admission and 5.9 days for readmission (p=0.01). Mean total charge for index admission was $44,768 compared to $48,766 for readmission (p<0.01). Mean total cost for index admission was $11,491 compared to $12,704 for readmission (p<0.01). A total of 30,943 hospital days were associated with readmission, and the total health care in-hospital economic burden was $65 million (in costs) and $251 million (in charges). Independent predictors of readmission were age, insurance status, higher Charlson comorbidity score, lower income, teaching status of hospital and longer stays in the hospital. Older age, private insurance, median income more than $48,000 were associated with lower odds for readmission, whereas higher comorbidities and admission to teaching hospital were associated with increased odds for readmission. Conclusions In a retrospective study of patients hospitalized for complicated IBD in 2016, 17.6% were readmitted to the hospital within 30 days of discharge. Readmission was associated with higher mortality, morbidity, and resource use. Age, insurance status, higher comorbidity score, lower income and admission to teaching hospital were independent predictors of readmission.

OP27 High-dimensional mass cytometry reveals the immune cell landscape in inflammatory bowel disease

2019 ◽  
Vol 13 (Supplement_1) ◽  
pp. S020-S020
Author(s):  
V van Unen ◽  
N Li ◽  
T Abdelaal ◽  
Y Kooy-Winkelaar ◽  
L Ouboter ◽  
...  
Keyword(s):  
Inflammatory Bowel Disease ◽  
Bowel Disease ◽  
Immune Cell ◽  
High Dimensional ◽  
Mass Cytometry ◽  
Inflammatory Bowel
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