Class of 2012 Abstract / Specific Aims: This study was aimed to evaluate inpatient clinical treatment characteristics associated with the use of intracranial implantation of chemotherapeutic wafers for malignant brain neoplasms within United States, and assess inpatient mortality and total charges regarding treatment with wafer versus without. Methods: A retrospective cohort investigation was conducted utilizing inpatient discharge records from the Agency for Healthcare Research and Quality (AHRQ) Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample from 2005 to 2009. From this nationally- representative sample, 9,455 adults aged 18 years or older were identified with malignant neoplasms of the brain treated with implantable chemotherapeutic wafers. Outcomes of inpatient mortality and charges were assessed via multivariate regression analysis, controlling for patient characteristics, hospital structure, comorbidities, and clinical complications. Main Results: The average age of patients with brain neoplasms was 56.6 (±16.5) years, and of those patients, 42.9% were female. The odds ratio for inpatient mortality of patients treated with implantable chemotherapeutic wafers was OR=0.380 (P<0.001), and patients that received wafer treatment had increased charges exp(b)=2.147 (P<0.001). Conclusions: Multiple factors were associated with inpatient mortality and charges among the 247,829 patients that were diagnosed with malignant brain neoplasms from 2005-2009. With regards to these patients, implantable chemotherapeutic wafers were associated with increased inpatient survival and increased charges.

Class of 2010 Abstract / OBJECTIVES: To assess disease-related and resource consumption characteristics of esophageal cancer mortality within hospital inpatient settings in the United States from 2002 to 2006. METHODS: This retrospective investigation of adults aged 18 years or older with diagnoses of malignant neoplasms of the esophagus (ICD-9: 150.x) utilized nationally-representative hospital discharge records from the Agency for Healthcare Research and Quality (AHRQ) Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample. Cases resulting in inpatient death were analyzed with respect to patient demographics, payer, hospital characteristics, number of procedures and diagnoses, Deyo-Charlson disease-based case-mix risk adjustor, and predominant comorbidities. RESULTS: Overall, 168,450 inpatient admissions for esophageal cancer were observed between 2002 and 2006, averaging 66.3 + or - 11.9 years, length of stay of 10.3 + or - 15.2 days, and charge of $51,600 + or _ 92,377. Predominant comorbidities within these persons included: secondary malignant neoplasms; disorders of fluid, electrolyte, and acid-base balance; pneumonia; respiratory failure/collapse or insufficiency; sepsis; anemia; hypertension; cardiac arrhythmias; obstructive pulmonary disease; acute or chronic renal disease; and heart failure. Significant predictors of increased charges included longer lengths of stay, higher numbers of diagnoses and procedures, median annual family income over $45k, urban hospital location, and presence of heart failure, chronic pulmonary disease, fluid and electrolyte disorders, or metastatic cancers (P< or = 0.05). Longer lengths of stay were associated with higher total charges, female sex, larger number of diagnoses and procedures, Medicaid, black race, increased case-mix severities, and fluid and electolyte disorders (P< or = 0.05). CONCLUSIONS: Patient mortality occurs in over one-tenth of esophageal cancer hospital admission cases. Further research is warranted to understand the impact of various comorbidities or treatment approaches and to assess potential disparities in lengths of stay.

Class of 2009 Abstract / OBJECTIVES: The purpose of the study was to determine the rate of Clostridium difficile infections (CDI) in hospitalized patients and the various factors that were associated with the risk of developing CDI by examining patient discharge data for hospitals in 37 states in the United States using Healthcare Cost and Utilization Project (HCUP). METHODS: Patient discharge information for all patients obtained using HCUP census for the years 2002-2005, either for primary or secondary (all-listed) occurrences of CDI using the ICD-9-CM code (008.45) specific for intestinal infections due to C. difficile, were included in the study. Regression analysis, either Generalized Linear Model log-link or power-link, or a logistic regression was employed to control for the multiple independent variables. RESULTS: The incidence rate for CDI was 9.4% for the years 2002-2005. Among the concomitant diagnoses and procedures, essential hypertension, volume depletion, congestive heart failure, urinary tract infection and venous catheterization were the top 5. The length of stay (LOS) for CDI was associated with being Black, Hispanic or Other race category, number of diagnoses and procedures, primary expected payer of Medicaid, private insurance and other (including worker’s compensation, CHAMPUS,CHAMPVA etc), and all groups classified based on median household income category for patient’s zip code. Predictors of CDI related to inpatient total hospital charges were being female, race (other than black), number of diagnoses and procedures, Death, LOS, patient location and with self-pay and no charge categories as primary expected payer. Predictors of higher CDI related inpatient hospital deaths were age, female sex, Hispanic race, number of diagnoses and procedures, LOS and having Medicaid, self-pay or other as primary expected payer. CONCLUSIONS: LOS, inpatient total hospital charges, and inpatient mortality were dependent on several patient and other characteristics.

Class of 2009 / OBJECTIVES: To determine and characterize the relative impact of patient demographics on hospital inpatient charges, length of stay, and inpatient mortality in patients with ovarian cancer from 2002-2005. METHODS: A retrospective database analysis of AHRQ’s Health Care Cost and Utilization Project (HCUP) Nationwide Inpatient Sample databases was conducted spanning from January 1, 2002, to December 31, 2005.Data were collected regarding age, race, payer status, median household income, location of hospital (urban/rural), comorbidities, procedures, total charges, length of stay, and inpatient mortality. Multivariate and gamma regression methods were utilized to examine incremental risks associated with length of stay, total charges, and inpatient mortality, after controlling for all other variables. RESULTS: Overall, data from 246,012 hospital admissions were obtained. The average length of stay of patients was 6.58 days (SD = 7.22), the average number of diagnoses was 7.18 (SD = 3.36), the average number of procedures performed was 2.71 (SD = 2.66). A total of 14,485 (5.9%) patients died during hospitalization. The average total charge was $29,698 (SD = $42,951). The IRR was 0.886 (95%CI, -0.105 to -0.04) for patients who were Hispanic, and 1.089 (95%CI, 0.017–0.153) for patients who were Black compared to patients who were white. When compared to patients who lived in large, metropolitan areas, the IRR was 0.88 (95%CI, -0.146 to - 0.109) for patients located in smaller, metropolitan areas, and the IRR was 0.74 (95%CI, -0.335 to -0.268) for patients located in non- urban areas. CONCLUSIONS: Patient demographics were found to have associations, both directly and indirectly, with length o

Background: It has been reported that transjugular intrahepatic portosystemic shunting (TIPS) might be utilized as a salvage option for hepatorenal syndrome (HRS), while randomized controlled trials are pending and real-world contemporary data on inpatient mortality is lacking. Methods: We conducted an observational retrospective cohort study from the National Inpatient Sample from 2005 to 2014. We included all adult patients admitted with HRS and cirrhosis, using ICD 9-CM codes. We excluded cases with variceal bleeding, Budd–Chiari, end-stage renal disease, liver transplant and transfers to acute-care facilities. TIPS’ association with inpatient mortality was assessed using multivariable mixed-effects logistic regression, as well as exact-matching, thus mitigating for TIPS selection bias. The exact-matched analysis was repeated among TIPS-only versus dialysis-only patients. Results: A total of 79,354 patients were included. Nine hundred eighteen (1.2%) underwent TIPS. Between TIPS and non-TIPS groups, mean age (58 years) and gender (65% males) were similar. Overall mortality was 18% in TIPS and 48% in dialysis-only cases (n = 10,379; 13.1%). Ninety six (10.5%) TIPS patients underwent dialysis. In-hospital mortality in TIPS patients was twice less likely than in non-TIPS patients (adjusted odds ratio [aOR] = 0.43, 95% CI 0.30–0.62; p < 0.001), with similar results in matched analysis [exact-matched (em) OR = 0.39, 95% CI 0.17–0.89; p < 0.024; groups = 96; unweighted n = 463]. Head-to-head comparison showed that TIPS-only patients were 3.3 times less likely to succumb inpatient versus dialysis-only patients (contrast aOR = 0.31, 95% CI 0.20–0.46; p < 0.001), with similar findings post-matching (emOR = 0.22, 95% CI 0.15–0.33; p < 0.001; groups = 54, unweighted n = 1457). Conclusions: Contemporary, real-world data reveal that TIPS on its own, and when compared to dialysis, is associated with decreased inpatient mortality when utilized in non-bleeders-HRS patients. Further randomized studies are needed to establish the long-term benefit of TIPS in these patients.

Background. In-hospital mortality is a measure recognized by US Agency for Healthcare Quality to represent quality of care within hospitals, that accounts for mortality based on three indicators: 1. select medical conditions and procedures; 2. procedures linked with questions of use (misuse, over/under use); 3. high volume procedures traditionally associated with lower mortality rates. Understanding how different comorbidity models measure in-hospital mortality is essential not only for determining patient health status in the hospital setting, but also help to regulating mortality risk and mortality risk predictions. One of the most widely used discriminatory models is the Charlson model, which predicts the risk of mortality within one year of hospitalization of patients with various comorbidities using CCSR codes for ICD-10 diagnoses which is quantified by the c-statistics, represented by the area under the curve (AUC). Objectives. To adapt a comorbidity index model to the National Inpatient Sample (NIS) database of 2020 to predict 1-year mortality for patients admitted with select ICD-10 codes of diagnoses. Methods Our study analysis examined mortality with comorbidity using the Charlson model in a sample population of estimated 5,533,477 adult inpatients (individuals ≥18 years of age). A multivariate logistic regression model was constructed with in-hospital mortality as the outcome variable and identifying predictor variables as defined by the Clinical Classifications Software Refined Variables (CCSR) codes for selected ICD-10 diagnoses (Table 3). Descriptive statistics and the base logistic regression analyses were conducted using SAS statistical software version 9.4. To avoid overpowering and avoid variables attaining statistical significance while only marginally changing the outcome, a subsample (n=100,000) was randomly selected from the original data set. Ultimately, 20 CCSR variables with p-values <0.20 from the base simple logistic regression models were included in the subsequent backward stepwise logistic regression analysis. Results Table 1 shows the prevalence of the selected diagnoses for our analysis. Anemia (28.32%), pulmonary disease (asthma, COPD, pneumoconiosis;21.88%), and diabetes without complications (19.47%) were the three most prevalent conditions among hospitalized patients. Table 2 shows the results of the base logistic regression analysis conducted, which excluded connective tissue/rheumatologic disorders, peptic ulcer disease, anemia, diabetes with complications, and human immunodeficiency as predictors of inpatient mortality. Results of the backward stepwise regression analysis revealed that severe liver disease/hepatic failure ([adjusted odds ratio (aOR): 10.50, (CI: 10.40-10.59)], acute myocardial infarction ([2.85, (2.83-2.87)] and malnutrition ([2.15, (2.14-2.16)] were three most important risk factors and had the highest impact on inpatient mortality (p-value <0.0001). However, smoking history, obesity, and liver disease were negatively associated with inpatient mortality. The c-statistic or the area under the curve (AUC) for the final model was 0.752. Conclusion Our findings, based on Charlson modeling procedures, indicate that independent variables representative of comorbidity with the strongest 1-year risk of mortality were among patients with ICD-10 codes relating to: severe liver disease/hepatic failure, acute myocardial infarction, and malnutrition. Hence, relevant stakeholders (patients, family members, and healthcare providers) can utilize this knowledge to advance models of care and prevention strategies that limit disease progression and improve patient outcomes.

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