Measurement of total hemoglobin reduces red cell transfusion in hospitalized patients undergoing cardiac surgery: a retrospective database analysis.

INTRODUCTION: Historically, perioperative hemoglobin monitoring has relied on calculated saturation, using blood gas devices that measure plasma hematocrit (Hct). Co-oximetry, which measures total hemoglobin (tHb), yields a more comprehensive assessment of hemodilution. The purpose of this study was to examine the association of tHb measurement by co-oximetry and Hct, using conductivity with red blood cell (RBC) transfusion, length of stay (LOS) and inpatient costs in patients having major cardiac surgery. METHODS: A retrospective study was conducted on patients who underwent coronary artery bypass graft (CABG) and/or valve replacement (VR) procedures from January 2014 to June 2016, using MedAssets discharge data. The patient population was sub-divided by the measurement modality (tHb and Hct), using detailed billing records and Current Procedural Terminology coding. Cost was calculated using hospital-specific cost-to-charge ratios. Multivariable logistic regression was performed to identify significant drivers of RBC transfusion and resource utilization. RESULTS: The study population included 18,169 cardiovascular surgery patients. Hct-monitored patients accounted for 66% of the population and were more likely to have dual CABG and VR procedures (10.4% vs 8.9%, p=0.0069). After controlling for patient and hospital characteristics, as well as patient comorbidities, Hct-monitored patients had significantly higher RBC transfusion risk (OR=1.26, CI 1.15-1.38, p<0.0001), longer LOS (IRR=1.08, p<0.0001) and higher costs (IRR=1.15, p<0.0001) than tHb-monitored patients. RBC transfusions were a significant driver of LOS (IRR=1.25, p<0.0001) and cost (IRR=1.22, p<0.0001). CONCLUSIONS: tHb monitoring during cardiovascular surgery could offer a significant reduction in RBC transfusion, length of stay and hospital cost compared to Hct monitoring.

The Rothman Index predicts unplanned readmissions to intensive care associated with increased mortality and hospital length of stay: a propensity-matched cohort study.

BACKGROUND: Patients with unplanned readmissions to the intensive care unit (ICU) are at high risk of preventable adverse events. The Rothman Index represents an objective real-time grading system of a patient's clinical condition and a predictive tool of clinical deterioration over time. This study was designed to test the hypothesis that the Rothman Index represents a sensitive predictor of unanticipated ICU readmissions. METHODS: A retrospective propensity-matched cohort study was performed at a tertiary referral academic medical center in the United States from January 1, 2022, to December 31, 2022. Inclusion criteria were adult patients admitted to an ICU and readmitted within seven days of transfer to a lower level of care. The control group consisted of patients who were downgraded from ICU without a subsequent readmission. The primary outcome measure was in-hospital mortality or discharge to hospice for end-of-life care. Secondary outcome measures were overall hospital length of stay, ICU length of stay, and 30-day readmission rates. Propensity matching was used to control for differences between the study cohorts. Regression analyses were performed to determine independent risk factors of an unplanned readmission to ICU. RESULTS: A total of 5,261 ICU patients met the inclusion criteria, of which 212 patients (4%) had an unanticipated readmission to the ICU within 7 days. The study cohort and control group were stratified by propensity matching into equal group sizes of n = 181. Lower Rothman Index scores (reflecting higher physiologic acuity) at the time of downgrade from the ICU were significantly associated with an unplanned readmission to the ICU (p < 0.0001). Patients readmitted to ICU had a lower mean Rothman Index score (p < 0.0001) and significantly increased rates of mortality (19.3% vs. 2.2%, p < 0.0001) and discharge to hospice (14.4% vs. 6.1%, p = 0.0073) compared to the control group of patients without ICU readmission. The overall length of ICU stay (mean 8.0 vs. 2.2 days, p < 0.0001) and total length of hospital stay (mean 15.8 vs. 7.3 days, p < 0.0001) were significantly increased in patients readmitted to ICU, compared to the control group. CONCLUSION: The Rothman Index represents a sensitive predictor of unanticipated readmissions to ICU, associated with a significantly increased mortality and overall ICU and hospital length of stay. The Rothman Index should be considered as a real-time objective measure for prediction of a safe downgrade from ICU to a lower level of care.

Quantifying the impact of novel metastatic cancer therapies on health inequalities in survival outcomes.

Background: Novel therapies in metastatic cancers have contributed to improvements in survival outcomes, yet real-world data suggest that improvements may be mainly driven by those patient groups who already had the highest survival outcomes. This study aimed to develop and apply a framework for quantifying the impact of novel metastatic cancer therapies on health inequalities in survival outcomes based on published aggregate data. Methods: Nine (N = 9) novel therapies for metastatic breast cancer (mBC), metastatic colorectal cancer (mCRC), and metastatic non-small cell lung cancer (mNSCLC) were identified, 3 for each cancer type. Individual patient data (IPD) for overall survival (OS) and progression-free survival (PFS) were replicated from published Kaplan-Meier (KM) curves. For each cancer type, data were pooled for the novel therapies and comparators separately and weighted based on sample size to ensure equal contribution of each therapy in the analyses. Parametric (mixture) distributions were fitted to the weighted data to model and extrapolate survival. The inequality in survival was defined by the absolute difference between groups with the highest and lowest survival for 2 stratifications: one for which survival was stratified into 2 groups and one using 5 groups. Additionally, a linear regression model was fitted to survival estimates for the 5 groups, with the regression coefficient or slope considered as the inequality gradient (IG). The impact of the pooled novel therapies was subsequently defined as the change in survival inequality relative to the pooled comparator therapies. A probabilistic analysis was performed to quantify parameter uncertainty. Results: The analyses found that novel therapies were associated with significant increases in inequalities in survival outcomes relative to their comparators, except in terms of OS for mNSCLC. For mBC, the inequalities in OS increased by 13.9 (95% CI: 1.4; 26.6) months, or 25.0%, if OS was stratified in 5 groups. The IG for mBC increased by 3.2 (0.3; 6.1) months, or 24.7%. For mCRC, inequalities increased by 6.7 (3.0; 10.5) months, or 40.4%, for stratification based on 5 groups; the IG increased by 1.6 (0.7; 2.4) months, or 40.2%. For mNSCLC, inequalities decreased by 14.9 (-84.5; 19.0) months, or 12.2%, for the 5-group stratification; the IG decreased by 2.0 (-16.1; 5.1) months, or 5.5%. Results for the stratification based on 2 groups demonstrated significant increases in OS inequality for all cancer types. In terms of PFS, the increases in survival inequalities were larger in a relative sense compared with OS. For mBC, PFS inequalities increased by 8.7 (5.9; 11.6) months, or 71.7%, for stratification based on 5 groups; the IG increased by 2.0 (1.3; 2.6) months, or 67.6%. For mCRC, PFS inequalities increased by 5.4 (4.2; 6.6) months, or 147.6%, for the same stratification. The IG increased by 1.3 (1.1; 1.6) months, or 172.7%. For mNSCLC, inequalities increased by 18.2 (12.5; 24.4) months, or 93.8%, for the 5-group stratification; the IG increased by 4.0 (2.8; 5.4) months, or 88.1%. Results from the stratification based on 2 groups were similar. Conclusion: Novel therapies for mBC, mCRC, and mNSCLC are generally associated with significant increases in survival inequalities relative to their comparators in randomized controlled trials, though inequalities in OS for mNSCLC decreased nonsignificantly when stratified based on 5 groups. Although further research using real-world IPD is warranted to assess how, for example, social determinants of health affect the impact of therapies on health inequalities among patient groups, the proposed framework can provide important insights in the absence of such data.

Cost-utility analysis of single nucleotide polymorphism panel-based machine learning algorithm to predict risk of opioid use disorder.

Aim: To conduct a cost-utility analysis of a novel genetic diagnostic test (OUDTEST) for risk of developing opioid use disorder for elective orthopedic surgery patients. Materials & Methods: A simulation model assessed cost-effectiveness and quality-adjusted life-years (QALYs) for OUDTEST from private insurer and self-insured employer perspectives over a 5-year time horizon for a hypothetical patient population. Results: OUDTEST was found to cost less and increase QALYs, over a 5-year period for private insurance (savings US$2510; QALYs 0.02) and self-insured employers (-US$2682; QALYs 0.02). OUDTEST was a dominant strategy in 71.1% (private insurance) and 72.7% (self-insured employer) of model iterations. Sensitivity analyses revealed robust results except for physician compliance. Conclusion: OUDTEST was expected to be a cost-effective solution for personalizing postsurgical pain management in orthopedic patients.

Stratifying Deterioration Risk by Acuity at Admission Offers Triage Insights for Coronavirus Disease 2019 Patients.

OBJECTIVES: Triaging patients at admission to determine subsequent deterioration risk can be difficult. This is especially true of coronavirus disease 2019 patients, some of whom experience significant physiologic deterioration due to dysregulated immune response following admission. A well-established acuity measure, the Rothman Index, is evaluated for stratification of patients at admission into high or low risk of subsequent deterioration. DESIGN: Multicenter retrospective study. SETTING: One academic medical center in Connecticut, and three community hospitals in Connecticut and Maryland. PATIENTS: Three thousand four hundred ninety-nine coronavirus disease 2019 and 14,658 noncoronavirus disease 2019 adult patients admitted to a medical service between January 1, 2020, and September 15, 2020. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Performance of the Rothman Index at admission to predict in-hospital mortality or ICU utilization for both general medical and coronavirus disease 2019 populations was evaluated using the area under the curve. Precision and recall for mortality prediction were calculated, high- and low-risk thresholds were determined, and patients meeting threshold criteria were characterized. The Rothman Index at admission has good to excellent discriminatory performance for in-hospital mortality in the coronavirus disease 2019 (area under the curve, 0.81-0.84) and noncoronavirus disease 2019 (area under the curve, 0.90-0.92) populations. We show that for a given admission acuity, the risk of deterioration for coronavirus disease 2019 patients is significantly higher than for noncoronavirus disease 2019 patients. At admission, Rothman Index-based thresholds segregate the majority of patients into either high- or low-risk groups; high-risk groups have mortality rates of 34-45% (coronavirus disease 2019) and 17-25% (noncoronavirus disease 2019), whereas low-risk groups have mortality rates of 2-5% (coronavirus disease 2019) and 0.2-0.4% (noncoronavirus disease 2019). Similarly large differences in ICU utilization are also found. CONCLUSIONS: Acuity level at admission may support rapid and effective risk triage. Notably, in-hospital mortality risk associated with a given acuity at admission is significantly higher for coronavirus disease 2019 patients than for noncoronavirus disease 2019 patients. This insight may help physicians more effectively triage coronavirus disease 2019 patients, guiding level of care decisions and resource allocation.

Real World Outcomes Associated with Idarucizumab: Population-Based Retrospective Cohort Study.

BACKGROUND: Idarucizumab reverses the anticoagulant effect of dabigatran, but few comparative studies have reported on clinical outcomes with idarucizumab. OBJECTIVE: Our objective was to determine the effect of idarucizumab on clinical outcomes. METHODS: We conducted a retrospective cohort study in a nationally representative sample of hospitals in the United States. The study population included adults ≥ 18 years who were hospitalized for dabigatran-associated major bleeding between January 1, 2015 and December 31, 2017. We compared idarucizumab-exposed patients to the unexposed group. Our primary outcome of interest was in-hospital mortality. RESULTS: We included 266 exposed and 1345 non-exposed participants across 271 hospitals. Among participants with gastrointestinal bleeding, there was no statistically significant difference in the odds of in-hospital mortality [9/153 (5.9%) vs 37/1124 (3.3%); adjusted odds ratio = 1.39, 95% confidence interval 0.51-3.45] between the idarucizumab-exposed and non-exposed groups. Among participants with intracranial bleeding, there was an excess of in-hospital mortality [13/112 (11.6%) vs 6/217 (2.8%)] associated with idarucizumab exposure, but limitations include sparse data and the inability to rule out residual confounding or confounding by disease severity. CONCLUSIONS: Among a large nationally representative sample of adult patients with dabigatran-associated major bleeding in the United States, we found no difference in in-hospital mortality among patients with gastrointestinal bleeding associated with idarucizumab exposure. An excess risk of in-hospital mortality associated with idarucizumab exposure among participants with intracranial bleeding deserves further exploration.

Outcomes of Hospitalized COVID-19 Patients by Risk Factors: Results from a United States Hospital Claims Database.

BACKGROUND/OBJECTIVE: The primary objective was to quantify the role of the number of Centers of Disease Control and Prevention (CDC) risk factors on in-hospital mortality. The secondary objective was to assess the associated hospital length of stay (LOS), intensive care unit (ICU) bed utilization, and ICU LOS with the number of CDC risk factors. METHODS: A retrospective cohort study consisting of all hospitalizations with a confirmed COVID-19 diagnosis discharged between March 15, 2020 and April 30, 2020 was conducted. Data was obtained from 276 acute care hospitals across the United States. Cohorts were identified based upon the number of the CDC COVID-19 risk factors. Multivariable regression modeling was performed to assess outcomes and utilization. The odds ratio (OR) and incidence rate ratio (IRR) were reported. RESULTS: Compared with patients with no CDC risk factors, patients with risk factors were significantly more likely to die during the hospitalization: One risk factor (OR 2.08, 95% CI, 1.60-2.70; P < 0.001), two risk factors (OR 2.63, 95% CI, 2.00-3.47; P < 0.001), and three or more risk factors (OR 3.49, 95% CI, 2.53-4.80; P < 0.001). The presence of CDC risk factors was associated with increased ICU utilization, longer ICU LOS, and longer hospital LOS compared to those with no risk factors. Patients with hypertension (OR 0.77, 95% CI, 0.70-0.86; P < 0.001) and those administered statins were less likely to die (OR 0.54, 95% CI, 0.49-0.60; P < 0.001). CONCLUSIONS: Quantifying the role of CDC risk factors upon admission may improve risk stratification and identification of patients who may require closer monitoring and more intensive treatment.

Geographic variation in hospital costs, payments, and length of stay for opioid-related hospital visits in the USA.

PURPOSE: Despite the rise in opioid-related hospitalizations, there has been little research regarding opioid-related healthcare utilization. The objective of this study was to estimate the mean adjusted hospital costs, payments, and length of stay (LOS) for opioid-related visits for the nation and each of the nine US census regions. METHODS: An observational study of retrospective claims data from the Vizient health system database was conducted. Eligible visits had a principal diagnosis of opioid use or dependence defined by ICD, ninth and tenth revision (ICD-9/10), and occurred between January 2014 and June 2017. Separate regression models for inpatient and outpatient visits were generated to estimate the adjusted costs, payments, and LOS for opioid-related visits. RESULTS: A total of 193,614 (32,713 inpatient and 160,901 outpatient) visits met the inclusion criteria. The overall adjusted mean cost, payment, and LOS for an inpatient opioid-related visit were $4,383 (range between regions: $2,894-$5,835), $6,689 (range between regions: $4,038-$9,001), and 4.35 days (range between regions: 3.8-5.7 days), respectively. The overall adjusted mean cost and payment for an outpatient opioid-related visit were $533 (range between regions: $395-$802) and $374 (range between regions: $187-$574), respectively. Opioid-related hospital costs, payments, and LOS varied across the US. Data on the regional variation and national averages are necessary for hospitals to benchmark their services and more effectively manage this population. CONCLUSION: Future research should examine intraregion utilization to understand the effect of prices and level of services.

Comparison of treatment patterns, resource utilization, and cost of care in patients with metastatic pancreatic cancer treated with first-line nab-paclitaxel plus gemcitabine or FOLFIRINOX.

BACKGROUND: We compared real-world treatment patterns, resource utilization, and cost of care for patients with metastatic pancreatic cancer treated with first-line nab-paclitaxel + gemcitabine or FOLFIRINOX (5-fluorouracil, leucovorin, irinotecan, oxaliplatin). METHODS: This was a retrospective study of inpatient and hospital-based outpatient data in the United States. Primary endpoints included median time to treatment discontinuation (TTD) and total cost of care per patient per month. Secondary endpoints included supportive care costs and hospitalization rate and length. RESULTS: Overall, 345 patients were included (nab-paclitaxel + gemcitabine, n = 182; FOLFIRINOX, n = 163). Median TTD was significantly longer with nab-paclitaxel + gemcitabine vs FOLFIRINOX (4.3 vs 2.8 months; P = .0009). Mean acquisition cost was higher with nab-paclitaxel + gemcitabine ($10,643 vs $6549; P = .0043), but mean total cost of care was lower ($16,628 vs $19,936; P = .1740). Supportive care cost was significantly lower with nab-paclitaxel + gemcitabine ($1995 vs $6456; P < .0001). Hospitalization rate and length were both significantly lower with nab-paclitaxel + gemcitabine. CONCLUSIONS: Despite higher acquisition costs with nab-paclitaxel + gemcitabine, FOLFIRINOX-treated patients had higher total costs driven by supportive care. Toxicity-related costs and drug acquisition costs should be considered when evaluating total cost of care.

Hospital-based inpatient resource utilization associated with autosomal dominant polycystic kidney disease in the US.

OBJECTIVE: Polycystic kidney disease (PKD) is a clinically and genetically heterogeneous class of genetic disorders characterized by development of renal cysts leading to renal failure and end stage renal disease (ESRD). Autosomal dominant polycystic kidney disease (ADPKD) accounts for the majority of PKD cases and is the predominant monogenic cause of ESRD. Limited information on patient characteristics and healthcare resource utilization is available in this population. This study assessed hospital-based inpatient utilization of patients with ADPKD in the US to help further understand the disease, which may lead to treatments that delay progression and reduce healthcare resource utilization. METHODS: A cross-sectional analysis was conducted using MedAssets Health System Data to investigate inpatient resource utilization for a total of 1876 patients hospitalized with ADPKD or chronic kidney disease (CKD). Patient characteristics and inpatient resource utilization were compared between hospitalized patients with ADPKD and CKD, including demographic and clinical characteristics, overall health, rates of complications and surgical interventions, and average length of hospital and intensive care unit stay. RESULTS: Compared with patients with CKD, patients with ADPKD were more likely to have commercial insurance as their primary payer (36.1 vs 17.8%) and were significantly younger (mean age 57.9 vs 69.5 years) and generally healthier (Charlson Comorbidity Score of 2.0 vs 3.3). Patients with ADPKD also had a substantially shorter average length of hospital stay (6.3 vs 10.3 days). However, patients with ADPKD experienced more kidney-related complications and a higher surgical procedure rate (mainly for transplant and complete nephrectomy). CONCLUSIONS: Although patients with ADPKD were generally healthier than patients with CKD, specific kidney function complications were more frequent. Patients with ADPKD had a higher rate of major kidney procedures, which may contribute to the high burden of ADPKD-related hospital-based inpatient resource utilization.