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To determine the effectiveness of booster vaccinations on the risk of hospitalization with coronavirus disease 2019 (COVID-19) and how it varies by enrollee characteristics and interval from the initial vaccination to receipt of a booster.This cohort study used 100% Medicare claims from January 1, 2020, through December 31, 2021, and matched 3,940,475 individuals who received boosters to 3,940,475 controls based on week and type of original COVID-19 vaccine and demographic and clinical characteristics. We compared the association of booster vs no booster with COVID-19 hospitalization using Cox proportional hazards regression models controlling for patient characteristics. We also determined the association of time from original vaccine to booster with COVID-19 hospitalization.Over a maximum of 130 days of follow-up, boosted enrollees had 8.20 (95% CI, 7.81 to 8.60) COVID-19 hospitalizations per million days vs 43.70 (95% CI, 42.79 to 44.64) for controls (81% effectiveness). Effectiveness varied by race, prior hospitalizations, and certain comorbidities, for example, leukemia/lymphoma (53% effectiveness), autoimmune disease (73%), and dementia (73%). Boosters received between 6 and 9 months after original vaccination varied between 81% and 85% effectiveness, while boosters received at 5 to 6 months (62%) or less than 5 months (58%) were less effective.Boosters are highly effective in the Medicare population. Approximately 69,225 hospitalizations would be prevented by boosters in the 15 million individuals aged 65 years or older currently not boosted in a period similar to the September 2020 through January 2021 period studied. Boosters provided the greatest benefits if they were received between 6 and 9 months following original vaccinations. However, boosters were associated with substantial decreases in COVID-19 hospitalizations in all categories of enrollees.

Anticoagulation among patients with cancer and atrial fibrillation is challenging due to elevated risk of bleeding and stroke. We characterized use of oral anticoagulants among patients with cancer and non-valvular atrial fibrillation (NVAF).We used Surveillance, Epidemiology, and End Results (SEER)-Medicare data and included patients with cancer aged ≥66 years with an incident diagnosis of NVAF from 2010 to 2016. We used a Cox proportional hazard model and multivariable logistic regression to identify factors associated with anticoagulant use versus no use and direct oral anticoagulants (DOACs) versus warfarin use, respectively.Of 27,702 patients with cancer and NVAF, 4469 (16.1%) used DOACs and 3577 (12.9%) used warfarin. Among 8046 anticoagulant users, DOACs use increased from 21.8% in 2011 to 76.2% in 2016, with a corresponding decline in warfarin use from 78.2% to 23.8%. Nearly 7 out of 10 patients with cancer and NVAF did not initiate anticoagulation in 2016. Anticoagulant use was more likely among those with higher CHA₂DS₂-VASc scores (hazard ratio [HR] 1.55, 95% confidence interval [CI] 1.27-1.90 for score ≥6 vs. 1) or with lower HAS-BLED scores (HR 1.96, 95% CI 1.67-2.30 for score 1 vs. ≥6). Among anticoagulant users, DOAC use was less likely than warfarin in those with higher CHA₂DS₂-VASc scores (odds ratio [OR] 0.53, 95% CI 0.33-0.84 for score ≥6 vs. 1).Nearly 7 out of 10 patients with cancer and NVAF did not receive anticoagulation. Use of DOACs increased from 2010 to 2016, with a corresponding decline in warfarin use. DOACs are used less than warfarin among those at higher risk of stroke.

Background There is an urgent need to understand the real-world effectiveness of remdesivir in the treatment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Methods This was a retrospective comparative effectiveness study. Individuals hospitalized in a large private healthcare network in the United States from 23 February 2020 through 11 February 2021 with a positive test for SARS-CoV-2 and ICD-10 diagnosis codes consistent with symptomatic coronavirus disease 2019 (COVID-19) were included. Remdesivir recipients were matched to controls using time-dependent propensity scores. The primary outcome was time to improvement with a secondary outcome of time to death. Results Of 96 859 COVID-19 patients, 42 473 (43.9%) received at least 1 remdesivir dose. The median age of remdesivir recipients was 65 years, 23 701 (55.8%) were male, and 22 819 (53.7%) were non-White. Matches were found for 18 328 patients (43.2%). Remdesivir recipients were significantly more likely to achieve clinical improvement by 28 days (adjusted hazard ratio [aHR] 1.19, 95% confidence interval [CI], 1.16–1.22). Remdesivir patients on no oxygen (aHR 1.30, 95% CI, 1.22–1.38) or low-flow oxygen (aHR 1.23, 95% CI, 1.19–1.27) were significantly more likely to achieve clinical improvement by 28 days. There was no significant impact on the likelihood of mortality overall (aHR 1.02, 95% CI, .97–1.08). Remdesivir recipients on low-flow oxygen were significantly less likely to die than controls (aHR 0.85, 95% CI, .77–.92; 28-day mortality 8.4% [865 deaths] for remdesivir patients, 12.5% [1334 deaths] for controls). Conclusions These results support the use of remdesivir for hospitalized COVID-19 patients on no or low-flow oxygen. Routine initiation of remdesivir in more severely ill patients is unlikely to be beneficial.

PURPOSE Because of toxicities, benzodiazepines are not usually recommended in older adults. We therefore sought to describe the trends in benzodiazepine use in long-term care and examine the variation in benzodiazepine use among nursing homes. METHODS In this retrospective repeated cross-sectional analysis of Medicare Parts A, B, and D claims data linked to the Minimum Data Set from 2013 to 2018, we included long-term residents who stayed in a nursing home for at least one entire quarter of a calendar year in 2013-2018. The outcome was whether residents were prescribed a benzodiazepine drug for at least 30 days during each quarter stay. We use mixed effects logistic regression models to assess the variation in benzodiazepine use among nursing homes, adjusting for patient and nursing home characteristics. RESULTS The cohort for the time trend analysis included 270,566 unique residents and 1,843,580 quarter stays for 2013-2018. Prescribing rates for short-acting benzodiazepines were stable over 2013-2016, then declined from 12.1% in 2016 to 10.6% in 2018. The rate of long-acting benzodiazepine use remained relatively steady at around 4% over 2013-2018. During 2017-2018, the variation among nursing homes in benzodiazepine use was 7.2% for short-acting vs. 9.3% for long-acting benzodiazepines, after controlling for resident characteristics. CONCLUSION Prescribing for short-acting benzodiazepines in long-term care declined after 2016, while long-acting benzodiazepine use did not change. The variation in benzodiazepine use among nursing homes is substantial. Identifying factors that explain this variation may help in developing strategies for deprescribing benzodiazepines in nursing home residents.

BACKGROUND: Relatively little is known about the use patterns of potential pharmacologic treatments of COVID-19 in the United States. OBJECTIVE: To use the National COVID Cohort Collaborative (N3C), a large, multicenter, longitudinal cohort, to characterize the use of hydroxychloroquine, remdesivir, and dexamethasone, overall as well as across individuals, health systems, and time. DESIGN: Retrospective cohort study. SETTING: 43 health systems in the United States. PARTICIPANTS: 137 870 adults hospitalized with COVID-19 between 1 February 2020 and 28 February 2021. MEASUREMENTS: Inpatient use of hydroxychloroquine, remdesivir, or dexamethasone. RESULTS: Among 137 870 persons hospitalized with confirmed or suspected COVID-19, 8754 (6.3%) received hydroxychloroquine, 29 272 (21.2%) remdesivir, and 53 909 (39.1%) dexamethasone during the study period. Since the release of results from the RECOVERY (Randomised Evaluation of COVID-19 Therapy) trial in mid-June, approximately 78% to 84% of people who have had invasive mechanical ventilation have received dexamethasone or other glucocorticoids. The use of hydroxychloroquine increased during March 2020, peaking at 42%, and started declining by April 2020. By contrast, remdesivir and dexamethasone use gradually increased over the study period. Dexamethasone and remdesivir use varied substantially across health centers (intraclass correlation coefficient, 14.2% for dexamethasone and 84.6% for remdesivir). LIMITATION: Because most N3C data contributors are academic medical centers, findings may not reflect the experience of community hospitals. CONCLUSION: Dexamethasone, an evidence-based treatment of COVID-19, may be underused among persons who are mechanically ventilated. The use of remdesivir and dexamethasone varied across health systems, suggesting variation in patient case mix, drug access, treatment protocols, and quality of care. PRIMARY FUNDING SOURCE: National Center for Advancing Translational Sciences; National Heart, Lung, and Blood Institute; and National Institute on Aging.

Background: While clinical guidelines recommend direct-acting oral anticoagulants (DOAC) over warfarin to treat isolated nonvalvular atrial fibrillation, guidelines are silent regarding nonvalvular atrial fibrillation treatment among individuals with cancer, reflecting the paucity of evidence in this setting. We quantified relative risk of ischemic stroke or systemic embolism and major bleeding (primary outcomes), and all-cause and cardiovascular death (secondary outcomes) among older individuals with cancer and nonvalvular atrial fibrillation comparing DOACs and warfarin. Methods: This retrospective cohort study used Surveillance, Epidemiology, and End Results cancer registry and linked US Medicare data from 2010 through 2016, and included individuals diagnosed with cancer and nonvalvular atrial fibrillation who newly initiated DOAC or warfarin. We used inverse probability of treatment weighting to control confounding. We used competing risk regression for primary outcomes and cardiovascular death, and Cox proportional hazard regression for all-cause death. Results: Among 7675 individuals included in the cohort, 4244 (55.3%) received DOACs and 3431 (44.7%) warfarin. In the inverse probability of treatment weighting analysis, there was no statistically significant difference among DOAC and warfarin users in the risk of ischemic stroke or systemic embolism (1.24 versus 1.19 events per 100 person-years, adjusted hazard ratio 1.41 [95% CI, 0.92–2.14]), major bleeding (3.08 versus 4.49 events per 100 person-years, adjusted hazard ratio 0.90 [95% CI, 0.70–1.17]), and cardiovascular death (1.88 versus 3.14 per 100 person-years, adjusted hazard ratio 0.82 [95% CI, 0.59–0.1.13]). DOAC users had significantly lower risk of all-cause death (7.09 versus 13.3 per 100 person-years, adjusted hazard ratio 0.81 [95% CI, 0.69–0.94]) compared to warfarin users. Conclusions: Older adults with cancer and atrial fibrillation exposed to DOACs had similar risks of stroke and systemic embolism and major bleeding as those exposed to warfarin. Relative to warfarin, DOAC use was associated with a similar risk of cardiovascular death and a lower risk of all-cause death.

Objective While several prescription drug-based risk indices have been developed, their design, performance, and application has not previously been synthesized. Study design and setting We searched Ovid MEDLINE, CINAHL and Embase from inception through March 3, 2020 and included studies that developed or updated a prescription drug-based risk index. Two reviewers independently performed screening and extracted information on data source, study population, cohort sizes, outcomes, study methodology and performance. Predictive performance was evaluated using C statistics for binary outcomes and R2 for continuous outcomes. The PROSPERO ID for this review is CRD42020165498. Results Of 19,112 articles that were retrieved, 124 were full-text screened and 25 were included, each of which represented a de novo or updated drug-based index. The indices were customized to varied age groups and clinical populations and most commonly evaluated outcomes including mortality (36%), hospitalization (24%) and healthcare costs (24%). C statistics ranged from 0.62 to 0.92 for mortality and 0.59 to 0.72 for hospitalization, while adjusted R2 for healthcare costs ranged from 0.06 to 0.62. Seven of the 25 risk indices included used global drug classification algorithms. Conclusions More than two-dozen prescription drug-based risk indices have been developed and they differ significantly in design, performance and application.

Background and ObjectivesTo determine the risk of hospitalization and death associated with pimavanserin use.MethodsWe conducted a retrospective cohort study of adults 65 years and older with Parkinson disease between November 1, 2015, and December 31, 2018, using an administrative dataset on residents of Medicare-certified long-term care facilities and linked Medicare claims data. Propensity score–based inverse probability of treatment weighting (IPTW) was used to balance pimavanserin users and nonusers on 24 baseline characteristics. Fine-Gray competing risk and Cox proportional hazards regression models were used to estimate the risk of hospitalization and death up to 1 year, respectively.ResultsThe study cohort included 2,186 pimavanserin users and 18,212 nonusers. There was a higher risk of 30-day hospitalization with pimavanserin use vs nonuse (IPTW-adjusted hazard ratio [aHR] 1.24, 95% confidence intervals [CI] 1.06–1.43). There was no association of pimavanserin use with 90-day hospitalization (aHR 1.10, CI 0.99–1.24) or with 30-day mortality (aHR 0.76, CI 0.56–1.03). Pimavanserin use vs nonuse was associated with increased 90-day mortality (aHR 1.20, CI 1.02–1.41) that persisted after 180 days (aHR 1.28, CI 1.13–1.45) and 1 year (aHR 1.56, CI 1.42–1.72).DiscussionPimavanserin use vs nonuse in older adults was associated with an increased risk of hospitalization at 1 month of initiation and a higher risk of death for up to 1 year following initiation. These findings, in a large real-world cohort within long-term care facilities, may help to inform decisions regarding its risk/benefit balance among patients with Parkinson disease.Classification of EvidenceThis study provides Class II evidence that in patients with Parkinson disease who are 65 or older and residing in Medicare-certified long-term care facilities, pimavanserin is associated with an increased risk of 30-day hospitalization and higher 90-, 180-, and 365-day mortality.

BACKGROUND: Older adults have many comorbidities contributing to mortality. OBJECTIVE: To develop a summary Elixhauser (S-Elixhauser) comorbidity score to predict 30-day, in-hospital, and 1-year mortality in older adults using the 38 comorbidities operationalized by the Agency for Healthcare Research and Quality (AHRQ). DESIGN: Retrospective cohort study. SETTING: Medicare beneficiaries from 2017 to 2019. PATIENTS: Persons hospitalized in 2018 (n = 899 844) and 3 disease-specific hospitalized cohorts. MEASUREMENTS: Weights were derived for 38 comorbidities to predict 30-day, in-hospital, and 1-year mortality. The S-Elixhauser score was internally validated and calibrated. Individual Elixhauser comorbidity indicators (38 comorbidities), the modified application of the AHRQ-derived Elixhauser summary score, the Charlson comorbidity indicators (17 comorbidities), and the Charlson summary score were externally validated. The c-statistic was used to evaluate discrimination of a comorbidity score model. RESULTS: The S-Elixhauser score was well calibrated and internally validated, with a c-statistic of 0.705 (95% CI, 0.703 to 0.707) in predicting 30-day mortality, 0.654 (CI, 0.651 to 0.657) for in-hospital mortality, and 0.743 (CI, 0.741 to 0.744) for 1-year mortality. In external validation of other comorbidity indices for 30-day mortality, the c-statistic was 0.711 (CI, 0.709 to 0.713) for the individual Elixhauser comorbidity indicators, 0.688 (CI, 0.686 to 0.690) for the AHRQ Elixhauser score, 0.696 (CI, 0.694 to 0.698) for the Charlson comorbidity indicators, and 0.690 (CI, 0.688 to 0.693) for the Charlson summary score. In 3 disease-specific populations, the discrimination of the S-Elixhauser score in predicting 30-day mortality ranged from 0.657 to 0.732. LIMITATIONS: Validation of the S-Elixhauser comorbidity score and head-to-head comparison with other comorbidity scores in an external population are needed to evaluate comparative performance. CONCLUSION: The S-Elixhauser comorbidity score is well calibrated and internally validated but its advantage over the AHRQ Elixhauser and Charlson summary scores is unclear. PRIMARY FUNDING SOURCE: National Institute on Aging.

Psychiatric illness may pose an additional risk of death for older adults during the COVID-19 pandemic. Older adults in the community versus institutions might be influenced by the pandemic differently. This study examines excess deaths during the COVID-19 pandemic among Medicare beneficiaries with and without psychiatric diagnoses (depression, anxiety, bipolar disorder, and schizophrenia) in the community versus nursing homes.This is a retrospective cohort study of a 20% random sample of 15,229,713 fee-for-service Medicare beneficiaries, from January 2019 through December 2021. Unadjusted monthly mortality risks, COVID-19 infection rates, and case-fatality rates after COVID-19 diagnosis were calculated. Excess deaths in 2020, compared to 2019 were estimated from multivariable logistic regressions.Of all included Medicare beneficiaries in 2020 (N = 5,140,619), 28.9% had a psychiatric diagnosis; 1.7% lived in nursing homes. In 2020, there were 246,422 observed deaths, compared to 215,264 expected, representing a 14.5% increase over expected. Patients with psychiatric diagnoses had more excess deaths than those without psychiatric diagnoses (1,107 vs. 403 excess deaths per 100,000 beneficiaries, p 0.01). The largest increases in mortality risks were observed among patients with schizophrenia (32.4% increase) and bipolar disorder (25.4% increase). The pandemic-associated increase in deaths with psychiatric diagnoses was only found in the community, not in nursing homes. The increased mortality for patients with psychiatric diagnoses was limited to those with medical comorbidities. The increase in mortality for psychiatric diagnoses was associated with higher COVID-19 infection rates (1-year infection rate = 7.9% vs. 4.2% in 2020), rather than excess case fatality.Excess deaths during the COVID-19 pandemic were disproportionally greater in beneficiaries with psychiatric diagnoses, at least in part due to higher infection rates. Policy interventions should focus on preventing COVID-19 infections and deaths among community-dwelling patients with major psychiatric disorders in addition to those living the nursing homes.

Stratification of patients with post-acute sequelae of SARS-CoV-2 infection (PASC, or long COVID) would allow precision clinical management strategies. However, long COVID is incompletely understood and characterised by a wide range of manifestations that are difficult to analyse computationally. Additionally, the generalisability of machine learning classification of COVID-19 clinical outcomes has rarely been tested.We present a method for computationally modelling PASC phenotype data based on electronic healthcare records (EHRs) and for assessing pairwise phenotypic similarity between patients using semantic similarity. Our approach defines a nonlinear similarity function that maps from a feature space of phenotypic abnormalities to a matrix of pairwise patient similarity that can be clustered using unsupervised machine learning.We found six clusters of PASC patients, each with distinct profiles of phenotypic abnormalities, including clusters with distinct pulmonary, neuropsychiatric, and cardiovascular abnormalities, and a cluster associated with broad, severe manifestations and increased mortality. There was significant association of cluster membership with a range of pre-existing conditions and measures of severity during acute COVID-19. We assigned new patients from other healthcare centres to clusters by maximum semantic similarity to the original patients, and showed that the clusters were generalisable across different hospital systems. The increased mortality rate originally identified in one cluster was consistently observed in patients assigned to that cluster in other hospital systems.Semantic phenotypic clustering provides a foundation for assigning patients to stratified subgroups for natural history or therapy studies on PASC.NIH (TR002306/OT2HL161847-01/OD011883/HG010860), U.S.D.O.E. (DE-AC02-05CH11231), Donald A. Roux Family Fund at Jackson Laboratory, Marsico Family at CU Anschutz.

This study aimed to quantify the association between pharmaceutical industry payments to physicians for pimavanserin and both pimavanserin prescription volume and Medicare expenditures.This retrospective cross-sectional study used 2016 and 2017 data from Open Payments and the Medicare Part D Prescriber Public Use Files. The authors used Poisson regression models to quantify the association between physician payments for pimavanserin and pimavanserin prescription volume and linear regression models to quantify the association with Medicare expenditures for pimavanserin.Of 1,609 physicians who prescribed pimavanserin, 45% received payments, which totaled to $6,369,922. Each $10,000 in physician payments was associated with a 14% increase in pimavanserin prescription volume (incident rate ratio=1.14, 95% confidence interval [CI]=1.13-1.14). Every $100 in physician payments was associated with a $175.84 increase in Medicare pimavanserin expenditures (95% CI=$161.55-$190.13).Extensive physician payments have been associated with increased pimavanserin prescription volume and Medicare expenditures.

Many academic institutions are collecting blood samples from patients seeking treatment for coronavirus disease 2019 (COVID‐19) to build research biorepositories. It may be feasible to extract pharmacogenomic (PGx) information from biorepositories for clinical use. We sought to characterize the potential value of multigene PGx testing among individuals hospitalized with COVID‐19 in the United States. We performed a cross‐sectional analysis of electronic health records from consecutive individuals hospitalized with COVID‐19 at a large, urban academic health system. We characterized medication orders, focusing on medications with actionable PGx guidance related to 14 commonly assayed genes (CYP2C19, CYP2C9, CYP2D6, CYP3A5, DPYD, G6PD, HLA‐A, HLA‐B, IFNL3, NUDT15, SLCO1B1, TPMT, UGT1A1, and VKORC1). A simulation analysis combined medication data with population phenotype frequencies to estimate how many treatment modifications would be enabled if multigene PGx results were available. Sixty‐four unique medications with PGx guidance were ordered at least once in the cohort (n = 1,852, mean age 60.1 years). Nearly nine in 10 individuals (89.7%) had at least one order for a medication with PGx guidance and 427 patients (23.1%) had orders for 4 or more actionable medications. Using a simulation, we estimated that 17 treatment modifications per 100 patients would be enabled if PGx results were available. The genes CYP2D6 and CYP2C19 were responsible for the majority of treatment modifications, and the medications most often affected were ondansetron, oxycodone, and clopidogrel. PGx results would be relevant for nearly all individuals hospitalized with COVID‐19 and would provide the opportunity to improve clinical care.

BACKGROUND/PURPOSE: The U.S. has an alarming rate of firearm injuries. Racial disparities among victims and predictors of outcomes are not well established. Our objective was to assess costs, length of stay (LOS), and inpatient mortality among nonfatal and fatal pediatric firearm injuries that required hospitalization. METHODS: Pediatric (≤ 18 years of age) hospitalizations with a firearm injury discharge diagnosis were identified from the national Kids’ Inpatient Databases (KID) for 2006 through 2012. Firearm injury intent, weapon type, and hospitalization rates by racial groups were examined. Inpatient mortality, costs, and length of stay were examined using regression models. RESULTS: Of 15,211 hospitalizations, the majority of injuries were due to assault (60%) and the intentions of firearm injury differed by race (p < 0.001). The median cost per hospitalization was $10,159 (interquartile range: $5,071 to $20,565), totaling more than a quarter of a billion dollars. On regression analysis, Black (OR: 0.41; CI: 0.30–0.55) and Hispanic (OR: 0.47; CI: 0.34–0.66) patients were less likely to die than White patients. CONCLUSION: Pediatric firearm injury circumstances and survival vary by race with Whites being more likely to experience unintentional injury and suicide, while Blacks and Hispanics are more likely to experience inflicted injury.

Background One out of five patients with muscle-invasive bladder cancer undergo radical cystectomy—a guideline-recommended treatment. Previous studies have primarily evaluated patient characteristics associated with the use of radical cystectomy, ignoring potential nesting of data. Objective To determine the impact of patient, diagnosing urologist, and hospital characteristics on the variation in the use of radical cystectomy. Design, setting, and participants This is a retrospective cohort study using the Surveillance, Epidemiology, and End Results Registry (SEER)-Medicare linked database. Outcome measurements and statistical analysis A total of 7097 muscle-invasive bladder cancer patients and 4601 diagnosing urologists affiliated to 822 hospitals from January 1, 2002 to December 31, 2012 were analyzed. Multilevel logistic regression analyses were used to determine variation and factors associated with the use of radical cystectomy. Results and limitations Of the 7097 patients, only 27% underwent radical cystectomy. The intraclass correlation coefficient for variation in the use of radical cystectomy attributed to the hospital level was 4.3%. Higher radical cystectomy volume by diagnosing urologists (more than five vs zero to one surgery: odds ratio [OR], 1.27; 95% confidence interval [CI], 1.00–1.62) and hospitals (more than five vs zero to four surgeries: OR,1.48; 95% CI, 1.14–1.93) was associated with increased use of radical cystectomy. Patients diagnosed by female rather than male urologists were more likely to undergo radical cystectomy (OR, 1.32; 95% CI, 1.07–1.62). Conclusions We found that 4.3% variation in the use of radical cystectomy was attributed to the hospital level, leaving 95.7% variation in use unexplained. We identified significantly increased use among higher-volume and female diagnosing urologists. These findings support further investigation into measures beyond hospital volume, which largely impact the utilization of radical cystectomy. Patient summary In this large population-based study, we found that 4.3% of variation in the use of radical cystectomy was attributed to the hospital level, leaving 95.7% variation in use unexplained. Higher radical cystectomy volume of diagnosing urologists and female urologists were independently associated with increased use of radical cystectomy. These findings support further investigation into measures beyond hospital volume, which largely impact the utilization of radical cystectomy., In this large population-based study, we found that 4.3% of variation in the use of radical cystectomy was attributed to the hospital level, leaving 95.7% variation in use unexplained. Higher radical cystectomy volume of diagnosing urologists and female urologists were independently associated with increased use of radical cystectomy. These findings support further investigation into measures beyond hospital volume, which largely impact the utilization of radical cystectomy.

Objective Length of hospital stay for patients following radical cystectomy is an important determinant for improved quality of care. We sought to develop and validate a predictive model for length of hospital stay following radical cystectomy. Methods Patients aged 66 to 90 years diagnosed with clinical stage T2-4a muscle-invasive bladder cancer who underwent radical cystectomy were included from January 1, 2002 through December 31, 2011 using the Surveillance, Epidemiology, and End Results (SEER)-Medicare data. Linear regression analyses were used to develop and validate a predictive model for length of hospital stay. Results A total of 2,448 patients met inclusion criteria. After random assignment, 1,224 patients were included in the discovery cohort and 1,224 patients included in the validation cohort. The cohorts were well balanced with no significant difference in any of the preoperative variables. A best model was developed using marital status, Surveillance, Epidemiology, and End Results (SEER) region, clinical stage, Charlson comorbidity index, logarithm of hospital cystectomy volume, and use of neoadjuvant chemotherapy in a backward selection to predict the length of stay. There was robust internal validation (sum square error (SSE): 258.1 vs. predicted sum of squares (PRESS): 264.0 at SLS = 0.10), consistent with the external validation (average square error (ASE): discovery (0.248) vs. validation (0.258)) cohort. The strength of the model in predicting length of stay for the entire cohort was (R2 = 0.048). Conclusion In this large population-based study, we developed and validated a model to predict length of hospital stay following radical cystectomy. Identification of at-risk patients for prolonged hospital stay may aid in targeted interventions to reduce length of stay, improve quality of care, and decrease healthcare costs.

Objective To develop and validate a claims-based comorbidity score for patients undergoing major surgery, and compare its performance with established comorbidity scores. Data source Five percent Medicare data from 2007 to 2014. Study design Retrospective cohort study of patients aged ≥65 years undergoing six major operations (N = 99 250). Data collection One-year mortality was the primary outcome. Secondary outcomes were hospital mortality, 30-day mortality, 30-day readmission, and length of stay. The comorbidity score was developed in the derivation cohort (70 percent sample) using logistic regression model. The comorbidity score was calibrated and validated in the validation cohort (30 percent sample), and compared against the Charlson, Elixhauser, and Centers for Medicare and Medicaid Services Hierarchical Condition Categories (CMS-HCC) comorbidity scores using c-statistic, net reclassification improvement, and integrated discrimination improvement. Principal findings In the validation cohort, the surgery-specific comorbidity score was well calibrated and performed better than the Charlson, Elixhauser, and CMS-HCC comorbidity scores for all outcomes; the performance was comparable to the CMS-HCC for 30-day readmission. For example, the surgery-specific comorbidity score (c-statistic = 0.792; 95% CI, 0.785-0.799) had greater discrimination than the Charlson (c-statistic = 0.747; 95% CI, 0.739-0.755), Elixhauser (c-statistic = 0.747; 95% CI, 0.735-0.755), or CMS-HCC (c-statistic = 0.755; 95% CI, 0.747-0.763) scores in predicting 1-year mortality. The net reclassification improvement and integrated discrimination improvement were greater for surgery-specific comorbidity score compared to the Charlson, Elixhauser, and CMS-HCC scores. Conclusions Compared to commonly used comorbidity measures, a surgery-specific comorbidity score better predicted outcomes in the surgical population.

Summary Background Many individuals take long-term immunosuppressive medications. We evaluated whether these individuals have worse outcomes when hospitalised with COVID-19 compared with non-immunosuppressed individuals. Methods We conducted a retrospective cohort study using data from the National COVID Cohort Collaborative (N3C), the largest longitudinal electronic health record repository of patients in hospital with confirmed or suspected COVID-19 in the USA, between Jan 1, 2020, and June 11, 2021, within 42 health systems. We compared adults with immunosuppressive medications used before admission to adults without long-term immunosuppression. We considered immunosuppression overall, as well as by 15 classes of medication and three broad indications for immunosuppressive medicines. We used Fine and Gray's proportional subdistribution hazards models to estimate the hazard ratio (HR) for the risk of invasive mechanical ventilation, with the competing risk of death. We used Cox proportional hazards models to estimate HRs for in-hospital death. Models were adjusted using doubly robust propensity score methodology. Findings Among 231 830 potentially eligible adults in the N3C repository who were admitted to hospital with confirmed or suspected COVID-19 during the study period, 222 575 met the inclusion criteria (mean age 59 years [SD 19]; 111 269 [50%] male). The most common comorbidities were diabetes (23%), pulmonary disease (17%), and renal disease (13%). 16 494 (7%) patients had long-term immunosuppression with medications for diverse conditions, including rheumatological disease (33%), solid organ transplant (26%), or cancer (22%). In the propensity score matched cohort (including 12 841 immunosuppressed patients and 29 386 non-immunosuppressed patients), immunosuppression was associated with a reduced risk of invasive ventilation (HR 0·89, 95% CI 0·83–0·96) and there was no overall association between long-term immunosuppression and the risk of in-hospital death. None of the 15 medication classes examined were associated with an increased risk of invasive mechanical ventilation. Although there was no statistically significant association between most drugs and in-hospital death, increases were found with rituximab for rheumatological disease (1·72, 1·10–2·69) and for cancer (2·57, 1·86–3·56). Results were generally consistent across subgroup analyses that considered race and ethnicity or sex, as well as across sensitivity analyses that varied exposure, covariate, and outcome definitions. Interpretation Among this cohort, with the exception of rituximab, there was no increased risk of mechanical ventilation or in-hospital death for the rheumatological, antineoplastic, or antimetabolite therapies examined. Funding None.

Because of toxicities, benzodiazepines are not usually recommended in older adults. We therefore sought to describe the trends in benzodiazepine use in long-term care and examine the variation in benzodiazepine use among nursing homes.In this retrospective repeated cross-sectional analysis of Medicare Parts A, B, and D claims data linked to the Minimum Data Set from 2013 to 2018, we included long-term residents who stayed in a nursing home for at least one entire quarter of a calendar year in 2013-2018. The outcome was whether residents were prescribed a benzodiazepine drug for at least 30 days during each quarter stay. We use mixed effects logistic regression models to assess the variation in benzodiazepine use among nursing homes, adjusting for patient and nursing home characteristics.The cohort for the time trend analysis included 270,566 unique residents and 1,843,580 quarter stays for 2013-2018. Prescribing rates for short-acting benzodiazepines were stable over 2013-2016, then declined from 12.1% in 2016 to 10.6% in 2018. The rate of long-acting benzodiazepine use remained relatively steady at around 4% over 2013-2018. During 2017-2018, the variation among nursing homes in benzodiazepine use was 7.2% for short-acting vs. 9.3% for long-acting benzodiazepines, after controlling for resident characteristics.Prescribing for short-acting benzodiazepines in long-term care declined after 2016, while long-acting benzodiazepine use did not change. The variation in benzodiazepine use among nursing homes is substantial. Identifying factors that explain this variation may help in developing strategies for deprescribing benzodiazepines in nursing home residents.

Objective: Despite population-level increases in use of direct oral anticoagulants (DOACs) over the last decade, less is known about their use among individuals with cancer and non-valvular atrial fibrillation (NVAF). We quantified DOAC initiation and switching among such individuals. Methods: We used Surveillance, Epidemiology, and End Results (SEER)-Medicare data from 2009 to 2016 and included patients aged ≥66 years diagnosed with cancer (breast, bladder, colorectal, esophagus, lung, ovary, kidney, pancreas, prostate, stomach or uterus). We limited the cohort to continuously enrolled beneficiaries with newly diagnosed NVAF following cancer diagnosis (from 2010 to 2016) who did not have any oral anticoagulant use during the 12-months prior to their NVAF diagnosis. We evaluated the initiation of warfarin or DOACs within 3 months of the incident NVAF diagnosis. Among warfarin users, we determined switching rates to DOACs and among DOACs users, we determined switching rates to warfarin. Descriptive statistics were used for all the analyses. Results: Of 1,028,784 Medicare beneficiaries with cancer, 158,744 (15.4%) were diagnosed with atrial fibrillation. After applying all inclusion criteria, the final study cohort included 19,513 cancer patients diagnosed with incident NVAF. Lung (20.2%), Breast (19.2%), prostate (19.2%) and colorectal (16.0%) cancer accounted for over three-fourths of the cohort. Overall, 7,604 patients (39%) initiated oral anticoagulants. Among these patients, 4,223/7,604 (55.5%) and 3,381/7,604 (44.5%) initiated DOACs and warfarin, respectively. Patients who initiated DOACs had lower Charlson comorbidity score (1.0 ± 1.4 vs. 1.3 ± 1.5) and CHA 2 DS 2 -VASc score (4.4 ± 1.7 vs. 4.8 ± 1.7) compared to warfarin users. Initiation of DOACs varied by cancer type; for example, 13.6% (55/405) of patients with stomach cancer initiated DOACs, whereas 29.8% (1120/3755) of patients with prostate cancer initiated DOACs. Among patients who initiated any oral anticoagulants, the use of DOACs increased from 22% (110/501) in 2011 to 75.3% (1335/1772) in 2016, whereas warfarin use declined from 78% (391/501) to 24.7% (437/1772). The switching rate among warfarin initiators to DOACs (623/3381, 18.4%) was higher than the switching rate among DOACs initiators to warfarin (281/4223, 6.7%). Conclusion: Among cancer patients with newly diagnosed NVAF, the use of DOACs has markedly increased from 2011 to 2016, with a corresponding decline in the use of warfarin. Moreover, cancer patients are more likely to switch from warfarin to DOACs. Our findings highlight the dynamic life cycle of these products and the value of real-world assessments of their comparative safety and effectiveness among Medicare beneficiaries.

Objective: Post-hoc analysis of three pivotal clinical trials suggests no difference in risk of ischemic stroke or systemic embolism among cancer patients with atrial fibrillation treated with direct oral anticoagulants (DOACs) vs. warfarin. However, these studies were underpowered and also do not reflect the context of real-world use. We compared the effectiveness of DOACs versus warfarin for the risk of stroke or systemic embolism and all-cause death in patients with NVAF. Methods: We used Surveillance, Epidemiology, and End Results (SEER)-Medicare data from 2009 to 2016 and included patients aged ≥66 years diagnosed with cancer (breast, bladder, colorectal, esophagus, lung, ovary, kidney, pancreas, prostate, stomach or uterus) and NVAF. We limited the cohort to patients who newly initiated warfarin or DOACs (from 2010 to 2016) with no history of ischemic stroke or systemic embolism. The primary outcome was hospitalization due to ischemic stroke or systemic embolism and the secondary outcome was all-cause death. We used Fine and Gray’s competing risk model, while treating death as a competing risk, to determine the association of oral anticoagulants with the incidence of stroke or systemic embolism. We also adjusted the analysis using inverse probability of treatment weighted (IPTW). Additionally, an IPTW-adjusted Cox proportional hazards regression model was constructed for all-cause death. Results: Of 1,028,784 patients with cancer, 158,744 (15.4%) were diagnosed with atrial fibrillation. After applying all inclusion criteria, the final study cohort included 7,334 cancer patients diagnosed with incident NVAF who newly initiated warfarin or DOACs, of which 3,194 (43.6%) used warfarin and 4,140 (56.4%) used DOACs. The unadjusted rate of stroke or systemic embolism was similar among warfarin and DOACs users (1.20 vs. 1.32 cases per 100 person-years, p=0.27). In the IPTW weighted competing risk model, the use of DOACs was not associated with an increased risk of stroke or systemic embolism compared with warfarin users (Hazard Ratio [HR] 1.41, 95% confidence intervals [CI] 0.90-2.20). However, DOACs users had a significantly lower risk of all-cause death compared with warfarin users (HR 0.82, CI 0.74-0.91). Conclusion: Among cancer patients diagnosed with NVAF, DOACs had a similar risk for stroke or systemic embolism compared to warfarin, although DOAC use was associated with reduced risk of all-cause mortality.

BackgroundEffects of timing of Convalescent plasma (CP) administration on hospitalized COVID-19 patients are not established.MethodsWe used the National COVID Cohort Collaborative data to perform a retrospective cohort study of hospitalized COVID-19 patients in the United States between 07-01-2020 and 12-19-2020. We stratified patients based on day of CP administration (Day 0, 1, 2, 3 and 4) from COVID-19 diagnosis. We used 35 predictors to frame matched cohorts accounting for clinical and sociodemographic characteristics. We used competing risk survival models to examine the association between CP administration and length of hospital stay with in-hospital death as a competing risk performing Gray’s test on the cumulative incidence function and Cox’s regression on cause specific hazard ratios.ResultsIn a cohort of 4,003 hospitalized COVID-19 patients, 197 (4.9%) received CP within the first 5 days following COVID-19 diagnosis. After adjusting for potential confounding variables, there were no statistically significant associations between day of CP administration and length of hospital stay. Day 0 CP administration signallled lower mortality but was not statistically significant (HR 0.45 [0.19-1.03]).ConclusionsWe found no association between the timing of CP administration and length of stay among hospitalized COVID-19 patients.

Diagnosis-related group (DRG) migration is defined as the reassignment of colectomy patients from DRG 331 to 330 based exclusively on postoperative complications. Strategic and comparative application of this metric has the potential to demonstrate baseline and excessive rates of complications related directly to patient care differences across institutions. The aim of this study was to report the variability of DRG migration across United States hospitals and its impact on overall cost and length of stay (LOS). This study investigated the variability of DRG migration rates across United States hospitals polling 5 per cent of the national Medicare data. The study end-points were total cost, LOS, and DRG migration rate. Hospitals were classified into tertiles for low (0.1–16.6%), moderate (16.7–23.0%), and high (23.1–83.3%) DRG migration rates. The study included 5120 patients from 615 hospitals. DRG migration rates for hospitals ranged from 0.1 per cent to 83.3 per cent, with 157 in the low, 183 in the moderate, and 364 in the high tertile. DRG migration resulted in a progressively increased LOS and hospital costs from the lowest to highest tertile. Several diagnoses were identified which are suggestive of failure to integrate evidence-based processes of care across the tertiles. The data confirm a wide variation in DRG migration rates from DRG 331 to 330 based only on postoperative complications. These ranges allow for the potential definition of both best practice, and opportunities for quality improvement with respect to postoperative complications, identification of hospital outliers, and the economics of care as part of a value-based care program.

Background It is unclear whether chronic use of immunosuppressive drugs worsens or improves the severity of coronavirus disease 2019 (COVID-19), with plausible mechanisms for both. Methods Retrospective cohort study in 2121 consecutive adults with acute inpatient hospital admission between 4 March and 29 August 2020 with confirmed or suspected COVID-19 in a large academic health system, with adjustment for confounding with propensity score–derived stabilized inverse probability of treatment weights. Chronic immunosuppression was defined as prescriptions for immunosuppressive drugs current at the time of admission. Outcomes included mechanical ventilation, in-hospital mortality, and length of stay. Results There were 2121 patients admitted with laboratory-confirmed (1967, 93%) or suspected (154, 7%) COVID-19 during the study period, with a median age of 55 years (interquartile range, 40–67). Of these, 108 (5%) were classified as immunosuppressed before COVID-19, primarily with prednisone (>7.5 mg/day), tacrolimus, or mycophenolate mofetil. Among the entire cohort, 311 (15%) received mechanical ventilation; the median (interquartile range) length of stay was 5.2 (2.5–10.6) days, and 1927 (91%) survived to discharge. After adjustment, there were no significant differences in the risk of mechanical ventilation (hazard ratio [HR], .79; 95% confidence interval [CI], .46–1.35), in-hospital mortality (HR, .66; 95% CI, .28–1.55), or length of stay (HR, 1.16; 95% CI, .92–1.47) among individuals with immunosuppression and counterparts. Conclusions Chronic use of immunosuppressive drugs was neither associated with worse nor better clinical outcomes among adults hospitalized with COVID-19 in one US health system., Among adults with confirmed or suspected coronavirus disease 2019 (COVID-19), chronic use of immunosuppressive drugs was neither associated with worse nor better clinical outcomes such as mechanical ventilation, in-hospital mortality, or length of stay.

OBJECTIVE To determine the respective associations of premorbid glucagon-like peptide-1 receptor agonist (GLP1-RA) and sodium–glucose cotransporter 2 inhibitor (SGLT2i) use, compared with premorbid dipeptidyl peptidase 4 inhibitor (DPP4i) use, with severity of outcomes in the setting of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. RESEARCH DESIGN AND METHODS We analyzed observational data from SARS-CoV-2–positive adults in the National COVID Cohort Collaborative (N3C), a multicenter, longitudinal U.S. cohort (January 2018–February 2021), with a prescription for GLP1-RA, SGLT2i, or DPP4i within 24 months of positive SARS-CoV-2 PCR test. The primary outcome was 60-day mortality, measured from positive SARS-CoV-2 test date. Secondary outcomes were total mortality during the observation period and emergency room visits, hospitalization, and mechanical ventilation within 14 days. Associations were quantified with odds ratios (ORs) estimated with targeted maximum likelihood estimation using a super learner approach, accounting for baseline characteristics. RESULTS The study included 12,446 individuals (53.4% female, 62.5% White, mean ± SD age 58.6 ± 13.1 years). The 60-day mortality was 3.11% (387 of 12,446), with 2.06% (138 of 6,692) for GLP1-RA use, 2.32% (85 of 3,665) for SGLT2i use, and 5.67% (199 of 3,511) for DPP4i use. Both GLP1-RA and SGLT2i use were associated with lower 60-day mortality compared with DPP4i use (OR 0.54 [95% CI 0.37–0.80] and 0.66 [0.50–0.86], respectively). Use of both medications was also associated with decreased total mortality, emergency room visits, and hospitalizations. CONCLUSIONS Among SARS-CoV-2–positive adults, premorbid GLP1-RA and SGLT2i use, compared with DPP4i use, was associated with lower odds of mortality and other adverse outcomes, although DPP4i users were older and generally sicker.

The increased hospital mortality rates from non-SARS-CoV-2 causes during the SARS-CoV-2 pandemic are incompletely characterized.To describe changes in mortality rates after hospitalization for non-SARS-CoV-2 conditions during the COVID-19 pandemic and how mortality varies by characteristics of the admission and hospital.Retrospective cohort study from January 2019 through September 2021 using 100% of national Medicare claims, including 4626 US hospitals. Participants included 8 448 758 individuals with non-COVID-19 medical admissions with fee-for-service Medicare insurance.Outcome was mortality in the 30 days after admission with adjusted odds generated from a 3-level (admission, hospital, and county) logistic regression model that included diagnosis, demographic variables, comorbidities, hospital characteristics, and hospital prevalence of SARS-CoV-2.There were 8 448 758 non-SARS-CoV-2 medical admissions in 2019 and from April 2020 to September 2021 (mean [SD] age, 73.66 [12.88] years; 52.82% women; 821 569 [11.87%] Black, 438 453 [6.34%] Hispanic, 5 351 956 [77.35%] White, and 307 218 [4.44%] categorized as other). Mortality in the 30 days after admission increased from 9.43% in 2019 to 11.48% from April 1, 2020, to March 31, 2021 (odds ratio [OR], 1.20; 95% CI, 1.19-1.21) in multilevel logistic regression analyses including admission and hospital characteristics. The increase in mortality was maintained throughout the first 18 months of the pandemic and varied by race and ethnicity (OR, 1.27; 95% CI, 1.23-1.30 for Black enrollees; OR, 1.25; 95% CI, 1.23-1.27 for Hispanic enrollees; and OR, 1.18; 95% CI, 1.17-1.19 for White enrollees); Medicaid eligibility (OR, 1.25; 95% CI, 1.24-1.27 for Medicaid eligible vs OR, 1.18; 95% CI, 1.16-1.18 for noneligible); and hospital quality score, measured on a scale of 1 to 5 stars with 1 being the worst and 5 being the best (OR, 1.27; 95% CI, 1.22-1.31 for 1 star vs OR, 1.11; 95% CI, 1.08-1.15 for 5 stars). Greater hospital prevalence of SARS-CoV-2 was associated with greater increases in odds of death from the prepandemic period to the pandemic period; for example, comparing mortality in October through December 2020 with October through December 2019, the OR was 1.44 (95% CI, 1.39-1.49) for hospitals in the top quartile of SARS-CoV-2 admissions vs an OR of 1.19 (95% CI, 1.16-1.22) for admissions to hospitals in the lowest quartile. This association was mostly limited to admissions with high-severity diagnoses.The prolonged elevation in mortality rates after hospital admission in 2020 and 2021 for non-SARS-CoV-2 diagnoses contrasts with reports of improvement in hospital mortality during 2020 for SARS-CoV-2. The results of this cohort study suggest that, with the continued impact of SARS-CoV-2, it is important to implement interventions to improve access to high-quality hospital care for those with non-SARS-CoV-2 diseases.

OBJECTIVE To investigate the time course of anticholinergic drug use in nursing home residents and assess if any temporal change in anticholinergic use varied by nursing home quality rating. DESIGN Retrospective repeated cross-sectional analysis of Medicare enrollment, Parts A, B, and D, claims data linked to the Minimum Data Set from 2009 to 2017. SETTING Medicare-certified nursing homes. PARTICIPANTS Long-term residents 65 years or older with nursing home stay of at least 100 consecutive days within a given calendar year. MEASUREMENTS Estimates of anticholinergic drug prescription rates between 2009 and 2017 were based on a binary variable indicating whether a resident received a drug with high anticholinergic activity, as defined by the Anticholinergic Cognitive Burden scale, for at least 1 day during the initial 100 consecutive days of nursing home stay in a given calendar year. We used mixed effects logistic regression models to determine adjusted rates of anticholinergic use each year and test the interaction between nursing home quality rating and year, while adjusting for patient and nursing home characteristics. RESULTS The cohort included 786,858 100-day nursing home stays (299,354 unique residents) in 6,703 nursing homes for the years 2009 to 2017. Prescription rates were stable at approximately 34% to 35% between 2009 and 2011, then gradually decreased to 24.3% in 2017 (P

ObjectivesThe coronavirus disease 2019 (COVID-19) pandemic has prompted many initiatives to identify safe and efficacious treatments, yet little is known regarding where early efforts have focused. We aimed to characterise registered clinical trials assessing drugs or plasma treatments for COVID-19.Design, setting and participantsCross-sectional analysis of clinical trials for the treatment of COVID-19 that were registered in the USA or in countries contributing to the WHO’s International Clinical Trials Registry Platform. Relevant trial entries of drugs or plasma were downloaded on 26 March 2020, deduplicated, verified with reviews of major medical journals and WHO websites and independently analysed by two reviewers.Main outcome(s)Trial intervention, sponsorship, critical design elements and specified outcomesResultsOverall, 201 clinical trials were registered for testing the therapeutic benefits of 92 drugs or plasma, including 64 in monotherapy and 28 different combinations. Only eight (8.7%) products or combinations involved new molecular entities. The other test therapies had a wide range of prior medical uses, including as antivirals, antimalarials, immunosuppressants and oncology treatments. In 152 trials (75.7%), patients were randomised to treatment or comparator, including 55 trials with some form of blinding and 97 open-label studies. The 49 (24.4%) of trials without a randomised design included 29 single armed studies and 20 trials with some comparison group. Most trial designs featured multiple endpoints. Clinical endpoints were identified in 134 (66.7%) of trials and included COVID-19 symptoms, death, recovery, required intensive care and hospital discharge. Clinical scales were being used in 33 (16.4%) trials, most often measures of oxygenation and critical illness. Surrogate endpoints or biomarkers were studied in 88 (42.3%) of trials, primarily assays of viral load. Although the trials were initiated in more than 17 countries or regions, 100 (49.8%) were registered in China and 78 (37.8%) in the USA. Registered trials increased rapidly, with the number of registered trials doubling from 1 March to 26 March 2020.ConclusionsWhile accelerating morbidity and mortality from the COVID-19 pandemic has been paralleled by early and rapid clinical investigation, many trials lack features to optimise their scientific value. Global coordination and increased funding of high-quality research may help to maximise scientific progress in rapidly discovering safe and effective treatments.

Introduction Prior studies noted substantial costs associated with radical cystectomy, however, they lack surgical comparison to a less costly partial cystectomy. We compared costs associated with radical versus partial cystectomy. Methods A total of 2,305 patients aged 66-85 years diagnosed with clinical stage T2-4a muscle-invasive bladder cancer from January 1, 2002 through December 31, 2011 were included. Total Medicare costs within one year of diagnosis following radical versus partial cystectomy were compared using inverse probability of treatment-weighted propensity score models. Cox regression and competing risks analysis were used to determine overall and cancer-specific survival, respectively. Results Median total costs were not significantly different for radical than partial cystectomy in 90 days ($73,907 vs. $65,721; median difference $16,796, 95% CI $10,038 to $23,558), 180 days ($113,288 vs. $82,840; median difference $36,369, 95% CI $25,744 to $47,392), and 365 days ($143,831 vs. $107,359; median difference $34,628, 95% CI $17,819 to $53,558), respectively. Hospitalization, surgery, pathology/laboratory, pharmacy, and skilled nursing facility costs contributed largely to costs associated with either treatment. Patients who underwent partial cystectomy had similar overall survival but had worse cancer-specific survival (Hazard Ratio (HR) 1.45, 95% Confidence Interval (CI), 1.34-1.58, p Conclusions While treatments for bladder cancer are associated with substantial costs, we showed radical cystectomy had similar total costs when compared to partial cystectomy among patients with muscle-invasive bladder cancer. However, partial cystectomy resulted in worse cancer-specific survival further supporting radical cystectomy as a high-value surgical procedure for muscle-invasive bladder cancer.

INTRODUCTION AND OBJECTIVE:One out of five patients with muscle-invasive bladder cancer undergo radical cystectomy—a guideline-recommended treatment. Previous studies have primarily evaluated patie...

Objectives Our objective was to assess the incidence of Alzheimer's Disease and related dementia diagnosis following treatment for muscle-invasive bladder cancer and impact on survival outcomes. Materials and Methods A total of 4814 patients diagnosed with clinical stage T2-T4a, N0, M0 bladder cancer between January 1, 2002 to December 31, 2011 using the Surveillance, Epidemiology, and End Results (SEER)-Medicare database were identified. Alzheimer's disease and related dementia diagnosis was identified using International Statistical Classification of Disease-Ninth Edition outpatient and inpatient codes. Incidence of dementia following treatment were calculated and reported as dementia cases per 10,000 person-years. Cox proportional hazards models were used to assess the impact of dementia on survival outcomes. Results Of the 4814 patients, 2403 (49.9%) underwent radical cystectomy (RC) and 2411 (50.1%) underwent radiotherapy (RTX) and/or chemotherapy (CTX). Overall, 837 (17.4%) patients developed Alzheimer's disease and related dementia following bladder cancer treatment. There was no significant difference in the incidence of Alzheimer's disease and related dementia following either treatment. Patients diagnosed with Alzheimer's disease and related dementia had worse overall (Hazard Ratio (HR), 2.64; 95% Confidence Interval (CI), 2.41–2.89) and cancer-specific (HR, 2.45; 95% CI, 2.18–2.76) survival than those without a dementia diagnosis following treatment. Conclusion While we observed no difference in new-onset Alzheimer's disease and related dementia diagnosis following RC or RTX and/or CTX, patients with a Alzheimer's and related dementia diagnosis was associated with worse overall and cancer-specific survival. These findings have important implications for screening and the development of targeted interventions for improving outcomes in older adults following complex cancer treatments, as observed in this bladder cancer population.

OBJECTIVE: Current information on opioid use in nursing home residents, particularly those with dementia, is unknown. We examined the temporal trends in opioid use by dementia severity and the association of dementia severity with opioid use in long-term care nursing home residents. DESIGN: Repeated measures cross-sectional study SETTING: Long-term care nursing homes PARTICIPANTS: Using 20% Minimum Data Set (MDS) and Medicare claims from 2011–2017, we included long-term care residents (n=734,739) from each year who had 120 days of consecutive stay. In a secondary analysis, we included residents who had an emergency room visit for a fracture (n=12,927). MEASUREMENTS: Dementia was classified as no, mild, moderate and severe based on the first MDS assessment each year. In the 120 days of nursing home stay, opioid use was measured as any, prolonged (>90 days) and high-dose (≥90 morphine milligram equivalent dose/day). For residents with a fracture, opioid use was measured within 7 days after emergency room discharge. Association of dementia severity with opioid use was evaluated using logistic regression. RESULTS: Overall, any opioid use declined by 8.4% (35.2% to 32.2%, p

Background Diagnosis-Related Group (DRG) migration, DRG 331 to 330, is defined by the assignment to a higher cost DRG due only to post admission comorbidity or complications (CC). Methods We assessed the 5% national Medicare data set (2011–2014) for colectomy (DRG's 331/330), excluding present on admission CC's and selecting patients with one or more CC's post-admission to define the impact on payments, cost, and length of stay (LOS). Results The incidence of DRG migration was 14.2%. This was associated with statistically significant increases in payments, hospital cost, and LOS compared to DRG 331 patients. Conclusions When DRG migration rate was extrapolated to the entire at risk population, the results were an increase of Centers for Medicare and Medicaid Services (CMS) cost by $98 million, hospital cost by $418 million, and excess hospital days equaling 68,669 days. These negative outcomes represent potentially unnecessary variations in the processes of care, and therefore a unique economic concept defining inefficient surgical care.

Background This study was designed to adapt the Elixhauser comorbidity index for 4 cancer-specific populations (breast, prostate, lung, and colorectal) and compare 3 versions of the Elixhauser comorbidity score (individual comorbidities, summary comorbidity score, and cancer-specific summary comorbidity score) with 3 versions of the Charlson comorbidity score for predicting 2-year survival with 4 types of cancer. Methods This cohort study used Texas Cancer Registry-linked Medicare data from 2005 to 2011 for older patients diagnosed with breast (n = 19,082), prostate (n = 23,044), lung (n = 26,047), or colorectal cancer (n = 16,693). For each cancer cohort, the data were split into training and validation cohorts. In the training cohort, competing risk regression was used to model the association of Elixhauser comorbidities with 2-year noncancer mortality, and cancer-specific weights were derived for each comorbidity. In the validation cohort, competing risk regression was used to compare 3 versions of the Elixhauser comorbidity score with 3 versions of the Charlson comorbidity score. Model performance was evaluated with c statistics. Results The 2-year noncancer mortality rates were 14.5% (lung cancer), 11.5% (colorectal cancer), 5.7% (breast cancer), and 4.1% (prostate cancer). Cancer-specific Elixhauser comorbidity scores (c = 0.773 for breast cancer, c = 0.772 for prostate cancer, c = 0.579 for lung cancer, and c = 0.680 for colorectal cancer) performed slightly better than cancer-specific Charlson comorbidity scores (ie, the National Cancer Institute combined index; c = 0.762 for breast cancer, c = 0.767 for prostate cancer, c = 0.578 for lung cancer, and c = 0.674 for colorectal cancer). Individual Elixhauser comorbidities performed best (c = 0.779 for breast cancer, c = 0.783 for prostate cancer, c = 0.587 for lung cancer, and c = 0.687 for colorectal cancer). Conclusions The cancer-specific Elixhauser comorbidity score performed as well as or slightly better than the cancer-specific Charlson comorbidity score in predicting 2-year survival. If the sample size permits, using individual Elixhauser comorbidities may be the best way to control for confounding in cancer outcomes research. Cancer 2018;124:2018-25. © 2018 American Cancer Society.

AIM The objectives were to determine trends in the use of chemotherapy as the initial treatment and to evaluate the comparative effectiveness of initial chemotherapy vs resection of the primary tumour on survival (intention-to-treat analysis) in Stage IV colorectal cancer (CRC). METHOD This cohort study used 2000-2011 data from the Surveillance, Epidemiology, and End Results (SEER)-Medicare linked database, including patients ≥ 66 years of age presenting with Stage IV CRC. Cox proportional hazards models and instrumental variable analysis were used to compare the effectiveness of chemotherapy as the initial treatment with resection of the primary tumour as the initial treatment, with 2-year survival as the end point. RESULTS The use of chemotherapy as the first treatment increased over time, from 26.8% in 2001 to 46.9% in 2009 (P

BACKGROUND This study investigated cost-related medication nonadherence among survivors of adolescent and young adult cancer and a comparison group in the United States. METHODS A cross-sectional analysis of the 2013 to 2015 National Health Interview Survey was performed. N=953 patients who were diagnosed with cancer between the ages of 15 and 39 years were identified, and a comparison group was created using propensity scores. Cost-related medication nonadherence was determined by individuals' report of skipping medication, taking less medication, or delaying filling medication to save money in the previous year. Covariates included demographics, insurance status, financial factors (eg, out-of-pocket health care expenditures), and health-related factors (eg, comorbidity and mental distress). Chi-square tests were used to compare nonadherence between survivors and the comparison group. Logistic regressions identified covariates associated with nonadherence. RESULTS Survivors were more likely to report nonadherence than the comparison group (23.8% vs 14.3%; P

The ACGME case log is one of the primary metrics used to determine resident competency; it is unclear if this is an accurate reflection of the residents' role and participation.Residents and faculty were independently administered 16-question surveys following each case over a three-week period. The main outcome was agreement between resident and faculty on resident role and percent of the case performed by the resident.Matched responses were collected for 87 cases. Agreement on percent performed occurred in 61% of cases, on role in 63%, and on both in 47%. Disagreement was more often due to resident perception they performed more of the case. Faculty with10 years experience were more likely to have disagreement compared to faculty with ≥10 years (p = 0.009).There was a high degree of disagreement between faculty and residents regarding percent of the case performed and role. Accurate understanding of participation and competency is vital for accrediting institutions and for resident self-assessment meriting further study of the causes for this disagreement to improve training and evaluation.

INTRODUCTION: Resident satisfaction is a key performance metric for surgery programs; we studied factors influencing resident satisfaction in operative cases, and the concordance of faculty and resident perceptions on these factors. METHODS: Resident and faculty were separately queried on satisfaction immediately following operative cases. Statistical significance of the associations between resident and faculty satisfaction and case-related factors were tested by Chi-square or Fisher’s exact test. RESULTS: Residents and faculty were very satisfied in 56/87 (64%) and 36/87 (41%) of cases respectively. Resident satisfaction was associated with their perceived role as surgeon (p50% of the case (p

Objectives To create a risk index (Mexican American Dementia Nomogram (MADeN)) that predicts dementia over a 10-year period for Mexican Americans aged 65 and older. Design Retrospective cohort study with longitudinal analysis. Setting Texas, New Mexico, Colorado, Arizona, and California. Participants Hispanic Established Populations for the Epidemiologic Study of the Elderly (H-EPESE) participants (n = 1,739). Measurements Dementia was defined as a decline of three or more points per year on the Mini-Mental State Examination and inability to perform one or more daily activities. Candidate risk factors included demographic characteristics, measures of social engagement, self-reported health conditions, ability to perform daily activities, and physical activity. Results The MADeN comprised the following risk factors: age, sex, education, not having friends to count on, not attending community events, diabetes mellitus, feeling the blues, pain, impairment in instrumental activities of daily living, and unable to walk a half-mile. The area under the receiver operating characteristic curve was 0.74 (95% confidence interval (CI) = 0.70–0.78) and a score of 16 points or higher had a sensitivity of 0.65 (95% CI = 0.59–0.72) and specificity of 0.70 (95% CI = 0.67–0.73) in predicting dementia. Conclusion The MADeN was able to predict dementia in a population of older Mexican-American adults with moderate accuracy. It has the potential to identify older Mexican-American adults who may benefit from interventions to reduce dementia risk and to educate this population about risk factors for dementia.