Factors associated with unplanned readmissions and costs following resection of brain metastases in the United States
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SUBMITTER: Tonse R
PROVIDER: S-EPMC8589950 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Introduction: Following the resection of brain metastases (BM), whole-brain radiotherapy (WBRT) is a long-established standard of care. Its position was recently challenged by the less toxic single-session radiosurgery (SRS) or fractionated stereotactic radiotherapy (FSRT) of the resection cavity, reducing dose exposure of the healthy brain. Patients and Methods: We analyzed 101 patients treated with either SRS/FSRT (n = 50) or WBRT (n = 51) following BM resection over a 5-year period. Propensity score adjustment was done for age, total number of BM, timepoint of BM diagnosis, controlled primary and extracranial metastases. A Cox Proportional Hazards model with univariate and multivariate analysis was fitted for overall survival (OS), local control (LC) and distant brain control (DBC). Results: Median patient age was 61 (interquartile range, IQR: 56-67) years and the most common histology was non-small cell lung cancer, followed by breast cancer. 38% of the patients had additional unresected BM. Twenty-four patients received SRS, 26 patients received FSRT and 51 patients received WBRT. Median OS in the SRS/FSRT subgroup was not reached (IQR NA-16.7 months) vs. 12.6 months (IQR 21.3-4.4) in the WBRT subgroup (hazard ratio, HR 3.3, 95%-CI: [1.5; 7.2] p < 0.002). Twelve-months LC-probability was 94.9% (95%-CI: [88.3; 100.0]) in the SRS subgroup vs. 81.7% (95%-CI: [66.6; 100.0]) in the WBRT subgroup (HR 0.2, 95%-CI: [0.01; 0.9] p = 0.037). Twelve-months DBC-probabilities were 65.0% (95%-CI: [50.8; 83.0]) and 58.8% (95%-CI: [42.9; 80.7]), respectively (HR 1.4, 95%-CI: [0.7; 2.7] p = 0.401). In propensity score-adjusted multivariate analysis, incomplete resection negatively impacted OS (HR 3.9, 95%-CI: [2.0;7.4], p < 0.001) and LC (HR 5.4, 95%-CI: [1.3; 21.9], p = 0.018). Excellent clinical performance (HR 0.4, 95%-CI: [0.2; 0.9], p = 0.030) and better graded prognostic assessment (GPA) score (HR 0.4, 95%-CI: [0.2; 1.0], p = 0.040) were prognostic of superior OS. A higher number of BM was associated with a greater risk of developing new distant BM (HR 5.6, 95%-CI: [1.0; 30.4], p = 0.048). In subgroup analysis, larger cavity volume (HR 1.1, 95%-CI: [1.0; 1.3], p = 0.033) and incomplete resection (HR 12.0, 95%-CI: [1.2; 118.3], p = 0.033) were associated with inferior LC following SRS/FSRT. Conclusion: This is the first propensity score-adjusted direct comparison of SRS/FSRT and WBRT following the resection of BM. Patients receiving SRS/FSRT showed longer OS and LC compared to WBRT. Future analyses will address the optimal choice of safety margin, dose and fractionation for postoperative stereotactic RT of the resection cavity.
| S-EPMC7232539 | biostudies-literature
Project description:Hospital readmissions following an acute myocardial infarction (MI) are associated with increased mortality and morbidity. The aim of this study was to investigate if there is a significant association between specific mental health disorders (MHD) and risk of hospital readmission after an index hospitalization for acute MI. We analyzed the U.S. National Readmission Database for adult acute MI hospitalizations from 2016 to 2017. Co-morbid diagnoses of MHD were obtained using appropriate ICD-10-CM diagnostic codes. The primary outcome of interest was 30-day all-cause unplanned readmission. Cox-regression analysis was used to identify the association of various MHD and risk of 30-day readmission adjusted for demographics, medical and cardiac comorbidities, and coronary revascularization. We identified a total of 1,045,752 hospitalizations for acute MI; patients had mean age of 67 ± 13 years with 37.6% female. The prevalence of any MHD was 15.0 ± 0.9%. After adjusting for potential confounders, comorbid diagnosis of major depression [HR 1.11 (95% CI 1.07-1.15)], bipolar disorders [1.32 (1.19-1.45)], anxiety disorders [1.09 (1.05-1.13)] and schizophrenia/other psychotic disorders [1.56 (1.43-1.69)] were independently associated with higher risk of 30-day readmission compared to those with no comorbid MHD. We conclude that MHD are significantly associated with a higher independent risk of 30-day all-cause hospital readmissions among acute MI hospitalizations.
| S-EPMC8885687 | biostudies-literature
Project description:ObjectivesPatients undergoing lung resection are at risk of perioperative complications, many of which necessitate unplanned critical care unit admission in the postoperative period. We sought to characterize this population, providing an up-to-date estimate of the incidence of unplanned critical care admission, and to assess critical care and hospital stay, resource use, mortality, and outcomes.MethodsA multicenter retrospective cohort study of patients undergoing lung resection in participating UK hospitals over 2 years. A comprehensive dataset was recorded for each critical care admission (defined as the need for intubation and mechanical ventilation and/or renal replacement therapy), in addition to a simplified dataset in all patients undergoing lung resection during the study period. Multivariable regression analysis was used to identify factors independently associated with critical care outcome.ResultsA total of 11,208 patients underwent lung resection in 16 collaborating centers during the study period, and 253 patients (2.3%) required unplanned critical care admission with a median duration of stay of 13 (4-28) days. The predominant indication for admission was respiratory failure (68.1%), with 77.8% of patients admitted during the first 7 days following surgery. Eighty-seven (34.4%) died in critical care. On multivariable regression, only the diagnosis of right ventricular dysfunction and the need for both mechanical ventilation and renal-replacement therapy were independently associated with critical care survival; this model, however, had poor predictive value.ConclusionsAlthough resource-intensive and subject to prolonged stay, following unplanned admission to critical care after lung resection outcomes are good for many patients; 65.6% of patients survived to hospital discharge, and 62.7% were discharged to their own home.
| S-EPMC9390490 | biostudies-literature
Project description:BackgroundTotal joint replacements are high-volume and high-cost procedures that should be monitored for cost and quality control. Models that can identify patients at high risk of readmission might help reduce costs by suggesting who should be enrolled in preventive care programs. Previous models for risk prediction have relied on structured data of patients rather than clinical notes in electronic health records (EHRs). The former approach requires manual feature extraction by domain experts, which may limit the applicability of these models.ObjectiveThis study aims to develop and evaluate a machine learning model for predicting the risk of 30-day readmission following knee and hip arthroplasty procedures. The input data for these models come from raw EHRs. We empirically demonstrate that unstructured free-text notes contain a reasonably predictive signal for this task.MethodsWe performed a retrospective analysis of data from 7174 patients at Partners Healthcare collected between 2006 and 2016. These data were split into train, validation, and test sets. These data sets were used to build, validate, and test models to predict unplanned readmission within 30 days of hospital discharge. The proposed models made predictions on the basis of clinical notes, obviating the need for performing manual feature extraction by domain and machine learning experts. The notes that served as model inputs were written by physicians, nurses, pathologists, and others who diagnose and treat patients and may have their own predictions, even if these are not recorded.ResultsThe proposed models output readmission risk scores (propensities) for each patient. The best models (as selected on a development set) yielded an area under the receiver operating characteristic curve of 0.846 (95% CI 82.75-87.11) for hip and 0.822 (95% CI 80.94-86.22) for knee surgery, indicating reasonable discriminative ability.ConclusionsMachine learning models can predict which patients are at a high risk of readmission within 30 days following hip and knee arthroplasty procedures on the basis of notes in EHRs with reasonable discriminative power. Following further validation and empirical demonstration that the models realize predictive performance above that which clinical judgment may provide, such models may be used to build an automated decision support tool to help caretakers identify at-risk patients.
| S-EPMC7732713 | biostudies-literature
Project description:To determine the rate of unplanned PICU readmissions, examine the characteristics of index admissions associated with readmission, and compare outcomes of readmissions versus index admissions.Retrospective cohort analysis.Ninety North American PICUs that participated in the Virtual Pediatric Intensive Care Unit Systems.One hundred five thousand four hundred thirty-seven admissions between July 2009 and March 2011.None.Unplanned PICU readmission within 48 hours of index discharge was the primary outcome. Summary statistics, bivariate analyses, and mixed-effects logistic regression model with random effects for each hospital were performed.There were 1,161 readmissions (1.2%). The readmission rate varied among PICUs (0-3.3%), and acute respiratory (56%), infectious (35%), neurological (28%), and cardiovascular (20%) diagnoses were often present on readmission. Readmission risk increased in patients with two or more complex chronic conditions (adjusted odds ratio, 1.72; p < 0.001), unscheduled index admission (adjusted odds ratio, 1.37; p < 0.001), and transfer to an intermediate unit (adjusted odds ratio, 1.29; p = 0.004, compared with ward). Trauma patients had a decreased risk of readmission (adjusted odds ratio, 0.67; p = 0.003). Gender, race, insurance, age more than 6 months, perioperative status, and nighttime transfer were not associated with readmission. Compared with index admissions, readmissions had longer median PICU length of stay (3.1 vs 1.7 d, p < 0.001) and higher mortality (4% vs 2.5%, p = 0.002).Unplanned PICU readmissions were relatively uncommon, but were associated with worse outcomes. Several patient and admission characteristics were associated with readmission. These data help identify high-risk patient groups and inform risk-adjustment for standardized readmission rates.
| S-EPMC4327890 | biostudies-literature
Project description:OBJECTIVE:To synthesise evidence on risk factors associated with paediatric unplanned hospital readmissions (UHRs). DESIGN:Systematic review. DATA SOURCE:CINAHL, EMBASE (Ovid) and MEDLINE from 2000 to 2017. ELIGIBILITY CRITERIA:Studies published in English with full-text access and focused on paediatric All-cause, Surgical procedure and General medical condition related UHRs were included. DATA EXTRACTION AND SYNTHESIS:Characteristics of the included studies, examined variables and the statistically significant risk factors were extracted. Two reviewers independently assessed study quality based on six domains of potential bias. Pooling of extracted risk factors was not permitted due to heterogeneity of the included studies. Data were synthesised using content analysis and presented in narrative form. RESULTS:Thirty-six significant risk factors were extracted from the 44 included studies and presented under three health condition groupings. For All-cause UHRs, ethnicity, comorbidity and type of health insurance were the most frequently cited factors. For Surgical procedure related UHRs, specific surgical procedures, comorbidity, length of stay (LOS), age, the American Society of Anaesthesiologists class, postoperative complications, duration of procedure, type of health insurance and illness severity were cited more frequently. The four most cited risk factors associated with General medical condition related UHRs were comorbidity, age, health service usage prior to the index admission and LOS. CONCLUSIONS:This systematic review acknowledges the complexity of readmission risk prediction in paediatric populations. This review identified four risk factors across all three health condition groupings, namely comorbidity; public health insurance; longer LOS and patients<12 months or between 13-18 years. The identification of risk factors, however, depended on the variables examined by each of the included studies. Consideration should be taken into account when generalising reported risk factors to other institutions. This review highlights the need to develop a standardised set of measures to capture key hospital discharge variables that predict unplanned readmission among paediatric patients.
| S-EPMC6352831 | biostudies-literature
Project description:BackgroundTraumatic brain injury (TBI) is a serious public health problem in the United States. Each year, TBIs substantially contribute to health care costs, which vary by severity. This is important to consider given the variability in recovery time by severity.Research designThis study quantifies the annual incremental health care costs of nonfatal TBI in 2016 for the US population covered by a private health insurance, Medicaid, or Medicare health plan. This study uses MarketScan and defines severity with the abbreviated injury scale for the head and neck region. Nonfatal health care costs were compared by severity.ResultsThe estimated 2016 overall health care cost attributable to nonfatal TBI among MarketScan enrollees was $40.6 billion. Total estimated annual health care cost attributable to TBI for low severity TBIs during the first year postinjury were substantially higher than costs for middle and high severity TBIs among those with private health insurance and Medicaid.ConclusionsThis study presents economic burden estimates for TBI that underscore the importance of developing strategies to prevent TBIs, regardless of severity. Although middle and high severity TBIs were more costly at the individual level, low severity TBIs, and head injuries diagnosed as "head injury unspecified" resulted in higher total estimated annual health care costs attributable to TBI.
| S-EPMC8026675 | biostudies-literature
Project description:BackgroundPopulation-based estimates of the impact of gender throughout the whole course of brain metastases (BMs) at the time of diagnosis of systemic malignancies are insufficient. We aimed to discover the influence of gender on the presence of BMs in newly diagnosed malignancies and the survival of those patients on a population-based level.MethodsMidlife patients (40 years ≤ age ≤60 years) with newly diagnosed malignancies and BMs at the time of diagnosis were abstracted from the Surveillance, Epidemiology, and End Results (SEER) database of the National Cancer Institute. Clinical variables adjusted patient data. The LASSO regression was performed to exclude the possibility of collinearity. Univariable and multivariable logistic regression analyses were applied to find independent predictors for the presence of BMs, while univariable and multivariable Cox proportional hazard regression analyses were used to determine prognosticators of survival. K-M curves were used to perform the survival analysis.Result276,327 population-based samples met inclusion criteria between 2014 and 2016, and 5747 (2.08%) patients were diagnosed with BMs at the time of diagnosis of systematic malignancies. Among all midlife patients with cancer, 44.02% (121,634) were male, while 51.68% (2970) were male among patients with BMs at the time of diagnosis. The most frequent tumor type was breast cancer (23.11%), and lung cancer had the highest incidence proportion of BMs among the entire cohort (19.34%). The multivariable logistic regression model suggested that female (vs. male, odds ratio [OR] 1.07, 95% CI: 1.01-1.14, p < 0.001) was associated with a higher risk of the presence of BMs at the time of diagnosis. Moreover, in the multivariable Cox model for all-cause mortality in individuals with BMs at diagnosis, female (vs. male, hazard ratio [HR], 0.86, 95% CI, 0.80-0.92, p < 0.001) was shown to have a lower risk of decreased all-cause mortality.ConclusionThe middle-aged females were at increased risk of developing BMs, while the middle-aged males with BMs were at higher risk of having poorer survival.
| S-EPMC8855893 | biostudies-literature
Project description:BACKGROUND:Fragmentation of care, wherein a patient is readmitted to a hospital different from the initial point of care, has been shown to be associated with worse patient outcomes in other medical specialties. However, postpartum fragmentation of care has not been well characterized in obstetrics. OBJECTIVE:To characterize risk for and outcomes associated with fragmentation of postpartum readmissions wherein the readmitting hospital is different than the delivery hospital. METHODS:The 2010 to 2014 Nationwide Readmissions Database was used for this retrospective cohort study. Postpartum readmissions within 60 days of delivery hospitalization discharge for women aged 15-54 years were identified. The primary outcome, fragmentation, was defined as readmission to a different hospital than the delivery hospital. Hospital, demographic, medical, and obstetric factors associated with fragmented readmission were analyzed. Adjusted log-linear models were performed to analyze risk for readmission with adjusted risk ratios and 95% confidence intervals as the measures of effect. The associations between fragmentation and secondary outcomes including (1) length of stay >90th percentile, (2) hospitalization costs >90th percentile, and (3) severe maternal morbidity were determined. Whether specific indications for readmission such as hypertensive diseases of pregnancy, wound complications, and other conditions were associated with higher or lower risk for fragmentation was analyzed. RESULTS:From 2010 to 2014, 141,276 60-day postpartum readmissions were identified, of which 15% of readmissions (n = 21,789) occurred at a hospital different from where the delivery occurred. Evaluating individual readmission indications, fragmentation was less likely for hypertension (11.1%), wound complications (10.7%), and uterine infections (11.0%), and more likely for heart failure (28.6%), thromboembolism (28.4%), and upper respiratory infections (33.9%) (P < .01 for all). In the adjusted analysis, factors associated with fragmentation included public insurance compared to private insurance (Medicare: adjusted risk ratio, 1.68; 95% confidence interval, 1.52, 1.86; Medicaid: adjusted risk ratio, 1.28; 95% confidence interval, 1.24, 1.32). Fragmentation was associated with increased risk for severe maternal morbidity during readmissions in both unadjusted (relative risk, 1.84; 95% confidence interval, 1.79, 1.89) and adjusted (adjusted risk ratio, 1.81; 95% confidence interval, 1.76, 1.86) analyses. In adjusted analyses, fragmentation was also associated with increased risk for length of stay >90th percentile (relative risk, 1.48; 95% confidence interval, 1.42-1.54) and hospitalization costs >90th percentile (adjusted risk ratio, 1.74; 95% confidence interval, 1.67, 1.81). CONCLUSION:This study of nationwide estimates of postpartum fragmentation found discontinuity of postpartum care was associated with increased risk for severe morbidity, high costs, and long length of stay. Reduction of fragmentation may represent an important goal in overall efforts to improve postpartum care.
| S-EPMC7367706 | biostudies-literature
Project description:IntroductionPatients with end-stage kidney disease have a high risk of 30-day readmission to hospital. These readmissions are financially costly to health care systems and are associated with poor health-related quality of life. The objective of this study was to describe and analyze the frequency, causes, and predictors of 30-day potentially avoidable readmission to hospital in patients on hemodialysis.MethodsWe conducted a retrospective cohort study using the US Renal Data System data from January 1, 2008, to December 31, 2008. A total of 107,940 prevalent United States hemodialysis patients with 248,680 index hospital discharges were assessed for the main outcome of 30-day potentially avoidable readmission, as identified by a computerized algorithm.ResultsOf 83,209 30-day readmissions, 59,045 (70.1%) resulted in a 30-day potentially avoidable readmission. The geographic distribution of 30-day potentially avoidable readmission in the United States varied by state. Characteristics associated with 30-day potentially avoidable readmission included the following: younger age, shorter time on hemodialysis, at least 3 or more hospitalizations in preceding 12 months, black race, unemployed status, treatment at a for-profit facility, longer length of index hospital stay, and index hospitalizations that involved a surgical procedure. The 5-, 15-, and 30-day potentially avoidable readmission cumulative incidences were 6.0%, 15.1%, and 25.8%, respectively.ConclusionPatients with end-stage kidney disease on maintenance hemodialysis are at high risk for 30-day readmission to hospital, with nearly three-quarters (70.1%) of all 30-day readmissions being potentially avoidable. Research is warranted to develop cost-effective and transferrable interventions that improve care transitions from hospital to outpatient hemodialysis facility and reduce readmission risk for this vulnerable population.
| S-EPMC5932139 | biostudies-literature