Analysis of Clinical Criteria for Discharge Among Patients Hospitalized for COVID-19: Development and Validation of a Risk Prediction Model.

BACKGROUND: Patients hospitalized with COVID-19 can clinically deteriorate after a period of initial stability, making optimal timing of discharge a clinical and operational challenge. OBJECTIVE: To determine risks for post-discharge readmission and death among patients hospitalized with COVID-19. DESIGN: Multicenter retrospective observational cohort study, 2020-2021, with 30-day follow-up. PARTICIPANTS: Adults admitted for care of COVID-19 respiratory disease between March 2, 2020, and February 11, 2021, to one of 180 US hospitals affiliated with the HCA Healthcare system. MAIN MEASURES: Readmission to or death at an HCA hospital within 30 days of discharge was assessed. The area under the receiver operating characteristic curve (AUC) was calculated using an internal validation set (33% of the HCA cohort), and external validation was performed using similar data from six academic centers associated with a hospital medicine research network (HOMERuN). KEY RESULTS: The final HCA cohort included 62,195 patients (mean age 61.9 years, 51.9% male), of whom 4704 (7.6%) were readmitted or died within 30 days of discharge. Independent risk factors for death or readmission included fever within 72 h of discharge; tachypnea, tachycardia, or lack of improvement in oxygen requirement in the last 24 h; lymphopenia or thrombocytopenia at the time of discharge; being ≤ 7 days since first positive test for SARS-CoV-2; HOSPITAL readmission risk score ≥ 5; and several comorbidities. Inpatient treatment with remdesivir or anticoagulation were associated with lower odds. The model's AUC for the internal validation set was 0.73 (95% CI 0.71-0.74) and 0.66 (95% CI 0.64 to 0.67) for the external validation set. CONCLUSIONS: This large retrospective study identified several factors associated with post-discharge readmission or death in models which performed with good discrimination. Patients 7 or fewer days since test positivity and who demonstrate potentially reversible risk factors may benefit from delaying discharge until those risk factors resolve.

Patient-Physician Sex Discordance and "Before Medically Advised" Discharge from Hospital: A Population-Based Retrospective Cohort Study.

BACKGROUND: Patient-physician sex discordance (when patient sex does not match physician sex) has been associated with reduced clinical rapport and adverse outcomes including post-operative mortality and unplanned hospital readmission. It remains unknown whether patient-physician sex discordance is associated with "before medically advised" hospital discharge (BMA discharge; commonly known as discharge "against medical advice"). OBJECTIVE: To evaluate whether patient-physician sex discordance is associated with BMA discharge. DESIGN: Retrospective cohort study using 15 years (2002-2017) of linked population-based administrative health data for all non-elective, non-obstetrical acute care hospitalizations from British Columbia, Canada. PARTICIPANTS: All individuals with eligible hospitalizations during study interval. MAIN MEASURES: Exposure: patient-physician sex discordance. OUTCOMES: BMA discharge (primary), 30-day hospital readmission or death (secondary). RESULTS: We identified 1,926,118 eligible index hospitalizations, 2.6% of which ended in BMA discharge. Among male patients, sex discordance was associated with BMA discharge (crude rate, 4.0% vs 2.9%; adjusted odds ratio [aOR] 1.08; 95%CI 1.03-1.14; p = 0.003). Among female patients, sex discordance was not associated with BMA discharge (crude rate, 2.0% vs 2.3%; aOR 1.02; 95%CI 0.96-1.08; p = 0.557). Compared to patient-physician sex discordance, younger patient age, prior substance use, and prior BMA discharge all had stronger associations with BMA discharge. CONCLUSIONS: Patient-physician sex discordance was associated with a small increase in BMA discharge among male patients. This finding may reflect communication gaps, differences in the care provided by male and female physicians, discriminatory attitudes among male patients, or residual confounding. Improved communication and better treatment of pain and opioid withdrawal may reduce BMA discharge.

Practice patterns and complications of hysterectomy for invasive cervical cancer after the Laparoscopic Approach to Cervical Cancer trial.

BACKGROUND: After the publication of the Laparoscopic Approach to Cervical Cancer trial, the standard surgical approach for early-stage cervical cancer is open radical hysterectomy. Only limited data were available regarding whether the change to open abdominal hysterectomy observed after the Laparoscopic Approach to Cervical Cancer trial led to an increase in postoperative complication rates as a consequence of the decrease in the use of the minimally invasive approach. OBJECTIVE: This study aimed to analyze whether there was a correlation between the publication of the Laparoscopic Approach to Cervical Cancer trial and an increase in the 30-day complications associated with surgical treatment of invasive cervical cancer. STUDY DESIGN: Data from the American College of Surgeons National Surgical Quality Improvement Program were used to compare the results in the pre-Laparoscopic Approach to Cervical Cancer period (January 2016 to December 2017) vs the results in the post-Laparoscopic Approach to Cervical Cancer period (January 2019 to December 2020). The rates of each surgical approach (open abdominal or minimally invasive) hysterectomy for invasive cervical cancer during the 2 periods were assessed. Subsequently, 30-day major complication, minor complication, unplanned hospital readmission, and intra- or postoperative transfusion rates before and after the publication of the Laparoscopic Approach to Cervical Cancer trial were compared. RESULTS: Overall, 3024 patients undergoing either open abdominal hysterectomy or minimally invasive hysterectomy for invasive cervical cancer were included in the study. Of the patients, 1515 (50.1%) were treated in the pre-Laparoscopic Approach to Cervical Cancer period, and 1509 (49.9%) were treated in the post-Laparoscopic Approach to Cervical Cancer period. The rate of minimally invasive approaches decreased significantly from 75.6% (1145/1515) in the pre-Laparoscopic Approach to Cervical Cancer period to 41.1% (620/1509) in the post-Laparoscopic Approach to Cervical Cancer period, whereas the rate of open abdominal approach increased from 24.4% (370/1515) in the pre-Laparoscopic Approach to Cervical Cancer period to 58.9% (889/1509) in the post-Laparoscopic Approach to Cervical Cancer period (P<.001). The overall 30-day major complications remained stable between the pre-Laparoscopic Approach to Cervical Cancer period (85/1515 [5.6%]) and the post-Laparoscopic Approach to Cervical Cancer period (74/1509 [4.9%]) (adjusted odds ratio, 0.85; 95% confidence interval, 0.61-1.17). The overall 30-day minor complications were similar in the pre-Laparoscopic Approach to Cervical Cancer period (103/1515 [6.8%]) vs the post-Laparoscopic Approach to Cervical Cancer period (120/1509 [8.0%]) (adjusted odds ratio, 1.17; 95% confidence interval, 0.89-1.55). The unplanned hospital readmission rate remained stable during the pre-Laparoscopic Approach to Cervical Cancer period (7.9% per 30 person-days) and during the post-Laparoscopic Approach to Cervical Cancer period (6.3% per 30 person-days) (adjusted hazard ratio, 0.78; 95% confidence interval, 0.58-1.04)]. The intra- and postoperative transfusion rates increased significantly from 3.8% (58/1515) in the pre-Laparoscopic Approach to Cervical Cancer period to 6.7% (101/1509) in the post-Laparoscopic Approach to Cervical Cancer period (adjusted odds ratio, 1.79; 95% confidence interval, 1.27-2.53). CONCLUSION: This study observed a significant shift in the surgical approach for invasive cervical cancer after the publication of the Laparoscopic Approach to Cervical Cancer trial, with a reduction in the minimally invasive abdominal approach and an increase in the open abdominal approach. The change in surgical approach was not associated with an increase in the rate of 30-day major or minor complications and unplanned hospital readmission, although it was associated with an increase in the transfusion rate.

Frailty in patients with IDH-mutant gliomas: experience from a high-volume tumor center.

PURPOSE: Gliomas are increasingly diagnosed in an aging population, with treatment outcomes influenced by factors like tumor genetics and patient frailty. This study focused on IDH-mutant gliomas and assessed how frailty affects 30-day readmission and overall survival (OS). We aimed to address a gap in understanding the impact of frailty on this specific glioma subtype. METHODS: 136 patients with an IDH-mutant glioma between 2007 and 2021 were identified at our institution. High frailty was classified by scores ≥ 1 on the 5-factor modified frailty index (mFI-5) and ≥ 3 on the Charlson Comorbidity Index (CCI). Patient and tumor characteristics including age, sex, race, Karnofsky Performance Status (KPS), Body Mass Index (BMI), tumor type and location, type of operation, and therapy course were recorded. Outcomes measured included 30-day readmission and overall survival (OS). Analysis was conducted utilizing logistic regression and Kaplan-Meier curves. RESULTS: Of the 136 patients, 52 (38%) had high frailty: 18 with CCI ≥ 3, 34 with mFI-5 ≥ 1. High frailty correlated with increased BMI (CCI: 30.2, mFI-5: 30.1 kg/m2), more neurological deficits (CCI: 61%, mFI-5: 56%), and older age at surgery (CCI: 63, mFI-5: 48 years). Hospital readmission within 30 days occurred in 8 (5.9%) patients. Logistic regression indicated no significant difference in 30-day readmission rates (CCI: p = 0.30, mFI-5: p = 0.62) or median OS between high and low frailty groups. However, patients treated at our institution with newly diagnosed tumors with high mFI-5 had a 6.79 times higher adjusted death hazard than those with low mFI-5 (p = .049). CONCLUSION: Our analysis revealed that CCI and mFI-5 were not significantly associated with 30-day nor OS. However, in patients with non-recurrent tumors, there was a significant association of mFI-5 with OS. Further study of frailty with larger cohorts is warranted to enhance prognostication of outcome after neurosurgical treatment.

Assessing racial bias in healthcare predictive models: Practical lessons from an empirical evaluation of 30-day hospital readmission models.

OBJECTIVE: Despite increased availability of methodologies to identify algorithmic bias, the operationalization of bias evaluation for healthcare predictive models is still limited. Therefore, this study proposes a process for bias evaluation through an empirical assessment of common hospital readmission models. The process includes selecting bias measures, interpretation, determining disparity impact and potential mitigations. METHODS: This retrospective analysis evaluated racial bias of four common models predicting 30-day unplanned readmission (i.e., LACE Index, HOSPITAL Score, and the CMS readmission measure applied as is and retrained). The models were assessed using 2.4 million adult inpatient discharges in Maryland from 2016 to 2019. Fairness metrics that are model-agnostic, easy to compute, and interpretable were implemented and apprised to select the most appropriate bias measures. The impact of changing model's risk thresholds on these measures was further assessed to guide the selection of optimal thresholds to control and mitigate bias. RESULTS: Four bias measures were selected for the predictive task: zero-one-loss difference, false negative rate (FNR) parity, false positive rate (FPR) parity, and generalized entropy index. Based on these measures, the HOSPITAL score and the retrained CMS measure demonstrated the lowest racial bias. White patients showed a higher FNR while Black patients resulted in a higher FPR and zero-one-loss. As the models' risk threshold changed, trade-offs between models' fairness and overall performance were observed, and the assessment showed all models' default thresholds were reasonable for balancing accuracy and bias. CONCLUSIONS: This study proposes an Applied Framework to Assess Fairness of Predictive Models (AFAFPM) and demonstrates the process using 30-day hospital readmission model as the example. It suggests the feasibility of applying algorithmic bias assessment to determine optimized risk thresholds so that predictive models can be used more equitably and accurately. It is evident that a combination of qualitative and quantitative methods and a multidisciplinary team are necessary to identify, understand and respond to algorithm bias in real-world healthcare settings. Users should also apply multiple bias measures to ensure a more comprehensive, tailored, and balanced view. The results of bias measures, however, must be interpreted with caution and consider the larger operational, clinical, and policy context.

A Prospective Multimodal Education Intervention for Providers Does Not Increase Hepatic Encephalopathy Treatment Rates.

BACKGROUND: Over 50% of hospitalizations from hepatic encephalopathy (HE) are preventable, but patients often do not receive medical treatment. AIMS: To use a multimodal education intervention (MMEI) to increase HE treatment rates and to evaluate (1) trends in HE treatment, (2) predictors of receiving treatment, and (3) the impact of treatment on hospitalization outcomes. METHODS: Prospective single-center cohort study of patients hospitalized with HE from April 1, 2020-September 30, 2022. The first 15 months were a control ("pre-MMEI"), the subsequent 15 months (MMEI) included three phases: (1) prior authorization resources, (2) electronic order set, and (3) in-person provider education. Treatment included receiving any drug (lactulose or rifaximin), or combination therapy. Treatment rates pre- vs. post-MMEI were compared using logistic regression. RESULTS: 471 patients were included. There were lower odds of receiving any drug post-MMEI (p = 0.03). There was no difference in receiving combination therapy pre- or post-MMEI (p = 0.32). Predictors of receiving any drug included alcohol-related or cryptogenic cirrhosis (p's < 0.001), and the presence of ascites (p = 0.005) and/or portal hypertension (p = 0.003). The only significant predictor of not receiving any drug treatment was having autoimmune cirrhosis (p < 0.001). Patients seen by internal medicine (p = 0.01) or who were intoxicated (p = 0.02) were less likely to receive rifaximin. Any treatment was associated with higher 30-day liver disease-specific readmission (p < 0.001). CONCLUSION: This MMEI did not increase HE treatment rates, suggesting that alternative strategies are needed to identify and address barriers to treatment.

Can prediction models for hospital readmission be improved by incorporating patient-reported outcome measures? A systematic review and narrative synthesis.

PURPOSE: To investigate the roles, challenges, and implications of using patient-reported outcome measures (PROMs) in predicting the risk of hospital readmissions. METHODS: We systematically searched four bibliometric databases for peer-reviewed studies published in English between 1 January 2000 and 15 June 2023 and used validated PROMs to predict readmission risks for adult populations. Reported studies were analysed and narratively synthesised in accordance with the CHARMS and PRISMA guidelines. RESULTS: Of the 2858 abstracts reviewed, 23 studies met predefined eligibility criteria, representing diverse geographic regions and medical specialties. Among those, 19 identified the positive contributions of PROMs in predicting readmission risks. Seven studies utilised generic PROMs exclusively, eleven used generic and condition-specific PROMs, while 5 focussed solely on condition-specific PROMs. Logistic regression was the most used modelling approach, with 13 studies aiming at predicting 30-day all-cause readmission risks. The c-statistic, ranging from 0.54 to 0.84, was reported in 22/23 studies as a measure of model discrimination. Nine studies reported model calibration in addition to c-statistic. Thirteen studies detailed their approaches to dealing with missing data. CONCLUSION: Our study highlights the potential of PROMs to enhance predictive accuracy in readmission models, while acknowledging the diversity in data collection methods, readmission definitions, and model evaluation approaches. Recognizing that PROMs serve various purposes beyond readmission reduction, our study supports routine data collection and strategic integration of PROMs in healthcare practices to improve patient outcomes. To facilitate comparative analysis and broaden the use of PROMs in the prediction framework, it is imperative to consider the methodological aspects involved.

Impact of hospital-administered extended-release naltrexone on readmission rates for patients with alcohol use disorder.

BACKGROUND AND AIMS: Alcohol use disorder (AUD) is a persistent public health concern, contributing significantly to mortality and morbidity. This study aims to evaluate the impact of in-hospital extended-release naltrexone (XR-NTX) administration on alcohol-related outcomes. METHODS: This retrospective cohort study, conducted at an academic medical centre, included 141 adult patients with AUD who received XR-NTX between December 2020 and June 2021. Primary and secondary outcomes were assessed 90 days before and after XR-NTX administration to identify number of alcohol-related hospitalisations, emergency department (ED) visits and average length of hospital stay. Subgroup analyses assessed outcomes in high hospital utilisers and marginally housed or unhoused populations. RESULTS: There was a significant decrease in ED visits and length of hospital stay post XR-NTX and no significant difference in the number of rehospitalisations. Subgroup analysis showed significant reduction in hospital readmissions and ED visits among high hospital utilisers. Our sample was a predominantly middle-aged, male and white patient population. CONCLUSIONS: In-hospital initiation of XR-NTX for AUD was associated with a significant decrease in ED visits and length of hospital stay. While no significant impact on the number of hospitalisations was observed overall, there was a substantial reduction in hospital readmissions and ED visits among high utilisers. Our findings suggest the potential benefits of in-hospital XR-NTX, emphasising the need for further research to establish causal relationships, assess cost-effectiveness and explore effectiveness across diverse patient populations. Effective in-hospital interventions, such as XR-NTX, hold promise for improving patient outcomes and reducing the healthcare burden associated with AUD.

Utility of the LACE index to assess risk of mortality and readmission in patients with spinal infections.

Retrospective cohort study. To assess the utility of the LACE index for predicting death and readmission in patients with spinal infections (SI). SIs are severe conditions, and their incidence has increased in recent years. The LACE (Length of stay, Acuity of admission, Comorbidities, Emergency department visits) index quantifies the risk of mortality or unplanned readmission. It has not yet been validated for SIs. LACE indices were calculated for all adult patients who underwent surgery for spinal infection between 2012 and 2021. Data were collected from a single academic teaching hospital. Outcome measures included the LACE index, mortality, and readmission rate within 30 and 90 days. In total, 164 patients were analyzed. Mean age was 64.6 (± 15.1) years, 73 (45%) were female. Ten (6.1%) patients died within 30 days and 16 (9.8%) died within 90 days after discharge. Mean LACE indices were 13.4 (± 3.6) and 13.8 (± 3.0) for the deceased patients, compared to 11.0 (± 2.8) and 10.8 (± 2.8) for surviving patients (p = 0.01, p < 0.001), respectively. Thirty-seven (22.6%) patients were readmitted ≤ 30 days and 48 (29.3%) were readmitted ≤ 90 days. Readmitted patients had a significantly higher mean LACE index compared to non-readmitted patients (12.9 ± 2.1 vs. 10.6 ± 2.9, < 0.001 and 12.8 ± 2.3 vs. 10.4 ± 2.8, p < 0.001, respectively). ROC analysis for either death or readmission within 30 days estimated a cut-off LACE index of 12.0 points (area under the curve [AUC] 95% CI, 0.757 [0.681-0.833]) with a sensitivity of 70% and specificity of 69%. Patients with SI had high LACE indices that were associated with high mortality and readmission rates. The LACE index can be applied to this patient population to predict the risk of early death or unplanned readmission.

Evaluating Algorithmic Bias in 30-Day Hospital Readmission Models: Retrospective Analysis.

BACKGROUND: The adoption of predictive algorithms in health care comes with the potential for algorithmic bias, which could exacerbate existing disparities. Fairness metrics have been proposed to measure algorithmic bias, but their application to real-world tasks is limited. OBJECTIVE: This study aims to evaluate the algorithmic bias associated with the application of common 30-day hospital readmission models and assess the usefulness and interpretability of selected fairness metrics. METHODS: We used 10.6 million adult inpatient discharges from Maryland and Florida from 2016 to 2019 in this retrospective study. Models predicting 30-day hospital readmissions were evaluated: LACE Index, modified HOSPITAL score, and modified Centers for Medicare & Medicaid Services (CMS) readmission measure, which were applied as-is (using existing coefficients) and retrained (recalibrated with 50% of the data). Predictive performances and bias measures were evaluated for all, between Black and White populations, and between low- and other-income groups. Bias measures included the parity of false negative rate (FNR), false positive rate (FPR), 0-1 loss, and generalized entropy index. Racial bias represented by FNR and FPR differences was stratified to explore shifts in algorithmic bias in different populations. RESULTS: The retrained CMS model demonstrated the best predictive performance (area under the curve: 0.74 in Maryland and 0.68-0.70 in Florida), and the modified HOSPITAL score demonstrated the best calibration (Brier score: 0.16-0.19 in Maryland and 0.19-0.21 in Florida). Calibration was better in White (compared to Black) populations and other-income (compared to low-income) groups, and the area under the curve was higher or similar in the Black (compared to White) populations. The retrained CMS and modified HOSPITAL score had the lowest racial and income bias in Maryland. In Florida, both of these models overall had the lowest income bias and the modified HOSPITAL score showed the lowest racial bias. In both states, the White and higher-income populations showed a higher FNR, while the Black and low-income populations resulted in a higher FPR and a higher 0-1 loss. When stratified by hospital and population composition, these models demonstrated heterogeneous algorithmic bias in different contexts and populations. CONCLUSIONS: Caution must be taken when interpreting fairness measures' face value. A higher FNR or FPR could potentially reflect missed opportunities or wasted resources, but these measures could also reflect health care use patterns and gaps in care. Simply relying on the statistical notions of bias could obscure or underplay the causes of health disparity. The imperfect health data, analytic frameworks, and the underlying health systems must be carefully considered. Fairness measures can serve as a useful routine assessment to detect disparate model performances but are insufficient to inform mechanisms or policy changes. However, such an assessment is an important first step toward data-driven improvement to address existing health disparities.

Trends and outcomes of outpatient total shoulder arthroplasty after its removal from CMS's inpatient-only list.

BACKGROUND: In January 2021, the US Medicare program approved reimbursement of outpatient total shoulder arthroplasties (TSA), including anatomic and reverse TSAs. It remains unclear whether shifting TSAs from the inpatient to outpatient setting has affected clinical outcomes. Herein, we describe the rate of outpatient TSA growth and compare inpatient and outpatient TSA complications, readmissions, and mortality. METHODS: Medicare fee-for-service claims for 2019-2022Q1 were analyzed to identify the trends in outpatient TSAs and to compare 90-day postoperative complications, all-cause hospital readmissions, and mortality between outpatients and inpatients. Outpatient cases were defined as those discharged on the same day of the surgery. To reduce the COVID-19 pandemic's impact and selection bias, we excluded 2020Q2-Q4 data and used propensity scores to match 2021-2022Q1 outpatients with inpatients from the same period (the primary analysis) and from 2019-2020Q1 (the secondary analysis), respectively. We performed both propensity score-matched and -weighted multivariate analyses to compare outcomes between the two groups. Covariates included sociodemographics, preoperative diagnosis, comorbid conditions, the Hierarchical Condition Category risk score, prior year hospital/skilled nursing home admissions, annual surgeon volume, and hospital characteristics. RESULTS: Nationally, the proportion of outpatient TSAs increased from 3% (619) in 2019Q1 to 22% (3456) in 2021Q1 and 38% (6778) in 2022Q1. A total of 55,166 cases were identified for the primary analysis (14,540 outpatients and 40,576 inpatients). Overall, glenohumeral osteoarthritis was the most common indication for surgery (70.8%), followed by rotator cuff pathology (14.6%). The unadjusted rates of complications (1.3 vs 2.4%, P < .001), readmissions (3.7 vs 6.1%, P < .001), and mortality (0.2 vs 0.4%, P = .024) were significantly lower among outpatient TSAs than inpatient TSAs. Using 1:1 nearest matching, 12,703 patient pairs were identified. Propensity score-matched multivariate analyses showed similar rates of postoperative complications, hospital readmissions, and mortality between outpatients and inpatients. Propensity score-weighted multivariate analyses resulted in similar conclusions. The secondary analysis showed a lower hospital readmission rate in outpatients (odds ratio: 0.8, P < .001). CONCLUSIONS: There has been accelerated growth in outpatient TSAs since 2019. Outpatient and inpatient TSAs have similar rates of postoperative complication, hospital readmission, and mortality.

A Preoperative Risk Assessment Tool for Predicting Adverse Outcomes among Total Shoulder Arthroplasty Patients.

BACKGROUND: With the increased utilization of Total Shoulder Arthroplasty (TSA) in the outpatient setting, understanding the risk factors associated with complications and hospital readmissions becomes a more significant consideration. Prior developed assessment metrics in the literature either consisted of hard-to-implement tools or relied on postoperative data to guide decision-making. This study aimed to develop a preoperative risk assessment tool to help predict the risk of hospital readmission and other postoperative adverse outcomes. METHODS: We retrospectively evaluated the 2019-2022(Q2) Medicare fee-for-service inpatient and outpatient claims data to identify primary anatomic or reserve TSAs and to predict postoperative adverse outcomes within 90 days post-discharge, including all-cause hospital readmissions, postoperative complications, emergency room visits, and mortality. We screened 108 candidate predictors, including demographics, social determinants of health, TSA indications, prior 12-month hospital and skilled nursing home admissions, comorbidities measured by hierarchical conditional categories, and prior orthopedic device-related complications. We used two approaches to reduce the number of predictors based on 80% of the data: 1) the Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression and 2) the machine-learning-based cross-validation approach, with the resulting predictor sets being assessed in the remaining 20% of the data. A scoring system was created based on the final regression models' coefficients, and score cutoff points were determined for low, medium, and high-risk patients. RESULTS: A total of 208,634 TSA cases were included. There was a 6.8% hospital readmission rate with 11.2% of cases having at least one postoperative adverse outcome. Fifteen covariates were identified for predicting hospital readmission with the area under the curve (AUC) of 0.70, and 16 were selected to predict any adverse postoperative outcome (AUC=0.75). The LASSO and machine learning approaches had similar performance. Advanced age and a history of fracture due to orthopedic devices are among the top predictors of hospital readmissions and other adverse outcomes. The score range for hospital readmission and an adverse postoperative outcome was 0 to 48 and 0 to 79, respectively. The cutoff points for the low, medium, and high-risk categories are 0-9, 10-14, ≥15 for hospital readmissions, and 0-11, 12-16, ≥17 for the composite outcome. CONCLUSION: Based on Medicare fee-for-service claims data, this study presents a preoperative risk stratification tool to assess hospital readmission or adverse surgical outcomes following TSA. Further investigation is warranted to validate these tools in a variety of diverse demographic settings and improve their predictive performance.

The impact of social deprivation on healthcare utilization patterns following rotator cuff repair.

BACKGROUND: Disparities in social determinants of health have been linked to worse patient reported outcomes, higher pain, and increased risk of revision surgery following rotator cuff repair. Identification of perioperative predictors of increased healthcare utilization is of particular interest to surgeons to improve outcomes and mitigate the total cost of care. The effect of social deprivation on healthcare utilization has not been fully characterized. METHODS: This is a retrospective review of a single institution's experience with primary rotator cuff repair between 2012 and 2020. Demographic variables (age, race, gender, American Society of Anesthesiologists (ASA) score) and healthcare utilization (hospital readmission, emergency department visits, follow-up visits, telephone calls) were recorded within 90 days of surgery. The Area Deprivation Index (ADI) was recorded, and patients were separated into terciles according to their relative level of social deprivation. Outcomes were then stratified based on ADI tercile and compared. RESULTS: A total of 1695 patients were included. The upper, middle, and lower terciles of ADI consisted of 410, 767, and 518 patients, respectively. The most deprived tercile had greater emergency department visitation and office visitation within 90 days of surgery relative to the least and intermediate deprived terciles. Higher levels of social deprivation were independent risk factors for increased emergency department (ED) visitation and follow-up visitation. There was no difference in 90-day readmission rates or telephone calls made between the least, intermediate, and most deprived patients. CONCLUSIONS: Patients with higher levels of deprivation demonstrated greater postoperative hospital utilization. We hope to use these results to identify risk factors for increased hospital use, guide clinical decision making, increase transparency, and manage patient outcomes following rotator cuff repair surgery.

Home health care is associated with an increased risk of readmission and cost of care without reducing risk of complication following shoulder arthroplasty: a propensity-score analysis.

BACKGROUND: Home health services provide patients with additional professional care and supervision following discharge from the hospital to theoretically reduce the risk of complication and reduce health care utilization. The aim of this investigation was to determine if patients assigned home health services following total shoulder arthroplasty (anatomic [TSA] and reverse [RSA]) exhibited lower rates of medical complications, lower health care utilization, and lower cost of care compared with patients not receiving these services. METHODS: A national insurance database was retrospectively reviewed to identify all patients undergoing primary TSA and RSA from 2010 to 2019. Patients who received home health services were matched using a propensity score algorithm to a set of similar patients who were discharged home without services. We compared medical complication rates, emergency department (ED) visits, readmissions, and 90-day cost of care between the groups. Multivariate regression analysis was performed to determine the independent effect of home health services on all outcomes. RESULTS: A total of 1119 patients received home health services and were matched to 11,190 patients who were discharged home without services. There was no significant difference in patients who received home health services compared with those who did not receive home health services with respect to rates of ED visits within 30 days (OR 1.293; P = .0328) and 90 days (OR 1.215; P = .0378), whereas the home health group demonstrated increased readmissions within 90 days (OR 1.663; P < .001). For all medical complications, there was no difference between cohorts. Episode-of-care costs for home health patients were higher than those discharged without these services ($12,521.04 vs. $9303.48; P < .001). CONCLUSION: Patients assigned home health care services exhibited higher cost of care and readmission rates without a reduction in the rate of complication or early return to the ED. These findings suggest that home health care services should be strongly analyzed on a case-by-case basis to determine if a patient may benefit from its implementation.

Decreased Risk of Readmission and Complications With Preoperative GLP-1 Analog Use in Patients Undergoing Primary Total Joint Arthroplasty.

BACKGROUND: There has been considerable interest in the use of GLP-1 receptor analogs (GLP-1 RAs) for weight optimization in patients undergoing elective arthroplasty. As there is limited data regarding the implications of their use, our study aimed to evaluate the association between preoperative GLP-1 RA use and postoperative outcomes in patients undergoing primary total hip arthroplasty (THA) and total knee arthroplasty (TKA). METHODS: The TrinetX research network was queried to identify all patients undergoing primary THA or TKA between May 2005 and December 2023 across 84 health care organizations. Patients were stratified based on preoperative GLP-1 RA use. Propensity score matching (1:1) was performed to account for baseline differences in demographics, laboratory investigations, and comorbidities. Subsequently, risk ratios were evaluated for postoperative outcomes. RESULTS: A total of 268,504 and 386,356 patients underwent THA and TKA, of which 1,044 and 2,095 used preoperative GLP-1 RAs. After matching, GLP-1 RA use was associated with a decreased 90-day risk of periprosthetic joint infection (2.1 versus 3.6%, RR = 0.58, P = .042) and readmission (1.1 versus 2.0%, RR = 0.53, P = .017) following THA and TKA, respectively. There was no difference in the risk of all other outcomes between comparison groups. CONCLUSIONS: Preoperative GLP-1 RA use is associated with a 42% decreased risk of periprosthetic joint infection and 47% decreased risk of readmission in the 90-day postoperative period following THA and TKA, respectively, with no difference in other risks, including aspiration. Our findings indicate that GLP-1 RAs may be safe to use in patients undergoing elective arthroplasty; however, further studies are warranted to inform the routine use of GLP-1 RAs for weight management in THA and TKA patients.

The Effect of 30-Day Adequate Transitions of Acute Stroke Care on 90-Day Readmission or Death.

OBJECTIVES: We explore patient-reported behaviors and activities within 30-days post-stroke hospitalization and their role in reducing death or readmissions within 90-days post-stroke. METHODS: We constructed the adequate transitions of care (ATOC) composite score, measuring patient-reported participation in eligible behaviors and activities (diet modification, weekly exercise, follow-up medical appointment attendance, medication adherence, therapy use, and toxic habit cessation) within 30 days post-stroke hospital discharge. We analyzed ATOC scores in ischemic and intracerebral hemorrhage stroke patients discharged from the hospital to home or rehabilitation facilities and enrolled in the NIH-funded Transitions of Care Stroke Disparities Study (TCSD-S). We utilized Cox regression analysis, with the progressive adjustment for sociodemographic variables, social determinants of health, and stroke risk factors, to determine the associations between ATOC score within 30-days and death or readmission within 90-days post-stroke. RESULTS: In our sample of 1239 stroke patients (mean age 64+/-14, 58% male, 22% Hispanic, 22% Black, 52% White, 76% discharged home), 13% experienced a readmission or death within 90 days (3 deaths, 160 readmissions, 3 readmissions with subsequent death). Seventy percent of participants accomplished a ≥75% ATOC score. A 25% increase in ATOC was associated with a respective 20% (95% CI 3%-33%) reduced risk of death or readmission within 90-days. CONCLUSION: ATOC represents modifiable behaviors and activities within 30-days post-stroke that are associated with reduced risk of death or readmission within 90-days post-stroke. The ATOC score should be validated in other populations, but it can serve as a tool for improving transitions of stroke care initiatives and interventions.

Risk factors for 30-day hospital readmission in patients with diabetic foot.

INTRODUCTION: Diabetic foot (DF) is part of the natural history of diabetes mellitus, ulceration being a severe complication with a prevalence of approximately 6.3 %, which confers a significant economic burden. Hospital readmission in the first thirty (30) days is considered a measure of quality of healthcare and it's been identified that the most preventable causes are the ones that occur in this period. This study seeks to identify the risk factors associated with readmission of patients with DF. METHODS: A case-control study was done by performing a secondary analysis of a database. Descriptive statistics were used for all variables of interest, bivariate analysis to identify statistically significant variables, and a logistic regression model for multivariate analysis. RESULTS: 575 cases were analyzed (113 cases, 462 controls). A 20 % incidence rate of 30-day readmission was identified. Statistically significant differences were found in relation to the institution of attention (Hospital Universitario de la Samaritana: OR 1.9, p value < 0.01, 95 % CI 1.2-3.0; Hospital Universitario San Ignacio: OR 0.5, p value < 0.01, 95 % CI 0.3-0.8) and the reasons for readmission before 30 days, especially due to surgical site infection (SSI) (OR 7.1, p value < 0.01, 95 % CI 4.1-12.4), sepsis (OR 8.4, p value 0.02, 95 % CI 1.2-94.0), dehiscence in amputation stump (OR 16.4, p value < 0.01, 95 % CI 4.2-93.1) and decompensation of other pathologies (OR 3.5, p value < 0.01, 95 % CI 2.1-5.7). CONCLUSION: The hospital readmission rate before 30 days for our population compares to current literature. Our results were consistent with exacerbation of chronic pathologies, but other relevant variables not mentioned in other studies were the hospital in which patients were taken care of, the presence of SSI, sepsis, and dehiscence of the amputation stump. We consider thoughtful and close screening of patients at risk in an outpatient setting might identify possible readmissions.

Low skeletal muscle mass is associated with mortality in kidney transplant recipients.

Muscle wasting in chronic kidney disease is associated with increased cardiovascular events, morbidity, and mortality. However, whether pretransplantation skeletal muscle mass affects kidney transplantation (KT) outcomes has not been established. We analyzed 623 patients who underwent KT between 2004 and 2019. We measured the cross-sectional area of total skeletal muscle at the third lumbar vertebra level on pretransplantation computed tomography scan. The patients were grouped into low and normal skeletal muscle mass groups based on the sex-specific skeletal muscle mass index lowest quartile. During the entire follow-up period, 45 patients (7.2%) died and 56 patients (9.0%) experienced death-censored graft loss. Pretransplantation low skeletal muscle mass was independently associated with all-cause mortality (adjusted hazard ratio, 2.269; 95% confidence interval, 1.232-4.182). Low muscle mass was also associated with an increased risk of hospital readmission within 1 year after transplantation. Death-censored graft survival rates were comparable between the 2 groups. The low muscle group showed higher creatinine-based estimated glomerular filtration rates (eGFRs) than the normal muscle group. Although cystatin C-based eGFRs were measured in only one-third of patients, cystatin C-based eGFRs were comparable between the 2 groups. Pretransplantation low skeletal muscle mass index is associated with an increased risk of mortality and hospital readmission after KT.

Partial and complete explantation of aortic endografts in the modern era.

OBJECTIVE: Despite the progressive advancement of devices for endovascular aortic repair (EVAR), endografts continue to fail, requiring explant. We present a single-institutional experience of EVAR explants, characterizing modern failure modes, presentation, and outcomes for partial and complete EVAR explantation. METHODS: A retrospective analysis was performed of all EVARs explanted at an urban quaternary center from 2001 to 2020, with one infected endograft excluded. Patient and graft characteristics, indications, and perioperative and long-term outcomes were analyzed. Partial versus complete explants were performed per surgeon discretion without a predefined protocol. This process was informed by patient risk factors; asymptomatic, symptomatic, or ruptured aneurysm presentation; and anatomical or intraoperative factors, including endoleak type. RESULTS: From 2001 to 2020, 52 explants met the inclusion and exclusion criteria. More than one-half (57.7%) were explants of EVAR devices placed at outside institutions, designated nonindex explants. Most patients were male (86.5%), the median age was 74 years (interquartile range, 70-78 years). More than one-half (61.5%) were performed in the second decade of the study period. The most commonly explanted grafts were Gore Excluder (n = 9 grafts), Cook Zenith (n = 8), Endologix AFX (n = 7), Medtronic Endurant (n = 5), and Medtronic Talent (n = 5). Most grafts (78.8%) were explanted for neck degeneration or sac expansion. Five were explanted for initial seal failure, five for symptomatic expansion, and seven for rupture. The median implant duration was 4.2 years, although ranging widely (interquartile range, 2.6-5.1 years), but similar between index and nonindex explants (4.2 years vs 4.1 years). Partial explantation was performed in 61.5%, with implant duration slightly lower, 3.2 years versus 4.4 years for complete explants. Partial explantation was more frequent in index explants (68.2% vs 56.7%). The median length of stay was 8 days. The median intensive care unit length of stay was 3 days, without significant differences in nonindex explants (4 days vs 3 days) and partial explants (4 days vs 3 days). Thirty-day mortality occurred in two nonindex explants (one partial and one complete explant). Thirty-day readmission was similar between partial and complete explants (9.7% vs 5.0%), without accounting for nonindex readmissions. Long-term survival was comparable between partial and complete explants in Cox regression (hazard ratio, 2.45; 95% confidence interval, 0.79-7.56; P = .12). CONCLUSIONS: Explants of EVAR devices have increased over time at our institution. Partial explant was performed in more than one-half of cases, per operating surgeon discretion, demonstrating higher blood loss, more frequent acute kidney injury, and longer intensive care unit stays, however with comparable short-term mortality and long-term survival.

The Early HOSPITAL Score to Predict 30-Day Readmission Soon After Hospitalization: a Prospective Multicenter Study.

BACKGROUND: The simplified HOSPITAL score is an easy-to-use prediction model to identify patients at high risk of 30-day readmission before hospital discharge. An earlier stratification of this risk would allow more preparation time for transitional care interventions. OBJECTIVE: To assess whether the simplified HOSPITAL score would perform similarly by using hemoglobin and sodium level at the time of admission instead of discharge. DESIGN: Prospective national multicentric cohort study. PARTICIPANTS: In total, 934 consecutively discharged medical inpatients from internal general services. MAIN MEASURES: We measured the composite of the first unplanned readmission or death within 30 days after discharge of index admission and compared the performance of the simplified score with lab at discharge (simplified HOSPITAL score) and lab at admission (early HOSPITAL score) according to their discriminatory power (Area Under the Receiver Operating characteristic Curve (AUROC)) and the Net Reclassification Improvement (NRI). KEY RESULTS: During the study period, a total of 3239 patients were screened and 934 included. In total, 122 (13.2%) of them had a 30-day unplanned readmission or death. The simplified and the early versions of the HOSPITAL score both showed very good accuracy (Brier score 0.11, 95%CI 0.10-0.13). Their AUROC were 0.66 (95%CI 0.60-0.71), and 0.66 (95%CI 0.61-0.71), respectively, without a statistical difference (p value 0.79). Compared with the model at discharge, the model with lab at admission showed improvement in classification based on the continuous NRI (0.28; 95%CI 0.08 to 0.48; p value 0.004). CONCLUSION: The early HOSPITAL score performs, at least similarly, in identifying patients at high risk for 30-day unplanned readmission and allows a readmission risk stratification early during the hospital stay. Therefore, this new version offers a timely preparation of transition care interventions to the patients who may benefit the most.