Multiple arterial vs. single arterial coronary artery bypass grafting: sex-related differences in outcomes.

BACKGROUND AND AIMS: Uncertainty exists over whether multiple arterial grafting has a sex-related association with survival after coronary artery bypass grafting. This study aims to compare the long-term survival of using multiple arterial grafting vs. single arterial grafting in women and men undergoing coronary artery bypass grafting. METHODS: The retrospective study used the Australian and New Zealand Society of Cardiothoracic Surgical Database with linkage to the National Death Index. Patients from 2001 to 2020 were identified. Sex-stratified, inverse probability weighted Cox proportional hazard model was used to facilitate survival comparisons. The primary outcome was all-cause mortality. RESULTS: A total number of 54 275 adult patients receiving at least two grafts in primary isolated bypass operations were analysed. The entire study cohort consisted of 10 693 (19.7%) female patients and 29 711 (54.7%) multiple arterial grafting procedures. At a median (interquartile range) postoperative follow-up of 4.9 (2.3-8.4) years, mortality was significantly lower in male patients undergoing multiarterial than single arterial procedures (adjusted hazard ratio 0.82; 95% confidence interval 0.77-0.87; P < .001). The survival benefit was also significant for females (adjusted hazard ratio 0.83; 95% confidence interval 0.76-0.91; P < .001) at a median (interquartile range) follow-up of 5.2 (2.4-8.7) years. The interaction model from Cox regression suggested insignificant subgroup effect from sex (P = .08) on the observed survival advantage. The survival benefits associated with multiple arterial grafting were consistent across all sex-stratified subgroups except for female patients with left main coronary disease. CONCLUSIONS: Compared to single arterial grafting, multiple arterial revascularization is associated with improved long-term survival for women as well as men.

Elevated levels of PDGF-BB and VEGF are associated with a decreased risk of readmission or death in children with severe malarial anemia.

BACKGROUND: Children with severe malarial anemia (SMA) typically have low in-hospital mortality but have a high risk of post-discharge readmission or death. We hypothesized that the dysregulation of hematopoiesis, vascular growth factors, and endothelial function that occurs in SMA might affect risk of readmission or death. METHODS: Plasma was obtained from children 18 months to 12 years old with SMA (N=145) in Kampala, Uganda on admission, and outcomes were assessed over 12-month follow-up. Admission plasma levels of ten biomarkers of vascular growth, hematopoiesis, and endothelial function were compared to risk of readmission or death over 12-month follow-up. RESULTS: Over 12-month follow-up, 19 of 145 children with SMA were either readmitted or died: 15 children were readmitted (13 with malaria) and 4 children died. In multivariable analyses adjusted for age and sex, elevated plasma levels of platelet-derived growth factor-BB (PDGF-BB) and vascular endothelial growth factor (VEGF) on admission were independently associated with a decreased risk of all-cause readmission or death (adjusted hazard ratios [95% confidence intervals], 0.28 [0.16-0.51] and 0.19 [0.08-0.48], respectively) and a decreased risk of readmission due to severe malaria (0.27 [0.15, 0.51] and 0.16 [0.05, 0.47]) but not with risk of uncomplicated malaria (1.01 [0.53, 1.95] and 2.07 [0.93-4.64]). CONCLUSIONS: In children with severe malarial anemia, elevated plasma levels of PDGF-BB and VEGF, two factors that promote angiogenesis, are associated with a decreased risk of readmission or death in the year following admission, primarily driven by a decrease in the risk of recurrent severe malaria.

Achieving Equity in Hospital Performance Assessments Using Composite Race-Specific Measures of Risk-Standardized Readmission and Mortality Rates for Heart Failure.

BACKGROUND: The contemporary measures of hospital performance for heart failure hospitalization and 30-day risk-standardized readmission rate (RSRR) and risk-standardized mortality rate (RSMR) are estimated using the same risk adjustment model and overall event rate for all patients. Thus, these measures are mainly driven by the care quality and outcomes for the majority racial and ethnic group, and may not adequately represent the hospital performance for patients of Black and other races. METHODS: Fee-for-service Medicare beneficiaries from January 2014 to December 2019 hospitalized with heart failure were identified. Hospital-level 30-day RSRR and RSMR were estimated using the traditional race-agnostic models and the race-specific approach. The composite race-specific performance metric was calculated as the average of the RSRR/RMSR measures derived separately for each race and ethnicity group. Correlation and concordance in hospital performance for all patients and patients of Black and other races were assessed using the composite race-specific and race-agnostic metrics. RESULTS: The study included 1 903 232 patients (75.7% White [n=1 439 958]; 14.5% Black [n=276 684]; and 9.8% other races [n=186 590]) with heart failure from 1860 hospitals. There was a modest correlation between hospital-level 30-day performance metrics for patients of White versus Black race (Pearson correlation coefficient: RSRR=0.42; RSMR=0.26). Compared with the race-agnostic RSRR and RSMR, composite race-specific metrics for all patients demonstrated stronger correlation with RSRR (correlation coefficient: 0.60 versus 0.74) and RSMR (correlation coefficient: 0.44 versus 0.51) for Black patients. Concordance in hospital performance for all patients and patients of Black race was also higher with race-specific (versus race-agnostic) metrics (RSRR=64% versus 53% concordantly high-performing; 61% versus 51% concordantly low-performing). Race-specific RSRR and RSMR metrics (versus race-agnostic) led to reclassification in performance ranking of 35.8% and 39.2% of hospitals, respectively, with better 30-day and 1-year outcomes for patients of all race groups at hospitals reclassified as high-performing. CONCLUSIONS: Among patients hospitalized with heart failure, race-specific 30-day RSMR and RSRR are more equitable in representing hospital performance for patients of Black and other races.

Changes in Cardiovascular Spending, Care Utilization, and Clinical Outcomes Associated With Participation in Bundled Payments for Care Improvement - Advanced.

BACKGROUND: Bundled Payments for Care Improvement - Advanced (BPCI-A) is a Medicare initiative that aims to incentivize reductions in spending for episodes of care that start with a hospitalization and end 90 days after discharge. Cardiovascular disease, an important driver of Medicare spending, is one of the areas of focus BPCI-A. It is unknown whether BPCI-A is associated with spending reductions or quality improvements for the 3 cardiovascular medical events or 5 cardiovascular procedures in the model. METHODS: In this retrospective cohort study, we conducted difference-in-differences analyses using Medicare claims for patients discharged between January 1, 2017, and September 30, 2019, to assess differences between BPCI-A hospitals and matched nonparticipating control hospitals. Our primary outcomes were the differential changes in spending, before versus after implementation of BPCI-A, for cardiac medical and procedural conditions at BPCI-A hospitals compared with controls. Secondary outcomes included changes in patient complexity, care utilization, healthy days at home, readmissions, and mortality. RESULTS: Baseline spending for cardiac medical episodes at BPCI-A hospitals was $25 606. The differential change in spending for cardiac medical episodes at BPCI-A versus control hospitals was $16 (95% CI, -$228 to $261; P=0.90). Baseline spending for cardiac procedural episodes at BPCI-A hospitals was $37 961. The differential change in spending for cardiac procedural episodes was $171 (95% CI, -$429 to $772; P=0.58). There were minimal differential changes in physicians' care patterns such as the complexity of treated patients or in their care utilization. At BPCI-A versus control hospitals, there were no significant differential changes in rates of 90-day readmissions (differential change, 0.27% [95% CI, -0.25% to 0.80%] for medical episodes; differential change, 0.31% [95% CI, -0.98% to 1.60%] for procedural episodes) or mortality (differential change, -0.14% [95% CI, -0.50% to 0.23%] for medical episodes; differential change, -0.36% [95% CI, -1.25% to 0.54%] for procedural episodes). CONCLUSIONS: Participation in BPCI-A was not associated with spending reductions, changes in care utilization, or quality improvements for the cardiovascular medical events or procedures offered in the model.

Association of Posttraumatic Stress Disorder and Race on Readmissions After Stroke.

BACKGROUND: There is limited research on outcomes of patients with posttraumatic stress disorder (PTSD) who also develop stroke, particularly regarding racial disparities. Our goal was to determine whether PTSD is associated with the risk of hospital readmission after stroke and whether racial disparities existed. METHODS: The analytical sample consisted of all veterans receiving care in the Veterans Health Administration who were identified as having a new stroke requiring inpatient admission based on the International Classification of Diseases codes. PTSD and comorbidities were identified using the International Classification of Diseases codes and given the date of first occurrence. The retrospective cohort data were obtained from the Veterans Affairs Corporate Data Warehouse. The main outcome was any readmission to Veterans Health Administration with a stroke diagnosis. The hypothesis that PTSD is associated with readmission after stroke was tested using Cox regression adjusted for patient characteristics including age, sex, race, PTSD, smoking status, alcohol use, and comorbidities treated as time-varying covariates. RESULTS: Our final cohort consisted of 93 651 patients with inpatient stroke diagnosis and no prior Veterans Health Administration codes for stroke starting from 1999 with follow-up through August 6, 2022. Of these patients, 12 916 (13.8%) had comorbid PTSD. Of the final cohort, 16 896 patients (18.0%) with stroke were readmitted. Our fully adjusted model for readmission found an interaction between African American veterans and PTSD with a hazard ratio of 1.09 ([95% CI, 1.00-1.20] P=0.047). In stratified models, PTSD has a significant hazard ratio of 1.10 ([95% CI, 1.02-1.18] P=0.01) for African American but not White veterans (1.05 [95% CI, 0.99-1.11]; P=0.10). CONCLUSIONS: Among African American veterans who experienced stroke, preexisting PTSD was associated with increased risk of readmission, which was not significant among White veterans. This study highlights the need to focus on high-risk groups to reduce readmissions after stroke.

Moderating Effects of Informal Care on the Relationship Between ADL Limitations and Adverse Outcomes in Stroke Survivors.

BACKGROUND: Stroke survivors with limitations in activities of daily living (ADL) have a greater risk of experiencing falls, hospitalizations, or physical function decline. We examined how informal caregiving received in hours per week by stroke survivors moderated the relationship between ADL limitations and adverse outcomes. METHODS: In this retrospective cohort, community-dwelling participants were extracted from the National Health and Aging Trends Study (2011-2020; n=277) and included if they had at least 1 formal or informal caregiver and reported an incident stroke in the prior year. Participants reported the amount of informal caregiving received in the month prior (low [<5.8], moderate [5.8-27.1], and high [27.2-350.4] hours per week) and their number of ADL limitations (ranging from 0 to 7). Participants were surveyed 1 year later to determine the number of adverse outcomes (ie, falls, hospitalizations, and physical function decline) experienced over the year. Poisson regression coefficients were converted to average marginal effects and estimated the moderating effects of informal caregiving hours per week on the relationship between ADL limitations and adverse outcomes. RESULTS: Stroke survivors were 69.7% White, 54.5% female, with an average age of 80.5 (SD, 7.6) years and 1.2 adverse outcomes at 2 years after the incident stroke. The relationships between informal caregiving hours and adverse outcomes and between ADL limitations and adverse outcomes were positive. The interaction between informal caregiving hours per week and ADL limitations indicated that those who received the lowest amount of informal caregiving had a rate of 0.12 more adverse outcomes per ADL (average marginal effect, 0.12 [95% CI, 0.005-0.23]; P=0.041) than those who received the highest amounts. CONCLUSIONS: Informal caregiving hours moderated the relationship between ADL limitations and adverse outcomes in this sample of community-based stroke survivors. Higher amounts relative to lower amounts of informal caregiving hours per week may be protective by decreasing the rate of adverse outcomes per ADL limitation.

Effect of Exercise Training on Prognosis in Community-acquired Pneumonia: A Randomized Controlled Trial.

OBJECTIVE: To investigate the effect of standard care (SoC) combined with supervised in-bed cycling (Bed-Cycle) or booklet exercises (Book-Exe) versus SoC in community-acquired pneumonia (CAP). METHODS: In this randomized controlled trial, 186 patients with CAP were assigned to SoC (n = 62), Bed-Cycle (n = 61), or Book-Exe (n = 63). Primary outcome length of stay (LOS) was analyzed with analysis of covariance. Secondary outcomes, 90-day readmission, and 180-day mortality were analyzed with Cox proportional hazard regression and readmission days with negative-binominal regression. RESULTS: LOS was -2% (95% CI: -24 to 25) and -1% (95% CI: -22 to 27) for Bed-Cycle and Book-Exe, compared with SoC. Ninety-day readmission was 35.6% for SoC, 27.6% for Bed-Cycle, and 21.3% for Book-Exe. Adjusted hazard ratio (aHR) for 90-day readmission was 0.63 (95% CI: .33-1.21) and 0.54 (95% CI: .27-1.08) for Bed-Cycle and Book-Exe compared with SoC. aHR for 90-day readmission for combined exercise was 0.59 (95% CI: .33-1.03) compared with SoC. aHR for 180-day mortality was 0.84 (95% CI: .27-2.60) and 0.82 (95% CI: .26-2.55) for Bed-Cycle and Book-Exe compared with SoC. Number of readmission days was 226 for SoC, 161 for Bed-Cycle, and 179 for Book-Exe. Incidence rate ratio for readmission days was 0.73 (95% CI: .48-1.10) and 0.77 (95% CI: .51-1.15) for Bed-Cycle and Book-Exe compared with SoC. CONCLUSIONS: Although supervised exercise training during admission with CAP did not reduce LOS or mortality, this trial suggests its potential to reduce readmission risk and number of readmission days. CLINICAL TRIALS REGISTRATION: NCT04094636.

Remdesivir Effectiveness in Reducing the Risk of 30-day Readmission in Vulnerable Patients Hospitalized for COVID-19: A Retrospective US Cohort Study Using Propensity Scores.

BACKGROUND: Reducing hospital readmission offer potential benefits for patients, providers, payers, and policymakers to improve quality of healthcare, reduce cost, and improve patient experience. We investigated effectiveness of remdesivir in reducing 30-day COVID-19-related readmission during the Omicron era, including older adults and those with underlying immunocompromising conditions. METHODS: This retrospective study utilized the US PINC AI Healthcare Database to identify adult patients discharged alive from an index COVID-19 hospitalization between December 01, 2021 and February 29, 2024. Odds of 30-day COVID-19-related readmission to the same hospital were compared between patients who received remdesivir vs those not, after balancing characteristics of two groups using inverse probability of treatment weighting (IPTW). Analyses were stratified by maximum supplemental oxygen requirement during index hospitalization. RESULTS: Of 326,033 patients hospitalized for COVID-19 during study period, 210,586 patients met the eligibility criteria. Of these, 109,551 (52%) patients were treated with remdesivir. After IPTW, lower odds of 30-day COVID-19-related readmission were observed in patients who received remdesivir vs those who did not, in the overall population (3.3% vs 4.2%, respectively; odds ratio [95% confidence interval]: 0.78 [0.75-0.80]), elderly population (3.7% vs 4.7%, respectively; 0.78 [0.75-0.81]), and those with underlying immunocompromising conditions (5.3% vs 6.2%, respectively; 0.86 [0.80-0.92]). These results were consistent irrespective of supplemental oxygen requirements. CONCLUSIONS: Treating patients hospitalized for COVID-19 with remdesivir was associated with a significantly lower likelihood of 30-day COVID-19-related readmission across all patients discharged alive from the initial COVID-19 hospitalization, including older adults and those with underlying immunocompromising conditions.

Effect of disability, homelessness, and neighborhood marginalization on risk-adjustment for hospital performance measurement.

Background It is not known how disability, homelessness, or neighborhood marginalization influence risk-adjusted hospital performance measurement in a universal health care system. Methods We evaluated the effect of including these equity-related factors in risk-adjustment models for in-hospital mortality, and 7- and 30-day readmission in 28 hospitals in Ontario, Canada. We compared risk-adjustment with commonly-used clinical factors to models that also included homelessness, disability, and neighborhood indices of marginalization. We evaluated models in historical data using internal-external cross-validation. We calculated risk-standardized outcome rates for each hospital in a recent reporting period using mixed-effects logistic regression. Results The cohort included 544,805 admissions. Adjustment for disability, homelessness, and neighborhood marginalization had little impact on discrimination or calibration of risk-adjustment models. However, it influenced comparative hospital performance on risk-standardized 30-day readmission rates, resulting in 5 hospitals being reclassified between below-average, average, and above-average groups. No hospitals were reclassified for mortality and 7-day readmission. Conclusion In a system with universally insured hospital services, adjustment for disability, homelessness, and neighborhood marginalization influenced estimates of hospital performance for 30-day readmission but not 7-day readmission or in-hospital mortality. These findings can inform researchers and policymakers as they thoughtfully consider when to adjust for these factors in hospital performance measurement.

Racial differences in length of stay and readmission for asthma in the all of us research program.

BACKGROUND: This study addresses the limited research on racial disparities in asthma hospitalization outcomes, specifically length of stay (LOS) and readmission, across the U.S. METHODS: We analyzed in-patient and emergency department visits from the All of Us Research Program, identifying various risk factors (demographic, comorbid, temporal, and place-based) associated with asthma LOS and 30-day readmission using Bayesian mixed-effects models. RESULTS: Of 17,233 patients (48.0% White, 30.7% Black, 19.7% Hispanic/Latino, 1.3% Asian, and 0.3% Middle Eastern and North African) with 82,188 asthma visits, Black participants had 20% shorter LOS and 12% higher odds of readmission, compared to White participants in multivariate analyses. Public-insured patients had 14% longer LOS and 39% higher readmission odds than commercially insured patients. Weekend admissions resulted in a 12% shorter LOS but 10% higher readmission odds. Asthmatics with chronic diseases had a longer LOS (range: 6-39%) and higher readmission odds (range: 9-32%) except for those with allergic rhinitis, who had a 23% shorter LOS. CONCLUSIONS: A comprehensive understanding of the factors influencing asthma hospitalization, in conjunction with diverse datasets and clinical-community partnerships, can help physicians and policymakers to systematically address racial disparities, healthcare utilization and equitable outcomes in asthma care.

An Automated Electronic Health Record Score to Estimate Length of Stay and Readmission in Patients Undergoing Radical Cystectomy for Bladder Cancer.

PURPOSE: Patients treated with radical cystectomy experience a high rate of postoperative complications and frequent hospital readmissions. We sought to explore the utility of the Care Assessment Need (CAN) score, derived from electronic health data, to estimate the risk of these adverse clinical outcomes, thereby aiding patient counseling and informed treatment decision-making. MATERIALS AND METHODS: We retrospectively examined data from 982 patients with bladder cancer who underwent radical cystectomy between 2013 and 2018 within the national Veterans Health Administration system. We tested for associations between the preoperative CAN score and length of stay, discharge location, and readmission rates. RESULTS: We observed a correlation between higher CAN scores and longer hospital stays (adjusted relative risk = 1.03 [95% CI: 1.02-1.05]). An increased CAN score was also linked to greater odds of discharge to a skilled nursing facility or death (adjusted odds ratio = 1.16 [95% CI: 1.06-1.26]). Furthermore, the score was associated with hospital readmission at both 30 and 90 days postdischarge (adjusted HR = 1.03 [95% CI: 1.00-1.07] and 1.04 [95% CI: 1.00-1.07], respectively). CONCLUSIONS: The CAN score is associated with length of hospital stay, discharge to a skilled nursing facility, and readmission within 30 and 90 days after radical cystectomy. These findings highlight the potential of health care systems leveraging electronic health records for automatically calculating multidimensional tools, such as the CAN score, to identify patients at risk of adverse clinical outcomes after radical cystectomy.

Predictive Validity of the Academy of Nutrition and Dietetics/American Society for Parental Nutrition Indicators to Diagnose Malnutrition and the Screening Tool for Risk on Nutritional Status and Growth among Hospitalized Children Relative to Medical Outcomes.

OBJECTIVE: To evaluate predictive validity of the Academy of Nutrition and Dietetics/American Society for Parenteral and Enteral Nutrition Indicators to diagnose pediatric malnutrition (AAIMp) and the Screening Tool for Risk on Nutritional Status and Growth (STRONGkids) in regard to pediatric patient outcomes in US hospitals. STUDY DESIGN: A prospective cohort study (Clinical Trial Registry: NCT03928548) was completed from August 2019 through January 2023 with 27 pediatric hospitals or units from 18 US states and Washington DC. RESULTS: Three hundred and forty-five children were enrolled in the cohort (n = 188 in the AAIMp validation subgroup). There were no significant differences in the incidence of emergency department visits and hospital readmissions, hospital length of stay (LOS), or health care resource utilization for children diagnosed with mild, moderate, or severe malnutrition using the AAIMp tool compared with children with no malnutrition diagnosis. The STRONGkids tool significantly predicted more emergency department visits and hospital readmissions for children at moderate and high malnutrition risk (moderate risk - incidence rate ratio 1.65, 95% CI: 1.09, 2.49, P = .018; high risk - incidence rate ratio 1.64, 95% CI: 1.05, 2.56, P = .028) and longer LOS (43.8% longer LOS, 95% CI: 5.2%, 96.6%, P = .023) for children at high risk compared with children at low risk after adjusting for patient characteristics. CONCLUSIONS: Malnutrition risk based on the STRONGkids tool predicted poor medical outcomes in hospitalized US children; the same relationship was not observed for a malnutrition diagnosis based on the AAIMp tool.

Readmission After Neonatal Intensive Care Unit Discharge: The Importance of Social Drivers of Health.

OBJECTIVE: To determine associations between sociodemographic and medical factors and odds of readmission after discharge from the neonatal intensive care unit for infants with very low birth weight (<1500g). STUDY DESIGN: Cohort study using linked data from the California Perinatal Quality Care Collaborative, California Vital Statistics, and the Child Opportunity Index (COI) 2.0. Infants with very low birth weight born from 2009 through 2018 in California were considered. Odds ratios of readmission within 30 days of discharge adjusting for infant medical factors, maternal sociodemographic factors, and birth hospital were calculated via multivariable logistic regression and fixed-effect logistic regression models. RESULTS: A total of 42 411 infants met inclusion criteria. Also, 8.5% of all infants were readmitted within 30 days of discharge. In addition to traditional medical risk factors, two sociodemographic factors were significantly associated with increased odds of readmission in adjusted models: payor other than private insurance for delivery [aOR = 1.25 (95% CI 1.14-1.36)] and maternal education of less than high school degree [aOR = 1.19 (95% CI 1.06-1.33)]. Neighborhood Child Opportunity Index was not associated with odds of readmission. CONCLUSIONS: Sociodemographic factors, including lack of private insurance and lower maternal educational attainment, are significantly and independently associated with increased odds of readmission after neonatal intensive care unit discharge, in addition to traditional medical risk factors. Socioeconomic deprivation and health literacy may contribute to risk of readmission. Targeted discharge interventions focused on addressing social drivers of health warrant exploration.

Impact of frailty in hospitalized patients undergoing catheter ablation for atrial fibrillation.

BACKGROUND: Catheter Ablation (CA) is an effective treatment for atrial fibrillation (AF). However, frail elderly patients have been understudied due to their exclusion from landmark trials. OBJECTIVES: Our study aims to evaluate outcomes in this population. METHODS: The national readmission database (2016-2020) was queried, and frailty categories were defined based on hospital risk frailty scores ≦5 as low while >5 as intermediate/high frailty (IHF). We used multivariate regression and propensity-matched analysis to compare outcomes in patients undergoing CA for atrial fibrillation based on frailty index. RESULTS: Among 55 936 CAs for AF, 33,248 patients had low frailty, while 22 688 had intermediate/high frailty (IHF). After propensity matching (N 12 448), IHF patients were found to have higher adverse events, including mortality (3% vs. 0.3%, p < .001), stroke (1.9% vs. 0.2%, p < .001), acute heart failure (53.8% vs. 42.2%, p < .001), AKI (42.5% vs. 6.8%, p < .001), pericardial complications (2.8 vs. 1.6%, p < .001), respiratory complications (27.8 vs. 7.2%, p < .001), major adverse cardiovascular events (21.2 vs. 9.4%, p < .001) and net adverse events (76.7 vs. 55%, p < .001). IHF patients had higher readmissions at 30 (15.5 vs. 12.6%, p < .001), 90 (31.9 vs. 25.1%, p < .001), and 180-day (41 vs. 34.7%, p < .001) intervals. A higher median length of stay (LOS) (7 vs. 3 days, p < .001) and cost ($44 287 vs. $27 517, p < .001) at index admission and subsequent readmissions were also observed (p < .001). CONCLUSION: Intermediate/high frailty patients undergoing catheter ablation had worse clinical outcomes, higher healthcare burden, and readmission rates. LOS has decreased in both groups from 2016 to 2020; however, total cost has increased.

Use of Imaging-guided Decongestion for Reducing Heart Failure Readmission and Death in High-risk Patients: A Multi-site Randomized Trial of a Nurse-led Strategy at the Point of Care.

BACKGROUND: Nurse-led disease management programs (DMPs) decrease readmission after acute decompensated heart failure (HF). We sought whether readmissions could be further reduced by lung ultrasound (LUS)-guided decongestion before discharge and during DMP. METHODS AND RESULTS: Of 290 patients hospitalized with acute decompensated HF, 122 at high risk for readmission or mortality were randomized to receive usual care (UC) (n = 64) or UC plus intervention (DMP-Plus) (n = 58), comprising LUS-guided management before discharge and during at-home follow-up. Residual congestion was identified by ≥10 B-lines detected in 8 lung zones. The outcomes included a composite of readmission and/or mortality at 30 and 90 days, and 90-day HF readmission. Residual congestion was detected equally among the patient groups. The 30-day composite outcome occurred in 28% DMP-plus patients and 22% UC patients (odd ratio [OR], 1.36; 95% confidence interval [CI], 0.59-3.1; P = .5) and the 90-day HF readmission outcome occurred in 22% and 31%, respectively (odds ratio, 0.63; 95% CI, 0.28-1.43; P = .3). Residual congestion, identified at predischarge LUS examination in high-risk patients, was associated with early (<14-day) HF readmission (relative risk, 1.19; 95% CI, 1.06-1.32; P = .002) and multiple (≥2) readmissions over 90 days of follow-up (relative risk, 1.09; 95% CI, 1.01-1.16; P = .012), independent of demographics and comorbidities. CONCLUSIONS: Readmission in patients with incomplete decongestion before discharge occurs within the first 2 weeks. However, our DMP-plus strategy did not improve the primary outcome.

Factors associated with 90-day reintervention following lower extremity revascularization.

OBJECTIVE: Peripheral artery disease (PAD) represents a high-volume, high-cost burden on the health care system. The Centers for Medicare and Medicaid Services has developed the Bundled Payments for Care Improvement-Advanced program, in which a single payment is provided for all services administered in a postsurgical 90-day episode of care. Factors associated with 30- and 90-day reinterventions after PAD interventions would represent useful data for both payors and stake holders. METHODS: We conducted a national cohort study of adults 65 years and older in the Vascular Quality Initiative and Centers for Medicare and Medicaid Services-linked dataset who underwent an open, endovascular, or hybrid revascularization procedure for PAD between January 1, 2010, and December 31, 2018. Procedures for acute limb ischemia and aneurysms were excluded. The primary outcome was 90-day reintervention. Reintervention at 30 days was a secondary outcome. Covariates of interest included demographics, comorbidities, and patient- and facility-level characteristics. Multivariable Cox regression was used to determine the association between patient- and facility-level characteristics and the risk of 30- and 90-day reinterventions. RESULTS: Among 42,429 patients (71.3% endovascular, 23.3% open, and 5.4% hybrid), median age was 74 years (interquartile range, 69-80 years), 57.9% were male, and 84.3% were White. Chronic limb-threatening ischemia was the operative indication in 40.4% of the procedures. Overall, 42.8% were completed in the outpatient setting (40.3% outpatient, 2.5% office-based lab). Over 70% of procedures for chronic limb-threatening ischemia were completed as inpatient, whereas 60% of the claudication interventions were done as outpatient. The 90-day reintervention rate was 14.5%, and the 30-day reintervention rate was 5.5%. Compared with inpatient procedures, PAD interventions completed in the outpatient or office-based lab setting had significantly higher 90- and 30-day reintervention rates (reference, inpatient; outpatient 90-day reintervention: hazard ratio [HR], 1.41; 95% confidence interval [CI] 1.25-1.60; outpatient 30-day reintervention: HR, 1.90; 95% CI, 1.62-2.24; office-based lab 90-day reintervention: HR, 2.09; 95% CI, 1.82-2.41; office-based lab 30-day reintervention: HR, 3.54; 95% CI, 3.17-3.94). Open and hybrid approaches demonstrated lower risk of reintervention compared with endovascular procedures at 30 and 90 days and, compared with aortoiliac disease, all other anatomic segments of disease were associated with higher 90-day reintervention, but no difference was noted at 30 days. CONCLUSIONS: Although outpatient PAD interventions may be convenient for patients and providers, the outpatient setting is associated with a significant risk of subsequent reintervention. Additional work is needed to understand how to improve the longevity of outpatient PAD interventions.

Targeted use of postoperative discharge phone calls to reduce early readmission rates.

OBJECTIVES: Postoperative readmissions are common and costly. Office-initiated phone calls to patients shortly after discharge may identify concerns and allow for early intervention to prevent readmission. We sought to evaluate our 30-day readmission rate after the implementation of a standardized postoperative discharge phone call (PODPC) intervention, compared with a historical aggregated cohort. METHODS: From July 2020 to 21, postoperative patients were prospectively identified at 48 hour after discharge. Medical assistants performed PODPCs, administering a survey designed to identify medical/surgical issues that could signify a complication and warrant escalation to a nurse practitioner (NP) for further management. Demographics, comorbidities, and procedure type were obtained retrospectively. Descriptive statistics were used to evaluate PODPC responses, frequency of escalation, readmission, and reasons. The electronic medical record identified a historical aggregated cohort (July 2018 to 2019) and the 30-day readmission rate. A χ2 analysis was used to compare readmission rates between the preintervention historical and PODPC intervention groups. Predictors of 30-day readmission were modeled with multivariable logistic regression. RESULTS: Of 411 PODPCs conducted, 106 patients (26%) reported not feeling well; having concerns. Eighty-four PODPCs (20%) triggered escalation to a NP; of these, 60 patients (71%) were counseled over the phone by an NP, 16 (19%) were brought into clinic, 6 (7%) were sent to the emergency department, and 2 (2%) did not answer the NP call. Of 411 patients, 17% (n = 68) were readmitted within 30 days. Comparatively, the historical aggregated cohort readmission rate was significantly higher at 28% (n = 346; P < .001). On multivariable analysis, chronic obstructive pulmonary disease (odds ratio [OR], 1.92; 95% confidence interval [CI], 1.01-3.65; P = .046), and feeling run down; having difficulty with movement; needing assistance for most activities (OR, 3.94; 95% CI, 2.09-7.43; P < .0001) were predictive of 30-day readmission when controlling for procedure type. CONCLUSIONS: Although readmissions remained common (>15%), being in the intervention cohort was associated with a significantly lower readmission rate compared with the historical aggregated cohort. One-fifth of PODPCs identified a concern; however, >90% of these could be managed by an NP by phone or in clinic. This PODPC intervention holds promise as a viable mechanism for decreasing readmissions.

Developing a Machine Learning Model to Predict 180-day Readmission for Elderly Patients with Angina.

Background: Readmission of elderly angina patients has become a serious problem, with a dearth of available prediction tools for readmission assessment. The objective of this study was to develop a machine learning (ML) model that can predict 180-day all-cause readmission for elderly angina patients. Methods: The clinical data for elderly angina patients was retrospectively collected. Five ML algorithms were used to develop prediction models. Area under the receiver operating characteristic curve (AUROC), area under the precision recall curve (AUPRC), and the Brier score were applied to assess predictive performance. Analysis by Shapley additive explanations (SHAP) was performed to evaluate the contribution of each variable. Results: A total of 1502 elderly angina patients (45.74% female) were enrolled in the study. The extreme gradient boosting (XGB) model showed good predictive performance for 180-day readmission (AUROC = 0.89; AUPRC = 0.91; Brier score = 0.21). SHAP analysis revealed that the number of medications, hematocrit, and chronic obstructive pulmonary disease were important variables associated with 180-day readmission. Conclusions: An ML model can accurately identify elderly angina patients with a high risk of 180-day readmission. The model used to identify individual risk factors can also serve to remind clinicians of appropriate interventions that may help to prevent the readmission of patients.

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.

Addressing Social Determinants of Health in Primary Care Patients May Reduce Hospital Readmissions: A Quasi-Experimental Study.

BACKGROUND: Health care systems are increasingly partnering with community-based organizations to address social determinants of health (SDH). We established a program that educates and connects patients with SDH needs at a primary care clinic to community services and facilitated referrals. OBJECTIVE: To evaluate the effect of addressing SDH soon after discharge on hospital readmission in a clinic population. DESIGN: Pre/post, quasi-experimental design with longitudinal data analysis for quality improvement. PARTICIPANTS: Clinic patients (n = 754) having at least one hospital discharge between June 1, 2020, and October 31, 2021, were included. Of these, 145 patients received the intervention and 609 served as comparison. INTERVENTIONS: A primary care liaison was employed to assess and educate recently discharged clinic patients for SDH needs and refer them for needed community services from June 1, 2020, to October 31, 2021. MAIN MEASURES: Hospital readmissions within 30, 60, and 90 days of discharge were tracked at 6-month intervals. Covariates included patient age, sex, race/ethnicity, insurance status, income, Hierarchical Condition Category risk scores, and Clinical Classification Software diagnosis groups. Data for all hospital discharges during the intervention period were used for the main analysis and data for the year before the intervention were extracted for comparison. KEY RESULTS: Overall, patients in the intervention group were older, sicker, and more likely to have public insurance. The reductions in 30-, 60-, and 90-day readmissions during the intervention period were 14.39%, 13.28%, and 12.04% respectively in the intervention group, while no significant change was observed in the comparison group. The group difference in reduction over time was statistically significant for 30-day (Diff = 12.54%; p = 0.032), 60-day (Diff = 14.40%; p = 0.012), and 90-day readmissions (Diff = 14.71%; p = 0.036). CONCLUSION: Our findings suggest that screening clinic patients for SDH, and educating and connecting them to community services during post-hospital care may be associated with reductions in hospital readmissions.