Temporal Trends, Outcomes, and Predictors of Next-Day Discharge and Readmission Following Uncomplicated Evolut Transcatheter Aortic Valve Replacement: A Propensity Score-Matched Analysis.

BACKGROUND: Next-day discharge (NDD) outcomes following uncomplicated self-expanding transcatheter aortic valve replacement have not been studied. Here, we compare readmission rates and clinical outcomes in NDD versus non-NDD transcatheter aortic valve replacement with Evolut. METHODS AND RESULTS: Society of Thoracic Surgeons/American College of Cardiology TVT (Transcatheter Valve Therapy) Registry patients (n=29 597) undergoing elective transcatheter aortic valve replacement with self-expanding supra-annular valves (Evolut R, PRO, and PRO+) from July 2019 to June 2021 were stratified by postprocedure length of stay: ≤1 day (NDD) versus >1 day (non-NDD). Propensity score matching was used to compare risk adjusted 30-day readmission rates and 1-year outcomes in NDD versus non-NDD, and multivariable regression to determine predictors of NDD and readmission. Between the first and last calendar quarter, the rate of NDD increased from 45.4% to 62.1% and median length of stay decreased from 2 days to 1. Propensity score matching produced relatively well-matched NDD and non-NDD cohorts (n=10 549 each). After matching, NDD was associated with lower 30-day readmission rates (6.3% versus 8.4%; P<0.001) and 1-year adverse outcomes (death, 7.0% versus 9.3%; life threatening/major bleeding, 1.6% versus 3.4%; new permanent pacemaker implantation/implantable cardioverter-defibrillator, 3.6 versus 11.0%; [all P<0.001]). Predictors of NDD included non-Hispanic ethnicity, preexisting permanent pacemaker implantation/implantable cardioverter-defibrillator, and previous surgical aortic valve replacement. CONCLUSIONS: Most patients undergoing uncomplicated self-expanding Evolut transcatheter aortic valve replacement are discharged the next day. This study found that NDD can be predicted from baseline patient characteristics and was associated with favorable 30-day and 1-year outcomes, including low rates of permanent pacemaker implantation and readmission.

Predictors of follow-up care for critically-ill patients with seizures and epileptiform abnormalities on EEG monitoring.

OBJECTIVE: Post-hospitalization follow-up visits are crucial for preventing long-term complications. Patients with electrographic epileptiform abnormalities (EA) including seizures and periodic and rhythmic patterns are especially in need of follow-up for long-term seizure risk stratification and medication management. We sought to identify predictors of follow-up. METHODS: This is a retrospective cohort study of all patients (age ≥ 18 years) admitted to intensive care units that underwent continuous EEG (cEEG) monitoring at a single center between 01/2016-12/2019. Patients with EAs were included. Clinical and demographic variables were recorded. Follow-up status was determined using visit records 6-month post discharge, and visits were stratified as outpatient follow-up, neurology follow-up, and inpatient readmission. Lasso feature selection analysis was performed. RESULTS: 723 patients (53 % female, mean (std) age of 62.3 (16.4) years) were identified from cEEG records with 575 (79 %) surviving to discharge. Of those discharged, 450 (78 %) had outpatient follow-up, 316 (55 %) had a neurology follow-up, and 288 (50 %) were readmitted during the 6-month period. Discharge on antiseizure medications (ASM), younger age, admission to neurosurgery, and proximity to the hospital were predictors of neurology follow-up visits. Discharge on ASMs, along with longer length of stay, younger age, emergency admissions, and higher illness severity were predictors of readmission. SIGNIFICANCE: ASMs at discharge, demographics (age, address), hospital care teams, and illness severity determine probability of follow-up. Parameters identified in this study may help healthcare systems develop interventions to improve care transitions for critically-ill patients with seizures and other EA.

Inpatient Hospital Costs, Emergency Department Visits, and Readmissions for Revision Hip and Knee Arthroplasty.

BACKGROUND: Revision total hip arthroplasty (THA) and total knee arthroplasty (TKA) tremendously burden hospital resources. This study evaluated factors influencing perioperative costs, including emergency department (ED) visits, readmissions, and total costs-of-care within 90 days following revision surgery. METHODS: A retrospective analysis of 772 revision TKAs and THAs performed on 630 subjects at a single center between January 2007 and December 2019 was conducted. Cost data was available from January 2015 to December 2019 for 277 patients. Factors examined included comorbidities, demographic information, pre-operative Anesthesia Society of Anesthesiologists score, implant selection, and operative indication using mixed-effects linear regression models. RESULTS: Among 772 revisions (425 THA and 347 TKA), 213 patients required an ED visit, and 90 required hospital readmission within 90 days. There were 22.6% of patients who underwent a second procedure after their initial revision. Liver disease was a significant predictor of ED readmission for THA patients (multivariable OR [odds ratio]: 3.473, P = 0.001), while aseptic loosening, osteolysis, or instability significantly reduced the odds of readmission for TKA patients (OR: 0.368, P = 0.014). In terms of ED visits, liver disease increased the odds for THA patients (OR: 1.845, P = 0.100), and aseptic loosening, osteolysis, or instability decreased the odds for TKA patients (OR: 0.223, P < 0.001). Increased age was associated with increased costs in both THA and TKA patients, with significant cost factors including congestive heart failure for TKA patients (OR: $7,308.17, P = 0.004) and kidney disease for THA patients. Revision surgeries took longer than primary ones, with TKA averaging 3.0 hours (1.6 times longer) and THA 2.8 hours (1.5 times longer). CONCLUSION: Liver disease increases ED readmission risk in revision THA, while aseptic loosening, osteolysis, or instability decreases it in revision TKA. Increased age and CHF are associated with increased costs. These findings inform postoperative care and resource allocation in revision arthroplasty.

Income-Based Disparities in Outcomes Following Pediatric Appendectomy: A National Analysis.

BACKGROUND: Appendectomy remains a common pediatric surgical procedure with an estimated 80,000 operations performed each year. While prior work has reported the existence of racial disparities in postoperative outcomes, we sought to characterize potential income-based inequalities using a national cohort. METHODS: All non-elective pediatric (<18 years) hospitalizations for appendectomy were tabulated in the 2016-2020 National Inpatient Sample. Only those in the highest (HI) and lowest income (LI) quartiles were considered for analysis. Multivariable regression models were developed to assess the independent association of income and postoperative major adverse events (MAE). RESULTS: Of an estimated 87,830 patients, 36,845 (42.0%) were HI and 50,985 (58.0%) were LI. On average, LI patients were younger (11 [7-14] vs 12 [8-15] years, P < .001), more frequently insured by Medicaid (70.7 vs 27.3%, P < .05), and more commonly of Hispanic ethnicity (50.8 vs 23.4%, P < .001). Following risk adjustment, the LI cohort was associated with greater odds of MAE (adjusted odds ratio [AOR] 1.30 95% confidence interval [CI] 1.06-1.64). Specifically, low-income status was linked with increased odds of infectious (AOR 1.65, 95% CI 1.12-2.42) and respiratory (AOR 1.67, 95% CI 1.06-2.62) complications. Further, LI was associated with a $1670 decrement in costs ([2220-$1120]) and a +.32-day increase in duration of stay (95% CI [.21-.44]). CONCLUSION: Pediatric patients of the lowest income quartile faced increased risk of major adverse events following appendectomy compared to those of highest income. Novel risk stratification methods and standardized care pathways are needed to ameliorate socioeconomic disparities in postoperative outcomes.

Predictive analytics for cardiovascular patient readmission and mortality: An explainable approach.

BACKGROUND: Cardiovascular patients experience high rates of adverse outcomes following discharge from hospital, which may be preventable through early identification and targeted action. This study aimed to investigate the effectiveness and explainability of machine learning algorithms in predicting unplanned readmission and death in cardiovascular patients at 30 days and 180 days from discharge. METHODS: Gradient boosting machines were trained and evaluated using data from hospital electronic medical records linked to hospital administrative and mortality data for 39,255 patients admitted to four hospitals in New South Wales, Australia between 2017 and 2021. Sociodemographic variables, admission history, and clinical information were used as potential predictors. The performance was compared to LASSO regression, as well as the HOSPITAL and LACE risk score indices. Important risk factors identified by the gradient-boosting machine model were explored using Shapley values. RESULTS: The models performed well, especially for the mortality outcomes. Area under the receiver operating characteristic curve values were 0.70 for readmission and 0.87-0.90 for mortality using the full gradient boosting machine algorithms. Among the top predictors for 30-day and 180-day readmission were increased red cell distribution width, old age (especially above 80 years), high measured troponin and urea levels, not being married or in a relationship, and low albumin levels. For mortality, these included increased red cell distribution width, old age (especially older than 70 years), high measured troponin and urea levels, high neutrophil and monocyte counts, and low eosinophil and lymphocyte counts. The Shapley values gave clear insight into the dynamics of decision-tree-based models. CONCLUSIONS: We demonstrated an explainable predictive algorithm to identify cardiovascular patients who are at high risk of readmission or death at discharge from the hospital and identified key risk factors.

Pediatric Tracheostomy Year in Review.

Tracheostomized children have higher mortality compared to adults due to smaller airway anatomy and greater medical complexity and are at high risk for life-threatening complications. Following new tracheostomy placement, caregivers are required to successfully complete extensive training before discharge home. Training for tracheostomy emergencies such as tube obstruction and accidental decannulation is challenging without real-life, hands-on experience, but simulation training has shown promising effects on improving caregiver knowledge and comfort in preparing for emergency situations. Readmissions and emergency department visits are common following discharge, with many due to respiratory illness. Inhaled antibiotics are frequently prescribed to treat bacterial respiratory infection. However, guidelines for standardized management of tracheostomy-related respiratory illness are not available. Although standardized decannulation protocols are utilized, evidence-based guidelines are lacking, and the role of routine polysomnogram prior to decannulation is unresolved. Several knowledge gaps in management of pediatric tracheostomy present the opportunity for future research to improve patient outcomes.

Cardiovascular outcomes in solid organ transplant recipients undergoing cardiac surgery: A matched pair analysis.

INTRODUCTION: This study aimed to compare postoperative outcomes after cardiac surgery in solid-organ transplant recipients and nontransplant patients. METHODS: We performed a retrospective analysis of 78 consecutive transplant recipients who underwent cardiac surgery at Asan Medical Center between 2000 and 2022 and were matched with 312 nontransplant patients who underwent cardiac surgery at a 1:4 ratio. The outcomes included 30-day mortality, all-cause death, cardiac death, readmission, and cardiac readmission. RESULTS: There was no significant difference in baseline characteristics between the two groups. The most common type of cardiac surgery performed in solid organ transplant recipients was isolated valve surgery, followed by isolated CABG. The 30-day mortality was not significantly different between transplant recipients and nontransplant patients (3.9% vs. 3.5%; P > .99). Solid organ transplant recipients showed a higher all-cause mortality compared to nontransplant patients (29.1% vs. 14.3% at 5 years; P = .001); however, there was no significant difference in cardiac death between the two groups (2.6% vs. 3.2% at 5 years; P = .80). In addition, the readmission and cardiac readmission rates showed comparable findings to that of mortality. CONCLUSION: Cardiac surgery can be performed safely in solid organ transplant recipients, with postoperative cardiovascular outcomes comparable to those observed in nontransplant patients.

Characteristics and Hospital Outcomes of 1403 Patients Hospitalized at Community Hospitals With Ankylosing Spondylitis.

Background: In this study, we aimed to assess the hospital course, outcomes after hospitalization, and predictors of outcomes in patients with ankylosing spondylitis (AS). Methods: We included 1403 patients with AS between 2016 and 2021 who were identified using International Classification of Disease (ICD) codes from a large for-profit healthcare system database. Demographics and clinical characteristics were compared between those who had a favorable outcome, defined as being discharged to home without readmission within 3 months of discharge, versus those who had an unfavorable outcome. A stepwise logistic regression was used to identify demographic and clinical characteristics associated with home discharge and readmission. Results: The mean age for all AS patients was 56.06 ± 17.01 years, which was younger in the favorable outcome group, and 82.47% of patients were discharged to home after the average length of stay of 3.72 ± 4.09 days, also shorter in the favorable outcome group. Of 1403 patients, 37.56% were readmitted within 3 months of discharge, at a lower rate in the group with home discharge. Opioids were the most commonly used medication during hospitalization (67.07%), prescribed at a lower rate in the favorable outcome group. Medical coverage by Medicare and Medicaid, fall at admission, hospital-acquired anemia, steroid, acetaminophen, muscle relaxant use, and an increased dose of morphine milligram equivalent at discharge were significantly associated with decreased odds of home discharge. Surgical procedures during admission, gastrointestinal complications, discharge to inpatient rehabilitation units, and use of benzodiazepine were associated with an increased risk of readmission within 3 months. Conclusion: Recognizing factors that put patients with AS at risk of unfavorable outcomes is useful information to improve patient care during hospitalization.

Risk Factors for Unexpected Admission Following Lumbar Spine Laminectomy: A National Database Study.

Introduction Laminectomy is one of the most common orthopedic spine surgeries performed in the United States. Compared to other spine operations such as fusions, laminectomies in isolation are of lower morbidity. However, complications may arise that result in readmission to an inpatient healthcare facility. The purpose of this study is to identify the demographics and risk factors associated with unplanned 30-day readmission following a laminectomy. Methods The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database was queried for patients who underwent a laminectomy procedure from 2015 to 2019 using CPT code 63030. This query yielded 61,708 cases. Demographic, lifestyle, comorbidity, and peri-operative factors were recorded. Independent samples Student's t-tests, chi-squared, and, where appropriate, Fisher's exact tests were used in univariate analyses to identify demographic, lifestyle, and peri-operative variables related to 30-day readmission following a laminectomy procedure. Multivariate logistic regression modeling was subsequently performed. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated and reported. Results Of the 61,708 patients included in our sample, 2,359 were readmitted within 30 days of surgery, corresponding to a readmission rate of 3.82%. Results of the univariate analysis revealed statistically significant relationships between readmission status and the following patient variables: patient age, sex, BMI, ASA classification, race, bleeding disorder, chronic obstructive pulmonary disease (COPD), diabetes, hypertension, congestive heart failure (CHF), chronic steroid use, total operative time, and tobacco use (p < 0.05). Multivariate logistic regression modeling confirmed that the following patient variables were associated with statistically significantly increased odds of readmission: age greater than 65 (p < 0.05), female sex (p = 0.013), bleeding disorder (p = 0.011), diabetes (p = 0.006), current smoker (p = 0.010), COPD (p < 0.001), steroid use (p = 0.006), ASA Class II or above (p < 0.05), and total operative time (p < 0.001). Conclusion Unplanned 30-day readmission after laminectomy is infrequent. However, increasing age, female sex, steroid use, current smokers, bleeding disorders, diabetes, COPD, CHF, a higher ASA classification, and longer operative times are independent risk factors for readmission following laminectomy.

Incidence and Predictors of Readmissions to Non-Index Hospitals After Transcatheter Aortic Valve Implantation in the Contemporary Era in New South Wales, Australia.

BACKGROUND: In Australia, transcatheter aortic valve implantation (TAVI) is only performed in a limited number of specialised metropolitan centres, many of which are private hospitals, making it likely that TAVI patients who require readmission will present to another (non-index) hospital. It is important to understand the impact of non-index readmission on patient outcomes and healthcare resource utilisation. METHOD: We analysed linked hospital and death records for residents of New South Wales, Australia, aged ≥18 years, who had an emergency readmission within 90 days following a TAVI procedure in 2013-2022. Mixed-effect, multi-level logistic regression models were used to evaluate predictors of non-index readmission, and associations between non-index readmission and readmission length of stay, 90-day mortality, and 1-year mortality. RESULTS: Of 4,198 patients (mean age, 82.7 years; 40.6% female) discharged alive following TAVI, 933 (22.2%) were readmitted within 90 days of discharge. Over three-quarters (76.0%) of those readmitted returned to a non-index hospital, with no significant difference in readmission principal diagnosis between index hospital and non-index hospital readmissions. Among readmitted patients, independent predictors of non-index readmission included: residence in regional or remote areas, lower socio-economic status, having a pre-procedure transfer, and a private index hospital. Readmission length of stay (median, 4 days), 90-day mortality (adjusted odds ratio [OR] 1.04, 95% confidence interval [CI] 0.56-1.96) and 1-year mortality (adjusted OR 1.01, 95% CI 0.64-1.58) were similar between index and non-index readmissions. CONCLUSIONS: Non-index readmission following TAVI was highly prevalent but not associated with increased mortality or healthcare utilisation. Our results are reassuring for TAVI patients in regional and remote areas with limited access to return to index TAVI hospitals.

Generalizability of machine learning models predicting 30-day unplanned readmission after primary total knee arthroplasty using a nationally representative database.

Unplanned readmission after primary total knee arthroplasty (TKA) costs an average of US $39,000 per episode and negatively impacts patient outcomes. Although predictive machine learning (ML) models show promise for risk stratification in specific populations, existing studies do not address model generalizability. This study aimed to establish the generalizability of previous institutionally developed ML models to predict 30-day readmission following primary TKA using a national database. Data from 424,354 patients from the ACS-NSQIP database was used to develop and validate four ML models to predict 30-day readmission risk after primary TKA. Individual model performance was assessed and compared based on discrimination, accuracy, calibration, and clinical utility. Length of stay (> 2.5 days), body mass index (BMI) (> 33.21 kg/m2), and operation time (> 93 min) were important determinants of 30-day readmission. All ML models demonstrated equally good accuracy, calibration, and discriminatory ability (Brier score, ANN = RF = HGB = NEPLR = 0.03; ANN, slope = 0.90, intercept = - 0.11; RF, slope = 0.93, intercept = - 0.12; HGB, slope = 0.90, intercept = - 0.12; NEPLR, slope = 0.77, intercept = 0.01; AUCANN = AUCRF = AUCHGB = AUCNEPLR = 0.78). This study validates the generalizability of four previously developed ML algorithms in predicting readmission risk in patients undergoing TKA and offers surgeons an opportunity to reduce readmissions by optimizing discharge planning, BMI, and surgical efficiency.

Home-based management on hospital re-admission rates in COPD patients: A systematic review.

AIM: To determine the impact of home-based management on hospital re-admission rates in patients with chronic obstructive pulmonary disease (COPD). DESIGN: Systematic review methodology was utilized, combining meta-analysis, where appropriate, or a narrative analysis of the data from included studies. DATA SOURCES: Electronic databases CINAHL, MEDLINE, PubMed, Embase and SAGE journals for primary papers, 2015 to 2021, were searched between December 2020 and March 2021, followed by hand-searching key journals, and reference lists of retrieved papers. METHODS: The review followed the guidance of PRISMA. Data were extracted using a predesigned data extraction tool. Quality appraisal was undertaken using RevMan 'risk of bias' tool. Meta-analysis was undertaken using RevMan software. RESULTS: This review integrates evidence from eight studies, five Random Control Trials, two observational studies and one retrospective study. The studies span three continents, Asia, Europe and North America, and include 3604 participants with COPD. Home-based management in patients with COPD resulted in a statistically significant reduction in rates of hospital readmission. For the outcomes, length of stay and mortality, while slightly in favour of home-based management, the results were not statistically significant. CONCLUSION: Given the burden of COPD on healthcare systems, and crucially on individuals, this review identified a reduction in hospital re-admission rate, a clinically important outcome. IMPACT: This study focused on the impact on hospital re-admission rates among the COPD patient cohort when home-based management was involved. A statistically significant reduction in rates of re-admission to the hospital was identified. This is positive for the patient, in terms of hospital avoidance, and reduces the burden on hospital systems. Further research is needed to determine the impact on cost-effectiveness and to quantify the most ideal type of care package that would be recommended for home-based management.

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.

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.

Impact of the method of calculating 30-day readmission rate after hospitalization for heart failure. Data from the VancOuver CoastAL Acute Heart Failure (VOCAL-AHF) registry.

BACKGROUND: Thirty-day readmission rate after heart failure (HF) hospitalization is widely used to evaluate healthcare quality. Methodology may substantially influence estimated rates. We assessed the impact of different definitions on HF and all-cause readmission rates. METHODS: Readmission rates were examined in 1,835 patients discharged following HF hospitalization using 64 unique definitions derived from five methodological factors: (1) ICD-10 codes (broad vs narrow), (2) index admission selection (single admission only first-in-year vs. random sample; or multiple admissions in year with vs. without 30-day blanking period), (3) variable denominator (number alive at discharge vs. number alive at 30-days), (4) follow-up period start (discharge date vs day following discharge), and (5) annual reference-period (calendar vs fiscal). The impact of different factors was assessed using linear-regression. RESULTS: The calculated 30-day readmission rate for HF varied more than 2-fold depending solely on the methodological approach (6.5% to 15.0%). All-cause admission rates exhibited similar variation (18.8% to 29.9%). The highest rates included all consecutive index admissions (HF 11.1-15.0%, all-cause 24.0-29.9%), and lowest only one index admission per patient per year (HF 6.5-11.3%, all-cause 18.8-22.7%). When including multiple index admissions and compared to blanking the 30-days post-discharge, not blanking was associated with 2.3% higher readmission rates. Selecting a single admission per year with a first-in-year approach lowered readmission rates by 1.5%, while random-sampling admissions lowered estimates further by 5.2% (p<0.001). CONCLUSION: Calculated 30-day readmission rates varied more than 2-fold by altering methods. Transparent and consistent methods are needed to ensure reproducible and comparable reporting.

Association of lactate/albumin ratio with 3-month readmission risk in heart failure patients: a retrospective study.

AIMS: The predictive value of the lactate/albumin ratio (LAR) in mortality is established in various conditions, yet its relevance to 3-month readmission risk in Chinese adults with heart failure (HF) remains unclear. METHOD AND RESULTS: Analysing data from 957 patients with HF at Zigong Fourth People's Hospital, Sichuan, China (December 2016 to June 2019), we assessed baseline characteristics, vital signs, comorbidities, and prescriptions. LAR demonstrated a linear correlation with 3-month readmission risk (HR = 1.60, 95% CI: 1.19-2.16). Tertile 3 (≥-0.48) exhibited higher risk than tertile 1 (<-0.83) and tertile 2 [-0.83, -0.48), with HRs and 95% CI of 1.49 (1.06-2.10), 1.43 (1.01-2.02), 1.48 (1.03-2.12), respectively. Subgroup and sensitivity analyses affirmed consistent influence of LAR on 3-month readmission risk for HF. CONCLUSIONS: Higher LAR significantly correlates with increased 3-month readmission risk in Chinese adult patients with HF, suggesting LAR is a valuable predictor for early readmission.

Comparative effectiveness of ehealth self-management interventions for patients with heart failure: A Bayesian network meta-analysis.

OBJECTIVE: This study evaluated the effectiveness of electronic self-management support interventions in reducing all-cause mortality, cardiovascular mortality, readmission rates, and HF-related readmission in heart failure patients. METHODS: Following the PRISMA-P guidelines and PRISMS taxonomy, we searched Pubmed, Cochrane Library, and Embase for RCTs and trials of electronic health technologies for heart failure interventions. Develop support programs in advance for education, monitoring, reminders, or a combination of these to screen and categorize studies. The Cochrane ROB2 tool was used to assess the risk of bias. RESULTS: The monitoring interventions may improve all-cause mortality (OR 0.77, 95% CI 0.63 to 0.93) and cardiovascular mortality (OR 0.75, 95% CI 0.61 to 0.93) compared to usual care. Reminder interventions were associated with significantly reducing readmission rates (OR 0.07, 95% CI 0.00 to 0.94). Mixed interventions were most effective in reducing HF-related readmission rates (OR 0.75, 95% CI 0.56 to 0.99). CONCLUSION: Electronic self-management interventions, particularly monitoring and reminders, can potentially improve outcomes of heart failure patients, including reducing all-cause mortality, cardiovascular mortality, and readmission rates. PRACTICE IMPLICATIONS: The eHealth model and the combination of self-management are significant for long-term intervention in patients with HF to improve their quality of life and prognosis.

Clinical outcomes of clostridioides difficile infection in the very elderly.

BACKGROUND: Clostridioides difficile infection (CDI) causes considerable morbidity, mortality, and economic cost. Advanced age, prolonged stay in healthcare facility, and exposure to antibiotics are leading risk factors for CDI. Data on CDI clinical outcomes in the very elderly patients are limited. METHODS: A retrospective cohort study of patients hospitalized between 2016 and 2018 with CDI. We evaluated demographic clinical and laboratory parameters. Major clinical outcomes were evaluated including duration of hospital stay, admission to intensive care unit (ICU), in-hospital mortality, 30 days post-discharge mortality, and readmission/mortality composite outcome. We compared patients aged up to 80 years (elderly) to those of 80 years old or more (very elderly). RESULTS: Of 196 patients included in the study, 112 (57%) were very elderly with a mean age of 86 versus 67 years in the elderly group. The duration of hospital stays, and intensive care unit admission frequency were significantly reduced in the very elderly (13 vs. 22 days p = 0.003 and 1.8% vs. 10.7% p = 0.01, respectively). No significant difference was found in the frequencies of in-hospital and in 30 days post-discharge mortality. CONCLUSIONS: In our cohort, the duration of hospital stay seemed to be shorter in the very elderly with no increase of in-hospital and post-discharge mortality. Although admitted less frequently to ICU, the in-hospital survival of the very elderly was not adversely affected compared to the elderly, suggesting that very advanced age per se should not be a major factor to consider in determining the prognosis of a patient with CDI.

Systematic Review and Meta-Analysis of the Financial Impact of 30-Day Readmissions for Selected Medical Conditions: A Focus on Hospital Quality Performance.

BACKGROUND: The Patient Protection and Affordable Care Act (ACA) established the Hospital Quality Initiative in 2010 to enhance patient safety, reduce hospital readmissions, improve quality, and minimize healthcare costs. In response, this study aims to systematically review the literature and conduct a meta-analysis to estimate the average cost of procedure-specific 30-day risk-standardized unplanned readmissions for Acute Myocardial Infarction (AMI), Heart Failure (HF), Pneumonia, Coronary Artery Bypass Graft (CABG), and Total Hip Arthroplasty and/or Total Knee Arthroplasty (THA/TKA). METHODS: Eligibility Criteria: This study included English language original research papers from the USA, encompassing various study designs. Exclusion criteria comprise studies lacking empirical evidence on hospital financial performance. INFORMATION SOURCES: A comprehensive search using relevant keywords was conducted across databases from January 1990 to December 2019 (updated in March 2021), covering peer-reviewed articles and gray literature. Risk of Bias: Bias in the included studies was assessed considering study design, adjustment for confounding factors, and potential effect modifiers. SYNTHESIS OF RESULTS: The review adhered to PRISMA guidelines. Employing Monte Carlo simulations, a meta-analysis was conducted with 100,000 simulated samples. Results indicated mean 30-day readmission costs: USD 16,037.08 (95% CI, USD 15,196.01-16,870.06) overall, USD 6852.97 (95% CI, USD 6684.44-7021.08) for AMI, USD 9817.42 (95% CI, USD 9575.82-10,060.43) for HF, and USD 21,346.50 (95% CI, USD 20,818.14-21,871.85) for THA/TKA. DISCUSSION: Despite the financial challenges that hospitals face due to the ACA and the Hospital Readmissions Reduction Program, this meta-analysis contributes valuable insights into the consistent cost trends associated with 30-day readmissions. CONCLUSIONS: This systematic review and meta-analysis provide comprehensive insights into the financial implications of 30-day readmissions for specific medical conditions, enhancing our understanding of the nexus between healthcare quality and financial performance.