Rate and Causes of Unplanned Hospital Returns within 60 Days following Head and Neck Surgery.

Introduction Unplanned hospital returns are frequent and may be preventable. Objective To comprehend the reasons for unplanned hospital readmission and return to the Outpatient Department (OPD) and Emergency Department (ED) within 60 days after discharge following head and neck surgery (HNS) at a tertiary care center in Saudi Arabia. Methods In the present retrospective study, the medical records of all patients who underwent HNS for benign and malignant conditions between January 2015 and June 2022 were reviewed in terms of demographic data, comorbidities, and reasons for hospital return. Results Out of 1,030 cases, 119 (11.55%) returned to the hospital within 60 days after discharge, 19 of which (1.84%) were readmitted. In total, 90 (8.74%) patients returned to the OPD, and 29 (2.82%), to the ED. The common reasons for readmission included infections (26.32%) and neurological symptoms (21.05%). For OPD visits, the common causes were hematoma (20%) and neurological symptoms (14.44%). For ED returns, the frequent causes were neurological symptoms (20.69%) and equipment issues (17.24%). Compared with nonreadmitted patients, readmitted patients had a higher preoperative baseline health burden when examined using the American Society of Anesthesiologists (ASA) score ( p = 0.004) and the Cumulative Illness Rating Scale (CIRS; p = 0.002). Conclusion The 60-day rates of unplanned hospital return to the OPD and ED were of 8.74% and 2.82% respectively, and 1.84% of the patients were readmitted. Hematoma, infections, and neurological symptoms were common causes. Addressing the common reasons may be beneficial to decrease postoperative hospital visits.

Effectiveness of the transitional care model in total knee arthroplasty patients: A randomized controlled trial.

AIM: This study has aimed to assess the effectiveness of the transitional care model (TCM) on functional status, perceived self-efficacy and healthcare utilization in patients undergoing total knee arthroplasty (TKA). METHOD: This randomized controlled study was conducted between February and November 2021 in a public hospital. The study randomly assigned patients to either a 6-week 'TCM' program or usual care. The sample size was n = 70, with each group comprising 35 individuals. Patient outcomes, including self-efficacy, functional status and healthcare service readmission rates, were monitored for TKA patients. RESULTS: Nursing care based on the 'TCM' was found to enhance functional status and increase the level of self-efficacy among TKA patients, leading to a decrease in healthcare service readmissions. CONCLUSIONS: The study recommends preparing patients and their families for the preoperative and postoperative processes. It emphasizes the importance of providing necessary training and consultancy services under the leadership of orthopaedic nurses responsible for TKA patient care, guided by the principles of TCM.

Machine learning in heart failure diagnosis, prediction, and prognosis: review.

Globally, cardiovascular diseases take the lives of over 17 million people each year, mostly through myocardial infarction, or MI, and heart failure (HF). This comprehensive literature review examines various aspects related to the diagnosis, prediction, and prognosis of HF in the context of machine learning (ML). The review covers an array of topics, including the diagnosis of HF with preserved ejection fraction (HFpEF) and the identification of high-risk patients with HF with reduced ejection fraction (HFrEF). The prediction of mortality in different HF populations using different ML approaches is explored, encompassing patients in the ICU, and HFpEF patients using biomarkers and gene expression. The review also delves into the prediction of mortality and hospitalization rates in HF patients with mid-range ejection fraction (HFmrEF) using ML methods. The findings highlight the significance of a multidimensional approach that encompasses clinical evaluation, laboratory assessments, and comprehensive research to improve our understanding and management of HF. Promising predictive models incorporating biomarkers, gene expression, and consideration of epigenetics demonstrate potential in estimating mortality and identifying high-risk HFpEF patients. This literature review serves as a valuable resource for researchers, clinicians, and healthcare professionals seeking a comprehensive and updated understanding of the role of ML diagnosis, prediction, and prognosis of HF across different subtypes and patient populations.

Pharmacist-Led Medication Management in Acute Geriatric Medicine and Its Associations with Rehospitalizations: A Cohort Study.

INTRODUCTION: Hospitalization and discharge in older patients are critical and clinical pharmacists have shown to ameliorate risks. Our objective was to assess their benefit as part of the geriatric team regarding rehospitalizations and related outcomes after discharge focusing on general practitioners' decision to continue or change discharge medication (GPD). METHODS: Prospective implementation study with 6-month follow-up in an acute geriatric clinic. Patients ≥70 years with comorbidities, impairments, and a current drug therapy were consecutively assigned to three groups: control group (CG), implementation group (IG), and wash-out group (WG). CG only received medication reconciliation (MR) at admission; IG and their hospital physicians received a pharmaceutical counseling and medication management; during WG, pharmaceutical counseling except for MR was discontinued. We used a negative-binomial model to calculate rehospitalizations and days spent at home as well as a recurrent events survival model to investigate recurrent rehospitalizations. RESULTS: One hundred thirty-two patients (mean age 82 years, 76 women [57.6%]) finished the project. In most of the models for rehospitalizations, a positive GPD led to fewer events. We also found an effect of pharmaceutical counseling on rehospitalizations and recurrent rehospitalizations in the CG versus WG but not in the CG versus IG models. 95.3% of medication recommendations by the pharmacist in the clinic setting were accepted. While the number of positive GPDs in CG was low (38%), pharmaceutical counseling directly to the GP in IG led to a higher number of positive GPDs (60%). DISCUSSION: Although rehospitalizations were not directly reduced by our intervention in the CG versus IG, the pharmacist's acceptance rate in the hospital was very high and a positive GPD led to fewer rehospitalization in most models.

Is it legitimate to use unplanned hospitalizations as a quality indicator for cancer patients? A retrospective French cohort study with special attention to the influence of social deprivation.

PURPOSE: Readmission indicators are used around the world to assess the quality of hospital care. We aimed to assess the relevance of this type of indicator in oncology, especially for socially deprived patients. Our objectives were (1) to assess the proportion of unplanned hospitalizations (UHs) in cancer patients, (2) to assess the proportion of UHs that were avoidable, i.e., related to poor care quality, and (3) to analyze cancer patients the effect of patients' deprivation level on the type of UH (avoidable UHs vs. unavoidable UHs). METHODS: In a French university hospital, we selected all hospitalizations over a year for a random sample of cancer patients. Based on medical records, we identified those among UHs due to avoidable health problems. We assessed the association between social deprivation, home-to-hospital distance, or home-to-general practitioner with the type of UH (avoidable vs. unavoidable) via a multivariate binary logit estimation. RESULTS: Among 2349 hospitalizations (355 patients), there were 383 UHs (16 %), among which 38% were avoidable. Among UHs, the European Deprivation Index was significantly associated with the risk of avoidable UHs, with a lower risk of avoidable UH for patients with medium or high social deprivation. CONCLUSION: Our results suggest that the use of UHs rate as a quality indicator is questionable in oncology. Indeed, the majority of UHs were not avoidable. Furthermore, within UHs, those involving patients with medium or high social deprivation are more often unavoidable in comparison with other patients.

Community Participation Transition After Stroke (COMPASS) Randomized Controlled Trial: Effect on Adverse Health Events.

OBJECTIVE: To compare adverse health events in intervention versus control group participants in the Community Participation Transition After Stroke trial to reduce barriers to independent living for community-dwelling stroke survivors. DESIGN: Randomized controlled trial. SETTING: Inpatient rehabilitation (IR) to home and community transition. PARTICIPANTS: Stroke survivors aged ≥50 years being discharged from IR who had been independent in activities of daily living prestroke (N=183). INTERVENTIONS: Participants randomized to intervention group (n=85) received home modifications and self-management training from an occupational therapist over 4 visits in the home. Participants randomized to control group (n=98) received the same number of visits consisting of stroke education. MAIN OUTCOME MEASURES: Death, skilled nursing facility (SNF) admission, 30-day rehospitalization, and fall rates after discharge from IR. RESULTS: Time-to-event analysis revealed that the intervention reduced SNF admission (cumulative survival, 87.8%; 95% confidence interval [CI], 78.6%-96.6%) and death (cumulative survival, 100%) compared with the control group (SNF cumulative survival, 78.9%; 95% CI, 70.4%-87.4%; P=.039; death cumulative survival, 87.3%; 95% CI, 79.9%-94.7%; P=.001). Thirty-day rehospitalization also appeared to be lower among intervention participants (cumulative survival, 95.1%; 95% CI, 90.5%-99.8%) than among control participants (cumulative survival, 86.3%; 95% CI, 79.4%-93.2%; P=.050) but was not statistically significant. Fall rates did not significantly differ between the intervention group (5.6 falls per 1000 participant-days; 95% CI, 4.7-6.5) and the control group (7.2 falls per 1000 participant-days; 95% CI, 6.2-8.3; incidence rate ratio, 0.78; 95% CI, 0.46-1.33; P=.361). CONCLUSIONS: A home-based occupational therapist-led intervention that helps stroke survivors transition to home by reducing barriers in the home and improving self-management could decrease the risk of mortality and SNF admission after discharge from rehabilitation.

Unplanned Readmissions in Children with Medical Complexity in Saudi Arabia: A Large Multicenter Study.

Background: Children with medical complexity (CMC) account for a substantial proportion of healthcare spending, and one-third of their expenditures are due to readmissions. However, knowledge regarding the healthcare-resource utilization and characteristics of CMC in Saudi Arabia is limited. Objectives: To describe hospitalization patterns and characteristics of Saudi CMC with an unplanned 30-day readmission. Methodology: This retrospective study included Saudi CMC (aged 0-14 years) who had an unplanned 30-day readmission at six tertiary centers in Riyadh, Jeddah, Dammam, Alahsa, and Almadina between January 2016 and December 2020. Hospital-based inclusion criteria focused on CMC with multiple complex chronic conditions (CCCs) and technology assistance (TA) device use. CMC were compared across demographics, clinical characteristics, and hospital-resource utilization. Results: A total of 9139 pediatric patients had unplanned 30-day readmission during the study period, of which 680 (7.4%) met the inclusion criteria. Genetic conditions were the most predominant primary pathology (66.3%), with one-third of cases (33.7%) involving the neuromuscular system. During the index admission, pneumonia was the most common diagnosis (33.1%). Approximately 35.1% of the readmissions were after 2 weeks. Pneumonia accounted for 32.5% of the readmissions. After readmission, 16.9% of patients were diagnosed with another CCC or received a new TA device, and the in-hospital mortality rate was 6.6%. Conclusion: The rate of unplanned 30-day readmissions in children with medical complexity in Saudi Arabia is 7.4%, which is lower than those reported from developed countries. Saudi children with CCCs and TA devices were readmitted approximately within similar post-discharge time and showed distinct hospitalization patterns associated with specific diagnoses. To effectively reduce the risk of 30-day readmissions, targeted measures must be introduced both during the hospitalization period and after discharge.

Nursing diagnoses and hospital readmission of patients with respiratory diseases: Findings from a case-control study.

AIM: The rate of readmission after hospitalisation for respiratory diseases has become a common and challenging clinical problem. Social and functional patient variables could help identify cases at high risk of readmission. The aim was to identify the nursing diagnoses that were associated with readmission after hospitalisation for respiratory disease in Spain. DESIGN: Case-control study within the cohort of patients admitted for respiratory disease during 2016-19 in a tertiary public hospital in Spain (n = 3781). METHODS: Cases were patients who were readmitted within the first 30 days of discharge, and their controls were the remaining patients. All nursing diagnoses (n = 130) were collected from the electronic health record. They were then grouped into 29 informative diagnostic categories. Clinical confounder-adjusted odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated using logistic regression models. RESULTS: The readmission rate was 13.1%. The nursing diagnoses categories 'knowledge deficit' (OR: 1.61; 95%CI: 1.13-2.31), 'impaired skin integrity and risk of ulcer infection' (OR: 1.45; 95%CI: 1.06-1.97) and 'activity intolerance associated with fatigue' (OR: 1.56; 95%CI: 1.21-2.01) were associated with an increased risk of suffering an episode of hospital readmission rate at 30% after hospital discharge, and this was independent of sociodemographic background, care variables and comorbidity. PATIENT OR PUBLIC CONTRIBUTION: The nursing diagnoses assigned as part of the care plan of patients during hospital admission may be useful for predicting readmissions.

Association of Inpatient Occupational Therapy Utilization With Reduced Risk for Psychiatric Readmission Among Veterans.

OBJECTIVE: The authors sought to investigate whether utilization of inpatient occupational therapy (OT) was associated with reduced risk for 30-day psychiatric readmission in the Veterans Health Administration (VHA). METHODS: The authors conducted a secondary analysis of VHA medical record data for veterans who received inpatient psychiatric care from 2015 to 2020 (N=176,889). Mixed-effects logistic regression was used to model psychiatric readmission within 30 days of discharge (yes or no) as a function of inpatient psychiatric OT utilization (none, one, two, three, or four or more encounters) and other care utilization (e.g., previous psychiatric hospitalization), as well as clinical (e.g., primary diagnosis), sociodemographic (e.g., race-ethnicity), and facility (e.g., complexity) characteristics. Sensitivity analyses were conducted to evaluate the robustness of findings (e.g., stratification by discharge disposition). RESULTS: Relatively few veterans received inpatient psychiatric OT (26.2%), and 8.4% were readmitted within 30 days. Compared with veterans who did not receive inpatient psychiatric OT, those with one (OR=0.76), two (OR=0.64), three (OR=0.67), or four or more encounters (OR=0.64) were significantly (p<0.001) less likely to be readmitted within 30 days. These findings were consistent across all sensitivity analyses. CONCLUSIONS: Veterans who received inpatient OT services were less likely to experience psychiatric readmission. A clear dose-response relationship between inpatient psychiatric OT and readmission risk was not identified. These findings suggest that OT services may facilitate high-value inpatient psychiatric care in the VHA by preventing readmissions that stymie recovery and incur high costs. Future research may establish the causality of this relationship, informing policy regarding increased access to inpatient psychiatric OT.

Hospital Readmission Rates for Patients Receiving In-Person vs. Telemedicine Discharge Follow-Up Care.

INTRODUCTION: Unplanned readmissions can be avoided by standardizing and improving the coordination of care after discharge. Telemedicine has been increasingly utilized; however, the quality of this care has not been well studied. Standardized measures can provide an objective comparison of care quality. The purpose of our study was to compare quality performance transitions of care management in the office vs telemedicine. METHODS: The Epic SlicerDicer tool was used to compare the percentage of encounters that were completed via telemedicine (video visits); or via in-person for comparison, Chi-squared tests were used. RESULTS: A total of 13,891 patients met the inclusion criteria during the study time frame. There were 12,846 patients in the office and 1,048 in the telemedicine cohort. The office readmission rate was 11.9% with 1,533 patients out of 12,846 compared with telemedicine with the rate of readmission at 12.1% with 126 patients out of 1,045 patients. The P-value for the Chi-squared test between the prepandemic and study time frame was 0.15 and 0.95, respectively. Demographic comparability was seen. DISCUSSION: Our study found a comparable readmission rate between patients seen via in-office and telemedicine for Transitions of Care Management (TCM) encounters. The findings of this study support the growing body of evidence that telemedicine augments quality performance while reducing cost and improving access without negatively impacting HEDIS performance in health care systems. CONCLUSION: Telemedicine poses little threat of negatively impacting HEDIS performance and might be as effective as posthospitalization traditional office care transitions of care management.

Acetazolamide As A Valuable Addition to Acute Heart Failure?

Consider IV Acetazolamide in addition to standard IV loop diuretic therapy in patients hospitalized for acute decompensated heart failure.1.

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.

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.

Increasing and sustaining discharges by noon - a multi-year process improvement project.

High hospital occupancy degrades emergency department performance by increasing wait times, decreasing patient satisfaction, and increasing patient morbidity and mortality. Late discharges contribute to high hospital occupancy by increasing emergency department (ED) patient length of stay (LOS). We share our experience with increasing and sustaining early discharges at a 650-bed academic medical center in the United States. Our process improvement project followed the Institute of Medicine Model for Improvement of successive Plan‒Do‒Study‒Act cycles. We implemented multiple iterative interventions over 41 months. As a result, the proportion of discharge orders before 10 am increased from 8.7% at baseline to 22.2% (p < 0.001), and the proportion of discharges by noon (DBN) increased from 9.5% to 26.8% (p < 0.001). There was no increase in balancing metrics because of our interventions. RA-LOS (Risk Adjusted Length Of Stay) decreased from 1.16 to 1.09 (p = 0.01), RA-Mortality decreased from 0.65 to 0.61 (p = 0.62) and RA-Readmissions decreased from 0.92 to 0.74 (p < 0.001). Our study provides a roadmap to large academic facilities to increase and sustain the proportion of patients discharged by noon without negatively impacting LOS, 30-day readmissions, and mortality. Continuous performance evaluation, adaptability to changing resources, multidisciplinary engagement, and institutional buy-in were crucial drivers of our success.

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.

Fatores Associados aos Custos do Tratamento no Primeiro Ano após Implantes Iniciais ou Trocas de Geradores de Pulsos de Marca-passos Cardíacos / Factors Associated with the Treatment Costs within the First Year after Pacemaker Implantation or Pulse Generator Replacement

Resumo Fundamento O uso de marca-passos cardíacos artificiais tem crescido constantemente, acompanhando o envelhecimento populacional. Objetivos Determinar as taxas de readmissões hospitalares e complicações após implante de marca-passo ou troca de gerador de pulsos e avaliar o impacto desses eventos nos custos anuais do tratamento sob a perspectiva do Sistema Único de Saúde (SUS). Métodos Registro prospectivo, com dados derivados da prática clínica assistencial, coletados na hospitalização índice e durante os primeiros 12 meses após o procedimento cirúrgico. O custo da hospitalização índice, do procedimento e do seguimento clínico foram estimados de acordo com os valores reembolsados pelo SUS e analisados ao nível do paciente. Modelos lineares generalizados foram utilizados para estudar fatores associados ao custo total anual do tratamento, adotando-se um nível de significância de 5%. Resultados No total, 1.223 pacientes consecutivos foram submetidos a implante inicial (n= 634) ou troca do gerador de pulsos (n= 589). Foram observados 70 episódios de complicação em 63 pacientes (5,1%). A incidência de readmissões hospitalares em um ano foi de 16,4% (IC 95% 13,7% - 19,6%) após implantes iniciais e 10,6% (IC 95% 8,3% - 13,4%) após trocas de geradores. Doença renal crônica, histórico de acidente vascular encefálico, tempo de permanência hospitalar, necessidade de cuidados intensivos pós-operatórios, complicações e readmissões hospitalares mostraram um impacto significativo sobre o custo anual total do tratamento. Conclusões Os resultados confirmam a influência da idade, comorbidades, complicações pós-operatórias e readmissões hospitalares como fatores associados ao incremento do custo total anual do tratamento de pacientes com marca-passo.

Abstract Background The use of artificial cardiac pacemakers has grown steadily in line with the aging population. Objectives To determine the rates of hospital readmissions and complications after pacemaker implantation or pulse generator replacement and to assess the impact of these events on annual treatment costs from the perspective of the Unified Health System (SUS). Methods A prospective registry, with data derived from clinical practice, collected during index hospitalization and during the first 12 months after the surgical procedure. The cost of index hospitalization, the procedure, and clinical follow-up were estimated according to the values reimbursed by SUS and analyzed at the patient level. Generalized linear models were used to study factors associated with the total annual treatment cost, adopting a significance level of 5%. Results A total of 1,223 consecutive patients underwent initial implantation (n=634) or pulse generator replacement (n=589). Seventy episodes of complication were observed in 63 patients (5.1%). The incidence of hospital readmissions within one year was 16.4% (95% CI 13.7% - 19.6%) after initial implants and 10.6% (95% CI 8.3% - 13.4%) after generator replacements. Chronic kidney disease, history of stroke, length of hospital stays, need for postoperative intensive care, complications, and hospital readmissions showed a significant impact on the total annual treatment cost. Conclusions The results confirm the influence of age, comorbidities, postoperative complications, and hospital readmissions as factors associated with increased total annual treatment cost for patients with pacemakers.

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.

Patient Readmission for Ischemic Stroke: Risk Factors and Impact on Mortality.

Patient readmission for ischemic stroke significantly strains the healthcare and medical insurance systems. Current understanding of the risk factors associated with these readmissions, as well as their subsequent impact on mortality within China, remains insufficient. This is particularly evident in the context of comprehensive, contemporary population studies. This 4-year retrospective cohort study included 125 397 hospital admissions for ischemic stroke from 838 hospitals located in 22 regions (13 urban and 9 rural) of a major city in western China, between January 1, 2015 and December 31, 2018. The Chi-square tests were used in univariate analysis. Accounting for intra-subject correlations of patients' readmissions, accelerated failure time (AFT) shared frailty models were used to examine readmission events and pure AFT models for mortality. Risk factors for patient readmission after ischemic stroke include frequent admission history, male gender, employee's insurance, advanced age, residence in urban areas, index hospitalization in low-level hospitals, extended length of stay (LOS) during index hospitalization, specific comorbidities and subtypes of ischemic stroke. Furthermore, our findings indicated that an additional admission for ischemic stroke increased patient mortality by 16.4% (P < .001). Stroke readmission contributed to an increased risk of hospital mortality. Policymakers can establish more effective and targeted policies to reduce readmissions for stroke by controlling these risk factors.

Multi-Trajectories of Symptoms and their Associations with Unplanned 30-day Hospital Readmission among Patients with Heart Failure: A longitudinal study.

AIMS: This study aimed to uncover hidden patterns and predictors of symptom multi-trajectories within 30 days after discharge in patients with heart failure and assess the risk of unplanned 30-day hospital readmission in different patterns. METHODS AND RESULTS: The study was conducted from September 2022 to September 2023 in four third-class hospitals in Tianjin, China. A total of 301 patients with heart failure were enrolled in the cohort, and 248 patients completed a 30-day follow-up after discharge. Three multi-trajectory groups were identified: mild symptom status (24.19%), moderate symptom status (57.26%), and severe symptom status (18.55%). With the mild symptom status group as a reference, physical frailty, psychological frailty, and comorbid renal dysfunction were predictors of the moderate symptom status group. Physical frailty, psychological frailty, resilience, taking diuretics, and comorbid renal dysfunction were predictors of the severe symptom status group. Compared with the mild symptom status group, the severe symptom status group was significantly associated with high unplanned 30-day hospital readmission risks. CONCLUSIONS: This study identified three distinct multi-trajectory groups among patients with heart failure within 30 days after discharge. The severe symptom status group was associated with a significantly increased risk of unplanned 30-day hospital readmission. Common and different factors predicted different symptom multi-trajectories. Healthcare providers should assess the physical and psychological frailty and renal dysfunction of patients with heart failure before discharge. Inpatient care aimed at alleviating physical and psychological frailty and enhancing resilience may be important to improve patients' symptom development post-discharge.