Heart failure (HF) remains a significant global health issue and poses challenges to patient families and healthcare systems through index hospitalizations and subsequent readmissions. The readmission rate has been utilized as a quality indicator, and a proportion of readmissions are perceived preventable. However, the definitions and measures of preventability remain unclear and inconsistent, lacking an explicit integration, analysis, and critique of current evidence.

This scoping review aims to improve the understanding of the definitions and measures of preventable readmissions for patients with HF, by identifying the judgements in published literature and examining the reasonings behind them.

Systematic literature searches with a search strategy combining three compartments describing preventability, readmission, and HF were conducted. The inclusion and exclusion were performed against prespecified eligibility criteria.

A total of 15 papers were identified. Substantial heterogeneity was observed in study characteristics and judgement of preventability. The proportion of readmissions deemed preventable ranged vastly from 6.66 % to 86 % and required careful interpretation due to inconsistency of denominators. The reasonings behind preventability can be categorized into four groups based on nature, focus, and purpose.

There is currently no consensus on definitions and measures of preventable readmissions for patients with HF. Scattered research efforts were observed with inconsistent and unstandardized methods, criteria, and data used for judgement of preventability. Adopting an identical readmission calculation framework is critical for fair comparison. The timeframe of readmission is worth further reconsideration and investigation. Comprehensive, explicit, and disease-specific judgement criteria for preventable readmissions are urgently needed.

Background: Antimicrobial therapy is becoming less effective because of the rising microbial resistance. Surgical site infections (SSI) are one of the major complications that require modifications in the infection control policy for effective management. Objective/Aim: To develop a model for predicting the readmission rates post-SSI treatment and to identify prevalent microbial isolates and the respective trends in resistance patterns. Methodology: A retrospective study was carried out in a tertiary care setting in India. A total of 549 patients were diagnosed with SSI from January 1, 2016, to August 25, 2021, visiting orthopedics (n = 373), general surgery (n = 135), and neurosurgery (n = 41) departments were included in the study. Patient data and microbial isolate data were collected. Logistic regression with purposeful selection of covariates (p ≤ 0.25) was used to identify the predictors. The model fit was validated using the omnibus test. The area under the curve (AUC) was considered for the model discrimination. The resistance trend of microbial isolates was graphically represented. Results: One hundred thirty-seven (24.9%) were readmitted because of repeated infections. Readmission happened with a mean of 152 ± 32 days post-surgery was estimated. Uni-variable logistic regression showed 40 significant variables. The multi-variable logistic regression eliminated three variables because of insufficient comparator levels. Collinearity statistics further excluded two variables, i.e., reconstruction type of surgery and peripheral surgical area (variance inflation factor >10). The model showed an AUC of 0.77 and an accurate prediction of 77.8% (Akaike Information Criterion [AIC]: 568; Bayesian Information Criterion [BIC]: 722). Fifteen types of micro-organisms were isolated from 75.4% of readmitted patients. Methicillin-resistant Staphylococcus aureus (23.8%) was the primary isolate showing a resistance trend toward cloxacillin, ciprofloxacin, and ofloxacin (25.69%) equally, followed by erythromycin (18.4%) and gentamycin (6.25%). Conclusion: The current study predicted the post-SSI readmission rate and the microbial isolates along with their resistance patterns. The results of the study could serve as a tool for assessing and managing the factors leading to readmissions.

Hospital readmission after surgery is a key quality indicator. This nationwide cohort study aimed to assess readmission rates following esophagectomy and gastrectomy for cancer and identify associated risk factors.

Data were extracted from the Dutch Upper GI Cancer Audit (DUCA) for patients with esophagogastric cancer who underwent esophagectomy or gastrectomy with curative intent between January 2011 and June 2016. Logistic regression analysis identified risk factors for 30-day readmission.

In total, 5566 patients were included. Readmission within 30 days occurred in 483 of 3488 (13.8%) patients after esophagectomy and 243 of 2078 patients (11.7%) after gastrectomy. Both minor (Clavien Dindo 1-2) and major (Clavien Dindo ≥3) postoperative complications were independent predictors of readmission after esophagectomy (OR 2.99; 95%CI 2.23-4.02; p < 0.001 and OR 5.20; 95%CI 3.82-7.09; p < 0.001). Specific complications included pulmonary (OR 1.49; 95%CI 1.20-1.85; p < 0.001), gastrointestinal (OR 2.43; 95%CI 1.94-3.05; p < 0.001), and infectious (OR 2.27; 95%CI 1.60-3.22; p < 0.001). Prolonged length of stay (pLOS) was associated with higher readmission rates in patients without complications following esophagectomy (OR 1.91 95% CI 1.19-3.07; p = 0.008), but lower rates in those with complications (OR 0.65 95% CI 0.51-0.83; p < 0.001). For gastrectomy, postoperative complications were also linked to readmission (OR 3.18; 95%CI 2.30-4.40; p < 0.001), particularly gastrointestinal (OR 2.16; 95%CI 1.40-3.32; p < 0.001), and infectious (OR 3.80; 95%CI 2.53-5.71; p < 0.001).

Readmission after esophagogastric resection is common, particularly among patients with both minor and major postoperative complications. Prolonged stay after esophagectomy impacts readmission risk differently based on the presence of complications.

Readmission can be be related to the work of several stakeholders involved in the care of individuals throughout the community, including, for example, primary care and social care providers. A narrative review was performed to assess definitions and frequency of readmission for older adults found in previous research. In addition, a dataset for a cohort of older adults in Stockholm, Sweden, was used to quantify how different definitions of readmission affect frequency.

The review was based on pre-specified search criteria within PubMed and Embase databases. All studies based on a cohort of older adults with a primary objective to assess readmission to inpatient care, were included for the assessment of readmission criteria. The dataset was based on a cohort of older adults treated at a geriatric department in Stockholm during 2016. Estimations of readmission were performed with the most common criteria found in the narrative review.

The narrative review showed that definitions of readmission included predominantly time-based criteria, either alone or combined with additional criteria such as medical condition or readmitting department. Frequency of readmission based on different definitions varied substantially; a 14-day time interval implied a rate of 8.0% whilst a 30-day interval-more commonly used-rendered a rate of 12.6%. The density of readmissions per day was higher during the first weeks after discharge, and then dropped continuously.

Transparency on definitions is imperative in studies that include rates of readmission. The levels of readmission rates are highly dependent on the study population and its context. Furthermore, the actual value of readmission monitoring is dependent on what purpose it is supposed to fulfill, and it is essential to put it into context of all relevant stakeholders including, for example, the primary care providers and different social care providers throughout the community.

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 coronavirus disease 2019 (COVID-19)-related readmission during the Omicron era, including older adults and those with underlying immunocompromising conditions.

This retrospective study utilized the US PINC AI Healthcare Database to identify adult patients discharged alive from an index COVID-19 hospitalization between December 2021 and February 2024. Odds of 30-day COVID-19-related readmission to the same hospital were compared between patients who received remdesivir vs those who did not, after balancing characteristics of the two groups using inverse probability of treatment weighting (IPTW). Analyses were stratified by maximum supplemental oxygen requirement during index hospitalization.

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 {CI}]: 0.78 [.75-.80]), elderly population (3.7% vs 4.7%, respectively; 0.78 [.75-.81]), and those with underlying immunocompromising conditions (5.3% vs 6.2%, respectively; 0.86 [.80-.92]). These results were consistent irrespective of supplemental oxygen requirements.

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.

The COVID-19 pandemic may have exacerbated the state of ill-health among patients with schizophrenia. We examined the number of patients diagnosed with schizophrenia, the number of hospital admissions and outpatient contacts and the quality of treatment during the pandemic in comparison with the previous years.

We identified patients ≥18 years old registered in the Danish Schizophrenia Registry from 2016 to 2022. Using a generalized linear model, we estimated prevalence ratios (PR) and 95 % confidence intervals (CI) for each variable of interest.

A minor reduction in the number of new cases, admissions and outpatient contacts was seen during the first lockdown; however, there was no overall change across the pandemic period compared with the pre-pandemic period. We found no change in the proportion of patients who were interviewed using a diagnostic tool (37.0 % during pandemic vs 37.9 % pre-pandemic; PR = 0.87; 95 % CI 0.68-1.12) or received family intervention (57.7 % vs 57.1 %; PR = 0.97; 95 % CI 0.81-1.15), and no decrease was observed in the proportion of patients assessed for social support. Furthermore, no change in the proportion of patients re-admitted within 30 days (35.9 % vs 35.0 %; PR = 0.96; 95 % CI 0.88-1.07) or screened for suicide risk in relation to discharge (55.2 % vs 56.8 %; PR = 0.96; 95 % CI 0.97-1.09) was observed.

Recognition and treatment of schizophrenia was minimally affected during the first lockdown, but across the pandemic period no overall change was observed. The quality of treatment of schizophrenia was unchanged.

Emergency departments (EDs) encounter substantial challenges during peak vacation periods, including increased patient volumes, limited access to medical histories, language and cultural barriers, insurance complexities, and disruptions in continuity of care. These factors strain emergency department operations, resulting in prolonged wait times, diagnostic errors, and compromised care quality. This study reviews the literature to identify patient satisfaction indicators and common challenges and evaluate strategies to improve patient outcomes during vacation-related emergency department visits. Findings highlight critical issues in staffing and resource allocation, leading to delayed care. Limited interoperability of electronic health records (EHRs) often prevents access to essential patient information, increasing diagnostic errors and unnecessary repeat testing. Language and cultural barriers contribute to higher rates of misdiagnosis and lower patient satisfaction, while insurance and payment issues create delays, particularly for out-of-network or international patients. Effective strategies to address these challenges include the use of predictive analytics for better forecasting of patient volumes, specialized triage protocols, public health education campaigns, and telemedicine for remote management of non-critical conditions. These interventions help reduce wait times, optimize resource allocation, and improve patient satisfaction. By implementing adaptive approaches, such as flexible staffing models and enhanced electronic health record use, healthcare systems can significantly improve care delivery and patient outcomes during vacation seasons.

Annually, about 4000 US children undergo a tracheostomy procedure to provide a functional, safe airway. In the hospital, qualified staff monitor and address problems, but post-discharge this responsibility shifts entirely to caregivers. The stress and constant demands of caregiving for a child with a tracheostomy with or without ventilator negatively affect caregivers. The aims of the study are to relieve the burden and stress experienced by caregivers at home, improve safety and outcomes for children post-discharge, and identify facilitators and barriers to implementation of comprehensive pediatric discharge programs.

The Boosting REsources and cAregiver empowerment for Tracheostomy care at HomE (BREATHE Study) is a pragmatic two-arm, randomized trial with six sites across the US. Caregivers of a child with a tracheostomy are randomized to comparator ("Trach Me Home") or intervention ("Trach Plus"). The Comparator arm is the current gold standard focusing on caregiver education, technical skill building, and case management. The Intervention arm contains all elements of the Comparator plus educational resources, social support and communication with the outpatient pediatrician. Caregivers will complete three surveys: baseline (pre-discharge), 4-week and 6-month post-discharge. Outpatient pediatricians will complete a survey to assess self-confidence in caring for a child with tracheostomy and satisfaction with discharge communication. Interviews with clinicians and staff will identify facilitators and barriers to implementation. The study will examine whether the Intervention arm leads to lower caregiver burden, lower readmission rates and higher pediatrician satisfaction than Comparator arm.

The BREATHE Study will advance our understanding of how hospitals can support caregivers with a child with a tracheostomy as they resume life, work, and family activities after discharge.

Registered on clinicaltrials.gov (NCT06283953). February 28, 2024.

This study aimed to investigate the predictive capabilities of historical patient records to predict patient adverse outcomes such as mortality, readmission, and prolonged length of stay (PLOS).

Leveraging a de-identified dataset from a tertiary care university hospital, we developed an eXplainable Artificial Intelligence (XAI) framework combining tree-based and traditional machine learning (ML) models with interpretations and statistical analysis of predictors of mortality, readmission, and PLOS.

Our framework demonstrated exceptional predictive performance with a notable area under the receiver operating characteristic (AUROC) of 0.9625 and an area under the precision-recall curve (AUPRC) of 0.8575 for 30-day mortality at discharge and an AUROC of 0.9545 and AUPRC of 0.8419 at admission. For the readmission and PLOS risk, the highest AUROC achieved were 0.8198 and 0.9797, respectively. The tree-based models consistently outperformed the traditional ML models in all 4 prediction tasks. The key predictors were age, derived temporal features, routine laboratory tests, and diagnostic and procedural codes.

The study underscores the potential of leveraging medical history for enhanced hospital predictive analytics. We present an accurate and intuitive framework for early warning models that can be easily implemented in the current and developing digital health platforms to predict adverse outcomes accurately.

Gaps in discharge planning are experienced by 41% of hospital patients in Australia. There is an established body of knowledge regarding the features of the discharge process that need to be improved to avoid subsequent hospital readmission and enhance the discharge experience. However, many of these studies have focused solely on factors related to unplanned hospital readmissions and there has been limited success in operationalising improvements to the discharge process. The aim of this study was to explore and describe the factors that influence the decision to discharge adult medical patients from hospital, from patient, carer and staff perspectives.

A qualitative descriptive study was conducted in one acute medical ward in Melbourne, Australia. The study data were collected by observations of clinical practice and semi-structured interviews with patients, carers and staff. Participants were: i) English-speaking adults identified for discharge home, ii) patient carers, and iii) staff involved in the discharge process. Observation data were analysed using content analysis and interviews data were analysed using thematic analysis.

Twenty-one discharges were observed, and 65 participants were interviewed: 21 patients, two carers, and 42 staff. Most patients (76%) were identified as being ready for discharge during morning medical rounds, and 90% of discharge decisions were made collaboratively by the medical team and the patient. Carers were observed to be notified in 15 discharges by the patient (n = 8), doctors (n = 4), or nursing staff (n = 3). Five themes were constructed from thematic analysis of interviews: Readiness for Home, Fragmented Collaboration, Health Literacy, Unrealistic Expectations, and Care beyond Discharge. A collaborative team and supportive carers were considered to enhance risk assessment and discharge planning, however fragmented communication between clinicians, and between clinicians and patients/carers was a barrier to discharge decision-making.

Our study highlights the need for a more coordinated approach to discharge decision-making that optimises communication with patients and carers and multidisciplinary workflows and reduces fragmentation. The importance of patient-centred care and a personalised approach to care are well established. However, there is a need to design systems to customise the entirety of the patient journey, including the approach to discharge decision making.

Total knee arthroplasty (TKA) can improve pain, quality of life, and functional outcomes. Although uncommon, postoperative complications are extremely consequential and thus must be carefully tracked and communicated to patients to assist their decision-making before surgery. Identification of the risk factors for complications and readmissions after TKA, taking into account common causes, temporal trends, and risk variables that can be changed or left unmodified, will benefit this process.

To assess readmission rates, early complications and their causes after TKA at 30 days and 90 days post-surgery.

This was a prospective and retrospective study of 633 patients who underwent TKA at our hospital between January 1, 2017, and February 28, 2022. Of the 633 patients, 28 were not contactable, leaving 609 who met the inclusion criteria. Both inpatient and outpatient hospital records were retrieved, and observations were noted in the data collection forms.

Following TKA, the 30-day and 90-day readmission rates were determined to be 1.1% (n = 7) and 1.8% (n = 11), respectively. The unplanned visit rate at 30 days following TKA was 2.6% (n = 16) and at 90 days was 4.6% (n = 28). At 90 days, the unplanned readmission rate was 1.4% (n = 9). Reasons for readmissions included medical (27.2%, n = 3) and surgical (72.7%, n = 8). Unplanned readmissions and visits within 90 days of follow-up did not substantially differ by age group (P = 0.922), body mass index (BMI) (P = 0.633), unilateral vs bilateral TKA (P = 0.696), or patient comorbidity status (30-day P = 0.171 and 90-day P = 0.813). Reoperation rates after TKA were 0.66% (n = 4) at 30 days and 1.15% (n = 8) at 90 days. The average length of stay was 6.53 days.

In this study, there was a low readmission rate following TKA. There was no significant correlation between readmission rate and patient factors such as age, BMI, and co-morbidity status.

In-hospital dysglycemia is associated with adverse outcomes. Identifying patients at risk of in-hospital dysglycemia early on admission may improve patient outcomes.

We analysed 117 inpatients admitted with pneumonia and type 2 diabetes monitored by continuous glucose monitoring. We assessed potential risk factors for in-hospital dysglycemia and adverse clinical outcomes.

Time in range (3.9-10.0 mmol/l) decreased by 2.9 %-points [95 % CI 0.7-5.0] per 5 mmol/mol [2.6 %] increase in admission haemoglobin A1c, 16.2 %-points if admission diabetes therapy included insulin therapy [95 % CI 2.9-29.5], and 2.4 %-points [95 % CI 0.3-4.6] per increase in the Charlson Comorbidity Index (CCI) (integer, as a measure of severity and amount of comorbidities). Thirty-day readmission rate increased with an IRR of 1.24 [95 % CI 1.06-1.45] per increase in CCI. In-hospital mortality risk increased with an OR of 1.41 [95 % CI 1.07-1.87] per increase in Early Warning Score (EWS) (integer, as a measure of acute illness) at admission.

Dysglycemia among hospitalised patients with pneumonia and type 2 diabetes was associated with high haemoglobin A1c, insulin treatment before admission, and the amount and severity of comorbidities (i.e., CCI). Thirty-day readmission rate increased with high CCI. The risk of in-hospital mortality increased with the degree of acute illness (i.e., high EWS) at admission. Clinical outcomes were independent of chronic glycemic status, i.e. HbA1c, and in-hospital glycemic status.

To develop machine learning (ML) models predicting unplanned readmission and reoperation among patients undergoing free flap reconstruction for head and neck (HN) surgery.

Data were extracted from the 2012-2019 NSQIP database. eXtreme Gradient Boosting (XGBoost) was used to develop ML models predicting 30-day readmission and reoperation based on demographic and perioperative factors. Models were validated using 2019 data and evaluated.

Four-hundred and sixty-six (10.7%) of 4333 included patients were readmitted within 30 days of initial surgery. The ML model demonstrated 82% accuracy, 63% sensitivity, 85% specificity, and AUC of 0.78. Nine-hundred and four (18.3%) of 4931 patients underwent reoperation within 30 days of index surgery. The ML model demonstrated 62% accuracy, 51% sensitivity, 64% specificity, and AUC of 0.58.

XGBoost was used to predict 30-day readmission and reoperation for HN free flap patients. Findings may be used to assist clinicians and patients in shared decision-making and improve data collection in future database iterations.

Burn injuries are a major cause of morbidity and mortality worldwide, affecting not only the patients but also their families. Family-based education and follow-up program are interventions that aim to improve the quality of life and psychosocial outcomes of patients with burns and their families. However, we find a lack of evidence on the effectiveness and feasibility of these programs in different settings and populations. This study aimed to evaluate the features of the family-based education and follow-up program (FBEFP), a pilot project that was developed and implemented at the Tabriz Sina Teaching Hospital in 2020 to improve its burn care system.

A mixed-methods approach was used to collect and analyze both quantitative and qualitative data from various sources, such as, questionnaires, medical records, interviews and observation notes, to assess the content, process, and outcome of the program. The study followed the three steps of the CDC's framework for program evaluation: describing the program, measuring its effectiveness, and providing recommendations for improvement.

The results of this study revealed the positive impacts of the FBEFP on the patients' physical, psychological, and social outcomes and quality of life. 4.8% of the people in the follow-up group were re-admitted, while this amount was 7.2% in the group without follow-up. Although the number of readmissions was less in the non-follow-up group, statistically no significant difference was observed between the two ratios before and after follow-up. In order to evaluate satisfaction rates, In the follow-up group, 72 patients and in the non-follow-up group, 38 patients were reached. After converting these data to normal distribution, using t-tests, it was determined that the difference between the two studied groups was highly significant. In other words, the follow-up process had favorable results on satisfaction of the studied people. However, the study also identified some challenges and barriers in implementing the program, such as lack of resources, staff training, and family involvement.

FBEFP is a promising intervention that enhances the well-being of patients with burns and their families. However, more evidence is needed to support its effectiveness and feasibility in different contexts and populations. The study also provided valuable insights into the benefits and challenges of implementing a Family-Based Education and Follow-up Program for patients with burns in a low-resource setting. The study contributed to the development of guidelines and recommendations for future research and practice in this field.

This study aimed to investigate the association between index trial participation status and 30-day unplanned readmission rates, causes, and outcomes in acute coronary syndrome (ACS) patients.

The National Readmission Database was analysed for all index hospitalizations with a principal diagnosis of ACS between October 2015 to November 2019, stratified by index trial participation status (International Classification of Diseases - 10th edition code: Z00.6). The 30-day unplanned readmission rates, causes and outcomes were analysed, including the assessment of factors associated with readmission. Multivariable regression analyses were reported as adjusted odds ratios (aOR) with 95 % confidence intervals (95 % CI). All analyses were weighted and utilized hierarchical multi-level organization.

A total of 2,066,328 cases with a principal diagnosis of ACS were included in the study, of which there were 4061 trial participants (0.2 %) and 189,240 (9.2 %) cases experienced unplanned 30-day readmission. Rates of unplanned 30-day readmission were similar between trial participants and non-participants (9.8 % vs. 9.2 %, p = 0.16). Consistently, after multivariable adjustment, there was no significant association between trial participation and unplanned 30-day readmissions (aOR 0.96, 95 % CI 0.86-1.07, p = 0.45). Compared with trial participants, the majority of readmissions in non-participants were related to cardiovascular conditions (55.2 % vs. 46.7 %, p = 0.005, respectively). There was no significant difference in all-cause mortality (5.5 % vs. 4.6 %, p = 0.368, respectively), but trial participants were more likely to develop major bleeding (3.5 % vs. 2.1 %, p = 0.044), ischemic stroke (4.0 % vs. 2.1 %, p = 0.008) and haemorrhagic stroke (2.0 % vs. 0.6 %, p < 0.001) at readmissions.

Overall rates of unplanned 30-day readmissions after ACS are similar between trial participants and non-participants, but non-participation in trials was associated with a higher likelihood of cardiovascular readmission.

Hospitals within the Veterans Affairs (VA) health care system exhibited growing use of observation care. It is unknown how this affected VA hospital performance since observation care is not included in acute inpatient measures. To examine changes in VA hospitalization outcomes and whether it was affected by shifting acute inpatient care to observation care. Longitudinal analysis of 986,355 acute hospitalizations and observation stays in 11 states 2011 to 2017. We estimated temporal changes in 30-day mortality, 30-day readmissions, costs, and length of stay (LOS) for all hospitalizations and 6 conditions in adjusted models. Changes in mortality and readmissions were compared including and excluding observation care. A 9% drop in acute hospitalizations was offset by a 157% increase in observation stays 2011 to 2017. A 30-day mortality decreased but readmissions did not when observation stays were included (all P < .05). Mean costs increased modestly; mean LOS was unchanged. There were differences by condition. VA hospital mortality decreased; there was no change in readmissions.

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).

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.

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.

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.

The economic burden of Clostridioides difficile infection (CDI) is considerable and mostly associated with a high frequency of hospitalizations. Numerous publications have demonstrated that CDI is associated with a higher risk of hospital readmission, but not always a specific rate or attributable to disease recurrence.

In this systematic review, we describe the incidence of 30-day CDI-associated readmission rates and the effect of active interventions. Three search engines were utilized for the literature search, and a total of 9 studies were included in this review. Hospital readmission proportions from interventional and observational studies were analyzed through meta-analysis with random effects.

Two thousand five hundred and twenty-one articles were identified. After screening full-text articles, 9 eligible articles published between 2002 and 2023 met the inclusion criteria. In total, 132,862 CDI patients were evaluated. Thirty-day CDI-associated readmissions were defined as either an ICD9/10 code indicating CDI admission with a prior admission within the past 30 days (n = 4) or a medical chart evaluation of signs and symptoms consistent with CDI (diarrhea) along with a positive diagnostic test (n = 5) with a prior hospitalization for CDI within the past 30 days. Meta-analysis of observational studies estimated 30-day CDI readmissions were 6% (95% CI, 5%-7%). Three studies evaluated the effect of active interventions to reduce CDI-associated 30-day readmission rates. Two of 3 interventions reduced the likelihood of CDI-associated 30-day readmissions.

This systematic review identified a 6% rate of 30-day CDI-associated hospital readmission. Antimicrobial stewardship efforts and the use of specific therapeutics were shown to reduce these rates.

Staffing is critical to hospital quality, but recent years have seen hospitals grappling with severe shortages, forcing them to rely on contract or agency staff for urgent patient care needs. This shift in staffing mix has raised questions about its impact on quality. Consequently, this study investigated whether the increased use of agency staff has affected healthcare quality in hospitals. Given the limited recent research on this topic, practitioners remain uncertain about the effectiveness of their staffing strategies and their potential impact on quality.

Drawing from agency theory, data were obtained from Definitive Healthcare which consolidates information from numerous public access databases pertaining to hospitals such as the American Hospital Association Annual Survey (hospital profile) and the Hospital Value-Based Purchasing Program (quality data). We conducted a cross-sectional study using a multivariable linear regression model (2021-2022) with appropriate organizational and market- level control variables. Quality was measured across eight variables while the independent variable of interest was agency labor cost ratio operationalized as the percentage of net patient revenue consumed by agency labor expense.

Our results suggested that the employment of agency staff was significantly and negatively associated with six of eight quality measures tested, including the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) star rating, Hospital Compare rating, the hospital Total Performance Score (TPS), and three of the four sub-domains that comprise the TPS: clinical domain score, person and community engagement domain score, and the efficiency and cost reduction score.

Our results indicated that the increased use of agency labor may have a significant negative influence on quality outcomes at the hospital level. Our findings support the premise that interventions that promote full-time staffing may be more supportive of the quality of care delivered as well as patients' perceptions of care.

The level of nurse-doctor interprofessional collaboration may influence patient outcomes, including mortality. To date, no systematic reviews have investigated the association between the quantity of nurse-doctor interprofessional collaboration and inpatient mortality. A systematic review was conducted. We included studies that measured the quantity of nurse-doctor interprofessional collaboration and in-patient mortality. Five databases (MEDLINE, EMBASE, PsycINFO, CINAHL, and the Cochrane Register) were searched. Two researchers undertook the title, abstract, and full-text screening. The risk of bias was determined using the Effective Public Health Practice Project (EPHPP) critical appraisal tool. Six reports from three observational studies met the inclusion criteria. Participants included 1.32 million patients, 29,591 nurses, and 191 doctors. The included studies had a high risk of bias. Of the three studies, one reported a significant association and one found no association between the quantity of nurse-doctor collaboration and mortality. The third study reported on the quantity of nurse-doctor collaboration but did not report the test of this association. We found no high-quality evidence to suggest the amount of nurse-doctor interprofessional collaboration was associated with mortality in medical and surgical inpatients. There is a need for further high-quality research to evaluate the association between the amount of nurse-doctor collaboration and patient outcomes.

Preventing readmission to hospital after giving birth is a key priority, as rates have been rising along with associated costs. There are many contributing factors to readmission, and some are thought to be preventable. Nurse and midwife understaffing has been linked to deficits in care quality. This study explores the relationship between staffing levels and readmission rates in maternity settings.

We conducted a retrospective longitudinal study using routinely collected individual patient data in three maternity services in England from 2015 to 2020. Data on admissions, discharges and case-mix were extracted from hospital administration systems. Staffing and workload were calculated in Hours Per Patient day per shift in the first two 12-hour shifts of the index (birth) admission. Postpartum readmissions and staffing exposures for all birthing admissions were entered into a hierarchical multivariable logistic regression model to estimate the odds of readmission when staffing was below the mean level for the maternity service.

64 250 maternal admissions resulted in birth and 2903 mothers were readmitted within 30 days of discharge (4.5%). Absolute levels of staffing ranged between 2.3 and 4.1 individuals per midwife in the three services. Below average midwifery staffing was associated with higher rates of postpartum readmissions within 7 days of discharge (adjusted OR (aOR) 1.108, 95% CI 1.003 to 1.223). The effect was smaller and not statistically significant for readmissions within 30 days of discharge (aOR 1.080, 95% CI 0.994 to 1.174). Below average maternity assistant staffing was associated with lower rates of postpartum readmissions (7 days, aOR 0.957, 95% CI 0.867 to 1.057; 30 days aOR 0.965, 95% CI 0.887 to 1.049, both not statistically significant).

We found evidence that lower than expected midwifery staffing levels is associated with more postpartum readmissions. The nature of the relationship requires further investigation including examining potential mediating factors and reasons for readmission in maternity populations.

Coronary artery disease (CAD) patients frequently face readmissions due to suboptimal disease management. Prediction models are pivotal for detecting early unplanned readmissions. This review offers a unified assessment, aiming to lay the groundwork for enhancing prediction models and informing prevention strategies.

A search through five databases (PubMed, Web of Science, EBSCOhost, Embase, China National Knowledge Infrastructure) up to September 2023 identified studies on prediction models for coronary artery disease patient readmissions for this review. Two independent reviewers used the CHARMS checklist for data extraction and the PROBAST tool for bias assessment.

From 12,457 records, 15 studies were selected, contributing 30 models targeting various CAD patient groups (AMI, CABG, ACS) from primarily China, the USA, and Canada. Models utilized varied methods such as logistic regression and machine learning, with performance predominantly measured by the c-index. Key predictors included age, gender, and hospital stay duration. Readmission rates in the studies varied from 4.8% to 45.1%. Despite high bias risk across models, several showed notable accuracy and calibration.

The study highlights the need for thorough external validation and the use of the PROBAST tool to reduce bias in models predicting readmission for CAD patients.

Stroke readmissions are considered a marker of health quality and may pose a burden to healthcare systems. However, information on the costs of post-stroke readmissions has not been systematically reviewed.

To systematically review information about the costs of hospital readmissions of patients whose primary diagnosis in the index admission was a stroke.

A rapid systematic review was performed on studies reporting post-stroke readmission costs in EMBASE, MEDLINE, and Web of Science up to June 2021. Relevant data were extracted and presented by readmission and stroke type. The original study's currency values were converted to 2021 US dollars based on the purchasing power parity for gross domestic product. The reporting quality of each of the included studies was assessed using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist.

Forty-four studies were identified. Considerable variability in readmission costs was observed among countries, readmissions, stroke types, and durations of the follow-up period. The UK and the USA were the countries reporting the highest readmission costs. In the first year of follow-up, stroke readmission costs accounted for 2.1-23.4%, of direct costs and 3.3-21% of total costs. Among the included studies, only one identified predictors of readmission costs.

Our review showed great variability in readmission costs, mainly due to differences in study design, countries and health services, follow-up duration, and reported readmission data. The results of this study can be used to inform policymakers and healthcare providers about the burden of stroke readmissions. Future studies should not solely focus on improving data standardization but should also prioritize the identification of stroke readmission cost predictors.

The scientific literature contains an abundance of prediction models for hospital readmissions. However, no review has yet synthesized their predictors across various patient populations. Therefore, our aim was to examine predictors of hospital readmissions across 13 patient populations.

An overview of systematic reviews was combined with a meta-analytical approach. Two thousand five hundred four different predictors were categorized using common ontologies to pool and examine their odds ratios and frequencies of use in prediction models across and within different patient populations.

Twenty-eight systematic reviews with 440 primary studies were included. Numerous predictors related to prior use of healthcare services (odds ratio; 95% confidence interval: 1.64; 1.42-1.89), diagnoses (1.41; 1.31-1.51), health status (1.35; 1.20-1.52), medications (1.28; 1.13-1.44), administrative information about the index hospitalization (1.23; 1.14-1.33), clinical procedures (1.20; 1.07-1.35), laboratory results (1.18; 1.11-1.25), demographic information (1.10; 1.06-1.14), and socioeconomic status (1.07; 1.02-1.11) were analyzed. Diagnoses were frequently used (in 37.38%) and displayed large effect sizes across all populations. Prior use of healthcare services showed the largest effect sizes but were seldomly used (in 2.57%), whereas demographic information (in 13.18%) was frequently used but displayed small effect sizes.

Diagnoses and patients' prior use of healthcare services showed large effects both across and within different populations. These results can serve as a foundation for future prediction modeling.

Peripheral artery disease (PAD) is associated with high rates of readmission following endovascular interventions and contributes to a significant hospital readmission burden. Quality metrics like hospital readmissions affect hospital performance, but must adjust to local trends. Our primary goal was to evaluate risk factors and readmission rates post-percutaneous peripheral intervention in a US-Mexico border city, at a single tertiary university hospital. We performed a retrospective review of patients with PAD undergoing first time peripheral intervention from July 2015 to June 2020. Among 212 patients, 58% were readmitted with median 235-day follow-up (inter-quartile range (IQR) 42-924); 35.3% of readmissions occurred within 30 days, and 30.2% of those were within 7 days. Median time to readmission was 62 days. Active smokers had 84% higher risk of readmission (hazard ratio (HR) 1.84, 95% CI 1.23-2.74, P < .01). Other significant factors noted were insurance status-Medicaid or uninsured (HR 1.94, 95% CI 1.22-3.09), prior amputation (HR 1.69, 95% CI 1.13-2.54), heart failure, both preserved (HR 4.35, 95% CI 2.07-9.16) and reduced ejection fraction (HR 1.88, 95% CI 1.14-3.10). Below the knee, interventions were less likely to be readmitted (adjusted HR .64, 95% CI 0.42-.96). Readmission rates were unrelated to medication adherence.

Late preterm and full-term infants comprise the majority of births in our hospital which serves a multicultural lower socioeconomic community. Patients give birth vaginally (normal birth, NB) or by cesarean birth (CB), and the majority of neonates are exclusively breastmilk fed until discharge. In this study we examined what factors within these two birth modes and feeding regimes of exclusive breast milk were associated with early postnatal readmission. Ideally, findings will aid initiatives to decrease readmission rates.

A retrospective cohort study was performed on maternal-infant pairs. All neonates from 2016 to 2018, exclusively breastmilk fed at discharge, born by NB (n = 4245) or CB (n = 1691), were grouped as non-Readmitted (Reference) or Readmitted within 30 days of discharge. Readmission reason was determined, and potential associations were identified using univariate analysis and multivariable logistic regression.

Rates of readmission were similar for both NB and CB infants (6.8% vs. 7.3%). In order, NB concerns were jaundice, infection, and feeding-this was reversed for the CB Group. NB readmission bilirubin levels were higher (293 ± 75 vs. 236 ± 112, μmol/L, NB:CB, p < 0.001). Factors associated with readmission for both groups were similar to previously published studies. Edinburgh Postnatal Depression Score (EPDS) was higher for Readmitted infant mothers. Importantly, for non-jaundice readmission EDPS categories indicated that both CB and NB mothers were more likely to have depression.

Early readmission of exclusively breastmilk-fed infants born by means of NB or CB is multifactorial. Early pregnancy mental health issues are associated with readmission, highlighting the potential effects of perinatal depression on neonatal health.

Administrators have focused on decreasing postoperative readmissions for cost reduction without fully understanding their preventability. This study describes the development and implementation of a surgeon-led readmission review process that assessed preventability.

A gastrointestinal surgical group at a tertiary referral hospital developed and implemented a template to analyze inpatient and outpatient readmissions. Monthly stakeholder assessments reviewed and categorized readmissions as potentially preventable or not preventable. Continuous variables were examined by the Student's t test and reported as means and standard deviations. Categorical variables were examined by the Pearson χ2 statistic and Fisher's exact test.

There were 61 readmission events after 849 inpatient operations (7.2%) and 16 after 856 outpatient operations (1.9%), the latter of which were all classified as potentially preventable. Colorectal procedures represented 65.6% of readmissions despite being only 37.2% of all cases. The majority (67.2%) of readmission events were not preventable. Compared to the not-preventable group, the potentially preventable group experienced more dehydration (30.0% vs 9.8%, P = .045) and ileostomy creation (78.6% vs 33.3%, P = .017). The potential for outpatient management to prevent readmission was significantly higher in the potentially preventable group (40.0% vs 0.0%, P < .001), as was premature discharge prevention (35.0% vs 0.0%, P < .001).

The use of the standardized template developed for analyzing readmission events after inpatient and outpatient procedures identified a disparate potential for readmission prevention. This finding suggests that a singular focus on readmission reduction is misguided, with further work needed to evaluate and implement appropriate quality-based strategies.

To describe the social services received by a 2016 Swedish cohort after discharge from inpatient geriatric care and to analyze the association between level of social services post-discharge and 30-day readmission.

Observational, closed-cohort study.

All patients admitted to 1 of 3 regionally operated inpatient geriatric care settings in Region Stockholm, Sweden, in 2016 (n = 7453).

Individual-level data from medical records and population registries were linked using unique personal identification numbers. Descriptive statistics were reported for 4 levels of municipal social services post-discharge: long-term care, 1 to 50 home help hours per month, >50 home help hours per month, and no home help. Multinomial logistic regression was performed to analyze the association between level of social services post-discharge and 3 outcomes within 30 days: readmission, death without readmission, or neither readmission nor death.

Results show that almost 11% of patients were discharged to long-term care and 54% received municipal home help services. Individuals with no municipal home help or with 1 to 50 hours per month were more likely to be readmitted within 30 days compared with those in long-term care. Living with more than 50 hours of help was not associated with an increased likelihood of 30-day readmission.

Patients who received inpatient geriatric care are significant users of municipal social services post-discharge. Living in long-term care or with extensive home help appears to be a protective factor in preventing readmission compared with more limited or no home help services. Care transitions for this frail patient group require careful social care planning. Supporting individuals discharged with fewer social service hours may help reduce readmissions.

The centralisation of rectal cancer management to high-volume oncology centres has translated to improved oncological and survival outcomes. We hypothesise that individual surgeon caseload, specialisation, and experience may be as significant in determining oncologic and postoperative outcomes in rectal cancer surgery.

A prospectively maintained colorectal surgery database was reviewed for patients undergoing rectal cancer surgery between January 2004 and June 2020. Data studied included demographics, Dukes' and TNM staging, neoadjuvant treatment, preoperative risk assessment scores, postoperative complications, 30-day readmission rates, length of stay (LOS), and long-term survival. Primary outcome measures were 30-day mortality and long-term survival compared to national and international standards and best practice guidelines.

In total, 87 patients were included (mean age: 66 years [range: 36-88]). The mean length of stay (LOS) was 16.5 days (SD 6.0). The median ICU LOS was 3 days (range 2-17). Overall, 30-day readmission rate was 16.4%. Twenty-four patients (26.4%) experienced ≥ 1 postoperative complication. The 30-day operative mortality rate was 3.45%. Overall 5-year survival rate was 66.6%. A significant correlation was observed between P-POSSUM scores and postoperative complications (p = 0.041), and all four variants of POSSUM, CR-POSSUM, and P-POSSUM scores and 30-day mortality.

Despite improved outcomes seen with centralisation of rectal cancer services at an institutional level, surgeon caseload, experience, and specialisation is of similar importance in obtaining optimal outcomes within institutions.

Hospital readmissions are core indicators of the quality of health care provision.

To understand factors associated with 30-day, all-cause hospital readmission rate for patients with COVID-19 in the United States during the early pandemic by utilizing the Nationwide Readmissions Database.

This retrospective study characterized the 30-day, all-cause hospital readmission rate for patients with COVID-19 in the United States during the early pandemic by utilizing the Nationwide Readmissions Database.

The 30-day, all-cause hospital readmission rate in this population was 3.2%. We found the most common diagnoses at readmission to be sepsis, acute kidney injury, and pneumonia. Chronic alcoholic liver cirrhosis and congestive heart failure were prominent predictors of readmission among patients with COVID-19. Moreover, we found that younger patients and patients from economically disadvantaged backgrounds were at higher risk of 30-day readmission. Acute complications during index hospitalization, including acute coronary syndrome, congestive heart failure, acute kidney injury, mechanical ventilation, and renal replacement therapy, also increased the risk of 30-day readmission for patients with COVID-19.

Based on the results of our study, we advise clinicians to promptly recognize patients with COVID-19 who are at high risk of readmission, and to subsequently manage their underlying comorbidities, to institute timely discharge planning, and to allocate resources to underprivileged patients in order to decrease the risk of 30-day hospital readmissions.

Increasing number of nurse prescribers could be part of a solution to the shortage of physicians, improve access to treatment and curb the rise in healthcare costs; however, readmissions after nurse prescribers' appointments are under-researched.

To describe and compare clients' initial appointments with nurse prescribers and physicians. In addition, client readmissions within 60 days in the target organisation after nurse prescribers' and physicians' appointments were investigated.

Retrospective register-based follow-up study.

Data included client appointments (n = 3986) with nurse prescribers and physicians, and clients' readmissions (n = 9038) from 1 January 2018 to 31 December 2019 from one hospital district in Finland. Data were analysed statistically using frequencies, percentages, rate ratios and cross-tabulation. STROBE checklist was used.

Initial appointments including trimethoprim, pivmecillinam, phenoxymethyl penicillin, chloramphenicol, fusidic acid and cephalexin prescriptions with nurse prescribers (n = 36) were 2131, and physicians (n = 140) 1855. On average, client readmissions (within 60 days) per initial appointment were 2.10 after appointments with nurse prescribers and 2.46 after physicians. After initial appointments, including phenoxymethyl penicillin prescriptions, with nurse prescribers, clients had more readmissions in all age groups than after initial appointments with physicians. However, in all, after initial appointments with physicians, clients had a higher proportion of readmissions.

Clients have fewer readmissions after appointments with nurse prescribers than physicians, including the same prescriptions. Nurse prescribers' skills may not have been fully utilised. Physicians treated many patients whose diseases nurse prescribers might have been able to treat based on the nurse prescribers' rights. However, physician clients may have more demanding service requirements.

Unplanned readmissions after colorectal cancer (CRC) surgery are common, expensive, and result from failure to progress in postoperative recovery. The context of their preventability and extent of predictability remains undefined. This study aimed to define the 30-day unplanned readmission (UR) rate after CRC surgery, identify risk factors, and develop a prediction model with external validation.

Consecutive patients who underwent CRC surgery between 2012 and 2017 at Christchurch Hospital were retrospectively identified. The primary outcome was UR within 30 days after index discharge. Statistically significant risk factors were identified and incorporated into a predictive model. The model was then externally evaluated on a prospectively recruited dataset from 2018 to 2019.

Of the 701 patients identified, 15.1% were readmitted within 30 days of discharge. Stoma formation (OR 2.45, 95% CI 1.59-3.81), any postoperative complications (PoCs) (OR 2.27, 95% CI 1.48-3.52), high-grade PoCs (OR 2.52, 95% CI 1.18-5.11), and rectal cancer (OR 2.11, 95% CI 1.48-3.52) were statistically significant risk factors for UR. A clinical prediction model comprised of rectal cancer and high-grade PoCs predicted UR with an AUC of 0.64 and 0.62 on internal and external validation, respectively.

URs after CRC surgery are predictable and occur within 2 weeks of discharge. They are driven by PoCs, most of which are of low severity and develop after discharge. Atleast 16% of readmissions are preventable by management in an outpatient setting with appropriate surgical expertise. Targeted outpatient follow-up within two weeks of discharge is therefore the most effective transitional-care strategy for prevention.

Atypical meningiomas represent approximately 20% of all intracranial meningiomas and are characterized by distinct histopathological criteria and an increased risk of postoperative recurrence. Recently, quality indicators have been introduced to monitor quality of the delivered care.

Which quality indicators/outcome measures are being applied in patients being operated for atypical meningiomas? What are risk factors associated with poor outcome? How is the surgical outcome and which quality indicators are reported in the literature?

The primary outcomes of interest were 30-days readmission-, 30-day reoperation-, 30-day mortality-, 30-day nosocomial infection- and the 30-day surgical site infection (SSI) rate, CSF-leakage, new neurological deficit, medical complications, and lengths of stay. The secondary aim was the identification of prognostic factors for the mentioned primary outcomes. A systematic review of the literature was performed screening studies for the mentioned outcomes.

We included 52 patients. 30-days outcomes in terms of unplanned reoperation were 0%, unplanned readmission 7.7%, mortality 0%, nosocomial infection 17.3%, and SSI 0%. Any adverse event occurred in 30.8%. Preoperative C-reactive protein over 5 ​mg/l was independent factor for the occurrence of any postoperative adverse event (OR: 17.2, p ​= ​0.003). A total of 22 studies were included into the review.

The 30-days outcomes at our department were comparable with reported outcomes in the literature. Currently applied quality indicators are helpful in determining the postoperative outcome but mainly report the indirect outcome after surgery and are influenced of patient, tumor and treatment related factors. Risk adjustment is vital.

Integrated care is seen as integral in combating the current and projected resource scarcity in the healthcare systems of developed economies. Previous research finds positive effects from implementing intermediate care but there is a lack of research on how this shift towards care integration has affected traditional quality indicators within healthcare, indicators such as mortality rates and hospital readmissions. We seek to contribute to the discourse by studying how the introduction of intermediate care in the form of municipal acute units (MAUs) in Norway has affected age adjusted mortality rates and hospital readmissions.

In this retrospective cohort study we utilize yearly population-based registry data from 2010 to 2016, analysed with fixed-effects regressions. Data on the implementation, characteristics and localization of the MAUs were gathered by telephone during the implementation period. Data on mortality rates and hospital readmissions were collected from Statistics Norway and the Norwegian patient registry.

Our analyses finds that the introduction of MAU was associated with a statistically significant reduction in both aggregated mortality rates and hospital readmission rates. In depth analyses finds that our results are contingent upon the age of the patients treated at the MAUs and the clinical characteristics of the medical units themselves.

Our findings indicate that the shift towards intermediate care through the introduction of MAUs has increased performance within the public healthcare sector in Norway. Our findings indicate that the introduction of MAU have had a positive public health impact by lowering the mortality and readmission rates for the oldest population cohort in Norway. Our findings suggests that countries with comparatively similar healthcare systems as Norway could achieve similar benefits from implementing intermediate care in the form of somatic medical institutions in the local communities.

Unplanned hospital readmissions after surgical operations are considered a marker for suboptimal care during index hospitalizations and are associated with poor patient outcomes and increased healthcare resource utilization. Patients undergoing lower extremity bypass (LEB) operations for severe peripheral arterial disease (PAD) have one of the highest readmission rates, among all the vascular and nonvascular surgical operations. This review is meant to evaluate the impact of pre-existing comorbidities (diabetes mellitus (DM), chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF), hypertension (HTN), and coronary artery disease (CAD))-on the 30-day readmission rates among patients who underwent LEB for severe PAD.

The review protocol was registered to the PROSPERO database (CRD42021261067). A systematic review of the English literature was performed using PubMed, Scopus, and the Cochrane Library databases from inception till April 2022. The review was based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines and included only studies reporting on 30-day readmission following LEB for occlusive PAD. The quality of evidence was assessed using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach and was reported as high, moderate, or low. The risk of bias was evaluated utilizing the Risk of Bias in Nonrandomized Studies - of Interventions (ROBINS-I) tool. A pooled odds ratio (OR) for each study was computed, and a P-value of <0.05 was designated as statistically significant. Interstudy heterogeneity was evaluated by Q-metric and quantified using Higgins I² statistics.

Five studies reported data on 30-day readmission after LEB for occlusive PAD. A total of 19,739 patients were included. Readmission occurred among 3,559 (18%) patients. DM and COPD were reported by all 5 selected studies, and CHF and HTN were reported by 4 studies. CAD was least reported among the selected 5 pre-existing conditions, with only 2 studies mentioning it. HTN (OR, 1.35; 95% confidence interval (CI), 1.10-1.64; P ≤ 0.001; I² = 52.20%), DM (OR, 1.52; 95% CI, 1.30-1.79; P ≤ 0.001; I² = 74.51%), and CHF (OR, 1.85; 95% CI, 1.51-2.25; P ≤ 0.001; I² = 50.48%) were all found to be associated with an increased risk of 30-day readmission, while the presence of COPD (OR, 1.16; 95% CI, 0.98-1.36; P = 0.09; I² = 61.93%) and CAD (OR, 1.30; 95% CI, 0.94-1.78; P = 0.11; I² = 51.01%) was not associated with early readmission on meta-analysis of the available studies.

The pre-existing comorbidities HTN, DM, and CHF increase the risk of 30-day readmission after LEB for occlusive PAD. The identification of these risk factors can help stratify the patients and further guide in understanding the variety of factors that contribute in hospital readmissions.

There are conflicting data on whether hospital length of stay (LOS) reduction affects readmission rates in older adults. We explored 20-year trends of hospital LOS and 30-day rehospitalizations in a cohort of Italian older people, and investigated their association.

Participants in the Pro.V.A. project (n = 3099) were followed-up from 1996 to 2018. LOS and 30-day rehospitalizations, i.e. new hospitalizations within 30 days from a previous discharge, were obtained from personal interviews and regional registers. Rehospitalizations in the 6 months before death were also assessed. Linear regressions evaluated the associations between LOS and the frequency of 30-day rehospitalizations, adjusting for the mean age of the cohort within each year.

Over 20 years, 2320 (74.9%) participants were hospitalized. Mean LOS gradually decreased from 17.3 days in 1996 to 11.3 days in 2018, while 30-day rehospitalization rates increased from 6.6% in 1996 to 13.6% in 2018. LOS was inversely associated with 30-day rehospitalizations frequency over time (β = -2.33, p = 0.01), similarly in men and women. A total of 1506 individuals was hospitalized within 6 months before death. The frequency of 30-day readmissions at the end of life increased from 1.4% in 1997 to 8.3% in 2017 and was associated with mean LOS (β = -1.17, p = 0.03).

The gradual LOS reduction observed in the latter decades is associated with higher 30-day readmission rates in older patients in Italy. This suggests that a careful pre-discharge assessment is warranted in older people, and that community healthcare services should be improved to reduce the risk of readmission.

The number of indicators used to monitor and improve the quality of care is debatable and may influence professionals' joy in work. We aimed to assess intensive care unit (ICU) professionals' perceived burden of documenting quality indicator data and its association with joy in work.

Cross-sectional survey.

ICUs of eight hospitals in the Netherlands.

Health professionals (ie, medical specialists, residents and nurses) working in the ICU.

The survey included reported time spent on documenting quality indicator data and validated measures for documentation burden (ie, such documentation being unreasonable and unnecessary) and elements of joy in work (ie, intrinsic and extrinsic motivation, autonomy, relatedness and competence). Multivariable regression analysis was performed for each element of joy in work as a separate outcome.

In total, 448 ICU professionals responded to the survey (65% response rate). The overall median time spent on documenting quality data per working day is 60 min (IQR 30-90). Nurses spend more time documenting these data than physicians (medians of 60 min vs 35 min, p<0.01). Most professionals (n=259, 66%) often perceive such documentation tasks as unnecessary and a minority (n=71, 18%) perceive them as unreasonable. No associations between documentation burden and measures of joy in work were found, except for the negative association between unnecessary documentations and sense of autonomy (β=-0.11, 95% CI -0.21 to -0.01, p=0.03).

Dutch ICU professionals spend substantial time on documenting quality indicator data they often regard as unnecessary. Despite the lacking necessity, documentation burden had limited impact on joy in work. Future research should focus on which aspects of work are affected by documentation burden and whether diminishing the burden improves joy in work.

A patient classification-based payment system called diagnosis-intervention packet (DIP) was piloted in a large city in southeast China in 2018.

This study evaluates the impact of DIP payment reform on total costs, out-of-pocket (OOP) payments, length of stay (LOS), and quality of care in hospitalised patients of different age.

An interrupted time series model was employed to examine the monthly trend changes of outcome variables before and after the DIP reform in adult patients, who were stratified into a younger (18-64 years) and an older group (≥ 65 years), further stratified into young-old (65-79 years) and oldest-old (≥ 80 years) groups.

The adjusted monthly trend of costs per case significantly increased in the older adults (0.5%, P = 0.002) and oldest-old group (0.6%, P = 0.015). The adjusted monthly trend of average LOS decreased in the younger and young-old groups (monthly slope change: -0.058 days, P = 0.035; -0.025 days, P = 0.024, respectively), and increased in the oldest-old group (monthly slope change: 0.107 days, P = 0.030) significantly. The changes of adjusted monthly trends of in-hospital mortality rate were not significant in all age groups.

Implementation of the DIP payment reform associated with increase in total costs per case in the older and oldest-old groups, and reduction in LOS in the younger and young-old groups without deteriorating quality of care.

Surgery is the cornerstone in the management of pediatric brain tumors. To provide safe and effective health services, quantifying and evaluating quality of care are important. To do this, there is a need for universal measures in the form of indicators reflecting quality of the delivered care. The objective of this study was to analyze currently applied quality indicators in pediatric brain tumor surgery and identify factors associated with poor outcome at a tertiary neurosurgical referral center in western Norway.

All patients younger than 18 years of age who underwent surgery for an intracranial tumor at the Department of Neurosurgery at Haukeland University Hospital in Bergen, Norway, between 2009 and 2020 were included. The primary outcomes of interest were classic quality indicators: 30-day readmission, 30-day reoperation, 30-day mortality, 30-day nosocomial infection, and 30-day surgical site infection (SSI) rates; and length of stay. The secondary aim was the identification of risk factors related to unfavorable outcome. The authors also conducted a systematic literature review. Articles concerning pediatric brain tumor surgery reporting at least two quality indicators were of interest.

The authors included 82 patients aged 0-17 years. The 30-day outcomes for unplanned reoperation, unplanned remission, mortality, nosocomial infection, and SSI were 9.8%, 14.6%, 0%, 6.1%, and 3.7%, respectively. Unplanned reoperation was associated with eloquent localization (p = 0.009), primary emergency surgery (p = 0.003), and CSF diversion procedures (p = 0.002). Greater tumor volume was associated with unplanned readmission (p = 0.008), nosocomial infection (p = 0.004), and CSF leakage (p = 0.005). In the systematic review, after full-text screening, 16 articles were included and provided outcome data for 1856 procedures. Overall, the 30-day mortality rate was low, varying from 0% to 9.3%. The 30-day reoperation rate varied from 1.5% to 12%. The SSI rate ranged between 0% and 3.9%, and 0% to 17.4% of patients developed CSF leakage. Four studies reported infratentorial tumor location as a risk factor for postoperative CSF leakage.

The 30-day outcomes in the authors' department were comparable to published outcomes. The most relevant factors related to unfavorable outcomes are tumor volume and location, both of which are not modifiable by the surgeon. This highlights the importance of risk adjustment. This evaluation of quality indicators reveals concerns related to the unclear and nonstandardized definitions of outcomes. Standardized outcome definitions and documentation in a large and multicentric database are needed in the future for further evaluation of quality indicators.

Emergency hospital readmissions within 30 days of discharge from hospital are considered a marker for the quality of hospital care, patient experience, the discharge process and integration with community services. This paper describes the frequency and variations in cause of emergency readmissions at 30 and 90 days following discharge after acute stroke from two stroke units.

Retrospective data collection of Hospital Episodes Statistics (HES) and Sentinel Stroke National Audit Programme (SSNAP) of consecutive acute stroke hospital discharges over 24 months from 2017 to 2019 from two specialist stroke units in England. HES data were used to calculate the Charlson comorbidity index (CCI). Covariates were analysed for their association with readmission rate, including: age; gender; CCI; length of stay for first stroke admission; living alone; discharge to a care home; discharge receiving stroke specialist early supported discharge (ESD) rehabilitation and stroke severity as determined by National Institute for Health Stroke Scale on stroke admission.

From 2017 to 2019 there were 1999 live discharges with a primary diagnosis of stroke. Both hospitals had a trend of increasing readmission rates with increasing stroke severity and comorbidity. Longer length of stroke admission, especially for patients with increasing stroke severity, and patients receiving ESD rehabilitation after discharge reduced 90-day readmissions. This association was stronger at 90 days than at 30 days. Different readmission event rates were found at 30 and 90 days and when events were compared between the two hospitals.

Understanding differences in readmission event rates between hospitals at 30 and 90 days can support local planning of patient needs in the first weeks after stroke discharge and to investigate ways for hospital to reduce the impact of readmission. It is recommended that stroke services use both 30 and 90-day readmissions to inform service evaluation and improvement.