Prolonged hospital stays can significantly impede patients\' recovery, negatively affecting anything from physical health via issues like hospital-acquired infections and increased complications due to immobility to psychological health. Several studies investigated the psychosocial impact of prolonged hospital stays, revealing a variety of patient perspectives, such as feeling uncertain and frustrated about their conditions, which can erode their trust in healthcare providers. Delayed discharges not only affect patients but also have multifaceted effects on healthcare providers, potentially reducing physician efficiency and contributing to higher rates of burnout among healthcare professionals. This article investigates the consequences of delayed versus early discharge on physicians, patients, and the overall hospital system. We conducted an extensive search through PubMed and Google Scholar using the keywords \"delayed discharge,\" \"hospital discharge,\" and \"bed blocking\" to identify all the recent studies highlighting the dynamics of patient discharge. Our results support the hypothesis that reducing delayed discharge rates will not only improve patient outcomes but also have widespread fiscal impacts. This review also outlines measures to reduce delayed discharges, ultimately leading to a significant enhancement in the healthcare system.

BACKGROUND: Improving patient activation may be an effective way to reduce healthcare costs and improve patient outcomes after surgery.
OBJECTIVE: To determine whether preoperative patient activation is associated with delayed discharge (i.e., length of stay >24 h) after elective laparoscopic cholecystectomy. Postoperative symptoms, unscheduled access to healthcare facilities within seven days of surgery, unplanned hospital readmissions, and postoperative complications were analyzed as secondary outcomes.
METHODS: This cohort study was a secondary analysis of the DeDiLaCo study (Delayed Discharge after day-surgery Laparoscopic Cholecystectomy) collecting data of patients undergoing elective laparoscopic cholecystectomy during 2021 in Italy. Data was analyzed from June 2022 to April 2023.
METHODS: 90 Italian surgical centers participating in the study.
METHODS: 4708 adult patients with an instrumental diagnosis of gallbladder disease and undergoing laparoscopic cholecystectomy. Patient activation was assessed using the Italian translation of Patient Activation Measure in the preoperative setting.
RESULTS: Of 4532 cases analyzed the median (IQR) Patient Activation Measure score was 80.3 (71.2-92.3). Participants were on average 55.5 years of age and 58.1 % were female. Two groups based on the activation level were created: 270 (6 %) had low activation, and 4262 had high activation. The low activation level was associated with the likelihood of delayed discharge (odds ratio [OR] 1.47, 95 % CI, 1.11-1.95; P = .008), higher symptom burden (OR 1.99, 95 % CI 1.49-2.66, P < .0001), and unplanned healthcare utilization within seven days after hospital discharge (OR 1.85, 95 % CI, 1.29-2.63; P = .001). There was no difference between the high and low activation groups in the incidence of postoperative complications (OR 1.28, 95 % CI, 0.95-1.73; P = .10) and hospital readmission after discharge (OR 0.95, 95 % CI, 0.30-3.05; P = .93).
CONCLUSIONS: Our results suggest that patients with low activation have 1.47 times the risk of delayed discharge compared with patients with higher activation, almost twice the risk of the onset of postoperative symptoms, and 1.85 times the risk of unscheduled use of hospital services. Screening for patient activation in the preoperative setting could not only identify patients not suitable for early discharge, but more importantly, help physicians and nurses develop tailored interventions.

Coronavirus disease 2019 (COVID-19) has spread throughout China. However, information about COVID-19 in cities and regions outside Wuhan is limited and the indicators that predict the length of hospital stay for patients with COVID-19 are unclear. Therefore, we collected clinical data from 47 patients with COVID-19 in Quanzhou City. The median age was 38 years [interquartile range (IQR): 31-50 years], and 24 (51%) were male. There were 8 mild, 36 moderate, and 3 severe/critical cases. The median interval from exposure to disease onset was 13 days (IQR: 8-18 days). The incidence of severe/critical cases was 33% (3/10) in patients with hypertension. Common symptoms included fever (83%), cough (77%), fatigue (40%), a sore, dry throat (28%), and diarrhea (21%). One patient (2%) developed respiratory distress syndrome on day 13 of inpatient treatment. Six patients had leukopenia, 17 had elevated C-reactive protein (CRP), and 8 had lymphocytopenia and elevated lactate dehydrogenase (LDH). The median length of hospitalization was 22 days (IQR: 16-30 days). Dynamic monitoring of LDH, CRP, and neutrophil-lymphocyte ratio predicted whether length of hospitalization would exceed 21 days. Most patients presented with mild and moderate disease. Patients with hypertension were more likely to become severe or critical. Dynamic monitoring of LDH, CRP, and neutrophil-lymphocyte ratio levels can help predict delayed discharge from the hospital.

OBJECTIVE: This article addresses the persistent challenge of Delayed Hospital Discharge (DHD) and aims to provide a comprehensive overview, synthesis, and actionable, sustainable plan based on the synthesis of the systematic review articles spanning the past 24 years. Our research aims to comprehensively examine DHD, identifying its primary causes and emphasizing the significance of effective communication and management in healthcare settings.
METHODS: We conducted the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) method for synthesizing findings from 23 review papers published over the last two decades, encompassing over 700 studies. In addition, we employed a practical and comprehensive framework to tackle DHD. Rooted in Linderman\'s model, our approach focused on continuous process improvement (CPI), which highlights senior management commitment, technical/administrative support, and social/transitional care. Our proposed CPI method comprised several stages: planning, implementation, data analysis, and adaptation, all contributing to continuous improvement in healthcare delivery. This method provided valuable insights and recommendations for addressing DHD challenges.
RESULTS: Our DHD analysis revealed crucial insights across multiple dimensions. Firstly, examining causes and interventions uncovered issues such as limited discharge destinations, signaling unsustainable solutions, and inefficient care coordination. The second aspect explored the patient and caregiver experience, emphasizing challenges linked to staff uncertainty and negative physical environments, with notable attention to the underexplored area of caregiver experience. The third theme explored organizational and individual factors, including cognitive impairment and socioeconomic influences. The findings emphasized the importance of incorporating patients\' data, recognizing its complexity and current avoidance. Finally, the role of transitional and social care and financial strategies was scrutinized, emphasizing the need for multicomponent, context-specific interventions to address DHD effectively.
CONCLUSIONS: This study addresses gaps in the literature, challenges prevailing solutions, and offers practical pathways for reducing DHD, contributing significantly to healthcare quality and patient outcomes. The synthesis introduces the vital CPI stage, enhancing Linderman\'s work and providing a pragmatic framework to eradicate delayed discharge. Future efforts will address practitioner consultations to enhance perspectives and further enrich the study.
UNASSIGNED: Our scoping review synthesizes and analyzes existing systematic review articles and emphasizes offering practical, actionable solutions. While our approach does not directly engage patients, it strategically focuses on extracting insights from the literature to create a CPI framework. This unique aspect is intentionally designed to yield tangible benefits for patients, service users, caregivers, and the public. Our actionable recommendations aim to improve hospital discharge processes for better healthcare outcomes and experiences. This detailed analysis goes beyond theoretical considerations and provides a practical guide to improve healthcare practices and policies.

BACKGROUND: Delayed discharge is problematic. It is financially costly and can create barriers to delivering best patient care, by preventing return to usual functioning and delaying admissions of others in need. This systematic review aimed to collate existing evidence on delayed discharge in psychiatric inpatient settings and to develop understanding of factors and outcomes of delays in these services.
METHODS: A search of relevant literature published between 2002 and 2022 was conducted on Pubmed, PsycInfo and Embase. Studies of any design, which published data on delayed discharge from psychiatric inpatient care in high income countries were included. Studies examining child and adolescent, general medical or forensic settings were excluded. A narrative synthesis method was utilised. Quality of research was appraised using the Mixed Methods Appraisal Tool (MMAT).
RESULTS: Eighteen studies from England, Canada, Australia, Ireland, and Norway met the inclusion criteria. Six main reasons for delayed discharge were identified: (1) accommodation needs, (2) challenges securing community or rehabilitation support, (3) funding difficulties, (4) family/carer factors, (5) forensic considerations and (6) person being out of area. Some demographic and clinical factors were also found to relate to delays, such as having a diagnosis of schizophrenia or other psychotic disorder, cognitive impairment, and increased service input prior to admission. Being unemployed and socially isolated were also linked to delays. Only one study commented on consequences of delays for patients, finding they experienced feelings of lack of choice and control. Four studies examined consequences on services, identifying high financial costs.
CONCLUSIONS: Overall, the findings suggest there are multiple interlinked factors relevant in delayed discharge that should be considered in practice and policy. Suggestions for future research are discussed, including investigating delayed discharge in other high-income countries, examining delayed discharge from child and forensic psychiatric settings, and exploring consequences of delays on patients and staff. We suggest that future research be consistent in terms used to define delayed discharge, to enhance the clarity of the evidence base.
UNASSIGNED: 292515.
UNASSIGNED: 9th December 2021.

The present study investigated the epidemiology and clinical characteristics of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant and determined the risk factors for delayed discharge or release from isolation for pediatric patients in Quanzhou, China in 2022. There were 145, 254 and 23 patients in the asymptomatic, mildly symptomatic and moderately symptomatic categories, respectively. The proportion of pediatric patients in the moderately symptomatic category increased with increasing age. No child aged <1 year and 9.02% of patients aged 13-18 years were in the moderately symptomatic category. The proportion of patients with asymptomatic infection did not differ significantly by vaccination status. The median days until the first negative conversion of viral RNA was 11 days, and the median hospitalization duration was 16 days. Most symptoms appeared in the upper respiratory tract. Notably, ~33.23% of patients showed elevated aspartate aminotransferase levels. C-reactive protein and interleukin-6 (IL-6) levels, and lymphocyte counts were consistently lower in asymptomatic patients than those in in symptomatic patients. Adjusted logistic regression analyses indicated that IL-6 levels and time to the first negative conversion of viral RNA were independent risk factors for delayed discharge. The area under the curve of the regression model for predicting delayed discharge was 0.760. In conclusion, these results could facilitate the formulation of global epidemic prevention policies for pediatric patients.

OBJECTIVE: This work aims to investigate the association between obesity and risk of delayed discharge and unplanned readmission in day surgery patients.
BACKGROUND: Day surgeries are well received and developing rapidly. Associations between obesity and delayed discharge and unplanned readmission, which are clinically relevant outcomes in day surgeries, are complex.
METHODS: A systematic review and meta-analysis was conducted.
METHODS: The PubMed, Web of Science, EMBASE, Cochrane Library, CNKI, VIP, and Wan Fang databases were comprehensively searched from inception until January 2021.
METHODS: Two independent reviewers assessed the studies and extracted data. Pooled estimates were obtained using a random-effects model.
RESULTS: Eleven articles published between 2007 and 2020 were finally included. Obesity appeared not to increase the risk of delayed discharge. However, morbid obesity seemed to be associated with a higher risk of delayed discharge. The meta-analysis revealed no relationship between higher body mass index (BMI) and unplanned readmission for day surgery patients.
CONCLUSIONS: Obesity appeared not to increase the risk of delayed discharge except in patients with morbid obesity. Additionally, a higher BMI was not associated with increased risk of unplanned readmission after day surgery. Future studies are required to address this issue further in different types of surgery and areas.

The objective of this study was to determine the factors that increase the odds of long-stay delayed discharge in alternate level of care (ALC) patients using data collected from the Ontario Wait Time Information System (WTIS) database.
Retrospective cohort study utilizing data from Niagara Health\'s WTIS database. WTIS includes individuals admitted to any of the Niagara Health sites that have been designated as ALC.
Sample consisted of 16,429 ALC patients who received care in Niagara Health hospitals from September 2014 to September 2019 and were recorded in the WTIS database.
ALC designation of 30 or more days was used as the threshold for a long-stay delayed discharge. This study used binary logistic regression modeling to analyze sex, age, admission source, and discharge destination as well needs/barriers requirements to assess the likelihood of a long-stay delayed discharge among acute care (AC) and post-acute care (PAC) patients given the presence of each variable. Sample sizes calculations and receiver operating characteristic curves were used to verify the validity of the regression model.
Overall, 10.2% of the sample were considered long-stay ALC patients. Both AC and PAC long-stay ALC patients were more likely to be male [OR = 1.23, (1.06-1.43); OR = 1.28, (1.03-1.60)] and have a discharge destination of a long-term care bed [OR = 28.68, (22.83-36.04); OR = 6.22, (4.75-8.15)]. AC patients had bariatric [OR = 7.16, (3.45-14.83)], behavioral [OR = 1.89, (1.22-2.91)], infection (isolation) [OR = 2.31, (1.63-3.28)], and feeding [OR = 6.38, (1.82-22.30)] barriers hindering discharge. PAC patients had no significant barriers hindering patient discharge.
Shifting the focus from ALC patient designation to short- vs long-stay ALC patients allowed this study to focus on the subset of patients that are disproportionately affecting delayed discharges. Understanding the importance of specialized patient requirements in addition to clinical factors can help hospitals become more prepared in preventing delayed discharges.

BACKGROUND: Because of their poor physical state, elderly hip fracture patients commonly require prolonged hospitalization, resulting in a drop in bed circulation rate and an increased financial burden. There are currently few predictive models for delayed hospital discharge for hip fractures. This research aimed to develop the optimal model for delayed hospital discharge for hip fractures in order to support clinical decision-making.
METHODS: This case-control research consisted of 1259 patients who were continuously hospitalized in the orthopedic unit of an acute hospital in Tianjin due to a fragility hip fracture between January and December 2021. Delayed discharge was defined as a hospital stay of more than 11 days. The prediction model was constructed through the use of a Cox proportional hazards regression model. Furthermore, the constructed prediction model was transformed into a nomogram. The model\'s performance was assessed using the area under the receiver operating characteristic curve (AUC), calibration curves and decision curve analysis (DCA). the STROBE checklist was used as the reporting guideline.
RESULTS: The risk prediction model developed contained the Charlson Comorbidity Index (CCI), preoperative waiting time, anemia, hypoalbuminemia, and lower limbs arteriosclerosis. The AUC for the risk of delayed discharge was in the training set was 0.820 (95% CI,0.79 ~ 0.85) and 0.817 in the testing sets. The calibration revealed that the forecasted cumulative risk and observed probability of delayed discharge were quite similar. Using the risk prediction model, a higher net benefit was observed than when considered all patients were at high risk, demonstrating good clinical usefulness.
CONCLUSIONS: Our prediction models could support policymakers in developing strategies for the optimal management of hip fracture patients, with a particular emphasis on individuals at high risk of prolonged LOS.

BACKGROUND: Day-surgery percutaneous nephrolithotomy (PCNL) is being developed quickly but some potential factors are affecting the recovery process. This study is aim to analyze the reasons and risk factors for delayed discharge after day-surgery PCNL.
METHODS: The data of 205 patients who accepted day-surgery PCNL in our institution between January 2018 and February 2020 were analyzed, retrospectively. Univariate and multivariate logistic regression analysis were used to analyze the risk factors for delayed discharge. Besides, the nomogram prediction model was established by the multivariable logistic regression analysis.
RESULTS: The rate of delayed discharge was 14.6%. Independent risk factors for delayed discharge were larger stone burden (odds ratio [OR] = 3.814, P = 0.046), positive urine nitrite (OR = 1.001, P = 0.030), longer duration of surgery (OR = 1.020, P = 0.044), multiple nephrostomy tubes (OR = 4.282, P = 0.008). The five main reasons that caused delayed discharge included psychological reasons, pain, bleeding, urosepsis, and urine leakage.
CONCLUSIONS: This study identified some independent risk factors for a hospital length of stay longer than 24 h. Patients with larger renal stones or positive urine nitrite may be at increased risk of delayed discharge after day-surgery PCNL. Reducing surgery time and nephrostomy tubes will help to facilitate recovery.