Elective Admissions Research Articles

Incidence and risk factors of blood transfusion after total knee arthroplasty: A retrospective nationwide inpatient sample database study

IntroductionCommon postoperative complications of total knee arthroplasty (TKA) include blood transfusion. Although risk factors and incidence of blood transfusion have been studied through national databases, the relative impact of each risk factor needs to be synthesized over a longer time period into a new model need to be revised. Material and methodsPatient data were extracted from the National Inpatient Sample (NIS), which is the largest hospital care database in the US, and analyse patient data retrospectively from 2010 through 2019. The final data included the patients undergoing TKA. The final analysis assessed the demographics of patients, type of insurance, type of hospital, length of stay (LOS), preoperative comorbidities, total charge, inpatient mortality, medical-surgical postoperative complications. ResultsAfter extracting data from the NIS database, a total of 1,250,533 patients with TKA were included in the analysis, and the rate of transfusion was 6.60 %. TKA patients who receive blood transfusion had longer LOS (from 2-3 days to 3–4 days), more preoperative comorbidities, higher inpatient mortality rate, and increased total charge (P < 0.001). Moreover, postoperative complications associated with inpatients included sepsis, acute myocardial infarction and shock. Elective admission and private insurance were also regarded as protective factors. ConclusionBlood transfusion could bring postoperative complications to patients, which were also linked to health costs and risks. It was also a common preoperative comorbidities for older patients who underwent TKA. Through better blood management strategies, we could reduce patient transfusion rates and improve clinical outcomes.Level of Evidence: Diagnostic Level Ⅲ.

Healthcare costs related to respiratory syncytial virus in paediatric intensive care units in the Netherlands: a nationwide prospective observational study (the BRICK study)

The implementation of the approved respiratory syncytial virus (RSV) preventive interventions in immunisation programmes is advancing rapidly. Insight into healthcare costs of RSV-related paediatric intensive care unit (PICU) admissions is lacking, but of great importance to evaluate the impact of implementation. Therefore, this study aimed to determine the total annual RSV-related paediatric intensive care healthcare costs in the Netherlands. A nationwide prospective, observational, multicenter study was performed from September 2021 until June 2023. The total annual RSV-related healthcare costs on PICUs in the Netherlands were calculated using RSV-related costs (subgroup I) and consequential costs (subgroup II and III). Subgroup I comprised all PICU admitted infants ≤12 months of age with laboratory-confirmed RSV infection. Subgroup II and III consisted of postponed elective PICU admissions and refused acute PICU admissions due to RSV-related lack of PICU capacity. A total of 424 infants with RSV-related PICU admission were included. Median age at PICU admission was 46 days (IQR 25-89). The median length of PICU admission was 5 days (IQR 3-8). The total RSV-related PICU costs are € 3,826,386 in 2021-2022, and € 3,183,888 in 2022-2023. Potential costs averted by RSV preventive interventions is € 1.9 to € 2.6 million depending on season, and the duration of protection. RSV-related PICU admissions cost €3.1 to €3.8 million in the Netherlands during one season. The introduction of new RSV preventive interventions into the Dutch immunisation programme will generate significant cost-savings on PICUs and decreases the admission burden of PICUs. None.

Incidence and Risk Factors of Delirium Following Brain Tumor Resection: A Retrospective National Inpatient Sample Database Study

The aim of this study was to evaluate the occurrence and factors predisposing to delirium following brain tumor resection. Data from patients who underwent brain tumor resection surgery from 2016 to 2019 were extracted from the National Inpatient Sample database and retrospectively analyzed. The difference between the 2 groups was compared by Wilcoxon rank test or χ2 test was used. Univariate and multivariate logistic regression analyses were used to identify the risk factors of delirium after brain tumor resection. From 2016 to 2019, 28,340 patients who underwent brain tumor resection were identified in the National Inpatient Sample database, with the incidence of delirium being 4.79% (1357/28,340). It was found that increased incidence of delirium was significantly associated with age over 75years and males (all P<0.001). Besides, patients with delirium were more likely to have multiple comorbidities and to receive elective surgery (all P<0.001). The results of logistic regression analysis showed that self-pay (odds ratio [OR]=0.51; confidence interval [CI]=0.31-0.83; P=0.007), elective admission (OR=0.53; CI=0.47-0.60; P<0.001), obesity (OR=0.77; CI=0.66-0.92; P=0.003), females (OR=0.79; CI=0.71-0.88; P<0.001), and private insurance (OR=0.80; CI=0.67-0.95; P=0.012) were associated with lower occurrence of delirium. Besides, delirium was related to extra total hospital charges (P<0.001), increased length of stay (P<0.001), higher inpatient mortality (P=0.001), and perioperative complications (including heart failure, acute renal failure, urinary tract infection, urinary retention, septicemia, pneumonia, blood transfusion, and cerebral edema) (P<0.001). Many factors were associated with the occurrence of delirium after brain tumor resection. Therefore, clinicians should identify high-risk patients prone to delirium in a timely manner and take effective management measures to reduce adverse outcomes.

Sex Disparities After Coronary Artery Bypass Grafting and Hospital Quality

Concern has been raised about persistent sex disparities after coronary artery bypass grafting, with female patients having higher mortality. However, whether these disparities persist across hospitals of different qualities is unknown. To evaluate sex disparities in 30-day mortality after coronary artery bypass grafting across high- and low-quality hospitals. This cross-sectional, retrospective cohort study evaluated Medicare beneficiaries undergoing coronary artery bypass grafting between October 1, 2015, and March 31, 2020. Data analysis was performed from July 1, 2023, to December 1, 2023. The primary exposures were hospital quality and sex. For hospital quality, hospitals were placed into rank order by their overall risk-adjusted mortality rate and divided into quintiles. Risk-adjusted 30-day mortality using a logistic regression model accounting for patient factors, including sex, age, comorbidities, elective vs unplanned admission, number of bypass grafts, use of arterial graft, and year of surgery. A total of 444 855 beneficiaries (mean [SD] age, 71.5 [7.5] years; 120 333 [27.1%] female and 324 522 [72.9%] male) were studied. Compared with male beneficiaries, female beneficiaries were more likely to have an unplanned admission (66 425 [55.2%] vs 157 895 [48.7%], P < .001) and receive care at low-quality (vs high-quality) hospitals (odds ratio, 1.26; 95% CI, 1.23-1.29; P < .001). Overall, risk-adjusted female mortality was 4.24% (95% CI, 4.20%-4.27%), and male mortality was 2.75% (95% CI, 2.75%-2.77%), with an absolute difference of 1.48 (95% CI, 1.45-1.51) percentage points (P < .001). At the highest-quality hospitals, male mortality was 1.57% (95% CI, 1.56%-1.59%), and female mortality was 2.58% (95% CI, 2.54%-2.62%), with an absolute difference of 1.01 (95% CI, 0.97-1.04) percentage points (P < .001). At the lowest-quality hospitals, male mortality was 4.94% (95% CI, 4.88%-5.01%), and female mortality was 7.02% (95% CI, 6.90%-7.13%), with an absolute difference of 2.07 (95% CI, 1.95-2.19) percentage points (P < .001). Female beneficiaries receiving care at low-quality hospitals had a higher mortality than male beneficiaries receiving care at the high-quality hospitals (7.02% vs 1.57%, P < .001). In this cohort study of Medicare beneficiaries undergoing coronary artery bypass grafting, female beneficiaries were more likely to receive care at low-quality hospitals, where the sex disparity in mortality was double that of high-quality hospitals. Quality improvement targeting low-quality hospitals as well as equitable referral of female beneficiaries to higher-quality hospitals may narrow the sex disparity after coronary artery bypass grafting.

The relationship between neighborhood socioeconomic status and short-term outcomes following colon resection

BackgroundThis study investigates the association between neighborhood socioeconomic status, measured by the Distressed Communities Index (DCI), and short-term outcomes following colon resection. MethodsUtilizing the Maryland State Inpatient Sample database (SID 2018–2020), we determined the association between DCI and post-op outcomes following colon resection including length of stay, readmissions, 30-day in-hospital mortality, and non-routine discharges. Multivariate regression analysis was performed to control for potential confounding factors. ResultsOf the 13,839 patients studied, median age was 63, with 54.3 ​% female and 64.5 ​% elective admissions. Laparoscopic surgery was performed in 36.9 ​% cases, with a median hospital stay of 5 days. Patients in distressed communities faced higher risks of emergency admission (OR: 1.31), prolonged hospitalization (OR: 1.29), non-routine discharges (OR: 1.36), and readmission (OR: 1.33). Black patients had longer stays than White patients (OR: 1.3). Despite adjustments, in-hospital mortality did not significantly differ among neighborhoods. ConclusionOur study reveals that patients residing in distressed neighborhoods face a higher risk of prolonged hospitalization, non-routine discharges, and readmission rate after colon resection.

Increasing Rates of Bowel Resection Surgery for Stricturing Crohn's Disease in the Biologic Era.

The era of biologics is associated with declining rates of surgery for Crohn's disease (CD), but the impact on surgery for stricturing CD is unknown. Our study aimed to assess nationwide trends in bowel resection surgery for obstruction in CD since the introduction of infliximab for CD in 1998. Using the Nationwide Inpatient Sample, we performed a nationwide analysis, identifying patients hospitalized for CD who underwent bowel resection for an indication of obstruction between 1998 and 2020 (era of biologics). Longitudinal trends in all CD-related resections and resection for obstruction were evaluated. Multivariable logistic regression identified patient and hospital characteristics associated with bowel resection surgery for obstruction. Hospitalizations for all CD-related resections decreased from 12.0% of all hospitalizations in 1998 to 6.9% in 2020, while hospitalizations for CD-related resection for obstructive indication increased from 1.3% to 2.0%. The proportion of resections for obstructive indication amongst all CD-related bowel resections increased from 10.8% in 1998 to 29.1% in 2020. In the multivariable models stratified by elective admission, the increasing year was associated with risk of resection for obstructive indication regardless of urgency (nonelective model: odds ratio, 1.01; 95% CI, 1.00-1.02; elective model: odds ratio, 1.06; 95% CI, 1.04-1.08). In the era of biologics, our findings demonstrate a decreasing annual rate of CD-related bowel resections but an increase in resection for obstructive indication. Our findings highlight the effect of medical therapy on surgical rates overall but suggest limited impact of current medical therapy on need of resection for stricturing disease.

Adaptation of the Risk Analysis Index for Frailty Assessment Using Diagnostic Codes

Frailty is associated with adverse outcomes after even minor physiologic stressors. The validated Risk Analysis Index (RAI) quantifies frailty; however, existing methods limit application to in-person interview (clinical RAI) and quality improvement datasets (administrative RAI). To expand the utility of the RAI utility to available International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) administrative data, using the National Inpatient Sample (NIS). RAI parameters were systematically adapted to ICD-10-CM codes (RAI-ICD) and were derived (NIS 2019) and validated (NIS 2020). The primary analysis included survey-weighed discharge data among adults undergoing major surgical procedures. Additional external validation occurred by including all operative and nonoperative hospitalizations in the NIS (2020) and in a multihospital health care system (UPMC, 2021-2022). Data analysis was conducted from January to May 2023. RAI parameters and in-hospital mortality. The association of RAI parameters with in-hospital mortality was calculated and weighted using logistic regression, generating an integerized RAI-ICD score. After initial validation, thresholds defining categories of frailty were selected by a full complement of test statistics. Rates of elective admission, length of stay, hospital charges, and in-hospital mortality were compared across frailty categories. C statistics estimated model discrimination. RAI-ICD parameters were weighted in the 9 548 206 patients who were hospitalized (mean [SE] age, 55.4 (0.1) years; 3 742 330 male [weighted percentage, 39.2%] and 5 804 431 female [weighted percentage, 60.8%]), modeling in-hospital mortality (2.1%; 95% CI, 2.1%-2.2%) with excellent derivation discrimination (C statistic, 0.810; 95% CI, 0.808-0.813). The 11 RAI-ICD parameters were adapted to 323 ICD-10-CM codes. The operative validation population of 8 113 950 patients (mean [SE] age, 54.4 (0.1) years; 3 148 273 male [weighted percentage, 38.8%] and 4 965 737 female [weighted percentage, 61.2%]; in-hospital mortality, 2.5% [95% CI, 2.4%-2.5%]) mirrored the derivation population. In validation, the weighted and integerized RAI-ICD yielded good to excellent discrimination in the NIS operative sample (C statistic, 0.784; 95% CI, 0.782-0.786), NIS operative and nonoperative sample (C statistic, 0.778; 95% CI, 0.777-0.779), and the UPMC operative and nonoperative sample (C statistic, 0.860; 95% CI, 0.857-0.862). Thresholds defining robust (RAI-ICD <27), normal (RAI-ICD, 27-35), frail (RAI-ICD, 36-45), and very frail (RAI-ICD >45) strata of frailty maximized precision (F1 = 0.33) and sensitivity and specificity (Matthews correlation coefficient = 0.26). Adverse outcomes increased with increasing frailty. In this cohort study of hospitalized adults, the RAI-ICD was rigorously adapted, derived, and validated. These findings suggest that the RAI-ICD can extend the quantification of frailty to inpatient adult ICD-10-CM-coded patient care datasets.

Does Elective Admission vs. Emergency Department Presentation Affect Surgical Outcomes in Metastatic Spine Surgery?

Approximately 20% of patients with metastatic spine disease develop symptomatic spinal cord compression, and these patients can present urgently to the emergency department (ED) or, in a more organized fashion, to a clinic. In a cohort of patients undergoing metastatic spine surgery, we sought to (1) determine the rate of ED presentation, (2) identify preoperative and perioperative risk factors associated with ED presentation, and (3) evaluate whether ED vs. clinic presentation impacts long-term outcomes. A single-institution, multi-surgeon, retrospective cohort study was undertaken of patients undergoing metastatic spinal tumor surgery between 02/2010 and 01/2021. The primary exposure variable was presentation setting, dichotomized to the ED vs. clinic. The primary outcomes were postoperative functional status, measured with the Karnofsky Performance Scale (KPS) and McCormick Scale (MMS), local recurrence (LR), and overall survival (OS). Secondary outcomes included complications and readmissions. A total of 311 patients underwent metastatic spine surgery (51.7% ED vs. 48.3% clinic). Those presenting to the ED had higher rates of smoking (21.7% vs. 16.0%, p = 0.02), were more likely to have 2+ comorbidities (47.2% vs. 32.7%, p = 0.011), and were more likely to have public insurance (43.5% vs. 32.0%, p = 0.043). Preoperative KPS was lower in ED patients (p < 0.001), while the Bilsky score was higher (p = 0.049). ED patients had higher rates of oligometastatic disease (p = 0.049), higher total decompressed levels (p = 0.041), and higher rates of costotransversectomy (p = 0.031) compared to clinic patients. Length of stay was significantly longer for ED patients (7.7 ± 6.1 vs. 6.1 ± 5.8 days, p = 0.020), and they were less likely to be discharged home (52.2% vs. 69.3%, p = 0.025). ED presentation was significantly associated with shorter overall survival (HR =1.53 95% CI = 1.13-2.08, p = 0.006). Of patients undergoing metastatic spine disease, approximately half presented through the ED vs. clinic. ED patients had higher rates of smoking, public insurance, and higher Bilsky score. ED patients also underwent more extensive surgery, had longer LOS, were less likely discharged home, and most importantly, had a shorter overall survival. These results suggest that initial presentation for patients undergoing surgery for metastatic spine disease significantly impacts outcomes, and signs/symptoms of metastatic spine disease should be recognized as soon as possible to prevent ED presentation.

Incidence and risk factors of postoperative delirium following hepatic resection: a retrospective national inpatient sample database study

BackgroundPostoperative delirium (POD) is a common complication after major surgery and can cause a variety of adverse effects. However, no large-scale national database was used to assess the occurrence and factors associated with postoperative delirium (POD) following hepatic resection.MethodsPatients who underwent hepatic resection from 2015 to 2019 were screened using the International Classification of Diseases (ICD) 10th edition clinical modification code from the National Inpatient Sample (NIS) Database. Peri-operative factors associated with delirium were screened and underwent statistical analysis to identify independent predictors for delirium following hepatic resection.ResultsA total of 80,070 patients underwent hepatic resection over a five-year period from 2015 to 2019. The overall occurrence of POD after hepatic resection was 1.46% (1039 cases), with a slight upward trend every year. The incidence of elective admission was 6.66% lower (88.60% vs. 81.94%) than that of patients without POD after hepatic resection and 2.34% (45.53% vs. 43.19%) higher than that of patients without POD in teaching hospitals (P < 0.001). In addition, POD patients were 6 years older (67 vs. 61 years) and comprised 9.27% (56.69% vs. 47.42%) more male patients (P < 0.001) compared to the unaffected population. In addition, the occurrence of POD was associated with longer hospitalization duration (13 vs. 5 days; P < 0.001), higher total cost ($1,481,89 vs. $683,90; P < 0.001), and higher in-hospital mortality (12.61% vs. 4.11%; P < 0.001). Multivariate logistic regression identified hepatic resection-independent risk factors for POD, including non-elective hospital admission, teaching hospital, older age, male sex, depression, fluid and electrolyte disorders, coagulopathy, other neurological disorders, psychoses, and weight loss. In addition, the POD after hepatic resection has been associated with sepsis, dementia, urinary retention, gastrointestinal complications, acute renal failure, pneumonia, continuous invasive mechanical ventilation, blood transfusion, respiratory failure, and wound dehiscence / non-healing.ConclusionAlthough the occurrence of POD after hepatic resection is relatively low, it is beneficial to investigate factors predisposing to POD to allow optimal care management and improve the outcomes of this patient population.

Optimization of elective patient admissions during pandemics: case of COVID-19

With advent of the Covid pandemic, hospitals grappled with how to manage the sudden surge in demand while still treating those in need of service for other reasons. This study aims to provide an adaptive elective admission scheduling policy that maximizes throughput during a pandemic while maintaining the ability of a hospital to empty a specified number of beds over a short warning period (e.g. 5 days). This ability we call nimbleness. We propose a heuristic method based on two mixed-integer linear programming models (MILP) and a simulation model. The first MILP creates the initial schedule for patient admissions over the planning horizon while maximizing patient throughput. The second MILP considers the uncertainty of the emergency arrivals (including pandemic induced) and the patients’ length of stay and maximizes the number of scheduled patients admitted while ensuring the hospital’s nimbleness. A simulation model is built to create daily random arrivals and discharges. The models connect through an automated feedback loop until the heuristic approach converges on a solution. Numerical results demonstrate the ability of the approach to maintain high throughput while still responding to pandemic surges.

The principles of enhanced recovery after percutaneous endoscopic gastrostomy (ERaPEG): a UK tertiary center experience.

Enhanced recovery after surgery (ERAS) pathways have been shown to improve surgical outcomes and patient satisfaction. The aim of the study was to assess whether the implementation of a perioperative enhanced recovery after percutaneous endoscopic gastrostomy (ERaPEG) pathway based on ERAS principles was safe, satisfactory to parents and improved outcomes. Following a quality improvement project, a multimodal ERaPEG pathway was introduced as standard practice within the department and children undergoing elective same-day admission percutaneous endoscopic gastrostomy (PEG) at a single UK tertiary center were prospectively enrolled. Exclusion criteria were patients undergoing other concurrent procedures and those who underwent a laparoscopic assisted/open procedure. Data included patient demographics, underlying diagnosis, indication, length of stay (LOS) and 30-day readmission. Parental experience and satisfaction were determined using a questionnaire including 5-point Likert scales. A retrospective cohort was used for comparison. Data were analyzed using Chi-Square test and Mann-Whitney U tests. Ninety-five patients met the inclusion criteria: 50 pre and 45 post the implementation of ERaPEG. Median age was 3 and 2years, respectively. Neurodisability was the underlying diagnosis in most patients (84%-pre-ERaPEG; 76%-post-ERaPEG). Most common PEG indication was medication/nutritional supplementation (52%-pre-ERaPEG; 51%-post-ERaPEG). The LOS significantly decreased from a median of 51.5h (pre-ERaPEG) to 32h (post-ERaPEG) (p < 0.001). Thirty-day readmission rates were similar (6% vs 11%). Most parents felt that the educational material was easy to access and understand. Post-operatively the majority of parents (≥ 80%) were confident in managing the gastrostomy device, setting up/giving the feeds and also felt that the LOS was appropriate. This study shows that the implementation of an ERaPEG pathway significantly reduced LOS following PEG. In addition, the pathway was satisfactory to parents and offered the benefit of improved resource utilization.

The impact of the COVID-19 pandemic on 397 631 elective dental admissions among the under-25s in England: a retrospective study.

COVID-19 caused widespread disruptions to health services worldwide, including reductions in elective surgery. Tooth extractions are among the most common reasons for elective surgery among children and young people (CYP). It is unclear how COVID-19 affected elective dental surgeries in hospitals over multiple pandemic waves at a national level. Elective dental tooth extraction admissions were selected using Hospital Episode Statistics. Admission trends for the first 14 pandemic months were compared with the previous five years and results were stratified by age (under-11s, 11-16s, 17-24s). The most socioeconomically deprived CYP comprised the largest proportion of elective dental tooth extraction admissions. In April 2020, admissions dropped by >95%. In absolute terms, the biggest reduction was in April (11-16s: -1339 admissions, 95% CI -1411 to -1267; 17-24s: -1600, -1678 to -1521) and May 2020 (under-11s: -2857, -2962 to -2752). Admissions differed by socioeconomic deprivation for the under-11s (P<0.0001), driven by fewer admissions than expected by the most deprived and more by the most affluent during the pandemic. Elective tooth extractions dropped most in April 2020, remaining below pre-pandemic levels throughout the study. Despite being the most likely to be admitted, the most deprived under-11s had the largest reductions in admissions relative to other groups.

Quantifying the impact of hospital catchment area definitions on hospital admissions forecasts: COVID-19 in England, September 2020–April 2021

BackgroundDefining healthcare facility catchment areas is a key step in predicting future healthcare demand in epidemic settings. Forecasts of hospitalisations can be informed by leading indicators measured at the community level. However, this relies on the definition of so-called catchment areas or the geographies whose populations make up the patients admitted to a given hospital, which are often not well-defined. Little work has been done to quantify the impact of hospital catchment area definitions on healthcare demand forecasting.MethodsWe made forecasts of local-level hospital admissions using a scaled convolution of local cases (as defined by the hospital catchment area) and delay distribution. Hospital catchment area definitions were derived from either simple heuristics (in which people are admitted to their nearest hospital or any nearby hospital) or historical admissions data (all emergency or elective admissions in 2019, or COVID-19 admissions), plus a marginal baseline definition based on the distribution of all hospital admissions. We evaluated predictive performance using each hospital catchment area definition using the weighted interval score and considered how this changed by the length of the predictive horizon, the date on which the forecast was made, and by location. We also considered the change, if any, in the relative performance of each definition in retrospective vs. real-time settings, or at different spatial scales.ResultsThe choice of hospital catchment area definition affected the accuracy of hospital admission forecasts. The definition based on COVID-19 admissions data resulted in the most accurate forecasts at both a 7- and 14-day horizon and was one of the top two best-performing definitions across forecast dates and locations. The “nearby” heuristic also performed well, but less consistently than the COVID-19 data definition. The marginal distribution baseline, which did not include any spatial information, was the lowest-ranked definition. The relative performance of the definitions was larger when using case forecasts compared to future observed cases. All results were consistent across spatial scales of the catchment area definitions.ConclusionsUsing catchment area definitions derived from context-specific data can improve local-level hospital admission forecasts. Where context-specific data is not available, using catchment areas defined by carefully chosen heuristics is a sufficiently good substitute. There is clear value in understanding what drives local admissions patterns, and further research is needed to understand the impact of different catchment area definitions on forecast performance where case trends are more heterogeneous.

An Analysis of New York Data: Fluctuations in Hospital Capacity Are Driven by Variability in Elective Admissions and Discharge Activity.

Background Hospital overcrowding compromises patient safety. The contribution of variability in admissions and discharges to overall hospital capacity needs to be quantified. This study describes the statewide day-to-day fluctuation in the volume of hospitalized patients, the variability and pattern of hospital admissions and discharges throughout the week, and the contribution of Emergency Department (ED) vs. elective (non-ED) admissions and discharges to the overall variability in the system across the week. Methodology This is a retrospective analysis of the New York State Statewide Planning and Research Cooperative System database, in which all New York healthcare facilities submit patient-level data monthly. The study period was from January 01 to December 31, 2015. Outcomes included total volumes of admissions and discharges and length of stay sorted by patient origin (ED vs. non-ED admits (elective)) and service type (medicine vs. surgery) by day of the week. Results We studied 1,692,090 hospital admissions. Admissions were highest on Mondays and Tuesdays and steadily decreased throughout the week. There was little variability in the ED admissions throughout the week. Surgical elective admissions had significant variability throughout the week, with higher admissions at the beginning of the week. There was a significant difference (p < 0.01) between admissions on weekdays vs. weekends. Discharges increased from Monday to Friday, with a dramatic drop on the weekends, for both ED and elective pathways. Systemwide, on Monday, hospitals were 21% above the mean volume, and on Fridays, hospitals were 32% below the mean volume. Conclusions Overall hospital capacity shows dramatic variability throughout the week, driven primarily by elective admissions and discharges from any source throughout the week. Because elective admissions are schedulable, hospitals can reduce variability by smoothing scheduling. Increased weekend discharges will also improve capacity.

COMPARATIVE ANALYSIS OF FEASIBILITY AND RELIABILITY OF PIM 3 SCORE VS. TRADITIONAL SCORING SYSTEMS: INSIGHTS FROM A SINGLE INSTITUTION

Objective: This comparative analysis explores the feasibility and reliability of the Pediatric Index of Mortality 3 (PIM 3) Score in contrast to traditional scoring systems within the context of a single institution. The study delves into the intricate landscape where the contemporary PIM 3 score converges with the time-honored methodologies of conventional scoring systems, offering valuable insights into prognostic evaluation.&#x0D; Methods: An observational prospective cohort study was conducted at Manipal Hospital, Bangalore, involving patients aged 1 mo to 18 y. The study focused on children admitted to the Pediatric Intensive Care Unit (PICU) for at least 1 hour, studying the feasibility of obtaining PIM 3 scores within the first hour. Exclusion criteria included neonates, infants less than one-month-old, and children requiring elective procedural sedation. Feasibility was assessed, and logistic regression was employed to evaluate PIM 3's ability to discriminate between survivors and non-survivors.&#x0D; Results: The training dataset comprised 2,534 patients with a mean age of 8.2 y. Patient characteristics, including age, gender, race, patient type, and origin, were well-distributed. Trauma and variables like elective admission and mechanical ventilation in the first hour were infrequent. The mortality rate across datasets was 1.0%. The PIM 3 risk of mortality and PICU medical length of stay were calculated, forming a comprehensive overview of patient profiles.&#x0D; Conclusion: The comparative analysis unfolds as a cerebral sojourn, revealing the intricate dance of perplexity and burstiness in the juxtaposition of PIM 3 score against traditional scoring systems. The study contributes nuanced insights, portraying each word and concept as integral notes in the composition of knowledge. This singular institutional perspective offers a profound understanding into the intricacies of prognostic evaluation, creating a narrative that transcends conventional methodologies.

When ‘Discharge Against Medical Advice’ (DAMA) rhymes with potential child neglect: a 10-year analysis in a tertiary care center

Introduction Taking into account parents’ privileged knowledge of their children, clinicians trust them to make the best decisions for their care. However, sometimes, their choices may appear misaligned with the child’s best interest, such as when “Discharge Against Medical Advice” (DAMA) occurs. In some instances, a DAMA will rhyme with a form of child maltreatment. Method This retrospective study analyzes all pediatric cases of DAMA presenting red flags for medical neglect from a tertiary care center in Saudi Arabia over 10 years (January 1, 2012, and December 31, 2022). The red flags were: 1) being an infant, 2) being vitally or clinically unstable, 3) refusing potential life-saving treatments, 4) presenting signs of physical, sexual, emotional abuse, or neglect, or 5) anticipating long-term consequences to forgo treatments. Data were retrieved from medical records. Results A total of 159 cases were identified with 47.2% females and a median age of 3.6 years. 57.9% were under 5 years. At baseline, 26.4% were medically free, and 73.6% had a significant or chronic illness. The most frequent reason for the encounter was an elective admission (44%). The most frequent red flag for neglect identified during DAMA was being “vitally or clinically unstable” (72.2%). Conclusion Clinicians may feel hesitant to disagree with parental care decisions which may make them worry as it may affect the trust between them. However, children are vulnerable, and all efforts should be made to ensure they get the required care. At times, this involves contacting Child Protection Services.

A119 ACUTE COLONOC PSEUDO-OBSTRUCTION AFTER ENDOSCOPIC RESECTION OF A FULLY CIRCUMFERENTIAL LARGE NON-PEDUNCULATED COLORECTAL POLYP

Abstract Background Complex large non-pedunculated colorectal polyps (LNPCPs), including those involving the full circumference of the bowel, are now readily managed by minimally invasive endoscopic resection techniques. Established procedure-related adverse events include sedation related adverse events, deep mural injury, clinically significant post-resection bleeding, delayed perforation and serositis. An appreciation for potential procedure-related adverse events is critical to the effective implementation of these techniques. Aims To describe a case of acute colonic pseudo-obstruction after endoscopic resection of a fully circumferential LNPCP. Methods Case report and review of the literature Results A 91-year-old male with a history of atrial fibrillation, chronic kidney disease and suspected McKittrick-Wheelock syndrome underwent successful endoscopic mucosal resection (EMR) of a 100mm fully circumferential LNPCP in the sigmoid colon. Histopathology diagnosed a tubulovillous adenoma with high-grade dysplasia. After elective admission, he suffered from clinically significant post-EMR bleeding requiring 2 units of packed red blood cells. On post-operative day 1 he began to suffer from nausea, abdominal pain and obstipation. On examination, he was visibly distended. Abdominal X-ray revealed extensive gas-filled loops of small and large bowel with the absence of gas in the rectum. He was managed conservatively with nasogastric tube decompression. Total duration of hospital stay was 9 days. Conclusions Critical to the continued expansion of minimally invasive endoscopic resection techniques is an awareness for potential procedure-related adverse events. To our knowledge this is the first description of acute colonic pseudo-obstruction after endoscopic resection Funding Agencies None

A232 TEMPORAL TRENDS IN RE-HOSPITALIZATION RATES AMONG PATIENTS WITH INFLAMMATORY BOWEL DISEASE IN THE POST-BIOLOGIC ERA

Abstract Background Hospitalization for severe inflammatory bowel disease (IBD) flares or complications are a major source of morbidity and healthcare expenditure. Aims To assess temporal trends in 30-day and 90-day re-hospitalization rates among persons with Crohn’s disease (CD) and ulcerative colitis (UC) in the post-biologic era. Methods We conducted a population-based study of all non-elective IBD-related hospitalizations among patients with CD and UC in Ontario, Canada between April 1, 2002 and March 31, 2020. We identified individuals, admissions, and variables of interest from Ontario population health administrative datasets housed at IC/ES. We performed multivariable logistic regression analysis to evaluate the association between time period of hospitalization (2002-2007 vs. 2002-2007 vs. 2007-2012 for CD; 2004-2008 vs. 2008-2012 vs. 2012-2016 vs. 2016-2020 for UC) and rates of 30-day and 90-day re-hospitalization, adjusting for patient age, sex, co-morbidities, residential setting, income quintile, hospital type of initial admission, and clustering of hospital admissions within patients. We excluded patients with elective admissions or length of stay ampersand:003C24 hours, and those without continuous valid Ontario health care registration during the 90-day period following hospital discharge. Results There were 18,625 hospitalizations among 14,868 patients with CD, and 10,830 hospitalizations among 9,264 patients with UC. The 30-day re-hospitalization rate was 8.5% for patients with CD and 9.7% for patients with UC, while the respective 90-day re-hospitalization rates were 15.0% and 13.8%. For CD, re-admission rates differed across the 3 time periods (pampersand:003C0.0001 for 30-day and p=0.012 for 90-day). For UC, re-hospitalization rates differed across the 4 time periods for 30-day re-hospitalization (p=0.048), but not 90-day (p=0.080). There was a higher relative odds of CD-related re-hospitalization in 2002-2007 as compared to 2012-2017 (adjusted odds ratio [aOR] 1.32, 95% confidence interval [CI] 1.16-1.50 for 30-day; aOR 1.14, 95% CI [1.03-1.26] for 90-day). For UC, there was a higher relative odds of re-hospitalization in 2012-2016 as compared to 2016-2020 (aOR 1.26, 95% CI [1.05-1.52] for 30-day; aOR 1.22, 95% CI [1.04-1.43] for 90-day). Conclusions Up to 15% of patients with IBD in Ontario are re-admitted to hospital within 90 days of hospital discharge. The risk of re-hospitalization may have decreased over time in the post-biologic era. Our findings could be explained by changing access to inpatient and/or outpatient resources, improvements to medical and/or surgical care, shifting patient behaviour with respect to healthcare resource utilization, or residual confounding. These results require validation in other jurisdictions. Funding Agencies None

A111 CHARACTERISTICS OF HOSPITALIZED PATIENTS WITH GASTROINTESTINAL DISEASE WHO LEAVE AGAINST MEDICAL ADVICE

Abstract Background Hospitalized inpatients who leave against medical advice (AMA) may have incomplete care, resulting in readmission and increased healthcare costs. Limited evidence exists in patients diagnosed with a primary gastrointestinal (GI) disease who leave AMA. Identifying patients with GI diagnoses who leave AMA may inform risk stratification to determine which patients are at risk of unplanned discharge. Aims Identify characteristics in patients diagnosed with GI diseases who leave AMA. Methods A retrospective evaluation was conducted using the National Inpatient Sample (NIS) from 2016 to 2020. The NIS provides national-level estimates of cost, quality, and outcomes from hospitalizations in the United States. We used International Classification of Diseases, Tenth Revision diagnostic coding to identify patients admitted with a primary GI problem. The proportion of patients who left AMA for each diagnosis was determined (Figure 1). A multivariable logistic regression was performed to determine factors associated with an AMA discharge, adjusting for age, sex, elective or weekend admission, primary payment method, race, hospital setting, geography, income, Elixhauser comorbidity index, alcohol and/or drug abuse and depression status. Results Between 2016 and 2020, 1.61% of patients with a GI primary problem left the hospital AMA. Characteristics associated with leaving AMA included: older age, female sex, non-white race, rural hospital admission, higher income and having comorbid conditions (Table 1). Patients with a history of alcohol abuse were more likely to leave AMA, while patients with a history of drug abuse were less likely to leave AMA. Conclusions Approximately 1 in 60 patients admitted with a primary GI problem leave hospital AMA and we identify both structural and patient-level factors associated with unplanned discharge. Table 1: Factors Associated With AMA Discharge For GI-related Diagnoses Funding Agencies None

Reliable Prediction of Discharge Disposition Following Cervical Spine Surgery With Ensemble Machine Learning and Validation on a National Cohort.

A retrospective cohort study. The purpose of this study is to develop a machine learning algorithm to predict nonhome discharge after cervical spine surgery that is validated and usable on a national scale to ensure generalizability and elucidate candidate drivers for prediction. Excessive length of hospital stay can be attributed to delays in postoperative referrals to intermediate care rehabilitation centers or skilled nursing facilities. Accurate preoperative prediction of patients who may require access to these resources can facilitate a more efficient referral and discharge process, thereby reducing hospital and patient costs in addition to minimizing the risk of hospital-acquired complications. Electronic medical records were retrospectively reviewed from a single-center data warehouse (SCDW) to identify patients undergoing cervical spine surgeries between 2008 and 2019 for machine learning algorithm development and internal validation. The National Inpatient Sample (NIS) database was queried to identify cervical spine fusion surgeries between 2009 and 2017 for external validation of algorithm performance. Gradient-boosted trees were constructed to predict nonhome discharge across patient cohorts. The area under the receiver operating characteristic curve (AUROC) was used to measure model performance. SHAP values were used to identify nonlinear risk factors for nonhome discharge and to interpret algorithm predictions. A total of 3523 cases of cervical spine fusion surgeries were included from the SCDW data set, and 311,582 cases were isolated from NIS. The model demonstrated robust prediction of nonhome discharge across all cohorts, achieving an area under the receiver operating characteristic curve of 0.87 (SD=0.01) on both the SCDW and nationwide NIS test sets. Anterior approach only, age, elective admission status, Medicare insurance status, and total Elixhauser Comorbidity Index score were the most important predictors of discharge destination. Machine learning algorithms reliably predict nonhome discharge across single-center and national cohorts and identify preoperative features of importance following cervical spine fusion surgery.