Exploring the role of in-patient magnetic resonance imaging use among admitted ischemic stroke patients in improving patient outcomes and reducing healthcare resource utilization.

Purpose: Despite the diagnostic and etiological significance of in-patient MRI in ischemic stroke (IS), its utilization is considered resource-intensive, expensive, and thus limiting feasibility and relevance. This study investigated the utilization of in-patient MRI for IS patients and its impact on patient and healthcare resource utilization outcomes. Methods: This retrospective registry-based study analyzed 1,956 IS patients admitted to Halifax's QEII Health Centre between 2015 and 2019. Firstly, temporal trends of MRI and other neuroimaging utilization were evaluated. Secondly, we categorized the cohort into two groups (MRI vs. No MRI; in addition to a non-contrast CT) and investigated adjusted differences in patient outcomes at admission, discharge, and post-discharge using logistic regression. Additionally, we analyzed healthcare resource utilization using Poisson log-linear regression. Furthermore, patient outcomes significantly associated with MRI use underwent subgroup analysis for stroke severity (mild stroke including transient ischemic attack vs. moderate and severe stroke) and any acute stage treatment (thrombolytic or thrombectomy or both vs. no treatment) subgroups, while using an age and sex-adjusted logistic regression model. Results: MRI was used in 40.5% patients; non-contrast CT in 99.3%, CT angiogram in 61.8%, and CT perfusion in 50.3%. Higher MRI utilization was associated with male sex, younger age, mild stroke, wake-up stroke, and no thrombolytic or thrombectomy treatment. MRI use was independently associated with lower in-hospital mortality (adjusted OR, 0.23; 95% CI, 0.15-0.36), lower symptomatic neurological status changes (0.64; 0.43-0.94), higher home discharge (1.32; 1.07-1.63), good functional outcomes at discharge (mRS score 0-2) (1.38; 1.11-1.72), lower 30-day stroke re-admission rates (0.48; 0.26-0.89), shorter hospital stays (regression coefficient, 0.92; 95% CI, 0.90-0.94), and reduced direct costs of hospitalization (0.90; 0.89-0.91). Subgroup analysis revealed significantly positive association of MRI use with most patient outcomes in moderate and severe strokes subgroup and non-acutely treated subgroup. Conversely, outcomes in mild strokes (including TIAs) subgroup and acute treatment subgroup were comparable regardless of MRI use. Conclusion: A substantial proportion of admitted IS patients underwent MRI, and MRI use was associated with improved patient outcomes and reduced healthcare resource utilization. Considering the multifactorial nature of IS patient outcomes, further randomized controlled trials are suggested to investigate the role of increased MRI utilization in optimizing in-patient IS management.

Obesity and Associated Outcomes for Blunt vs Penetrating Mechanism in Trauma Laparotomy Patients.

Obesity in trauma patients is an established risk factor contributing to postoperative complications, but the relationship between body mass index (BMI) and trauma patient outcomes is not well-defined, especially when stratified by mechanism of injury. We surveyed the trauma laparotomy registry at an academic level 1 trauma center over a 3-year period to identify mortality, injury severity score, and hospital length of stay (hLOS) outcome measures across BMI classes, with further stratification by mechanism of injury: blunt vs penetrating trauma. A total of 442 patients were included with mean age 44.6 (SD = 18.7) and mean BMI 28.55 (SD = 7.37). These were subdivided into blunt trauma (n = 313) and penetrating trauma (n = 129). Within the blunt trauma subgroup, the hLOS among patients who survived hospitalization significantly increased 9% for each successive BMI class (P = .022, 95% CI = 1.29-17.5). We conclude that successive increase in BMI class is associated with longer hospital stay for blunt trauma patient survivors requiring laparotomy, though additional analysis is needed to establish this relationship to other outcome measures and among penetrating trauma patients.

Outcomes and complications of heart failure with iron deficiency anemia: a nationwide analysis.

INTRODUCTION: Heart failure is a pressing public health concern, affecting millions in the United States and projected to rise significantly by 2030. Iron deficiency, prevalent in nearly half of ambulatory heart failure patients, contributes to anemia and diminishes patient outcomes. In this study, we aim to evaluate the impact of iron deficiency anemia on acute heart failure hospitalizations outcomes. METHODS: Utilizing the 2019 National Inpatient Sample (NIS) database, a retrospective observational study assessed 112,864 adult patients hospitalized with heart failure and 7,865 cases also had a concomitant diagnosis of iron deficiency anemia (IDA). RESULTS: Among 112,864 heart failure hospitalizations in 2019, approximately 7% had concomitant iron deficiency anemia (IDA). Heart failure patients with IDA exhibited distinct demographic characteristics, with females comprising 51.1% (p < 0.01) and higher rates of complicated hypertension (p < 0.01), complicated diabetes (p < 0.01), and peripheral vascular disease (p < 0.01). Adjusted mean LOS for patients with IDA was significantly longer at 1.31 days (95% CI 0.71-1.47; p < 0.01), persisting in both HFpEF and HFrEF subgroups. While total hospital charges were comparable in HFpEF, HFrEF patients with IDA incurred significantly higher charges ($13427.32, 95% CI: 1463.35-$25391.29, p = 0.03) than those without IDA. Complications such as atrial fibrillation and acute kidney injury were notably more prevalent in HFpEF and HFrEF patients with IDA. CONCLUSION: The study highlighted that iron deficiency in heart failure patients leads to extended hospital stays, increased costs, and heightened risks of specific complications, particularly in HFrEF. Our study emphasized the implications of IDA in patients with heart failure ranging from prolonged hospitalizations and increased costs. Addressing iron deficiency is crucial, given its substantial impact on heart failure hospitalizations and outcomes, emphasizing the need for proactive diagnosis and management.

Opportunity for Reduction of Intensive Care Unit Resource Utilization in Pediatric Blunt Liver and Spleen Injuries: A National Trauma Data Bank Analysis.

INTRODUCTION: Guidelines for blunt liver and spleen injury (BLSI) by the Arizona-Texas-Oklahoma-Memphis-Arkansas Consortium (ATOMAC) emphasize hemodynamic stability over injury grade when considering non-operative management (NOM). In this study, we examined rates of intensive care unit (ICU) admission for children with isolated low-risk BLSI among US hospitals. METHODS: The National Trauma Data Bank (NTDB) was queried for patients ages 1-15 admitted between 2017 and 2019 with BLSI. Patients with penetrating injuries and/or concomitant non-abdominal injuries with AIS score ≥3 were excluded. Isolated BLSI was considered low-risk if the patient had normal admission vitals and did not require operative intervention. Primary outcomes measured were ICU admission, ICU length of stay (LOS), and overall LOS. RESULTS: 5777 patients ages 15 and under presented with isolated BLSI during the study period. 2031/5777 (35.2%) were considered low-risk. Low-risk patients had lower rates of ICU admission compared to high-risk patients (30.9% vs. 41.6%, p < 0.001) and had shorter ICU LOS (median 2 days vs. 2, p < 0.001) and shorter overall LOS (median 41 h vs. 54, p < 0.001). Pediatric verified and non-pediatric verified trauma centers had similar rates of ICU admission (36.8% vs. 38.9%, p = 0.11). CONCLUSION: Further work is needed to capture opportunities for reduction in ICU utilization in isolated BLSI. LEVEL OF EVIDENCE: III.

Ketamine-based Sedation Use in Mechanically Ventilated Critically Ill Patients with COVID-19: A Multicenter Cohort Study.

Backgrounds: Ketamine possesses analgesia, anti-inflammation, anticonvulsant, and neuroprotection properties. However, the evidence that supports its use in mechanically ventilated critically ill patients with COVID-19 is insufficient. The study's goal was to assess ketamine's effectiveness and safety in critically ill, mechanically ventilated (MV) patients with COVID-19. Methods: Adult critically ill patients with COVID-19 were included in a multicenter retrospective-prospective cohort study. Patients admitted between March 1, 2020, and July 31, 2021, to five ICUs in Saudi Arabia were included. Eligible patients who required MV within 24 hours of ICU admission were divided into two sub-cohort groups based on their use of ketamine (Control vs. Ketamine). The primary outcome was the length of stay (LOS) in the hospital. P/F ratio differences, lactic acid normalization, MV duration, and mortality were considered secondary outcomes. Propensity score (PS) matching was used (1:2 ratio) based on the selected criteria. Results: In total, 1,130 patients met the eligibility criteria. Among these, 1036 patients (91.7 %) were in the control group, whereas 94 patients (8.3 %) received ketamine. The total number of patients after PS matching, was 264 patients, including 88 patients (33.3 %) who received ketamine. The ketamine group's LOS was significantly lower (beta coefficient (95 % CI): -0.26 (-0.45, -0.07), P = 0.008). Furthermore, the PaO2/FiO2 ratio significantly improved 24 hours after the start of ketamine treatment compared to the pre-treatment period (6 hours) (124.9 (92.1, 184.5) vs. 106 (73.1, 129.3; P = 0.002). Additionally, the ketamine group had a substantially shorter mean time for lactic acid normalization (beta coefficient (95 % CI): -1.55 (-2.42, -0.69), P 0.01). However, there were no significant differences in the duration of MV or mortality. Conclusions: Ketamine-based sedation was associated with lower hospital LOS and faster lactic acid normalization but no mortality benefits in critically ill patients with COVID-19. Thus, larger prospective studies are recommended to assess the safety and effectiveness of ketamine as a sedative in critically ill adult patients.

Models to predict length of stay in the emergency department: a systematic literature review and appraisal.

INTRODUCTION: Prolonged Length of Stay (LOS) in ED (Emergency Department) has been associated with poor clinical outcomes. Prediction of ED LOS may help optimize resource utilization, clinical management, and benchmarking. This study aims to systematically review models for predicting ED LOS and to assess the reporting and methodological quality about these models. METHODS: The online database PubMed, Scopus, and Web of Science (10 Sep 2023) was searched for English language articles that reported prediction models of LOS in ED. Identified titles and abstracts were independently screened by two reviewers. All original papers describing either development (with or without internal validation) or external validation of a prediction model for LOS in ED were included. RESULTS: Of 12,193 uniquely identified articles, 34 studies were included (29 describe the development of new models and five describe the validation of existing models). Different statistical and machine learning methods were applied to the papers. On the 39-point reporting score and 11-point methodological quality score, the highest reporting scores for development and validation studies were 39 and 8, respectively. CONCLUSION: Various studies on prediction models for ED LOS were published but they are fairly heterogeneous and suffer from methodological and reporting issues. Model development studies were associated with a poor to a fair level of methodological quality in terms of the predictor selection approach, the sample size, reproducibility of the results, missing imputation technique, and avoiding dichotomizing continuous variables. Moreover, it is recommended that future investigators use the confirmed checklist to improve the quality of reporting.

Retrospective study on the health and economic burden of hospitalized patients due to pneumonia and invasive pneumococcal infections in Belgium settings.

INTRODUCTION: pneumococcal infections are associated with high morbidity, hospitalisation and mortality. The objective of this study was to investigate the health and economic burden of all-cause pneumonia and invasive pneumococcal disease in Belgian hospital settings, by patient's age and risk profile. METHODS: This descriptive retrospective study was conducted in 17 Belgian hospitals. Univariate and multivariate logistic linear regression models were performed. The Health Insurance and patient's cost perspectives were considered because a few studies report these costs. RESULTS: The analysis has included 4,712 hospital admissions over the year 2018. Median hospitalization costs were higher for invasive pneumococcal infection diagnosis than for all-cause pneumonia (p < 0,001), respectively 4,051€ and 3,362€. Other factors associated with higher hospitalization cost were patient's high-risk profile, admission to emergency unit, transfer from nursing home, admission to intensive care unit and length of stay. CONCLUSION: Streptococcus pneumoniae infections remain a public health problem with significant cost for the Health Insurance and poor prognosis. Invasive pneumococcal infections are associated with longer hospital stays and required more intensive care than all other causes of pneumonia, in addition to be more costly, which justifies more attention for vaccination. This study also suggests an increase of economic and health burden with age and presence of underlying conditions.

Treatment with systemic corticosteroid versus placebo for exacerbations of COPD: A systematic review and meta-analysis.

BACKGROUND: For the treatment of COPD exacerbations, systemic corticosteroids are recommended in addition to short-acting bronchodilators. Although there have been several systemic reviews, many of the included studies were conducted before 2007 and a re-evaluation has not been performed since 2014. Therefore, we conducted a systematic review and meta-analysis to evaluate the efficacy and safety profile of systemic corticosteroids in patients with COPD during exacerbations. METHODS: We searched relevant randomized control trials (RCTs) and analyzed the treatment failure, relapse, lung function, improvement in PaO2 and PaCO2, dyspnea, quality of life (QOL), length of stay in hospital and adverse events including hyperglycemia and mortality as the outcomes of interest. RESULTS: We identified a total of 12 RCTs (N = 1336). Systemic corticosteroids significantly reduced the treatment failure (odds ratios; OR 0.41, 95% confidence intervals; CI 0.25 to 0.67) and hospital length of stay (mean difference; MD -1.57 days, 95% CI -2.36 to -0.78) and improved FEV1 (MD 0.18 L, 95% CI 0.08 to 0.28) and dyspnea (transitional dyspnea index; MD 1.90, 95% CI 0.26 to 3.54) in COPD exacerbations compared to placebo. However, systemic corticosteroids were associated with a significantly higher incidence of adverse events (OR 1.83, 95% CI 1.25 to 2.69) and hyperglycemia (OR 2.94, 95% CI 1.68 to 5.14). CONCLUSIONS: In patients with moderate and severe COPD and severe obstructive impairment during exacerbations, systemic corticosteroids cause more adverse events, including hyperglycemia, than placebo but significantly reduce the treatment failure and hospital length of stay and improve FEV1 and dyspnea.

The i-gel® supraglottic airway device compared to endotracheal intubation as the initial prehospital advanced airway device: A natural experiment during the COVID-19 pandemic.

Objective: Unlike randomized controlled trials, practical real-world studies can offer important information about implementation of prehospital interventions, particularly in community settings where there may be reluctance to adopt new practices. We present the results of a natural experiment that was driven by mandated COVID-19 pandemic-driven shift from endotracheal intubation (ETI) to the i-gel® supraglottic airway (SGA) as a primary advanced airway management device in the prehospital setting to reduce emergency medical services (EMS) personnel exposure to potentially infectious secretions. The objective was to compare first-pass success and timing to successful airway placement between ETI and the i-gel® SGA under extenuating circumstances. Methods: This pre/post study compared airway placement metrics in prehospital patients requiring advance airway management for non-trauma-related conditions. Data from EMS records were extracted over 2 years, 12 months pre-pandemic, and 12 months post-pandemic. During the pre-COVID-19 year, the EMS protocols utilized ETI as the primary advanced airway device (ETI group). Post-pandemic paramedics were mandated to utilize i-gel® SGA as the primary advanced airway device to reduce exposure to secretions (SGA group). Results: There were 199 adult patients, 83 (42%) in the ETI group and 116 (58%) in the SGA group. First-pass success was significantly higher with SGA 96% (92%-99%) than ETI 68% (57%-78%) with paramedics citing the inability to visualize the airway in 52% of ETI cases. Time to first-pass success was significantly shorter in the SGA group (5.9 min [5.1-6.7 min]) than in the ETI group (8.3 min [6.9-9.6 min]), as was time to overall successful placement at 6.0 min (5.1-6.8 min) versus 9.6 min (8.2-11.1 min), respectively. Multiple placement attempts were required in 26% of ETI cases and 1% of the SGA cases. There were no statistically significant differences in the number and types of complications between the cohorts. Return of spontaneous circulation (on/before emergency department [ED] arrival), mortality at 28 days, intensive care unit length of stay, or ventilator-free days between the groups were not statistically different between the groups. Conclusion: In this natural experiment, the SGA performed significantly better than ETI in first-pass airway device placement success and was significantly faster in achieving first-pass success, and overall airway placement, thus potentially reducing exposure to respiratory pathogens. Practical real-world studies can offer important information about implementation of prehospital interventions, particularly in community settings and in systems with a low frequency of tracheal intubations.

Reduced Opioid Use Among Patients Who Received Liposomal Bupivacaine Brachial Plexus Block for Total Shoulder Arthroplasty.

Purpose This retrospective cohort explores the efficacy of regional shoulder blocks using Exparel™ in patients undergoing total shoulder arthroplasty (TSA)/reverse total shoulder arthroplasty (RSA) to reduce total opioid prescription, refills, and length of stay in the acute care setting. Methods Patients who underwent TSA/RSA by a single surgeon in a three-year period were evaluated. Patients in the case group received liposomal bupivacaine 1.3% brachial plexus block while the control group received ropivacaine 0.5% interscalene brachial plexus block. Outcomes of the study included the number of opioids taken, opioids prescribed, and length of hospital stay. Results Thirty-six patients underwent TSA/RSA between January 2017 and March 2020. Patients who received an Exparel brachial plexus block had decreased opioid use within the first 24 hours after surgery compared to the ropivacaine group, 9.00 ± 14.10 and 26.20 ± 24.8 morphine milligram equivalent (MME), respectively (p=0.0213). Patients who received an Exparel brachial plexus block had decreased opioid prescriptions over the entire postoperative follow-up, 411.00 ± 200.74 MME in the case group and 593.07 ± 297.57 MME in the control group (p=0.0314). Lastly, patients who received an Exparel brachial plexus block had a shorter length of hospital stay, 1.28 ± 0.91 days as compared to the control group's 2.15 ± 1.49 days (p=0.0451). Conclusion This study demonstrates a significant reduction in opioid prescribing and use in patients who receive Exparel brachial plexus nerve blocks compared to non-liposomal local anesthetics, as well as a significant reduction in the length of hospital stay. The data suggest that Exparel use may decrease the risks associated with opioid use while providing adequate analgesia in patients undergoing shoulder arthroplasty.

Factors associated with increased length of stay in degenerative cervical spine surgery: a cohort analysis from the Canadian Spine Outcomes and Research Network.

OBJECTIVE: Postoperative length of stay (LOS) significantly contributes to healthcare costs and resource utilization. The primary goal of this study was to identify patient, clinical, surgical, and institutional variables that influence LOS after elective surgery for degenerative conditions of the cervical spine. The secondary objectives were to examine the variability in LOS and institutional practices used to decrease LOS. METHODS: This was a multicenter observational retrospective cohort study of patients enrolled in the Canadian Spine Outcomes and Research Network (CSORN) between January 2015 and October 2020 who underwent elective anterior cervical discectomy and fusion (ACDF) (1-3 levels) or posterior cervical fusion (PCF) (between C2 and T2) with/without decompression for degenerative conditions of the cervical spine. Prolonged LOS was defined as LOS greater than the median for the ACDF and PCF populations. The principal investigators at each participating CSORN healthcare institution completed a survey to capture institutional practices implemented to reduce postoperative LOS. RESULTS: In total, 1228 patients were included (729 ACDF and 499 PCF patients). The median (IQR) LOS for ACDF and PCF were 1.0 (1.0) day and 5.0 (4.0) days, respectively. Predictors of prolonged LOS after ACDF were female sex, myelopathy diagnosis, lower baseline SF-12 mental component summary score, multilevel ACDF, and perioperative adverse events (AEs) (p < 0.05). Predictors of prolonged LOS after PCF were nonsmoking status, education less than high school, lower baseline numeric rating scale score for neck pain and EQ5D score, higher baseline Neck Disability Index score, and perioperative AEs (p < 0.05). Myelopathy did not significantly predict prolonged LOS within the PCF cohort after multivariate analysis. Of the 8 institutions (57.1%) with an enhanced recovery after surgery (ERAS) protocol or standardized protocol, only 3 reported using an ERAS protocol specific to patients undergoing ACDF or PCF. CONCLUSIONS: Patient and clinical factors predictive of prolonged LOS after ACDF and PCF are highly variable, warranting individual consideration for possible mitigation. Perioperative AEs remained a consistent independent predictor of prolonged LOS in both cohorts, highlighting the importance of preventing intra- and postoperative complications.

Delayed discharge in inpatient psychiatric care: a systematic review.

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. CONCLUSION: 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. REVIEW REGISTRATION NUMBER ON PROSPERO: 292515. DATE OF REGISTRATION: 9th December 2021.

Factors affecting hospital admission, hospital length of stay and new discharge destination post proximal humeral fracture: a retrospective audit.

BACKGROUND: Outcomes following proximal humeral fracture (PHF) may be impacted by a range of clinical, fracture and premorbid factors. The aim of this study was to examine factors impacting hospital admission; length of stay (LOS) and new discharge destination for patients presenting to hospital with PHF. METHODS: Retrospective audit conducted at a tertiary health service. Data was collected from adult patients presenting to hospital with a PHF over a 54-month period. Fractures that were pathological or sustained during admission were excluded. Univariable and multivariable logistic and negative binomial regression were used to explore factors associated with hospital admission, LOS and new discharge destination. RESULTS: Data were analyzed from 701 participants (age 70 years (IQR 60, 81); 72.8% female); 276 (39.4%) participants required a hospital admission. New discharge destination was required for 109 (15.5%) participants, of whom 49 (45%) changed from home alone to home with family/friend(s). Greater comorbidities, as indicated by the Charlson Comorbidity Index score, were associated with hospital admission, longer LOS and new discharge destination. Premorbid living situations of home with family/friend(s) or from an external care facility were associated with a decreased likelihood of hospital admission, shorter LOS and reduced risk of a new discharge destination. Surgical treatment was associated with shorter LOS. Older age and dementia diagnosis were associated with a new discharge destination. CONCLUSIONS: Many factors potentially impact on the likelihood or risk of hospitalization, LOS and new discharge destination post PHF. Patients with greater comorbidities are more likely to have negative outcomes, while patients who had premorbid living situations of home with family/friend(s) or from an external care facility are more likely to have positive outcomes. Early identification of factors that may impact patient outcomes may assist timely decision making in hospital settings. Further research should focus on developing tools to predict hospital outcomes in the PHF population.

Is alcohol and psychoactive medication use associated with excess hospital length-of-stay and admission frequency? A cross-sectional, observational study.

BACKGROUND: Hospital length-of-stay and admission frequency are commonly used indicators of disease burden and health resource expenditures. However, the impact of psychoactive prescription medication use and harmful alcohol consumption on both the duration and frequency of hospital admissions is under-explored. METHODS: We conducted an analysis of data gathered from 2872 patients admitted to the Emergency Department at Lovisenberg Diaconal Hospital in Oslo, Norway. Psychoactive medicines (benzodiazepines, opioids, and z-hypnotics) were detected via liquid chromatography-mass spectrometry analysis of whole blood, while alcohol consumption was self-reported through the Alcohol Use Disorder Identification Test-4 (AUDIT-4). Using logistic regression, we examined associations with our primary outcomes, which were excess length-of-stay and admission frequency, defined as exceeding the sample median of 3.0 days and 0.2 admissions per year, respectively. RESULTS: Compared to the absence of psychoactive medication, and after adjusting for age, gender, malignant disease, pre-existing substance use disorder and admission due to intoxication, the detection of two or more psychoactive medicines was associated with both excess length-of-stay (odds ratio [OR], 1.60; 95% confidence interval [CI], 1.20 to 2.14) and yearly hospitalization rate (OR, 3.72; 95% CI, 2.64 to 5.23). This association persisted when increasing the definition for excess length-of-stay to 4 and 5 days and to 1.0 and 1.5 admissions per year for admission frequency. Harmful alcohol consumption (AUDIT-4 scores of 9 to 16) was not associated with excess length-of-stay, but with excess admission frequency when defined as more than 1.0 admission per year when compared to scores of 4 to 6 (OR, 2.68; 95% CI, 1.58 to 4.57). CONCLUSIONS: Psychoactive medication use is associated with both excess length-of-stay and increased antecedent admission frequency, while harmful alcohol consumption may be associated with the latter. The utility of our findings as a causal factor should be explored through intervention-based study designs.

Interpretable Deep Learning System for Identifying Critical Patients Through the Prediction of Triage Level, Hospitalization, and Length of Stay: Prospective Study.

BACKGROUND: Triage is the process of accurately assessing patients' symptoms and providing them with proper clinical treatment in the emergency department (ED). While many countries have developed their triage process to stratify patients' clinical severity and thus distribute medical resources, there are still some limitations of the current triage process. Since the triage level is mainly identified by experienced nurses based on a mix of subjective and objective criteria, mis-triage often occurs in the ED. It can not only cause adverse effects on patients, but also impose an undue burden on the health care delivery system. OBJECTIVE: Our study aimed to design a prediction system based on triage information, including demographics, vital signs, and chief complaints. The proposed system can not only handle heterogeneous data, including tabular data and free-text data, but also provide interpretability for better acceptance by the ED staff in the hospital. METHODS: In this study, we proposed a system comprising 3 subsystems, with each of them handling a single task, including triage level prediction, hospitalization prediction, and length of stay prediction. We used a large amount of retrospective data to pretrain the model, and then, we fine-tuned the model on a prospective data set with a golden label. The proposed deep learning framework was built with TabNet and MacBERT (Chinese version of bidirectional encoder representations from transformers [BERT]). RESULTS: The performance of our proposed model was evaluated on data collected from the National Taiwan University Hospital (901 patients were included). The model achieved promising results on the collected data set, with accuracy values of 63%, 82%, and 71% for triage level prediction, hospitalization prediction, and length of stay prediction, respectively. CONCLUSIONS: Our system improved the prediction of 3 different medical outcomes when compared with other machine learning methods. With the pretrained vital sign encoder and repretrained mask language modeling MacBERT encoder, our multimodality model can provide a deeper insight into the characteristics of electronic health records. Additionally, by providing interpretability, we believe that the proposed system can assist nursing staff and physicians in taking appropriate medical decisions.

Predictors of prolonged length of stay in adult patients with respiratory syncytial virus infections - a multi-center historical cohort study.

Objectives: Several studies have reported risk factors for severe disease and mortality in hospitalized adults with RSV infections. There is limited information available regarding the factors that affect the duration of a patient's hospital length of stay (LOS). Methods: This was a multicenter historical cohort study of adult patients hospitalized for laboratory-confirmed RSV in Southeast Michigan between January 2017 and December 2021. Hospitalized patients were identified using the International Classification of Diseases, Tenth Revision 10 codes for RSV infection. Mean LOS was computed; prolonged LOS was defined as greater than the mean. Results: We included 360 patients with a mean age (SD) of 69.9 ± 14.7 years, 63.6% (229) were female and 63.3% (228) of white race. The mean hospital LOS was 7.1 ± 5.4 days. Factors associated with prolonged LOS in univariable analysis were old age, body mass index (BMI), smoking status, Charlson Weighted Index of Comorbidity (CWIC), home oxygen, abnormal chest x-ray (CXR), presence of sepsis, use of oxygen, and antibiotics at the time of presentation. Predictors for prolonged LOS on admission in multivariable analysis were age on admission (p < 0.001), smoking status (p = 0.001), CWIC (p = 0.038) and abnormal CXR (p = 0.043). Interpretation: Our study found that age on admission, smoking history, higher CWIC and abnormal CXR on admission were significantly associated with prolonged LOS among adult patients hospitalized with RSV infection. These findings highlight the significance of promptly recognizing and implementing early interventions to mitigate the duration of hospitalization for adult patients suffering from RSV infection.

A Novel Digital Health Platform With Health Coaches to Optimize Surgical Patients: Feasibility Study at a Large Academic Health System.

BACKGROUND: Pip is a novel digital health platform (DHP) that combines human health coaches (HCs) and technology with patient-facing content. This combination has not been studied in perioperative surgical optimization. OBJECTIVE: This study's aim was to test the feasibility of the Pip platform for deploying perioperative, digital, patient-facing optimization guidelines to elective surgical patients, assisted by an HC, at predefined intervals in the perioperative journey. METHODS: We conducted an institutional review board-approved, descriptive, prospective feasibility study of patients scheduled for elective surgery and invited to enroll in Pip from 2.5 to 4 weeks preoperatively through 4 weeks postoperatively at an academic medical center between November 22, 2022, and March 27, 2023. Descriptive primary end points were patient-reported outcomes, including patient satisfaction and engagement, and Pip HC evaluations. Secondary end points included mean or median length of stay (LOS), readmission at 7 and 30 days, and emergency department use within 30 days. Secondary end points were compared between patients who received Pip versus patients who did not receive Pip using stabilized inverse probability of treatment weighting. RESULTS: A total of 283 patients were invited, of whom 172 (60.8%) enrolled in Pip. Of these, 80.2% (138/172) patients had ≥1 HC session and proceeded to surgery, and 70.3% (97/138) of the enrolled patients engaged with Pip postoperatively. The mean engagement began 27 days before surgery. Pip demonstrated an 82% weekly engagement rate with HCs. Patients attended an average of 6.7 HC sessions. Of those patients that completed surveys (95/138, 68.8%), high satisfaction scores were recorded (mean 4.8/5; n=95). Patients strongly agreed that HCs helped them throughout the perioperative process (mean 4.97/5; n=33). The average net promoter score was 9.7 out of 10. A total of 268 patients in the non-Pip group and 128 patients in the Pip group had appropriate overlapping distributions of stabilized inverse probability of treatment weighting for the analytic sample. The Pip cohort was associated with LOS reduction when compared to the non-Pip cohort (mean 2.4 vs 3.1 days; median 1.9, IQR 1.0-3.1 vs median 3.0, IQR 1.1-3.9 days; mean ratio 0.76; 95% CI 0.62-0.93; P=.009). The Pip cohort experienced a 49% lower risk of 7-day readmission (relative risk [RR] 0.51, 95% CI 0.11-2.31; P=.38) and a 17% lower risk of 30-day readmission (RR 0.83, 95% CI 0.30-2.31; P=.73), though these did not reach statistical significance. Both cohorts had similar 30-day emergency department returns (RR 1.06, 95% CI 0.56-2.01, P=.85). CONCLUSIONS: Pip is a novel mobile DHP combining human HCs and perioperative optimization content that is feasible to engage patients in their perioperative journey and is associated with reduced hospital LOS. Further studies assessing the impact on clinical and patient-reported outcomes from the use of Pip or similar DHPs HC combinations during the perioperative journey are required.

The COVID-19 Tracheostomy Experience at a Large Academic Medical Center in New York during the First Year.

Background: New York City was the epicenter of the initial surge of the COVID-19 pandemic in the United States. Tracheostomy is a critical procedure in the care of patients with COVID-19. We hypothesized that early tracheostomy would decrease the length of time on sedation, time on mechanical ventilation, intensive care unit length of stay, and mortality. Methods: A retrospective analysis of outcomes for all patients with COVID-19 who underwent tracheostomy during the first year of the COVID-19 pandemic at the Mount Sinai Hospital in New York City, New York. All adult intensive care units at the Mount Sinai Hospital, New York. Patients/subjects: 888 patients admitted to intensive care with COVID-19. Results: All patients admitted to the intensive care unit with COVID-19 (888) from 1 March 2020 to 1 March 2021 were analyzed and separated further into those intubated (544) and those requiring tracheostomy (177). Of those receiving tracheostomy, outcomes were analyzed for early (≤12 days) or late (>12 days) tracheostomy. Demographics, medical history, laboratory values, type of oxygen and ventilatory support, and clinical outcomes were recorded and analyzed. Conclusions: Early tracheostomy resulted in reduced duration of mechanical ventilation, reduced hospital length of stay, and reduced intensive care unit length of stay in patients admitted to the intensive care unit with COVID-19. There was no effect on overall mortality.

Enhancing discharge decision-making through continuous monitoring in an acute admission ward: a randomized controlled trial.

In Acute Admission Wards, vital signs are commonly measured only intermittently. This may result in failure to detect early signs of patient deterioration and impede timely identification of patient stability, ultimately leading to prolonged stays and avoidable hospital admissions. Therefore, continuous vital sign monitoring may improve hospital efficacy. The objective of this randomized controlled trial was to evaluate the effect of continuous monitoring on the proportion of patients safely discharged home directly from an Acute Admission Ward. Patients were randomized to either the control group, which received usual care, or the sensor group, which additionally received continuous monitoring using a wearable sensor. The continuous measurements could be considered in discharge decision-making by physicians during the daily bedside rounds. Safe discharge was defined as no unplanned readmissions, emergency department revisits or deaths, within 30 days after discharge. Additionally, length of stay, the number of Intensive Care Unit admissions and Rapid Response Team calls were assessed. In total, 400 patients were randomized, of which 394 completed follow-up, with 196 assigned to the sensor group and 198 to the control group. The proportion of patients safely discharged home was 33.2% in the sensor group and 30.8% in the control group (p = 0.62). No significant differences were observed in secondary outcomes. The trial was terminated prematurely due to futility. In conclusion, continuous monitoring did not have an effect on the proportion of patients safely discharged from an Acute Admission Ward. Implementation challenges of continuous monitoring may have contributed to the lack of effect observed. Trial registration: https://clinicaltrials.gov/ct2/show/NCT05181111 . Registered: January 6, 2022.

A comprehensive benchmark for COVID-19 predictive modeling using electronic health records in intensive care.

The COVID-19 pandemic highlighted the need for predictive deep-learning models in health care. However, practical prediction task design, fair comparison, and model selection for clinical applications remain a challenge. To address this, we introduce and evaluate two new prediction tasks-outcome-specific length-of-stay and early-mortality prediction for COVID-19 patients in intensive care-which better reflect clinical realities. We developed evaluation metrics, model adaptation designs, and open-source data preprocessing pipelines for these tasks while also evaluating 18 predictive models, including clinical scoring methods and traditional machine-learning, basic deep-learning, and advanced deep-learning models, tailored for electronic health record (EHR) data. Benchmarking results from two real-world COVID-19 EHR datasets are provided, and all results and trained models have been released on an online platform for use by clinicians and researchers. Our efforts contribute to the advancement of deep-learning and machine-learning research in pandemic predictive modeling.