Quality of hospital care and clinical outcomes: a comparison between the Lombardy Region and the Italian national data.

Background: Improving the quality and effectiveness of healthcare is a key priority in health policy. The emergence of the COVID-19 pandemic has exerted considerable pressure on hospital networks, requiring unprecedented reorganization and restructuring actions. This study analyzed data from the Italian National Outcomes Program to compare some volumes and outcomes of public and private accredited hospitals in the Lombardy Region with national data. Study design: Observational study. Methods: A thorough examination of hospital outcomes between 2019 and 2021 was conducted, considering 45 volume indicators and 48 process and outcome indicators, comparing Lombardy with other Italian regions and public versus private accredited hospitals. Results: In 2020, Italy and Lombardy experienced a considerable reduction in overall hospital admissions, with Lombardy showing a deeper decline (21.3% compared with 16.0% in Italy). In 2021, both experienced a partial recovery, especially marked in the Lombardy region (+7.3%, compared with national data). Focusing specifically on the private sector in Lombardy, a recovery of +9.3% in hospitalization was observed. In the analysis of clinical outcomes, Lombardy outperformed the national average for 63% of the indicators in 2020 and 83.3% in 2021. Conclusions: The study shows the continuing decline in volumes compared to 2019 (pre-COVID), the excellent performance of hospitals in Lombardy and a relevant contribution for the volumes and the quality of outcomes of private accredited hospitals.

Pediatric Mental Health Hospitalizations at Acute Care Hospitals in the US, 2009-2019.

Importance: Approximately 1 in 6 youth in the US have a mental health condition, and suicide is a leading cause of death among this population. Recent national statistics describing acute care hospitalizations for mental health conditions are lacking. Objectives: To describe national trends in pediatric mental health hospitalizations between 2009 and 2019, to compare utilization among mental health and non-mental health hospitalizations, and to characterize variation in utilization across hospitals. Design, Setting, and Participants: Retrospective analysis of the 2009, 2012, 2016, and 2019 Kids' Inpatient Database, a nationally representative database of US acute care hospital discharges. Analysis included 4 767 840 weighted hospitalizations among children 3 to 17 years of age. Exposures: Hospitalizations with primary mental health diagnoses were identified using the Child and Adolescent Mental Health Disorders Classification System, which classified mental health diagnoses into 30 mutually exclusive disorder types. Main Outcomes and Measures: Measures included number and proportion of hospitalizations with a primary mental health diagnosis and with attempted suicide, suicidal ideation, or self-injury; number and proportion of hospital days and interfacility transfers attributable to mental health hospitalizations; mean lengths of stay (days) and transfer rates among mental health and non-mental health hospitalizations; and variation in these measures across hospitals. Results: Of 201 932 pediatric mental health hospitalizations in 2019, 123 342 (61.1% [95% CI, 60.3%-61.9%]) were in females, 100 038 (49.5% [95% CI, 48.3%-50.7%]) were in adolescents aged 15 to 17 years, and 103 456 (51.3% [95% CI, 48.6%-53.9%]) were covered by Medicaid. Between 2009 and 2019, the number of pediatric mental health hospitalizations increased by 25.8%, and these hospitalizations accounted for a significantly higher proportion of pediatric hospitalizations (11.5% [95% CI, 10.2%-12.8%] vs 19.8% [95% CI, 17.7%-21.9%]), hospital days (22.2% [95% CI, 19.1%-25.3%] vs 28.7% [95% CI, 24.4%-33.0%]), and interfacility transfers (36.9% [95% CI, 33.2%-40.5%] vs 49.3% [95% CI, 45.9%-52.7%]). The percentage of mental health hospitalizations with attempted suicide, suicidal ideation, or self-injury diagnoses increased significantly from 30.7% (95% CI, 28.6%-32.8%) in 2009 to 64.2% (95% CI, 62.3%-66.2%) in 2019. Length of stay and interfacility transfer rates varied significantly across hospitals. Across all years, mental health hospitalizations had significantly longer mean lengths of stay and higher transfer rates compared with non-mental health hospitalizations. Conclusions and Relevance: Between 2009 and 2019, the number and proportion of pediatric acute care hospitalizations due to mental health diagnoses increased significantly. The majority of mental health hospitalizations in 2019 included a diagnosis of attempted suicide, suicidal ideation, or self-injury, underscoring the increasing importance of this concern.

What's the Future of Hospital at Home in the United States?

Sustainable and equitable payment structures are urgently needed for this promising acute care model.

Changes in In-Hospital Survival and Long-Term Neurodevelopmental Outcomes of Extremely Preterm Infants: A Retrospective Study of a Japanese Tertiary Center.

OBJECTIVES: The objective of this study was to elucidate whether the survival and long-term neurodevelopmental outcomes of extremely preterm infants have improved in a Japanese tertiary center with an active treatment policy for infants born at 22-23 weeks of gestation. STUDY DESIGN: This single-centered retrospective cohort study enrolled extremely preterm infants treated at Saitama Medical Center, Saitama Medical University, from 2003 to 2014. Patients with major congenital abnormalities were excluded. Primary outcomes were in-hospital survival and severe neurodevelopmental impairment (NDI) at 6 years of age, which was defined as having severe cerebral palsy, severe cognitive impairment, severe visual impairment, or deafness. We assessed the changes in primary outcomes between the first (period 1; 2003-2008) and the second half (period 2; 2009-2014) of the study period and evaluated the association between birth-year and primary outcomes using multivariate logistic regression models. RESULTS: Of the 403 eligible patients, 340 (84%) survived to discharge. Among 248 patients available at 6 years of age, 43 (14%) were classified as having severe NDI. Between the 2 periods, in-hospital survival improved from 155 of 198 (78%) to 185 of 205 (90%), but severe NDI increased from 11 of 108 (10%) to 32 of 140 (23%). In multivariate logistic regression models adjusted for gestational age, birthweight, sex, singleton birth, and antenatal corticosteroids, the aOR (95% CI) of birth-year for in-hospital survival and severe NDI was 1.2 (1.1-1.3) and 1.1 (1.0-1.3), respectively. CONCLUSION: Mortality among extremely preterm infants has improved over the past 12 years; nevertheless, no significant improvement was observed in the long-term neurodevelopmental outcomes.

Hospital Characteristics and Early Enrollment Trends in the American College of Cardiology Voluntary Public Reporting Program.

Importance: Limited data exist regarding the characteristics of hospitals that do and do not participate in voluntary public reporting programs. Objective: To describe hospital characteristics and trends associated with early participation in the American College of Cardiology (ACC) voluntary reporting program for cardiac catheterization-percutaneous coronary intervention (CathPCI) and implantable cardioverter-defibrillator (ICD) registries. Design, Setting, and Participants: This cross-sectional study analyzed enrollment trends and characteristics of hospitals that did and did not participate in the ACC voluntary public reporting program. All hospitals reporting procedure data to the National Cardiovascular Data Registry (NCDR) CathPCI or ICD registries that were eligible for the public reporting program from July 2014 (ie, program launch date) to May 2017 were included. Stepwise logistic regression was used to identify hospital characteristics associated with voluntary participation. Enrollment trends were evaluated considering the date US News & World Report (USNWR) announced that it would credit participating hospitals. Data analysis was performed from March 2017 to January 2018. Main Outcomes and Measures: Hospital characteristics and participation in the public reporting program. Results: By May 2017, 561 of 1747 eligible hospitals (32.1%) had opted to participate in the program. Enrollment increased from 240 to 376 hospitals (56.7%) 1 month after the USNWR announcement that program participation would be considered as a component of national hospital rankings. Compared with hospitals that did not enroll, program participants had increased median (IQR) procedural volumes for PCI (481 [280-764] procedures vs 332 [186-569] procedures; P < .001) and ICD (114 [56-220] procedures vs 62 [25-124] procedures; P < .001). Compared with nonparticipating hospitals, an increased mean (SD) proportion of participating hospitals adhered to composite discharge medications after PCI (0.96 [0.03] vs 0.92 [0.07]; P < .001) and ICD (0.88 [0.10] vs 0.81 [0.12]; P < .001). Hospital factors associated with enrollment included participation in 5 or more NCDR registries (odds ratio [OR],1.98; 95% CI, 1.24-3.19; P = .005), membership in a larger hospital system (ie, 3-20 hospitals vs ≤2 hospitals in the system: OR, 2.29; 95% CI, 1.65-3.17; P = .001), participation in an NCDR pilot public reporting program of PCI 30-day readmissions (OR, 2.93; 95% CI, 2.19-3.91; P < .001), university affiliation (vs government affiliation: OR, 3.85, 95% CI, 1.03-14.29; P = .045; vs private affiliation: OR, 2.22; 95% CI, 1.35-3.57; P < .001), Midwest location (vs South: OR, 1.47; 95% CI, 1.06-2.08; P = .02), and increased comprehensive quality ranking (4 vs 1-2 performance stars in CathPCI: OR, 8.08; 95% CI, 5.07-12.87; P < .001; 4 vs 1 performance star in ICD: OR, 2.26; 95% CI, 1.48-3.44; P < .001) (C statistic = 0.829). Conclusions and Relevance: This study found that one-third of eligible hospitals participated in the ACC voluntary public reporting program and that enrollment increased after the announcement that program participation would be considered by USNWR for hospital rankings. Several hospital characteristics, experience with public reporting, and quality of care were associated with increased odds of participation.

Trend of lung cancer surgery, hospital selection, and survival between 2005 and 2016 in South Korea.

BACKGROUND: Studies on the clinical implication of hospital selection for patients with lung cancer are few. Therefore, this study aimed to analyze 2005-2016 data from the Korean national database to assess annual trends of lung cancer surgery and clinical outcomes according to hospital selection. METHODS: Data of 212 554 patients with lung cancer who underwent upfront surgery were screened. Trends according to sex, age, residence, and income were examined. Descriptive statistics were performed, and ptrend values were estimated. The association between survival and hospital selection was assessed using the log-rank test. A multivariate Cox regression analysis was also performed. RESULTS: A total of 49 021 patients were included in this study. Surgery was prevalent among men, patients aged 61-75 years, capital area residents, and high-income patients. However, with the increasing rate of surgery among women, patients aged ≥76 years, city residents, and middle-income patients, the current distribution of lung cancer surgery could change. The rate of lobectomy among these groups increased. All patients, except those in capital areas, preferred a hospital outside their area of residence (HOR); the number of patients with this tendency also increased. However, this trend was not observed among low-income patients and those aged ≥76 years. There were significant differences in survival according to hospital selection. CONCLUSIONS: The trend of lung cancer surgery is changing. The current medical system is effective in providing lobectomy for patients including women, aged ≥76 years, city residents, and middle-income. Increasing tendency to choose an HOR requires further study.

Determinants of hospital variability in perioperative red blood cell transfusions during coronary artery bypass graft surgery.

OBJECTIVE: To identify to what extent distinguishing patient and procedural characteristics can explain center-level transfusion variation during coronary artery bypass grafting surgery. METHODS: Observational cohort study using the Perfusion Measures and Outcomes Registry from 43 adult cardiac surgical programs from July 1, 2011, to July 1, 2017. Iterative multilevel logistic regression models were constructed using patient demographic characteristics, preoperative risk factors, and intraoperative conservation strategies to progressively explain center-level transfusion variation. RESULTS: Of the 22,272 adult patients undergoing isolated coronary artery bypass surgery using cardiopulmonary bypass, 7241 (32.5%) received at least 1 U allogeneic red blood cells (range, 10.9%-59.9%). When compared with patients who were not transfused, patients who received at least 1 U red blood cells were older (68 vs 64 years; P < .001), were women (41.5% vs 15.9%; P < .001), and had a lower body surface area (1.93 m2 vs 2.07 m2; P < .001), respectively. Among the models explaining center-level transfusion variability, the intraclass correlation coefficients were 0.07 for model 1 (random intercepts), 0.12 for model 2 (patient factors), 0.14 for model 3 (intraoperative factors), and 0.11 for model 4 (combined). The coefficient of variation for center-level transfusion rates were 0.31, 0.29, 0.40, and 0.30 for models 1 through 4, respectively. The majority of center-level variation could not be explained through models containing both patient and intraoperative factors. CONCLUSIONS: The results suggest that variation in center-level red blood cells transfusion cannot be explained by patient and procedural factors alone. Investigating organizational culture and programmatic infrastructure may be necessary to better understand variation in transfusion practices.

Racial Disparities in Stroke Readmissions Reduced in Hospitals With Better Nurse Staffing.

BACKGROUND: Racial minorities are disproportionately affected by stroke, with Black patients experiencing worse poststroke outcomes than White patients. A modifiable aspect of acute stroke care delivery not yet examined is whether disparities in stroke outcomes are related to hospital nurse staffing levels. OBJECTIVES: The aim of this study was to determine whether 7- and 30-day readmission disparities between Black and White patients were associated with nurse staffing levels. METHODS: We conducted a secondary analysis of 542 hospitals in four states. Risk-adjusted, logistic regression models were used to determine the association of nurse staffing with 7- and 30-day all-cause readmissions for Black and White ischemic stroke patients. RESULTS: Our sample included 98,150 ischemic stroke patients (87% White, 13% Black). Thirty-day readmission rates were 10.4% (12.7% for Black patients, 10.0% for White patients). In models accounting for hospital and patient characteristics, the odds of 30-day readmissions were higher for Black than White patients. A significant interaction was found between race and nurse staffing, with Black patients experiencing higher odds of 30- and 7-day readmissions for each additional patient cared for by a nurse. In the best-staffed hospitals (less than three patients per nurse), Black and White stroke patients' disparities were no longer significant. DISCUSSION: Disparities in readmissions between Black and White stroke patients may be linked to the level of nurse staffing in the hospitals where they receive care. Tailoring nurse staffing levels to meet the needs of Black ischemic stroke patients represents a promising intervention to address systemic inequities linked to readmission disparities among minority stroke patients.

Sustentabilidad hospitalaria, calidad y seguridad del paciente en el Hospital Clínico Universidad de Chile / Hospital sustainability, quality and patient safety in Hospital Clínico Universidad de Chile

The sustainability of the Universidad de Chile Clinical Hospital must be understood comprehensively; providing higher quality and safety for our patients, ensuring highest standards of medical care. The quality of care must be understood not only in complying with the minimum standards to accredit and grant GES benefits, establish agreements with health insurers and be financially competitive; It must be incorporated into its management the dimensions of quality - effectiveness, efficiency, accessibility, safety, equity and patient-centered care- minimizing the costs of non-quality work. Our Clinical Hospital, as our country's main training center in healthcare professions, must include training at the undergraduate students' curriculum in quality and patient safety issues. (AU)

The hospital autopsy: the importance in keeping autopsy an option

Autopsy has been one of the most powerful diagnostic tools in medicine for over a century. Despite its importance in establishing cause of death and elucidating pathophysiology of disease, rates of hospital autopsies continue to decline. In this study we aim to determine if physicians believe autopsies are essential to patient care through discussion of autopsy with families. At the same time, we analyzed whether families are more willing to consent to autopsy if physicians are involved in autopsy discussion at the time of death, and what may be the reasons for not wanting an autopsy. Our results showed a doubling in autopsy consent when autopsy was discussed by the physician. Additionally, the biggest reason for families not consenting to autopsy was because they believed they already knew what caused death. The emergence of Coronavirus 2019 (COVID-19) has re-established the value of autopsy, as seen by increased autopsy rates in the past year. This study demonstrates that physician conversation with families on autopsy leads to an increased chance of autopsy consent.

Association Between Implementation of the Severe Sepsis and Septic Shock Early Management Bundle Performance Measure and Outcomes in Patients With Suspected Sepsis in US Hospitals.

Importance: In October 2015, the Centers for Medicare & Medicaid Services began requiring US hospitals to report adherence to the Severe Sepsis and Septic Shock Early Management Bundle (SEP-1). Objective: To evaluate the association of SEP-1 implementation with sepsis treatment patterns and outcomes in diverse hospitals. Design, Setting, and Participants: This retrospective cohort study with interrupted time-series analysis and logistic regression models was conducted among adults admitted to 114 hospitals from October 2013 to December 2017 with suspected sepsis (blood culture orders, ≥2 systemic inflammatory response syndrome criteria, and acute organ dysfunction) within 24 hours of hospital arrival. Data analysis was conducted from September 2020 to September 2021. Exposures: SEP-1 implementation in the fourth quarter (Q4) of 2015. Main Outcomes and Measures: The primary outcome was quarterly rates of risk-adjusted short-term mortality (in-hospital death or discharge to hospice). Secondary outcomes included lactate testing and administration of anti-methicillin-resistant Staphylococcus aureus (MRSA) or antipseudomonal ß-lactam antibiotics within 24 hours of hospital arrival. Generalized estimating equations with robust sandwich variances were used to fit logistic regression models to assess for changes in level or trends in these outcomes, adjusting for baseline characteristics and severity of illness. Results: The cohort included 117 510 patients (median [IQR] age, 67 years [55-78] years; 60 530 [51.5%] men and 56 980 [48.5%] women) with suspected sepsis. Lactate testing rates increased from 55.1% (95% CI, 53.9%-56.2%) in Q4 of 2013 to 76.7% (95% CI, 75.4%-78.0%) in Q4 of 2017, with a significant level change following SEP-1 implementation (odds ratio [OR], 1.34; 95% CI, 1.04-1.74). There were increases in use of anti-MRSA antibiotics (19.8% [95% CI, 18.9%-20.7%] in Q4 of 2013 to 26.3% [95% CI, 24.9%-27.7%] in Q4 of 2017) and antipseudomonal antibiotics (27.7% [95% CI, 26.7%-28.8%] in Q4 of 2013 to 40.5% [95% CI, 38.9%-42.0%] in Q4 of 2017), but these trends preceded SEP-1 and did not change with SEP-1 implementation. Unadjusted short-term mortality rates were similar in the pre-SEP-1 period (Q4 of 2013 through Q3 of 2015) vs the post-SEP-1 period (Q1 of 2016 through Q4 of 2017) (20.3% [95% CI, 20.0%-20.6%] vs 20.4% [95% CI, 20.1%-20.7%]), and SEP-1 implementation was not associated with changes in level (OR, 0.94; 95% CI, 0.68-1.29) or trend (OR, 1.00; 95% CI, 0.97-1.04) for risk-adjusted short-term mortality rates. Conclusions and Relevance: In this cohort study, SEP-1 implementation was associated with an immediate increase in lactate testing rates, no change in already-increasing rates of broad-spectrum antibiotic use, and no change in short-term mortality rates for patients with suspected sepsis. Other approaches to decrease sepsis mortality may be warranted.

Birth Volume and Geographic Distribution of US Hospitals With Obstetric Services From 2010 to 2018.

Importance: Timely access to clinically appropriate obstetric services is critical to the provision of high-quality perinatal care. Objective: To examine the geographic distribution, proximity, and urban adjacency of US obstetric hospitals by annual birth volume. Design, Setting, and Participants: This retrospective population-based cohort study identified US hospitals with obstetric services using the American Hospital Association (AHA) Annual Survey of Hospitals and Centers for Medicare & Medicaid provider of services data from 2010 to 2018. Obstetric hospitals with 10 or more births per year were included in the study. Data analysis was performed from November 6, 2020, to April 5, 2021. Exposure: Hospital birth volume, defined by annual birth volume categories of 10 to 500, 501 to 1000, 1001 to 2000, and more than 2000 births. Main Outcomes and Measures: Outcomes assessed by birth volume category were percentage of births (from annual AHA data), number of hospitals, geographic distribution of hospitals among states, proximity between obstetric hospitals, and urban adjacency defined by urban influence codes, which classify counties by population size and adjacency to a metropolitan area. Results: The study included 26 900 hospital-years of data from 3207 distinct US hospitals with obstetric services, reflecting 34 054 951 associated births. Most infants (19 327 487 [56.8%]) were born in hospitals with more than 2000 births/y, and 2 528 259 (7.4%) were born in low-volume (10-500 births/y) hospitals. More than one-third of obstetric hospitals (37.4%; 10 064 hospital-years) were low volume. A total of 46 states had obstetric hospitals in all volume categories. Among low-volume hospitals, 18.9% (1904 hospital-years) were not within 30 miles of any other obstetric hospital and 23.9% (2400 hospital-years) were within 30 miles of a hospital with more than 2000 deliveries/y. Isolated hospitals (those without another obstetric hospital within 30 miles) were more frequently low volume, with 58.4% (1112 hospital-years) located in noncore rural areas. Conclusions and Relevance: In this cohort study, marked variations were found in birth volume, geographic distribution, proximity, and urban adjacency among US obstetric hospitals from 2010 to 2018. The findings related to geographic isolation and rural-urban distribution of low-volume obstetric hospitals suggest the need to balance proximity with volume to optimize effective referral and access to high-quality perinatal care.

Hospital-specific Template Matching for Benchmarking Performance in a Diverse Multihospital System.

BACKGROUND: Hospital-specific template matching is a newer method of hospital performance measurement that may be fairer than regression-based benchmarking. However, it has been tested in only limited research settings. OBJECTIVE: The objective of this study was to test the feasibility of hospital-specific template matching assessments in the Veterans Affairs (VA) health care system and determine power to detect greater-than-expected 30-day mortality. RESEARCH DESIGN: Observational cohort study with hospital-specific template matching assessment. For each VA hospital, the 30-day mortality of a representative subset of hospitalizations was compared with the pooled mortality from matched hospitalizations at a set of comparison VA hospitals treating sufficiently similar patients. The simulation was used to determine power to detect greater-than-expected mortality. SUBJECTS: A total of 556,266 hospitalizations at 122 VA hospitals in 2017. MEASURES: A number of comparison hospitals identified per hospital; 30-day mortality. RESULTS: Each hospital had a median of 38 comparison hospitals (interquartile range: 33, 44) identified, and 116 (95.1%) had at least 20 comparison hospitals. In total, 8 hospitals (6.6%) had a significantly lower 30-day mortality than their benchmark, 5 hospitals (4.1%) had a significantly higher 30-day mortality, and the remaining 109 hospitals (89.3%) were similar to their benchmark. Power to detect a standardized mortality ratio of 2.0 ranged from 72.5% to 79.4% for a hospital with the fewest (6) versus most (64) comparison hospitals. CONCLUSIONS: Hospital-specific template matching may be feasible for assessing hospital performance in the diverse VA health care system, but further refinements are needed to optimize the approach before operational use. Our findings are likely applicable to other large and diverse multihospital systems.

Between-centre differences in care for in-hospital cardiac arrest: a prospective cohort study.

BACKGROUND: Survival after in-hospital cardiac arrest is poor, but current literature shows substantial heterogeneity in reported survival rates. This study aims to evaluate care for patients suffering in-hospital cardiac arrest (IHCA) in the Netherlands by assessing between-hospital heterogeneity in outcomes and to explain this heterogeneity stemming from differences in case-mix or differences in quality of care. METHODS: A prospective multicentre study was conducted comprising 14 centres. All IHCA patients were included. The adjusted variation in structure and process indicators of quality of care and outcomes (in-hospital mortality and cerebral performance category [CPC] scale) was assessed with mixed effects regression with centre as random intercept. Variation was quantified using the median odds ratio (MOR), representing the expected odds ratio for poor outcome between two randomly picked centres. RESULTS: After excluding centres with less than 10 inclusions (2 centres), 701 patients were included of whom, 218 (32%) survived to hospital discharge. The unadjusted and case-mix adjusted MOR for mortality was 1.19 and 1.05, respectively. The unadjusted and adjusted MOR for CPC score was 1.24 and 1.19, respectively. In hospitals where personnel received cardiopulmonary resuscitation (CPR) training twice per year, 183 (64.7%) versus 290 (71.4%) patients died or were in a vegetative state, and 59 (20.8%) versus 68 (16.7%) patients showed full recovery (p < 0.001). CONCLUSION: In the Netherlands, survival after IHCA is relatively high and between-centre differences in outcomes are small. The existing differences in survival are mainly attributable to differences in case-mix. Variation in neurological outcome is less attributable to case-mix.

Using machine learning for predicting intensive care unit resource use during the COVID-19 pandemic in Denmark.

The COVID-19 pandemic has put massive strains on hospitals, and tools to guide hospital planners in resource allocation during the ebbs and flows of the pandemic are urgently needed. We investigate whether machine learning (ML) can be used for predictions of intensive care requirements a fixed number of days into the future. Retrospective design where health Records from 42,526 SARS-CoV-2 positive patients in Denmark was extracted. Random Forest (RF) models were trained to predict risk of ICU admission and use of mechanical ventilation after n days (n = 1, 2, …, 15). An extended analysis was provided for n = 5 and n = 10. Models predicted n-day risk of ICU admission with an area under the receiver operator characteristic curve (ROC-AUC) between 0.981 and 0.995, and n-day risk of use of ventilation with an ROC-AUC between 0.982 and 0.997. The corresponding n-day forecasting models predicted the needed ICU capacity with a coefficient of determination (R2) between 0.334 and 0.989 and use of ventilation with an R2 between 0.446 and 0.973. The forecasting models performed worst, when forecasting many days into the future (for large n). For n = 5, ICU capacity was predicted with ROC-AUC 0.990 and R2 0.928, and use of ventilator was predicted with ROC-AUC 0.994 and R2 0.854. Random Forest-based modelling can be used for accurate n-day forecasting predictions of ICU resource requirements, when n is not too large.

Preparation and Practice of the Necessary Documents in Hospital for the "Act on Decision of Life-Sustaining Treatment for Patients at the End-of-Life".

PURPOSE: Six forms relating to decisions on life-sustaining treatment (LST) for patients at the end-of-life (EOL) in hospital are required by the "Act on Decision of LST for Patients at the EOL." We investigated the preparation and creation status of these documents from the database of the National Agency for Management of LST. MATERIALS AND METHODS: We analyzed the contents and details of each document necessary for decisions on LST, and the creation status of forms. We defined patients completing form 1 as "self-determined" of LST, and those whose family members had completed form 11/12 as "family decision" of LST. According to the determination subject, we compared the four items of LST on form 13 (the paper of implementation of LST) and the documentation time interval between forms. RESULTS: The six forms require information about the patient, doctor, specialized doctor, family members, institution, decision for LST, and intention to use hospice services. Of 44,381 who had completed at least one document, 36,693 patients had form 13. Among them, 11,531, 10,976, and 12,551 people completed forms 1, 11, and 12, respectively. The documentation time interval from forms 1, 11, or 12 to form 13 was 8.6±13.6 days, 1.0±9.5 days, and 1.5±9.7 days, respectively. CONCLUSION: The self-determination rate of LST was 31% and the mean time interval from self-determination to implementation of LST was 8.6 days. The creation of these forms still takes place when the patients are close to death.

Hospital use following anterior cervical discectomy and fusion.

Most existing anterior cervical discectomy and fusion (ACDF) outcome studies omit emergency department (ED) use. To our knowledge, this study on ED use following ACDF surgery is the first to use a direct patient chart review and the first to include revision patients, 1-5 levels of ACDFs, and performance of corpectomy in the analysis. This study examines the frequency and basis of hospital service use within 30 days of ACDF surgery, specifically ED visits, hospital readmissions, and returns to the operating room. A retrospective chart review was performed for 1273 consecutive patients who underwent ACDF surgery at one institution from July 2013 to June 2016. Of the 1273 patients with ACDF, 97 (7.6%) presented to the ED within 30 days after surgery. Of 43 patients with revision ACDF, 9 (20.9%) returned to the ED, compared with 88 (7.2%) of 1230 patients with primary ACDF (P = 0.001). Of the 111 ED visits by 97 patients, 40 (36%) were for cervicalgia, 13 (12%) were for dysphagia, 8 (7%) were for trauma, 7 (6%) were for nausea, 4 (4%) were for medication refill, 3 (3%) were for dehiscence, 3 (3%) were for pneumonia, and 3 (3%) were for urinary tract infection. Of the ED presentations, 8 (7%) occurred during the first 2 days after surgery, and 46 (41%) occurred within the first postoperative week.

Disparities in diagnosis of cerebral amyloid angiopathy based on hospital characteristics.

Cerebral amyloid angiopathy (CAA) categorized as a cerebral small vessel disease can cause lobar intracerebral hemorrhage (ICH), convexity subarachnoid hemorrhage (SAH) and ischemic stroke (IS). The purpose of this study was to evaluate the differences in the diagnosis of CAA based on hospital characteristics and to assess the discharge outcomes of patients with CAA admitted for IS, ICH and SAH. Adult patients admitted with secondary diagnosis of CAA were identified in National Inpatient Sample in 2016 and 2017. Multivariable logistic regression analysis was performed to evaluate outcomes. A total of 16,040 patients had a secondary diagnosis of CAA. Among CAA patients, 1810 (11.3%) patients were admitted for IS, 4765 (29.7%) for ICH and 490 (3.1%) for SAH. Diagnosis of CAA was five-fold higher among patients admitted to urban teaching hospitals (aOR = 5.4;95% CI = 4.1-7.2) compared to rural hospitals and two-fold higher in large bed size hospitals (aOR = 2.3;95% CI = 2.0-2.7) compared to small bed size hospitals. Compared to non-CAA group, patients with history of CAA had lower odds of in-hospital mortality among patients admitted for ICH (10% vs 23%, aOR = 0.35; 95%CI = 0.27-0.44) and SAH (6% vs 19%, aOR = 0.24; 95%CI = 0.10-0.55); and higher odds of discharge to home among patients admitted for ICH (17% vs 18%, aOR = 1.27; 95%CI = 1.05-1.53). CAA diagnosis is less common in rural and small bed size hospitals compared to urban and large bedside hospitals, respectively. Patients with CAA admitted for ICH have better discharge outcomes compared to non-CAA patients admitted for ICH.

Hospital Variation in 30-Day Readmissions Following Transcatheter Aortic Valve Replacement.

Background Data on hospital variation in 30-day readmission rates after transcatheter aortic valve replacement (TAVR) are limited. Further, whether such variation is explained by differences in hospital characteristics and hospital practice patterns remains unknown. Methods and Results We used the 2017 Nationwide Readmissions Database to identify hospitals that performed at least 5 TAVRs. Hierarchical logistic regression models were used to examine between-hospital variation in 30-day all-cause risk-standardized readmission rate (RSRR) after TAVR and to explore reasons underlying hospital variation in 30-day RSRR. The study included 27 091 index TAVRs performed across 325 hospitals. The median (interquartile range) hospital-level 30-day RSRR was 11.9% (11.1%-12.8%) ranging from 8.8% to 16.5%. After adjusting for differences in patient characteristics, there was significant between-hospital variation in 30-day RSRR (hospital odds ratio, 1.59; 95% CI, 1.39-1.77). Differences in length of stay and discharge disposition accounted for 15% of the between-hospital variance in RSRRs. There was no significant association between hospital characteristics and 30-day readmission rates after TAVR. There was statistically significant but weak correlation between 30-day RSRR after TAVR and that after surgical aortic valve replacement, percutaneous coronary intervention, acute myocardial infarction, heart failure, and pneumonia (r=0.132-0.298; P<0.001 for all). Causes of 30-day readmission varied across hospitals, with noncardiac readmissions being more common at the bottom 5% hospitals (ie, those with the highest RSRRs). Conclusions There is significant variation in 30-day RSRR after TAVR across hospitals that is not entirely explained by differences in patient or hospital characteristics as well as hospital-wide practice patterns. Noncardiac readmissions are more common in hospitals with the highest RSRRs.