Estudio observacional nacional sobre tratamiento quirúrgico de fístula anal: ¿tiene impacto en los resultados el tipo de hospital? / National observational study about the surgical treatment of anal fistula: does the kind of hospital modify the results?

Introducción: En algunos procedimientos quirúrgicos se ha demostrado que la centralización en hospitales de alto volumen mejora los resultados obtenidos. Sin embargo, este punto aún no ha sido estudiado en los pacientes que son intervenidos por una fístula anal (FA). Material y métodos: Se realizó un estudio multicéntrico retrospectivo en el que se incluyeron los pacientes operados de FA durante el año 2019 en 56 centros españoles. Se hizo un análisis uni y multivariante para analizar la relación entre el tamaño del lugar, el porcentaje de curación de la fístula y el desarrollo de incontinencia fecal (IF). Resultados: Se incluyeron en el estudio a 1.809 pacientes. La cirugía se llevó a cabo en un hospital pequeño en 127 usuarios (7,0%), uno mediano en 571 (31,6%) y uno grande en 1.111 (61,4%). Tras un seguimiento medio de 18,9 meses, 72,3% de los participantes (1.303) se consideraron curados y 132 (7,6%) presentaron IF. El porcentaje de los rehabilitados de la FA fue de 74,8, 75,8 y 70,3% (p = 0,045) en los centros pequeño, mediano y grande, respectivamente. En cuanto a la IF no se evidenciaron diferencias significativas según el tipo de lugar (4,8, 8,0 y 7,7%, respectivamente, p = 0,473). En el análisis multivariante no se observó relación entre el tamaño del hospital y la curación de la fístula o el desarrollo de IF. Conclusión: Los resultados de curación e IF posoperatoria en los pacientes sometidos a una cirugía por FA fueron independientes del volumen hospitalario.(AU)

Introduction: Performing the surgical procedure in a high-volume center has been seen to be important for some surgical procedures. However, this issue has not been studied for patients with an Anal Fistula (AF). Material and methods: A retrospective multicentric study was performed including the patients who underwent AF surgery in 2019 in 56 Spanish hospitals. A univariate and multivariate analysis was performed to analyse the relationship between hospital volume and AF cure and Fecal Incontinence (FI). Results: 1809 patients were include. Surgery was performed in a low, middle, and high-volume hospitals in 127 (7.0%), 571 (31.6%) y 1111 (61.4%) patients respectively. After a mean follow-up of 18.9 months 72.3% (1303) patients were cured and 132 (7.6%) developed FI. The percentage of patients cured was 74.8%, 75.8% and 70.3% (p=0.045) for low, middle, and high-volume hospitals. Regarding FI, no statistically significant differences were observed depending on the hospital volume (4.8%, 8.0% and 7.7% respectively, p=0.473). Multivariate analysis didńt observe a relationship between AF cure and FI. Conclusion: Cure and FI in patients who underwent AF surgery were independent from hospital volume.(AU)

Time to surgery after proximal femur fracture in geriatric patients depends on hospital size and provided level of care: analysis of the Registry for Geriatric Trauma (ATR-DGU).

PURPOSE: Proximal femur fractures predominantly affect older patients and can mark a drastic turning point in their lives. To avoid complications and reduce mortality, expert associations recommend surgical treatment within 24-48 h after admission. Due to the high incidence, treatment is provided at a wide range of hospitals with different size and level of care, which may affect time to surgery. METHODS: Data from 19,712 patients included from 2016 to 2019 in the Registry for Geriatric Trauma (ATR-DGU) were analyzed in terms of time to surgery, in-house mortality, mobilization on the first postoperative day, ambulation status on the 7th day after surgery, and initiation of osteoporosis therapy. Participating hospitals were grouped according to their classification as level I, II or III trauma centers. Also presence of additional injuries, intake and type of anticoagulants were considered. Linear and logistic regression analysis was performed to evaluate the influence of hospitals level of care on each item. RESULTS: 28.6% of patients were treated in level I, 37.7% in level II, and 33.7% in level III trauma centers. There was no significant difference in age, sex and ASA-score. Mean time to surgery was 19.2 h (IQR 9.0-29.8) in level I trauma centers and 16.8 h (IQR 6.5-24) in level II/III trauma centers (p < 0.001). Surgery in the first 24 h after admission was provided for 64.7% of level I and 75.0% of level II/III patients (p < 0.001). Treatment in hospitals with higher level of care and subsequent increased time to surgery showed no significant influence on in-house mortality (OR 0.90, 95%-CI 0.78-1.04), but negative effects on walking ability 7 days after surgery could be observed (OR 1.28, 95%-CI 1.18-1.38). CONCLUSION: In hospitals of larger size and higher level of care the time to surgery for patients with a proximal femur fracture was significantly higher than in smaller hospitals. No negative effects regarding in-house mortality, but for ambulation status during in-hospital stay could be observed. As the number of these patients will constantly increase, specific treatment capacities should be established regardless of the hospitals size.

Trends in intravenous thrombolysis utilization for acute ischemic stroke based on hospital size: Paul Coverdell National Acute Stroke Program, 2010-2019.

INTRODUCTION: The rate of intravenous thrombolysis (IVT) utilization in acute ischemic stroke (AIS) has been increasing, and this has coincided with improved door-to-needle times (DNTs). Smaller hospitals have been observed to utilize IVT less frequently or even not at all. Using a multistate stroke registry, we sought to determine the impact of hospital size on trends in IVT utilization for AIS. METHODS: Utilizing data from the Paul Coverdell National Acute Stroke Program (PCNASP), we studied trends in IVT for AIS patients between 2010 and 2019 based on hospital size. Hospitals were grouped into quartiles based on size. We studied the impact of hospital size on DNTs and overall IVT utilization. RESULTS: During the study period, there were 530,828 AIS patients (mean age 70.3 ± 0.02 years, 50.4% men) from 540 participating hospitals. We did not identify a significant trend in IVT utilization among hospitals within the first quartile (p = 0.1005), but there were significantly increased trends within the hospitals belonging to the second, third, and fourth quartiles (p < 0.001 for all). All quartiles were observed to have significantly increased trends in DNTs ≤60 min (p < 0.0001), but only hospitals within the second, third, and fourth quartiles experienced significantly increased trends in DNTs ≤45 min (p < 0.0001). CONCLUSION: In our registry-based analysis, we observed an increased trend in IVT utilization for AIS among larger hospitals. There was an overall improvement in rates of DNTs ≤60 min, but only larger hospitals were observed to have improved DNTs ≤45 min.

Hospital size, remoteness and stroke outcome.

INTRODUCTION: Previous studies have shown an association between number of stroke admissions and outcomes. Small hospitals often support more remote areas and we studied national data to determine if an association exists between hospital remoteness and stroke care. METHODS: Data from the Irish National Audit of Stroke (INAS) on average stroke admissions, adjusted mortality for ischaemic stroke, thrombolysis rate and proportion with door to needle (DTN) ≤45 min were analysed. Hospital remoteness was quantified by distance to the next hospital, nearest neurointerventional centre and location within 10 km of the national motorway network. RESULTS: Data for 23 of 24 stroke services were evaluated. Median number of strokes admitted per year was 186 (range 84-497). Nine hospitals (39%) admitted ≥200 stroke patients per year (mean 332). Average adjusted mortality (7.0 vs. 7.3, P = 0.67 t-test), mean thrombolysis rate (12.1% vs. 9.2%, P = 0.09) and mean proportion of patients treated ≤45 min (40.4% vs. 31.3%, P = 0.2) did not differ significantly between higher and lower volume hospitals.Hospitals close to the motorway network (n = 15) had a higher mean thrombolysis rate (11.9% vs. 7.5%, P = 0.01 t-test) and proportion DTN ≤45 min (43.7-18.4%, P < 0.001).Number of stroke admissions did not correlate with mortality (r = 0.06, P = 0.78), DTN (r = 0.12, P = 0.95) or thrombolysis rate (r = 0.35, P = 0.20). Distance to next hospital correlated strongly negatively with DTN (r = -0.47, P = 0.02) and thrombolysis rate (-0.43, P = 0.04). CONCLUSION: Remoteness of hospitals is associated with worse measures of stroke outcome and management.

The Impact of Hospital Size and Teaching Status on Outcomes Following Total Ankle Arthroplasty.

The popularity and utilization of total ankle arthroplasty (TAA) as treatment for ankle arthritis has increased exponentially from 1998 to 2012. Overall the outcomes have improved for TAA with the introduction of new-generation implants and this has increased the focus on optimizing other variables affecting outcomes for TAA. The purpose of this study was to examine the effects of hospital characteristics and teaching status on outcomes for TAA. The Nationwide Inpatient Sample database was queried from 2002 to 2012 using the ICD-9 procedure code for TAA. The primary outcomes evaluated included: in-hospital mortality, length of stay, total hospital charges, discharge disposition, perioperative complications, and patient demographics. Analyses were carried out based on hospital size: small, medium, and large; and teaching status: rural nonteaching, urban nonteaching, and urban teaching. A total weighted national estimate of 16,621 discharges for patients undergoing TAA was reported over the 10-year period. There were significant differences in length of stay and total charges between all hospitals when comparing location and teaching status; however, no significant differences were noted for in-hospital mortality. Rural, nonteaching hospitals had higher odds of perioperative complications. There were also significant differences in length of stay and total charges when comparing hospital sizes. Overall, there is no increased risk of mortality after TAA regardless of hospital size or setting. However, rural hospitals had increased rates of perioperative complications compared to urban hospitals. Our analyses demonstrated important factors affecting cost and resource utilization for TAA, clearly additional work is needed to optimize this relationship, especially in the upcoming bundled payment models.

The Perioperative Use of Benzodiazepines for Major Orthopedic Surgery in the United States.

BACKGROUND: Despite numerous indications for perioperative benzodiazepine use, associated risks may be exacerbated in elderly and comorbid patients. In the absence of national utilization data, we aimed to describe utilization patterns using national claims data from total hip/knee arthroplasty patients (THA/TKA), an increasingly older and vulnerable surgical population. METHODS: We included data on 1,863,996 TKAs and 985,471 THAs (Premier Healthcare claims data, 2006-2019). Benzodiazepine utilization (stratified by long- and short-acting agents) was assessed by patient- and health care characteristics, and analgesic regimens. Given the large sample size, standardized differences instead of P values were utilized to signify meaningful differences between groups (defined by value >0.1). RESULTS: Among 1,863,996 TKA and 985,471 THA patients, the utilization rate of benzodiazepines was 80.5% and 76.1%, respectively. In TKA, 72.6% received short-acting benzodiazepines, while 7.9% received long-acting benzodiazepines, utilization rates 68.4% and 7.7% in THA, respectively. Benzodiazepine use was particularly more frequent among younger patients (median age [interquartile range {IQR}]: 66 [60-73]/64 [57-71] among short/long-acting compared to 69 [61-76] among nonusers), White patients (80.6%/85.4% short/long-acting versus 75.7% among nonusers), commercial insurance (36.5%/34.0% short/long-acting versus 29.1% among nonusers), patients receiving neuraxial anesthesia (56.9%/56.5% short/long-acting versus 51.5% among nonusers), small- and medium-sized (≤500 beds) hospitals (68.5% in nonusers, and 74% and 76.7% in short- and long-acting benzodiazepines), and those in the Midwest (24.6%/25.4% short/long-acting versus 16% among nonusers) in TKA; all standardized differences ≥0.1. Similar patterns were observed in THA except for race and comorbidity burden. Notably, among patients with benzodiazepine use, in-hospital postoperative opioid administration (measured in oral morphine equivalents [OMEs]) was substantially higher. This was even more pronounced in patients who received long-acting agents (median OME with no benzodiazepines utilization 192 [IQR, 83-345] vs 256 [IQR, 153-431] with short-acting, and 329 [IQR, 195-540] with long-acting benzodiazepine administration). Benzodiazepine use was also more frequent in patients receiving multimodal analgesia (concurrently 2 or more analgesic modes) and regional anesthesia. Trend analysis showed a persistent high utilization rate of benzodiazepines over the last 14 years. CONCLUSIONS: Based on a representative sample, 4 of 5 patients undergoing major orthopedic surgery in the United States receive benzodiazepines perioperatively, despite concerns for delirium and delayed postoperative neurocognitive recovery. Notably, benzodiazepine utilization was coupled with substantially increased opioid use, which may project implications for perioperative pain management.

The Impact of Commission on Cancer Accreditation Status, Hospital Rurality and Hospital Size on Quality Measure Performance Rates.

BACKGROUND: Rural cancer patients receive lower-quality care and experience worse outcomes than urban patients. Commission on Cancer (CoC) accreditation requires hospitals to monitor performance on evidence-based quality measuresPlease confirm the list of authors is correc, but the impact of accreditation is not clear due to lack of data from non-accredited facilities and confounding between patient rurality and hospital accreditation, rurality, and size. METHODS: This retrospective, observational study assessed associations between rurality, accreditation, size, and performance rates for four CoC quality measures (breast radiation, breast chemotherapy, colon chemotherapy, colon nodal yield). Iowa Cancer Registry data were queried to identify all eligible patients diagnosed between 2011 and 2017. Cases were assigned to the surgery hospital to calculate performance rates. Univariate and multivariate regression models were fitted to identify patient- and hospital-level predictors and assess trends. RESULTS: The study cohort included 10,381 patients; 46% were rural. Compared with urban patients, rural patients more often received treatment at small, rural, and non-accredited facilities (p < 0.001 for all). Rural hospitals had fewer beds and were far less likely to be CoC-accredited than urban hospitals (p < 0.001 for all). On multivariate analysis, CoC accreditation was the strongest, independent predictor of higher hospital performance for all quality measures evaluated (p < 0.05 in each model). Performance rates significantly improved over time only for the colon nodal yield quality measure, and only in urban hospitals. CONCLUSIONS: CoC accreditation requires monitoring and evaluating performance on quality measures, which likely contributes to better performance on these measures. Efforts to support rural hospital accreditation may improve existing disparities in rural cancer treatment and outcomes.

The impact of hospital size on national trends and outcomes in isolated open proximal aortic surgery.

OBJECTIVE: To determine the impact of hospital size on national trend estimates of isolated open proximal aortic surgery for benchmarking hospital performance. METHODS: Patients age >18 years who underwent isolated open proximal aortic surgery for aneurysm and dissection from 2002 to 2014 were identified using the National Inpatient Sample. Concomitant valvular, vessel revascularization, re-do procedures, endovascular, and surgery for descending and thoracoabdominal aorta were excluded. Discharges were stratified by hospital size and analyzed using trend, multivariable regression, propensity-score matching analysis. RESULTS: Over a 13-year period, 53,657 isolated open proximal aortic operations were performed nationally. Although the total number of operations/year increased (∼2.9%/year increase) and overall in-hospital mortality decreased (∼4%/year; both P < .001 for trend), these did not differ by hospital size (P > .05). Large hospitals treated more sicker and older patients but had shorter length of stay and lower hospital costs (both P < .001). Even after propensity-score matching, large hospital continued to demonstrate superior in-hospital outcomes, although only statistically for major in-hospital cardiac complications compared with non-large hospitals. In our subgroup analysis of dissection versus non-dissection cohort, in-hospital mortality trends decreased only in the non-dissection cohort (P < .01) versus dissection cohort (P = .39), driven primarily by the impact of large hospitals (P < .01). CONCLUSIONS: This study demonstrates increasing volume and improving outcomes of isolated open proximal aortic surgeries nationally over the last decade regardless of hospital bed size. Moreover, the resource allocation of sicker patients to larger hospital resulted shorter length of stay and hospital costs, while maintaining similar operative mortality to small- and medium-sized hospitals.

Prolonged Prehospital Time Is a Risk Factor for Pneumonia in Trauma (the PRE-TRIP Study): A Retrospective Analysis of the United States National Trauma Data Bank.

BACKGROUND: Although multiple risk factors for development of pneumonia in patients with trauma sustained in a motor vehicle accident have been studied, the effect of prehospital time on pneumonia incidence post-trauma is unknown. RESEARCH QUESTION: Is prolonged prehospital time an independent risk factor for pneumonia? STUDY DESIGN AND METHODS: We retrospectively analyzed prospectively collected clinical data from 806,012 motor vehicle accident trauma incidents from the roughly 750 trauma hospitals contributing data to the National Trauma Data Bank between 2010 and 2016. RESULTS: Prehospital time was independently associated with development of pneumonia post-motor vehicle trauma (P < .001). This association was primarily driven by patients with low Glasgow Coma Scale scores. Post-trauma pneumonia was uncommon (1.5% incidence) but was associated with a significant increase in mortality (P < .001, 4.3% mortality without pneumonia vs 12.1% mortality with pneumonia). Other pneumonia risk factors included age, sex, race, primary payor, trauma center teaching status, bed size, geographic region, intoxication, comorbid lung disease, steroid use, lower Glasgow Coma Scale score, higher Injury Severity Scale score, blood product transfusion, chest trauma, and respiratory burns. INTERPRETATION: Increased prehospital time is an independent risk factor for development of pneumonia and increased mortality in patients with trauma caused by a motor vehicle accident. Although prehospital time is often not modifiable, its recognition as a pneumonia risk factor is important, because prolonged prehospital time may need to be considered in subsequent decision-making.

ECMO use in Germany: An analysis of 29,929 ECMO runs.

BACKGROUND: Extracorporeal Membrane Oxygenation (ECMO) use is increasing despite limited evidence. The aim of this study was to demonstrate heterogeneity of ECMO use and its association with hospital size and annual frequency in Germany. METHODS: This is a database analysis of all ECMO cases in Germany from 2010 to 2016 using the German Diagnosis Related Groups (DRG) coding system for ECMO. RESULTS: During the study period, 510 hospitals performed 29,929 ECMO runs (12,572 vvECMO, 11,504 vaECMO, 1993 pECLA) with an increase over time. Mortality ranged between 58% and 66% for vaECMO cases and 66% and 53% for vvECMO cases. 304 (61%) hospitals performed only one ECMO per year. 78%% of all ECMO runs were performed in centres with more than 20 cases per year and more than half of all ECMO runs were performed in hospitals with >1.000 beds. Mortality for vv and vaECMO was highest in very small hospitals (< 200 beds; 70%; 74%) and very large hospitals (>1000 beds; 60%; 62%). CONCLUSIONS: Use of ECMO is still increasing and a substantial proportion of hospitals performs very few ECMO runs. Small hospitals had a significantly higher mortality, but dependence on hospital size and ECMO mortality was irregular.

Scope of Practice of US Interventional Cardiologists from an Analysis of Medicare Billing Data.

The contemporary scope of practice of interventional cardiologists (ICs) in the United States and recent trends are unknown. Using Medicare claims from 2013 to 2017, we categorized ICs into 4 practice categories (only percutaneous coronary intervention [PCI], PCI with noninvasive imaging, PCI with specialized interventions [peripheral/structural], and all 3 services) and evaluated associations with region, hospital bed size and teaching status, gender, and graduation year. Of 6,083 ICs in 2017, 10.9% performed only PCI, 68.3% PCI with noninvasive imaging, 5.7% PCI with specialized interventions, and 15.1% all 3 services. A higher proportion of Northeast ICs (vs South ICs) were performing only PCI (24.8% vs 7.3%) and PCI with specialized interventions (12% vs 3.4%), but lower PCI and noninvasive imaging (53.8% vs 71.7%) and all 3 services (9.3% and 17.6%). Regarding ICs at larger hospitals (bed size >575 vs <218), a higher proportion was performing only PCI (23.8% vs 5.2%) or PCI with specialized interventions (13.5% vs 1.7%) and lower proportion was performing PCI with noninvasive imaging (48.8% vs 78%), similar to teaching hospitals. Female ICs (vs male ICs) more frequently performed only PCI (18.9% vs 10.6%) and less frequently all 3 services (8.3% vs 15.4%). A lower proportion of recent graduates (2001 to 2016) performed only PCI (9.8% vs 13.8%) and PCI with noninvasive imaging (66.3% vs 72.6%) but a higher proportion performed all 3 services (18% vs 8.4%) than earlier graduates (1959 to 1984). From 2013 to 2017, only PCI and PCI with noninvasive imaging decreased, whereas PCI and specialized interventions and all 3 services increased (all p <0.001). In conclusion, there is marked heterogeneity in practice responsibilities among ICs, which has implications for training and competency assessments.

The dialysis facility levels and sizes are associated with outcomes of incident hemodialysis patients.

The outcomes of patients with incident kidney failure who start hemodialysis are influenced by several factors. Whether hemodialysis facility characteristics are associated with patient outcomes is unclear. We included adults diagnosed as having kidney failure requiring hemodialysis during January 1, 2001 to December 31, 2013 from the Taiwan National Health Insurance Research Database to perform this retrospective cohort study. The exposures included different sizes and levels of hemodialysis facilities. The outcomes were all-cause mortality, cardiovascular death, infection-related death, hospitalization, and kidney transplantation. During 2001-2013, we identified 74,406 patients and divided them in to three groups according to the facilities where they receive hemodialysis: medical center (n = 8263), non-center hospital (n = 40,008), and clinic (n = 26,135). The multivariable Cox model demonstrated that a larger facility size was associated with a low mortality risk (hazard ratio [HR] 0.991, 95% confidence interval [95% CI] 0.984-0.998; every 20 beds per facility). Compared with medical centers, patients in non-center hospitals and clinics had higher mortality risks (HR 1.13, 95% CI 1.09-1.17 and HR 1.11, 95% CI 1.06-1.15, respectively). Patients in medical centers and non-center hospitals had higher risk of hospitalization (subdistribution HR [SHR] 1.11, 95% CI 1.10-1.12 and SHR 1.22, 95% CI 1.21-1.23, respectively). Patients in medical centers had the highest rate of kidney transplantation among the three groups. In patients with incident kidney failure, a larger hemodialysis facility size was associated with lower mortality. Overall, medical center patients had a lower mortality rate and higher transplantation rate, whereas clinic patients had a lower hospitalization risk.

Significance of Hospital Size in Outcomes of Single-Level Elective Anterior Cervical Discectomy and Fusion: A Nationwide Readmissions Database Analysis.

OBJECTIVE: To elucidate risk factors for 90-day readmission in anterior cervical discectomy and fusion (ACDF) for small, medium, and large hospitals. To assess differences in length of stay, charges, and complication rates across hospitals of different size. METHODS: A retrospective analysis was performed using elective, single-level ACDF data from 2016 to 2018 in the Healthcare Cost and Utilization Project Nationwide Readmissions Database. Elective single-level ACDF cases were stratified into 3 groups by hospital bed size (small, medium, and large). All-cause complication rates, mean charges, length of stay, and 90-day readmission rates were compared across hospital size. Frequencies of specific comorbidities were compared between readmitted and nonreadmitted patients for each hospital size. Comorbidities significant on univariate analysis were evaluated as independent risk factors for 90-day readmission for each hospital size using multivariate regression. RESULTS: The overall 90-day readmission rate was 6.43% in 36,794 patients, and the rates for small, medium, and large hospitals were 6.25%, 6.28%, and 6.56%, respectively (P = 0.537). Length of stay increased significantly with hospital size (P < 0.001), and small hospitals had the lowest charges (P < 0.001). Although different independent predictors of 90-day readmission were identified for each hospital size, cardiac arrhythmia, chronic pulmonary disease, neurologic disorders, and rheumatic disease were identified as risk factors for hospitals of all sizes. CONCLUSIONS: Hospital size is a determining factor for charges and length of stay associated with elective single-level ACDF. Variation in risk factors for readmission exists across hospital size in context of similar 90-day readmission rates.

Fifteen-Year Trends in Incidence of Cardiogenic Shock Hospitalization and In-Hospital Mortality in the United States.

Background There is a lack of contemporary data on cardiogenic shock (CS) in-hospital mortality trends. Methods and Results Patients with CS admitted January 1, 2004 to December 31, 2018, were identified from the US National Inpatient Sample. We reported the crude and adjusted trends of in-hospital mortality among the overall population and selected subgroups. Among a total of 563 949 644 hospitalizations during the period from January 1, 2004, to December 30, 2018, 1 254 358 (0.2%) were attributed to CS. There has been a steady increase in hospitalizations attributed to CS from 122 per 100 000 hospitalizations in 2004 to 408 per 100 000 hospitalizations in 2018 (Ptrend<0.001). This was associated with a steady decline in the adjusted trends of in-hospital mortality during the study period in the overall population (from 49% in 2004 to 37% in 2018; Ptrend<0.001), among patients with acute myocardial infarction CS (from 43% in 2004 to 34% in 2018; Ptrend<0.001), and among patients with non-acute myocardial infarction CS (from 52% in 2004 to 37% in 2018; Ptrend<0.001). Consistent trends of reduced mortality were seen among women, men, different racial/ethnic groups, different US regions, and different hospital sizes, regardless of the hospital teaching status. Conclusions Hospitalizations attributed to CS have tripled in the period from January 2004 to December 2018. However, there has been a slow decline in CS in-hospital mortality during the studied period. Further studies are necessary to determine if the recent adoption of treatment algorithms in treating patients with CS will further impact in-hospital mortality.

Influence of hospital size on antimicrobial resistance and advantages of restricting antimicrobial use based on cumulative antibiograms in dogs with Staphylococcus pseudintermedius infections in Japan.

BACKGROUND: Antimicrobial resistance in Staphylococcus pseudintermedius (SP) and the prevalence of meticillin-resistant SP (MRSP) is increasing in dogs worldwide. OBJECTIVES: To evaluate the influence of hospital size on antimicrobial resistance of SP and whether restricted use of antimicrobials based on antibiograms could reduce the identification of antimicrobial resistance in SP from infected dogs. METHODS AND MATERIALS: In Study 1, a total of 2,294 SP isolates from dogs with pyoderma (n = 1,858, 52 hospitals) or otitis externa (OE; n = 436, 44 hospitals) taken between 2017 and 2019 were analysed. Clinics were categorised into small, medium and large based on numbers of practicing veterinary surgeons. In Study 2, a cumulative antibiogram was constructed for 12 antimicrobials from one large veterinary clinic from 2017 to 2018. Referring to this antibiogram, the clinic introduced strict antimicrobial selection criteria to treat dogs with pyoderma and OE, starting in 2018. RESULTS: MRSP was identified in 981 dogs (42.8%). In large clinics, the isolation rate of MRSP was 51.1% (404 of 791), which was significantly higher (P < 0.01) than in small clinics with less than two veterinary practitioners (34.0%, 154 of 453). In the antibiogram study, the susceptibility rates of oxacillin (MPIPC, 61.5%), cefpodoxime (CPDX, 55.8%) and minocycline (MINO, 55.8%) were significantly higher in 2019 (n = 52) than in 2017 to 2018 (n = 54; MPIPC, 37.0%; CPDX, 33.3%; MINO, 20.4%; P < 0.05). CONCLUSIONS AND CLINICAL RELEVANCE: Hospital size could affect the isolation rate of MRSP in dogs. Restricted use of antimicrobials for over a year based on cumulative antibiograms could reduce the resistance rate of multiple antimicrobials in SP isolated from dogs with pyoderma and OE.

An approach to exploring associations between hospital structural measures and patient satisfaction by distance-based analysis.

BACKGROUND: Patient satisfaction studies have explored domains of patient satisfaction, the determinants of domains, and score differences of domains by patient/hospital structural measures but reports on the structure of patient satisfaction with respect to similarities among domains are scarce. This study is to explore by distance-based analysis whether similarities among patient-satisfaction domains are influenced by hospital structural measures, and to design a model evaluating relationships between the structure of patient satisfaction and hospital structural measures. METHODS: The Hospital Consumer Assessment of Healthcare Providers and Systems 2012 survey scores and their structural measures from the Hospital Compare website reported adjusted percentages of scale for each hospital. Contingency tables of nine measures and their ratings were designed based on hospital structural measures, followed by three different distance-based analyses - clustering, correspondence analysis, and ordinal multidimensional scaling - for robustness to identify homogenous groups with respect to similarities. RESULTS: Of 4,677 hospitals, 3,711 (79.3%) met the inclusion criteria and were analyzed. The measures were divided into three groups plus cleanliness. Certain combinations of these groups were shown to be dependent on hospital structural measures. High value ratings for communication and low value ratings for medication explanation, quietness and staff responsiveness were not influenced by hospital structural measures, but the varied-ratings domain group similarities, including items such as global evaluation and pain management, were affected by hospital structural measures. CONCLUSIONS: Distance-based analysis can reveal the hidden structure of patient satisfaction. This study suggests that hospital structural measures including hospital size, the ability to provide acute surgical treatment, and hospital interest in improving medical care quality are factors which may influence the structure of patient satisfaction.

Nontraditional Small House Nursing Homes Have Fewer COVID-19 Cases and Deaths.

OBJECTIVES: Green House and other small nursing home (NH) models are considered "nontraditional" due to their size (10-12 beds), universal caregivers, and other home-like features. They have garnered great interest regarding their potential benefit to limit Coronavirus Disease 2019 (COVID-19) infections due to fewer people living, working, visiting, and being admitted to Green House/small NHs, and private rooms and bathrooms, but this assumption has not been tested. If they prove advantageous compared with other NHs, they may constitute an especially promising model as policy makers and providers reinvent NHs post-COVID. DESIGN: This cohort study compared rates of COVID-19 infections, COVID-19 admissions/readmissions, and COVID-19 mortality, among Green House/small NHs with rates in other NHs between January 20, 2020 and July 31, 2020. SETTING AND PARTICIPANTS: All Green House homes that held a skilled nursing license and received Medicaid or Medicare payment were invited to participate; other small NHs that replicate Green House physical design and operational practices were eligible if they had the same licensure and payer sources. Of 57 organizations, 43 (75%) provided complete data, which included 219 NHs. Comparison NHs (referred to as "traditional NHs") were up to 5 most geographically proximate NHs within 100 miles that had <50 beds and ≥50 beds for which data were available from the Centers for Medicare and Medicaid Services (CMS). Because Department of Veterans Affairs organizations are not required to report to CMS, they were not included. METHODS: Rates per 1000 resident days were derived for COVID-19 cases and admissions, and per 100 COVID-19 positive cases for mortality. A log-rank test compared rates between Green House/small NHs and traditional NHs with <50 beds and ≥50 beds. RESULTS: Rates of all outcomes were significantly lower in Green House/small NHs than in traditional NHs that had <50 beds and ≥50 beds (log-rank test P < .025 for all comparisons). The median (middle value) rates of COVID-19 cases per 1000 resident days were 0 in both Green House/small NHs and NHs <50 beds, while they were 0.06 in NHs ≥50 beds; in terms of COVID-19 mortality, the median rates per 100 positive residents were 0 (Green House/small NHs), 10 (<50 beds), and 12.5 (≥50 beds). Differences were most marked in the highest quartile: 25% of Green House/small NHs had COVID-19 case rates per 1000 resident days higher than 0.08, with the corresponding figures for other NHs being 0.15 (<50 beds) and 0.74 (≥50 beds). CONCLUSIONS AND IMPLICATIONS: COVID-19 incidence and mortality rates are less in Green House/small NHs than rates in traditional NHs with <50 and ≥50 beds, especially among the higher and extreme values. Green House/small NHs are a promising model of care as NHs are reinvented post-COVID.

Implementation of Ontario's emergency department asthma care pathway for adults: determinants of uptake.

OBJECTIVE: The Ontario Government funded the development and implementation of a standardized adult emergency department (ED) asthma care pathway (EDACP). We aimed to describe baseline patterns of ED use by adults for asthma in Ontario, Canada, and determine site characteristics associated with the EDACP implementation workshop attendance and subsequent pathway implementation. METHODS: All Ontario EDs were offered EDACP implementation workshops by the Lung Assocation-Ontario between 2008 and 2011, and were surveyed regarding site implementation status as of October, 2013. Survey data were linked by site to Ontario's administrative health databases. Logistic regression models investigated the association between site and patient characteristics and: a) workshop attendance; b) pathway implementation. RESULTS: In the 2 years prior to EDACP implementation, there were 41 143 asthma visits to 167 sites by adults (62.3% female). Asthma-related return visits within 72 h varied by hospital type (teaching 2.1%, community 2.8%, small 4.0%; p < 0.05). Implementation workshops were attended by staff from 122 sites (72.6%). Implementation status was known for 108 sites and varied by hospital type (p < 0.001), but not workshop attendance (p = 0.11). By 2013, 47% of all hospitals were using or planning to use the EDACP. Uptake was more likely in community hospitals. CONCLUSIONS: Ontario adult asthma ED visitors are more often women. Asthma-related return visits are uncommon, but significantly higher in small community hospitals. This provincial QI initiative reached almost 75% of Ontario EDs, and achieved almost 50% implementation rate within 2 years. Factors other than workshop attendance, such as hospital size, were associated with EDACP implementation.

Evaluation of Risk-Adjusted Home Time After Hospitalization for Heart Failure as a Potential Hospital Performance Metric.

Importance: Thirty-day home time, defined as time spent alive and out of a hospital or facility, is a novel, patient-centered performance metric that incorporates readmission and mortality. Objectives: To characterize risk-adjusted 30-day home time in patients discharged with heart failure (HF) as a hospital-level quality metric and evaluate its association with the 30-day risk-standardized readmission rate (RSRR), 30-day risk-standardized mortality rate (RSMR), and 1-year RSMR. Design, Setting, and Participants: This hospital-level cohort study retrospectively analyzed 100% of Medicare claims data from 2 968 341 patients from 3134 facilities from January 1, 2012, to November 30, 2017. Exposures: Home time, defined as time spent alive and out of a short-term hospital, skilled nursing facility, or intermediate/long-term facility 30 days after discharge. Main Outcomes and Measures: For each hospital, a risk-adjusted 30-day home time for HF was calculated similar to the Centers for Medicare & Medicaid Services risk-adjustment models for 30-day RSRR and RSMR. Hospitals were categorized into quartiles (lowest to highest risk-adjusted home time). The correlations between hospital rates of risk-adjusted 30-day home time and 30-day RSRR, 30-day RSMR, and 1-year RSMR were estimated using the Pearson correlation coefficient. Distribution of days lost from a perfect 30-day home time were calculated. Reclassification of hospital performance using 30-day home time vs 30-day RSRR was also evaluated. Results: Overall, 2 968 341 patients (mean [SD] age, 81.0 [8.3] years; 53.6% female) from 3134 hospitals were included in this study. The median hospital risk-adjusted 30-day home time for patients with HF was 21.77 days (range, 8.22-28.41 days). Hospitals in the highest quartile of risk-adjusted 30-day home time (best-performing hospitals) were larger (mean [SD] number of beds, 285 [275]), with a higher volume of patients with HF (median, 797 patients; interquartile range, 395-1484) and were more likely academic hospitals (59.9%) with availability of cardiac surgery (51.1%) and cardiac rehabilitation (68.8%). A total of 72% of home time lost was attributable to stays in an intermediate- or long-term care facility (mean [SD], 2.65 [6.44] days) or skilled nursing facility (mean [SD], 3.96 [9.04] days), 13% was attributable to short-term readmissions (mean [SD], 1.25 [3.25] days), and 15% was attributable to death (mean [SD], 1.37 [6.04] days). Among 30-day outcomes, the 30-day RSRR and 30-day RSMR decreased in a graded fashion across increasing 30-day home time categories (correlation coefficients: 30-day RSRR and 30-day home time, -0.23, P < .001; 30-day RSMR and 30-day home time, -0.31, P < .001). Similar patterns of association were also noted for 1-year RSMR and 30-day home time (correlation coefficient, -0.35, P < .001). Thirty-day home time meaningfully reclassified hospital performance in 30% of the hospitals compared with 30-day RSRR and in 25% of hospitals compared with 30-day RSMR. Conclusions and Relevance: In this study, 30-day home time among patients discharged after a hospitalization for HF was objectively assessed as a hospital-level quality metric using Medicare claims data and was associated with readmission and mortality outcomes and with reclassification of hospital performance compared with 30-day RSRR and 30-day RSMR.