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.

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.

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.

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.

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.

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.

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.

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.

Predictors of hospital transfer and associated risks of mortality in acute pancreatitis.

BACKGROUND: There is limited research in prognosticators of hospital transfer in acute pancreatitis (AP). Hence, we sought to determine the predictors of hospital transfer from small/medium-sized hospitals and outcomes following transfer to large acute-care hospitals. METHODS: Using the 2010-2013 Nationwide Inpatient Sample (NIS), patients ≥18 years of age with a primary diagnosis of AP were identified. Hospital size was classified using standard NIS Definitions. Multivariable analyses were performed for predictors of "transfer-out" from small/medium-sized hospitals and mortality in large acute-care hospitals. RESULTS: Among 381,818 patients admitted with AP to small/medium-sized hospitals, 13,947 (4%) were transferred out to another acute-care hospital. Multivariable analysis revealed that older patients (OR = 1.04; 95%CI 1.03-1.06), men (OR = 1.15; 95%CI 1.06-1.24), lower income quartiles (OR = 1.54; 95%CI 1.35-1.76), admission to a non-teaching hospital (OR = 3.38; 95%CI 3.00-3.80), gallstone pancreatitis (OR = 3.32; 95%CI 2.90-3.79), pancreatic surgery (OR = 3.14; 95%CI 1.76-5.58), and severe AP (OR = 3.07; 95%CI 2.78-3.38) were predictors of "transfer-out". ERCP (OR = 0.53; 95%CI 0.43-0.66) and cholecystectomy (OR = 0.14; 95%CI 0.12-0.18) were associated with decreased odds of "transfer-out". Among 507,619 patients admitted with AP to large hospitals, 31,058 (6.1%) were "transferred-in" from other hospitals. The mortality rate for patients "transferred-in" was higher than those directly admitted (2.54% vs. 0.91%, p < 0.001). Multivariable analysis revealed that being "transferred-in" from other hospitals was an independent predictor of mortality (OR = 1.47; 95% CI 1.22-1.77). CONCLUSIONS: Patients with AP transferred into large acute-care hospitals had a higher mortality than those directly admitted likely secondary to more severe disease. Early implementation of published clinical guidelines, triage, and prompt transfer of high-risk patients may potentially offset these negative outcomes.

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.

Reperfusion Therapy Frequency and Outcomes in Mild Ischemic Stroke in the United States.

BACKGROUND AND PURPOSE: More than half of patients with acute ischemic stroke have minor neurological deficits; however, the frequency and outcomes of reperfusion therapy in regular practice has not been well-delineated. METHODS: Analysis of US National Inpatient Sample of hospitalizations with acute ischemic stroke and mild deficits (National Institutes of Health Stroke Scale [NIHSS] score 0-5) from October 1, 2016, to December 31, 2017. Patient- and hospital-level characteristics associated with use and outcome of reperfusion therapies were analyzed. Primary outcomes included excellent discharge disposition (discharge to home without assistance); poor discharge disposition (discharge to facility or death); in-hospital mortality; and radiological intracranial hemorrhage. RESULTS: Among 179 710 acute ischemic stroke admissions with recorded NIHSS during the 15-month study period, 103 765 (57.7%) had mild strokes (47.3% women; median age, 69 [interquartile range, 59-79] years; median NIHSS score of 2 [interquartile range, 1-4]). Considering reperfusion therapies among strokes with documented NIHSS, mild deficit hospitalizations accounted for 40.0% of IVT and 10.7% of mechanical thrombectomy procedures. Characteristics associated with IVT and with mechanical thrombectomy utilization were younger age, absence of diabetes, higher NIHSS score, larger/teaching hospital status, and Western US region. Excellent discharge outcome occurred in 48.2% of all mild strokes, and in multivariable analysis, was associated with younger age, male sex, White race, lower NIHSS score, absence of diabetes, heart failure, and kidney disease, and IVT use. IVT was associated with increased likelihood of excellent outcome (odds ratio, 1.90 [95% CI, 1.71-2.13], P<0.001) despite an increased risk of intracranial hemorrhage (odds ratio, 1.41 [95% CI, 1.09-1.83], P<0.001). CONCLUSIONS: In national US practice, more than one-half of acute ischemic stroke hospitalizations had mild deficits, accounting for 4 of every 10 IVT and 1 of every 10 mechanical thrombectomy treatments, and IVT use was associated with increased discharge to home despite increased intracranial hemorrhage.

Adoption rates of electronic health records in Turkish Hospitals and the relation with hospital sizes.

BACKGROUND: Nation-wide adoption of electronic health records (EHRs) in hospitals has become a Turkish policy priority in recognition of their benefits in maintaining the overall quality of clinical care. The electronic medical record maturity model (EMRAM) is a widely used survey tool developed by the Healthcare Information and Management Systems Society (HIMSS) to measure the rate of adoption of EHR functions in a hospital or a secondary care setting. Turkey completed many standardizations and infrastructural improvement initiatives in the health information technology (IT) domain during the first phase of the Health Transformation Program between 2003 and 2017. Like the United States of America (USA), the Turkish Ministry of Health (MoH) applied a bottom-up approach to adopting EHRs in state hospitals. This study aims to measure adoption rates and levels of EHR use in state hospitals in Turkey and investigate any relationship between adoption and use and hospital size. METHODS: EMRAM surveys were completed by 600 (68.9%) state hospitals in Turkey between 2014 and 2017. The availability and prevalence of medical information systems and EHR functions and their use were measured. The association between hospital size and the availability/prevalence of EHR functions was also calculated. RESULTS: We found that 63.1% of all hospitals in Turkey have at least basic EHR functions, and 36% have comprehensive EHR functions, which compares favourably to the results of Korean hospitals in 2017, but unfavorably to the results of US hospitals in 2015 and 2017. Our findings suggest that smaller hospitals are better at adopting certain EHR functions than larger hospitals. CONCLUSION: Measuring the overall adoption rates of EHR functions is an emerging approach and a beneficial tool for the strategic management of countries. This study is the first one covering all state hospitals in a country using EMRAM. The bottom-up approach to adopting EHR in state hospitals that was successful in the USA has also been found to be successful in Turkey. The results are used by the Turkish MoH to disseminate the nation-wide benefits of EHR functions.

Hospitais de Cidades Pequenas: inserção e pactuação no Sistema Único de Saúde (SUS) / Small Towns Hospitals: insertion and agreement in the Brazilian Unified Health System

RESUMO: Importância do problema: É indiscutível a importância do hospital na organização no Sistema Único de Saúde (SUS). Os hospitais com 50 leitos ou menos, também chamados de hospitais de pequeno porte (HPP) são essenciais para a construção das redes de atenção à saúde (RAS) considerando sua capilaridade no sistema. Objetivo: Descrever a caracterização dos hospitais de pequeno porte e sua adequação à política vigente. Método: Trata-se de um estudo transversal, descritivo, realizado a partir de dados secundários obtidos de bases de dados nacionais: Cadastro Nacional de Estabelecimentos de Saúde (CNES-MS), Sistema de Informações Hospitalares (SIH/SUS) e o sistema de registro de dados hospitalares da Regional de Saúde. O estudo foi realizado em uma região de saúde localizada no norte do Paraná, Brasil. Resultados: Neste estudo, 100% dos hospitais em cidades pequenas da 17ª Regional de Saúde do Paraná são de pequeno porte. A oferta de leitos atende à estabelecida pela portaria do Ministério da Saúde n° 1.101/2002. Observou-se a extrema ociosidade da capacidade instalada, centros cirúrgicos inativos e baixíssima ocupação dos leitos hospitalares. Conclusão: Conclui-se que a forma de pactuação/contratualização isolada de cada hospital não surtiu os efeitos desejados pela Política Nacional de HPP (PNHPP). Sugere-se que uma nova vinculação ocorra de forma regionalizada e que se criem um sistema unificado de gestão. (AU)

ABSTRACT: Importance of the problem: The importance of the hospital in the organization of the Brazilian Unified Health System (UHS)is indisputable. Hospitals with 50 beds or fewer, also called small hospitals are essential for building health care networks considering their capillarity in the system. Objective: Describing the characterization of small hospitals and their adequacy to current policy and confirm the results presented so far in the literature. Method: This is a cross-sectional, descriptive study based on secondary data obtained from the national databases: National Registry of Health Establishments, Hospital Information System, and registry of data of the Regional of Health. The study was conducted in a health region located in northern Paraná, Brazil. Results: In this study, more than 90% of the hospitals in towns of the 17th Regional of Health of Paraná are small. The supply of beds meets the guidelines of the Ministry of Health n. 1,101/2002. It was observed the extreme idleness of facilities, inactive surgical centers, and low occupation of hospital beds. Conclusion: It is concluded that the form of agreement isolated from each hospital did not have the desired effects by national small hospital policy. It is suggested that a new connection occurs regionally and that a unified management system might be created. (AU)

COVID-19 Pandemic in Assisted Living Communities: Results from Seven States.

OBJECTIVE: To describe variations in COVID-19 confirmed cases and deaths among assisted living (AL) residents and examine their associations with key AL characteristics. DESIGN: Observational study employing data on confirmed COVID-19 cases and deaths in ALs from seven states, through May 29, 2020. SETTING: Information on COVID-19 cases/deaths in ALs was obtained from state government websites. A national inventory of ALs was used to identify communities with and without COVID-19 cases/deaths. Medicare Beneficiary Summary File identifying AL residents was employed to develop AL characteristics. County-level COVID-19 laboratory-confirmed cases/deaths were obtained from publicly available data. PARTICIPANTS: We found 4,865 ALs (2,647 COVID-19 cases and 777 deaths) in the seven states. After excluding missing data, the sample consisted of 3,994 ALs (82.1%) with 2,542 cases (96.0%) and 675 deaths (86.9%). MAIN OUTCOMES AND MEASURES: Outcomes were AL-level counts of cases and deaths. Covariates were AL characteristics and county-level confirmed COVID-19 cases/deaths. Multivariable two-part models determined the associations of independent variables with the likelihood of at least one case and death in the AL, and with the count of cases (deaths). RESULTS: State case fatality ranged from 3.32% in North Carolina to 9.26% in Connecticut, but for ALs in these states it was 12.89% and 31.59%, respectively. Among ALs with at least one case, midsize communities had fewer cases (incidence rate ratio (IRR) = 0.829; P = .004) than small ALs. ALs with higher proportions of racial/ethnic minorities had more COVID-19 cases (IRR = 1.08; P < .001), as did communities with higher proportions of residents with dementia, chronic obstructive pulmonary disease, and obesity. CONCLUSIONS AND RELEVANCE: ALs with a higher proportion of minorities had more COVID-19 cases. Many of the previously identified individual risk factors are also present in this vulnerable population. The impact of COVID-19 on ALs is as critical as that on nursing homes, and is worth equal attention from policy makers.