scholarly journals Temporal Trends and Hospital Variation in Time to Antibiotics for Sepsis

Author(s):  
M. Wayne ◽  
S. Seelye ◽  
D. Molling ◽  
X.Q. Wang ◽  
J. Donnelly ◽  
...  
2021 ◽  
Vol 4 (9) ◽  
pp. e2123950
Author(s):  
Max T. Wayne ◽  
Sarah Seelye ◽  
Daniel Molling ◽  
Xiao Qing Wang ◽  
John P. Donnelly ◽  
...  

2013 ◽  
Vol 166 (2) ◽  
pp. 315-324.e1 ◽  
Author(s):  
Lakshmi Venkitachalam ◽  
Darren K. McGuire ◽  
Kensey Gosch ◽  
Kasia Lipska ◽  
Silvio E. Inzucchi ◽  
...  

2013 ◽  
Vol 41 (6) ◽  
pp. 1405-1411 ◽  
Author(s):  
Thomas W. DeCato ◽  
Ruth A. Engelberg ◽  
Lois Downey ◽  
Elizabeth L. Nielsen ◽  
Patsy D. Treece ◽  
...  

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S74-S74
Author(s):  
Sophia Kazakova ◽  
Natalie McCarthy ◽  
James Baggs ◽  
Kelly M Hatfield ◽  
Hannah Wolford ◽  
...  

Abstract Background Decreasing inappropriate urine cultures in hospitalized patients has been a target of diagnostic stewardship to improve infection surveillance and antimicrobial use. The impact of such efforts has been largely unstudied. This study assessed temporal trends in urine culture rates in a cohort of acute care hospitals (ACHs) between 2012 and 2017. Hospital Level Variation in Admission Urine Culture Rates Hospital Level Variation in Post-admission Urine Culture Rates Methods We used microbiology data from ACHs participating in the Premier Healthcare Database and Cerner Health Facts to measure monthly urine culture rates. All cultures from the urinary tract collected on or before day 3 were defined as admission cultures (AC) and those collected on day 4 or later as post-admission cultures (PAC). Temporal trends in AC and PAC rates were estimated using general estimating equation models adjusting for hospital-level clustering, hospital size, teaching status, urban/rural designation, discharge month, and region. Results During the study period, ACHs had 20.8 million discharges and performed 4,946,717 urine cultures, of which 21% were PAC. In 2012 and 2017, the unadjusted AC rates were 18.7 and 18.4 per 100 discharges; the unadjusted PAC rates were 11.5 and 8.5 per 1,000 patient days (PD) respectively. The median annual hospital-level AC rate was 17.2 with inter-hospital variation ranging from 12.7 (quartile 1) to 24.1 (quartile 3) per 100 discharges, Figure 1. Similarly, the PAC rates varied among the ACHs with a median of 7.1 and inter-hospital variation ranging from 4.6 (quartile 1) to 10.5 (quartile 3) per 1,000 PDs, Figure 2. In multivariable analysis, no temporal trends in AC rates were detected (rate ratio (RR) 1.01; 95% confidence interval (CI): 0.99–1.02). However, PAC rates decreased 6.3% annually (RR 0.937; 95% CI: 0.93–0.95). Factors significantly associated (p< 0.02) with PAC rates were discharge month, teaching status, bed size, and region. For AC, significant associations (p< 0.0001) were discharge month and region. Conclusion Between 2012 and 2017, the rate of AC remained unchanged, but PAC rates decreased significantly. Factors driving this trend are unknown, but potential explanations include changes in culturing practices and/or decreases in hospital-onset urinary tract infections. Understanding factors related to the decrease and the impact on patient outcomes warrants further study. Disclosures All Authors: No reported disclosures


2021 ◽  
Vol 78 (19) ◽  
pp. B59-B60
Author(s):  
Amit Vora ◽  
Hemal Gada ◽  
Pratik Manandhar ◽  
Andrzej Kosinski ◽  
Ajay Kirtane ◽  
...  

2020 ◽  
Vol 13 (Suppl_1) ◽  
Author(s):  
Aya Ozaki ◽  
Cynthia JACKEVICIUS ◽  
Alice Chong ◽  
Maria Koh ◽  
Maneesh Sud ◽  
...  

Background: Ticagrelor is a P2Y12 inhibitor with better cardiovascular outcomes than clopidogrel in clinical trials for acute coronary syndromes. However, the adoption of ticagrelor into clinical practice has been understudied. Therefore, we evaluated: 1) temporal trends in ticagrelor use, 2) factors associated with its use, and 3) hospital variation in its adoption and clinical outcomes. Methods: We conducted a population-based cohort study using administrative claims data in Ontario, Canada between 4/2014 and 3/2018. We identified individuals >65 years of age who were admitted for myocardial infarction (MI) or unstable angina (UA) and filled a prescription for ticagrelor or clopidogrel at or within 7 days of discharge. We categorized hospitals into quartiles based on ticagrelor utilization rates. The primary composite outcome was 1-year death or hospitalization for MI/UA, and 1-year bleeding hospitalization was a secondary outcome. Outcomes were evaluated using a Cox proportional hazards model to compare high vs. low utilization groups. Further, we quantified the between-hospital variability of ticagrelor utilization using multi-level logistic regression analysis, expressed as median odds ratios (MOR). Results: Among 23 962 patients in our cohort, 42.5% were prescribed ticagrelor ≤7 days post-hospital discharge. Ticagrelor utilization increased from 32.6% in 2014 to 51.8% in 2017. Hospitals at the lowest quartile of ticagrelor utilization (<8.8%) had a higher hazard of the primary outcome (adjusted hazard ratio: 1.27 95%CI: 1.11-1.46, p<0.001) compared with high ticagrelor utilization hospitals (>40%). No significant difference in bleeding hospitalization across hospital quartiles was observed. Some factors associated with higher ticagrelor use were cardiologist as most responsible physician during index hospitalization and urban hospital. After adjusting for patient-, prescriber- and hospital-level characteristics, substantial variation remained between hospitals in the likelihood of patients receiving ticagrelor at discharge (MOR: 2.54). Conclusion: Increasing trends of ticagrelor utilization were observed. Ticagrelor utilization rates varied across hospitals, and hospitals with higher ticagrelor adoption were associated with better clinical outcomes.


2020 ◽  
Vol 29 (2) ◽  
pp. 206-217
Author(s):  
Jianyuan Ni ◽  
Monica L. Bellon-Harn ◽  
Jiang Zhang ◽  
Yueqing Li ◽  
Vinaya Manchaiah

Objective The objective of the study was to examine specific patterns of Twitter usage using common reference to tinnitus. Method The study used cross-sectional analysis of data generated from Twitter data. Twitter content, language, reach, users, accounts, temporal trends, and social networks were examined. Results Around 70,000 tweets were identified and analyzed from May to October 2018. Of the 100 most active Twitter accounts, organizations owned 52%, individuals owned 44%, and 4% of the accounts were unknown. Commercial/for-profit and nonprofit organizations were the most common organization account owners (i.e., 26% and 16%, respectively). Seven unique tweets were identified with a reach of over 400 Twitter users. The greatest reach exceeded 2,000 users. Temporal analysis identified retweet outliers (> 200 retweets per hour) that corresponded to a widely publicized event involving the response of a Twitter user to another user's joke. Content analysis indicated that Twitter is a platform that primarily functions to advocate, share personal experiences, or share information about management of tinnitus rather than to provide social support and build relationships. Conclusions Twitter accounts owned by organizations outnumbered individual accounts, and commercial/for-profit user accounts were the most frequently active organization account type. Analyses of social media use can be helpful in discovering issues of interest to the tinnitus community as well as determining which users and organizations are dominating social network conversations.


1993 ◽  
Vol 32 (01) ◽  
pp. 79-81 ◽  
Author(s):  
P. Millard ◽  
S. McClean

Abstract:The flow of patients through geriatric hospitals has been previously described in terms of acute and long-stay states where the bed occupancy at a census point is modelled by a mixed exponential model. Using data for sixteen years the model was fitted to successive annual census points, in order to provide a description of temporal trends. While the number of acute patients has remained fairly stable during the period, the model shows that there has been a decrease in the number of long-stay patients. Mean lengths of stay in our geriatric hospital before death or discharge have decreased during the study period for both acute and long-stay patients.Using these fits of the mixed exponential model to census data, a method is provided for predicting future turnover of patients. These predictions are reasonably good, except when the turnover patterns go through a period of flux in which assumption of stability no longer holds. Overall, a methodology is presented which relates census analysis to the behaviour of admission cohorts, thus producing a means of predicting future behaviour of patients and identifying where there is a change in patterns.


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