scholarly journals Electronic Health Records and Teaching Status Effects on Mortality in New York State Hospitals

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Eduard Babulak
2015 ◽  
Vol 68 ◽  
pp. S15-S20 ◽  
Author(s):  
Remle Newton-Dame ◽  
Jason J. Wang ◽  
Michelle S. Kim ◽  
Zoe R. Edelstein ◽  
Blayne Cutler ◽  
...  

2006 ◽  
Vol 22 (4) ◽  
pp. 339-342 ◽  
Author(s):  
Randall Zuckerman ◽  
Brit Doty ◽  
Michael Gold ◽  
James Bordley ◽  
Patrick Dietz ◽  
...  

2008 ◽  
Vol 36 (10) ◽  
pp. 702-705 ◽  
Author(s):  
Rachel L. Stricof ◽  
Karolina A. Schabses ◽  
Boldtsetseg Tserenpuntsag

PLoS ONE ◽  
2010 ◽  
Vol 5 (9) ◽  
pp. e12658 ◽  
Author(s):  
Hossein Khiabanian ◽  
Antony B. Holmes ◽  
Brendan J. Kelly ◽  
Mrinalini Gururaj ◽  
George Hripcsak ◽  
...  

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 6640-6640
Author(s):  
Umut Sarpel ◽  
Natalia Egorova ◽  
Eugene Sosunov ◽  
Rebeca Franco ◽  
Yohana Taveras ◽  
...  

6640 Background: 30-day readmission rates are currently being used as a measure of performance quality. Among surgical patients, readmissions may be reducible for certain complications such as deep venous thrombosis or wound infection. We report 30-day readmission rates for potentially preventable readmissions following surgical treatment of the most common malignancies in the US. Methods: The most common cancer hospitalizations were identified from the Healthcare Cost and Utilization Project. Previously reported ICD-9 codes of preventable readmissions from cancer surgery were used to assess 30-day readmissions in New York State in 2009. We measured comorbidity using CMS hierarchical condition categories. Hospital teaching status was based on the American Hospital Association designation. Random effect hierarchical logistic regression models were run to account for clustering within hospitals. Results: 21,945 index admissions for cancer surgery occurred in 2009 at 169 teaching and 73 non-teaching hospitals. The most common operations were for prostate, breast, colon, lung, and renal cancer. 51% of patients were male and 12% were black. The overall readmission rate was 9.3% with readmissions being higher in non-teaching hospitals (11.2%) vs. teaching hospitals (8.6%) (p<0.0001). There was a significant interaction between hospital teaching status and patient race. In teaching hospitals, there was no racial difference in readmission. However, in non-teaching hospitals, black patients were more likely to be readmitted (15.1% vs 10.9%; p=0.02). Multivariate models found that being male (OR=1.17; 95% CI: 1.04; 1.31; p=0.007), undergoing surgery at a non-teaching hospital (OR=1.16; 95% CI: 1.00; 1.35; p=0.048), black race (OR=1.47; 95% CI: 1.04; 2.08; p=0.029), and certain comorbidities increased a patient’s risk of 30-day readmission for a preventable cause. Conclusions: The 30-day preventable readmission rate after index hospitalizations for cancer surgery is higher in non-teaching hospitals, and this difference is more pronounced for black patients. Clinical protocols in teaching hospitals may play a role in this phenomenon. Efforts to address remediable causes of this disparity are warranted.


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