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Dec 2011

Mortality Associated With Nonelective Hospital Admission

Author Affiliations

Author Affiliations: Department of Internal Medicine, Hospital Clinico San Carlos (Dr Marco), Department of Internal Medicine, Hospital Infanta Cristina, Parla (Dr Barba), and Department of Internal Medicine, Hospital Universitario Fuenlabrada (Dr Zapatero), Madrid, Spain.

Arch Surg. 2011;146(12):1451. doi:10.1001/archsurg.2011.957

We have read with interest the article by Ricciardi et al1 entitled “Mortality Rate After Noelective Hospital Admission” that presented data demonstrating significantly worse outcomes after nonelective admission during the weekend compared with weekdays across demographic groups for 16 of 25 medical and surgical diagnoses. The work was done using data from nearly 30 million admissions coming from the Nationwide Inpatient Sample of the Healthcare Cost and Utilization Project of the Agency for Healthcare Research and Quality, which contains data from approximately 7 to 8 million hospital stays per year in 1000 hospitals in 35 states. We have recently published a similar work about the weekend effect on acute exacerbations of patients with chronic obstructive pulmonary disease.2 Previous studies on the subject failed to demonstrate this type of effect, probably owing to a problem with the size of the sample.3 However, using also a large clinical, administrative database obtained from the Spanish Ministry of Health, we were able to include nearly 390 000 patients and to identify differences in mortality that persisted after adjustment for age, sex, and coexisting disorders (odds ratio, 1.05 [95% CI, 1.02-1.08]) between patients admitted on weekdays and patients admitted on weekends. We would like to stress the importance and validity of the research done with this type of large administrative, clinical database. It can be argued (and we would agree) that this type of research has some drawbacks for the analysis of specific clinical outcomes. However, this type of research is invaluable for reaching conclusions about clinical problems in which the size of the sample is crucial.

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