Journal of

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Background: Nowadays, Medical error as a major challenge has been attention of health authorities and community. The main purpose of this study was survey of medical errors in Shiraz public hospitals. Materials & Methods: This study was a survey which conducted as analytical in 2013. Study population was Shiraz public hospitals which 10 hospitals were examined. Standard checklist was used for collecting data of medical error documentations. Data entered in SPSS software version 21 and used of descriptive, spearman and chi-square test for data analysis. Results: the number of medical errors in hospitals during the one year was 4379 recorded and the most of error was related to larger hospitals. Nurses committed wrong more than other groups and systemic error had the highest frequency. There was a significant relationship between trespassing, time and type of error, (P=0.000). Moreover, there was a significant relationship between type of error with wards and hospitals). P=0.000, P=0.011 respectively) Conclusion: The number of errors occurring in hospitals is symptoms of poor performance, therefore to prevent and reduce the medical errors and costs, managers should pay more attention to hospital performance and treatment guidelines are revised. Moreover, the hospital staff, especially nurses should pay more attention to their activities.

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Background: Approximately, more than 60 percent of the hospital costs allocate to hospital human resources. The study aimed at determining the number of nurses in the poisoning department of a general hospital in Shiraz.

Methods: This study was an applicable one based on hospital information.  Study population was patients who referred to a hospital poisoning department of Shiraz in 2012.  The medical records were checked up. Monthly stratified data was obtained from the statistics office and patient records (physician's orders and nursing notes) using a monthly systematic data collection randomly. Linear programming techniques using lingo version 8 software were performed to data analysis in order to calculating appropriate number of nurses.

Results: Two nurses in morning, two in evening, three in night and seven in all shifts were at least required nurses in the poisoning department of the general hospital. The number of available nurses was more than estimated number in the department.

Conclusion: The numbers of nurses were over the approximated number in the department in morning and evening shifts.  Besides, the estimated of nurses from quantitative methods such as linear programming were lower than those calculated experimentally by nursing managers. It is recommended to Hospital administrators considering these techniques calculation to achieve appropriate distribution of staff in departments.