Journal of

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Background: This research aims to design and implement a software with the ability to identify patients who are facing the risk of pulmonary embolism and deep venous thrombosis instantly as well as the ability to send timely reminders for any prophylactic action. The main target is introduce a clinical decision- support system which could finally lead to preventing mortality and handicap cases caused by embolism and thromboses in patients who are confined to bed in hospitals. Materials and Methods: The software was designed using the Visual Basic.Net and SQL Server database. Afterwards the software was installed in the largest educational hospital of Kerman and a survey was conducted amongst the physicians using multiple questionnaires and interviews. Finally, the data were analyzed using the SPSS software. Results: The average score was 21.16 for the physicians and 20.76 for the nurses. T-Test results show that there is no significant difference between the total average score of the physicians and that of the nurses. Conclusion: The results have shown that both groups (physicians and nurses) have a positive viewpoint about the software therefore using the clinical decision support system can be effective in reducing the occurrence of pulmonary embolism and deep venous thrombosis through sending timely electronic alerts to the medical staff.

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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: Reduction of errors is necessary to improve the quality of healthcare, promoting communication between the hospital staff and patients, and decreasing the patient's complaints in hospitals. Due to the high probability of error in the operating room (OR), this study aimed to detect the potential errors in the OR of Nemazee hospital using FMEA.
Materials and Methods: This study was a qualitative one which assessed Failure Mode and effects of OR in six steps using FMEA technique. At First, the OR activities were listed, then the failure modes were recognized. Next, the Risk Priority Number (RPN) of each error was calculated according to the indicators of Occurrence (O), Severity (S) and Detectability (D).
 Results: Totally,204 failure modes in 36 activities in five process in surgery ward were recognized.15.7 percent of failure modes classified as high risk factors (RPN ≥ 100). The most and the least distribution of origin factors were related to human and organization and technical errors, respectively.
Conclusion: The majority of errors in OR was set in of human skills category. Besides, the most and the least failure modes were belonged to “patient anesthesia by circular activity number 20, RPN=1795.23)” and “not to oxygenation for patients (the activity number 36, RPN=99.33) respectively. Identification of 36 activities and 204 errors in the 5 processes of Operating Room represents the comprehensiveness of HFMEA method in the identification, classification, evaluation and analysis of the health system errors.