Shahram Tofighi - Health Management Research Center, Baqiyatallah University of Medical Sciences
Abbas Ebadi - Nursing Faculty, Baqiyatallah University of Medical Sciences, Tehran, Iran
Roohollah Zaboli - Health Services Management Department, Health School, Baqiyatallah University of Medical Sciences.
Sharareh Rostam Niakan Kalbori - Department of Public Health, School of Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran

Introduction: one of the important aims was to provide services with the quality oforganizational intelligence and aim of this study was to assess the organizational intelligencein Baqiyatallah hospital that conducted based on Karl Albrecht's Organizationalintelligence components. We tried to evaluate the status of the quality of servicesbased on these components.Methods- the study was descriptive and was conducted through cross-sectionalmethod. The sampling method was full enumeration from the top and middle managersof Baqiyatallah hospital in which 107 respondents were questioned. Data was collectedby the Karl Albrecht's standard questionnaire of organizat ional intelligence that included7 component and 49 questions. The validity of questionnaire assessed by faceand content-related validity and reliability was obtained using Cronbach's alpha 0/92.Data was analyzed in SPSS 15. We used descriptive statistics such as mean, standarddeviation and inferential statistics such as Pearson's test, t -test.Findings- 57% of participants were male and 43% were female. Findings indicatedthat unity and agreement in hospital with mean 3.18, SD 0.4 and appetite for changewith mean 2.61, SD 0.5 had highest and lowest rating respectively. The total score oforganizational in the hospital had mean 2.92 and SD 0.4.Conclusion- according to scores obtained, the organizational intelligence of the hospital(with mean 2.94 and SD 0.4) had the middle level. We can perform and implementthe organizational intelligence through some corrective measures.

Business Intelligence, Organizational Intelligence, Hospital, data, data Mining