Europäisches Journal für Experimentalbiologie Offener Zugang

Abstrakt

Hospital information systems success: A study based on the model adjusted DeLone and McLean in UMSU hospitals

Reza Safdari, Marjan Ghazisaeidi, Mohamad Jebraeily, Elham Masarat, Mostafa Shikhtayefeh and Sedigheh Farajolahi

In information systems, quality dimensions play an important role in determining their success. DeLone - McLean model, a thorough understanding of the information system provided successful and widely used as a comprehensive model for assessing information systems has been accepted. The aim of this study was assessment of HIS success in hospitals of Urmia university of medical sciences is based on the model Adjusted DeLone - McLean. This is a descriptive - cross sectional study which was inducted in 2014.The study population consists of 180 HIS users from Teaching Hospitals Affiliated to Urmia University of Medical Sciences. Data were collected using a self-structured questionnaire which was estimated as both reliable and valid. The data were analyzed by SPSS software descriptive statistics and analytical statistics (t-test and chi-square). HIS highest success rate based on three criteria related to the quality of system (3.11) and the lowest information quality (2.78) is. The tests result showed that none of the three criteria (system quality, information quality and service quality) were not satisfactory success rate HIS (P < 0.05). According to the survey results, it seems necessary to improve the system quality: user friendly, speed data entry, integration and exchange of information, usability and flexibility HIS pointed out. Improve the comprehensiveness, accuracy, and appropriateness to date reports could lead to increased information quality of HIS. Using hardware and advanced equipment, such as portable computers, smart sensors, useful applications optimized to reduce medical errors and support services, which will allow users to have complete satisfaction from the service quality of HIS.

Haftungsausschluss: Dieser Abstract wurde mit Hilfe von Künstlicher Intelligenz übersetzt und wurde noch nicht überprüft oder verifiziert