Elham Maserrat defended her Thesis titledDesigning of an Intelligent Hybrid Decision Support System for Management of Colorectal Cancer Screening Program


Colorectal cancer (CRC) is a major cause of morbidity and mortality throughout the world. Colorectal cancer screening is an optimal way for reducing of morbidity and mortality. The use of computer technologies as decision support systems (DSS) facilitate decision making and improve efficiency of screening process. The aim of this study is to design an intelligent hybrid decision support system for management of colorectal cancer screening program. This was an applied – developing study. Situation analyzing of screening information system and surveying data elements of screening program were performed respectively in the first and second stage by checklist tool. The third stage was to design of decision support system that comprised of three phases. The first phase was a qualitative survey of feasibility based on interview. The second phase was a comparative study that performed between three courtiers was selected from 25 countries that are member in the international Cancer Screening Network (ICSN).

This phase was performed for approving of screening guidelines. These guidelines were achieved by literature review and expert opinions. The next step; guidelines were approved, coded and implemented. The third phase, survival rate of covered populations was estimated by Naive Bayes technique. Outputs accuracy was surveyed by experts and usability of system were evaluated by Nielsen criteria. In this study, current screening information system was surveyed of six dimensions. These dimensions were general specification, functions, technologies, data resources, users, manual and standards of screening information system. Functions, technologies, data resource, users, manual and standards of present screening information system. Data elements of covered populations, health care provider and organizational-administrative data elements were surveyed in current screening information system.

We performed feasibility study according to five aspects, including necessity for DSS implementing, preparation for implementing, barriers and challenges, specifications of DSS, capabilities and functions and DSS infrastructures. The next step; we approved and implemented four risk assessment guidelines, clinical criteria for hereditary syndromes and roadmap of genetic and pathologic analysis. Designed intelligent system has estimated survival rates of covered populations with precision of 95.6%. Designed DSS provides real-time decision making during a clinical interaction. Also this system has predicted survival rate with the high precision. Estimating of survival rate has a key role for health care planning. A big obstacle for the DSS implementing is to obtain the patient and relatives information required for decision making. As a conclusion, it is recommended to consider the necessity of reengineering of screening process and also eliminating of information gaps.




Supervisors: Dr Reza Safsari, Professor

Dr Mohammad Reza Zali, Professor

Advisors: Dr. Hamid Asadzadeh Aghdaei, Assistant professor

Reviewers: Dr Ghazi saeedi, Assistant professor

Dr Sharareh Niyakan, Assistant professor

Dr Shahram Tophighi, Assistant Professor

Dr Afsaneh Sharifiyan, Associate Professor