Özlem Müge Testik1, Amir Shaygan, Erdi Dasdemir, Guray Soydan. 1. Department of Industrial Engineering, Hacettepe University, Ankara, Turkey (Dr Testik and Messrs Shaygan and Dasdemir); and Department of Medical Pharmacology, Hacettepe University, Ankara, Turkey (Dr Soydan).
Abstract
OBJECTIVES: It is often vital to identify, prioritize, and select quality improvement projects in a hospital. Yet, a methodology, which utilizes experts' opinions with different points of view, is needed for better decision making. METHODS: The proposed methodology utilizes the cause-and-effect diagram to identify improvement projects and construct a project hierarchy for a problem. The right improvement projects are then prioritized and selected using a weighting scheme of analytical hierarchy process by aggregating experts' opinions. An approach for collecting data from experts and a graphical display for summarizing the obtained information are also provided. RESULTS: The methodology is implemented for improving a hospital appointment system. The top-ranked 2 major project categories for improvements were identified to be system- and accessibility-related causes (45%) and capacity-related causes (28%), respectively. For each of the major project category, subprojects were then ranked for selecting the improvement needs. CONCLUSION: The methodology is useful in cases where an aggregate decision based on experts' opinions is expected. Some suggestions for practical implementations are provided.
OBJECTIVES: It is often vital to identify, prioritize, and select quality improvement projects in a hospital. Yet, a methodology, which utilizes experts' opinions with different points of view, is needed for better decision making. METHODS: The proposed methodology utilizes the cause-and-effect diagram to identify improvement projects and construct a project hierarchy for a problem. The right improvement projects are then prioritized and selected using a weighting scheme of analytical hierarchy process by aggregating experts' opinions. An approach for collecting data from experts and a graphical display for summarizing the obtained information are also provided. RESULTS: The methodology is implemented for improving a hospital appointment system. The top-ranked 2 major project categories for improvements were identified to be system- and accessibility-related causes (45%) and capacity-related causes (28%), respectively. For each of the major project category, subprojects were then ranked for selecting the improvement needs. CONCLUSION: The methodology is useful in cases where an aggregate decision based on experts' opinions is expected. Some suggestions for practical implementations are provided.