Prioritizing the Surgical Waiting List-Cosine Consistency Index: An Optimized Framework for Prioritizing Surgical Waiting List

2020 ◽  
Vol 10 (12) ◽  
pp. 2876-2892
Author(s):  
Hemant Petwal ◽  
Rinkle Rani

This paper aims to examine patient prioritization challenges faced by surgeons attending to patients awaiting surgery and proposes a decision-making framework named PSWL-CCI to prioritize patients in the surgical waiting list. The proposed framework deals with two critical issues: One, to prioritize patients from the surgical waiting list. Two, to refine and optimize cosine consistency index (CCI) of inconsistent pairwise comparison matrix (PCM) and obtain consistent priorities. The judgment of surgeons on identified parameters in the term of rating helps in determining priorities from the surgical waiting list. The cosine maximization method (CM), along with the analytic hierarchy process (AHP), is used to evaluate the resulting priority. To improve inconsistent pairwise comparison matrix (PCM), a novel hybrid algorithm HMWCA (Hybrid modified water cycle algorithm), is proposed and incorporated in PSWL-CCI. The proposed algorithm exploits the feature of three traditional algorithms, namely the evaporation-based water cycle algorithm (ER-WCA), genetic algorithm, and 2-opt heuristic. In this paper, the concept of salt concentration and absorption introduced into the evaporation rate (ER) that extends ER-WCA to a modified water cycle algorithm (MWCA). MWCA iteratively modifies the entries in PCM until PCM is optimized. The genetic algorithm helps MWCA to determine the evaporation rate and enhance the rate of convergence. The 2-OPT algorithm improvises the optimal solution. The proposed algorithm is tested with different datasets, and the improved CCI values are validated through paired sample t-test. Finally, the proposed PSWL-CCI framework is validated through a case study of a real patient dataset from an orthopedic surgery department of a multispecialty hospital in India. The experimental results obtained in this study reveal that the proposed methodology and algorithms significantly improve the CCI values, thus generating optimum priorities for the patients of the surgical waiting list.

2017 ◽  
Vol 35 ◽  
pp. 93-110 ◽  
Author(s):  
Dhruv Kler ◽  
Pallavi Sharma ◽  
Ashish Banerjee ◽  
K.P.S. Rana ◽  
Vineet Kumar

2010 ◽  
Vol 118-120 ◽  
pp. 712-716 ◽  
Author(s):  
Li Jun Yan ◽  
Zong Bin Li ◽  
Xiao Chun Yang

The key issue of FAHP application is how to derive fuzzy weights from fuzzy pairwise comparison matrix. The most of applications, however, were founding avoiding the use of sophisticated approaches such as fuzzy least squares method and using a simple extent analysis method to derive fuzzy weight from pairwise comparison matrix for the sake of simplicity. But the extent analysis method proves to be incorrect and may lead to a wrong decision result. So, this paper proposes a sound yet simple linear goal programming model to derive weights from pairwise fuzzy comparison matrix, which takes minimizing inconsistence degree of comparison matrix as objective and obtain a normalized weight vector finally. The proposed model is validated by an application to new product development scheme screening decision making.


Sign in / Sign up

Export Citation Format

Share Document