# Developing a Decision-Making Framework to Improve Healthcare Service Quality during a Pandemic
## 4 Results
### Scenario 1  
In Scenario 1, all nine criteria (Figure 11) are assigned to all stakeholders irrespective of their work background or preferences. Every stakeholder provides a preference value to each criterion in order to find the consensus solution. Step 1: Determining Best and Worst Criteria: Table 3 shows the selected best and worst criteria for all stakeholders. Step 2: Rating the Best Criterion over the Other Criteria, and the Other Criteria over the Worst Criterion: The stakeholders' preference values for the best criterion versus the others are listed in Table 11, and the preference values for the other criteria over the worst criterion is listed in Table 12.  
Step 3: Determining the Optimal Weights of the Selected Criteria: The optimal weights of the selected criteria were calculated using Equation (4). The results are summarized in Table 4.  
Step 4: Comparison of Each Criterion with All Alternatives: Figure 12 shows the SMART evaluation performed by STKH1 for criterion CR1. Step 5: Selection of the Best Alternatives for Each Stakeholder: Figure 13 shows the sensitivity analysis result for STKH 1. The alternative ranking varies based on the stakeholder's weight value; for example, in Figure 13, the top-ranked alternatives for CR1 are A1 and A4, with a weight value of 0.281. These changes in the alternative rankings are grouped, and an average value is obtained, which serves as the overall result. Figure 14 provides a graphic rendering of the overall result of Scenario 1, while Tables 5 and 13 show the calculated alternative weights and their rankings, respectively. As the ranking of alternatives shows, each STKH selects their preferred alternatives (no consensus), even though the criteria are the same. The obtained results (Table 5) show that there is no consensus among the stakeholders since everyone has a different highest-ranked alternative. To deal this issue, and to predict the best alternative, the MOLP is implemented with the help of SIMUS. Step 6: Solving the Multi-Objective Linear Programming (MOLP) Model: As per Equations (5) and (6), each criterion is considered as an objective function to determine the consensus solution for Scenario 1. Step 7: Forming an Efficient Result Matrix (ERM): The ranking of alternatives for Scenario 1 was A1 > A4 > A3 > A2 > A5. Figure 15 shows the MOLP results situated within a normalized ERM matrix, and Figure 16 shows the ERM ranking of alternatives. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline  & **CR 1** & **CR 2** & **CR 3** & **CR 4** & **CR 5** & **CR 6** & **CR 7** & **CR 8** & **CR 9** \\ \hline STKH1 & 0.280 & 0.074 & 0.092 & 0.074 & 0.123 & 0.185 & 0.053 & 0.023 & 0.092 \\ \hline STKH2 & 0.140 & 0.032 & 0.070 & 0.084 & 0.308 & 0.140 & 0.070 & 0.070 & 0.084 \\ \hline STKH3 & 0.267 & 0.021 & 0.067 & 0.101 & 0.134 & 0.202 & 0.067 & 0.057 & 0.080 \\ \hline STKH4 & 0.143 & 0.143 & 0.095 & 0.143 & 0.223 & 0.095 & 0.022 & 0.035 & 0.095 \\ \hline STKH5 & 0.115 & 0.268 & 0.086 & 0.086 & 0.173 & 0.115 & 0.057 & 0.023 & 0.069 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Optimal weights of each criterion for each stakeholder. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Stakeholder** & **Best Criteria** & **Worst Criteria** \\ \hline STKH 1 & CR 1 & CR 8 \\ \hline STKH 2 & CR 5 & CR 2 \\ \hline STKH 3 & CR 1 & CR 2 \\ \hline STKH 4 & CR 5 & CR 7 \\ \hline STKH 5 & CR 2 & CR 8 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Best and worst criteria by stakeholder. Step 8: Forming a Project Dominance Matrix (PDM): Figure A7 shows the actual PDM results with the ranking of alternatives. Step 9: Result Analysis and Final Selection of the Best Alternative with Consensus: At this step, the final ranking of alternatives can be obtained for Scenario 1 (A1 > A4 > A3 > A2 > A5). The obtained results show that the ERM and PDM rankings match exactly and that there is no difference in the results. The alternative A1 (hiring part-time physicians and medical staff) ranks top in both rankings.