Prioritization and transparency in software development: An action research in public administration

The prioritization of requirements is a critical activity in quality assurance. However, in public institutions, prioritization faces conflicts with financial constraints. Problem: Increasing the complexity of requirements. Objective: Proposition of a Kanban method to improve the transparency of activities and facilitate prioritization. Method: An action research carried out in two cycles at the Attorney General's Office of the State of Pernambuco, involving the development team and public managers. Result: The presentation of the method's effectiveness as a mechanism facilitating transparency and as a support to management in prioritization.

An integrated FMEA approach using Best-Worst and MARCOS methods based on D numbers for prioritization of failures

Failure modes and effects analysis (FMEA) is a useful reliability analysis technique to identify potential failure modes in a wide range of industries. However, the conventional FMEA method is deficient in dealing with the risk evaluation and prioritization method. To overcome the shortcomings, this paper presents a new risk priority model using Best-Worst Method based on D numbers (D-BWM) and the Measurement of Alternatives and Ranking according to COmpromise Solution based on D numbers (D-MARCOS). First, D numbers are used to deal with the uncertainty of FMEA team members’ subjective judgment. Second, the distance-based method is proposed to determine the objective weight of each team member. Then, the D-BWM was used to determine the weight of risk factors. The combination rule of D number theory combined the evaluation information of multiple members into group opinions. Finally, D-MARCOS method is proposed to obtain the risk priority of the failure modes. An example and the results of comparative analysis show the method is effective.

Patients’ Prioritization on Surgical Waiting Lists: A Decision Support System

Currently, in Chile, more than a quarter-million of patients are waiting for an elective surgical intervention. This is a worldwide reality, and it occurs as the demand for healthcare is vastly superior to the clinical resources in public systems. Moreover, this phenomenon has worsened due to the COVID-19 sanitary crisis. In order to reduce the impact of this situation, patients in the waiting lists are ranked according to a priority. However, the existing prioritization strategies are not necessarily systematized, and they usually respond only to clinical criteria, excluding other dimensions such as the personal and social context of patients. In this paper, we present a decision-support system designed for the prioritization of surgical waiting lists based on biopsychosocial criteria. The proposed system features three methodological contributions; first, an ad-hoc medical record form that captures the biopsychosocial condition of the patients; second, a dynamic scoring scheme that recognizes that patients’ conditions evolve differently while waiting for the required elective surgery; and third, a methodology for prioritizing and selecting patients based on the corresponding dynamic scores and additional clinical criteria. The designed decision-support system was implemented in the otorhinolaryngology unit in the Hospital of Talca, Chile, in 2018. When compared to the previous prioritization methodology, the results obtained from the use of the system during 2018 and 2019 show that this new methodology outperforms the previous prioritization method quantitatively and qualitatively. As a matter of fact, the designed system allowed a decrease, from 2017 to 2019, in the average number of days in the waiting list from 462 to 282 days.