Banca de DEFESA: JOAO MARIA MACEDO DA COSTA

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : JOAO MARIA MACEDO DA COSTA
DATE: 27/11/2025
TIME: 14:00
LOCAL: Remoto - Google Meet
TITLE:

A multi-criteria decision support model for classifying types of healthcare service: an application in the care of patients with HIV

KEY WORDS:

Multi-Criteria Decision Making; FITradeoff; HIV; Care Classification; Public Health

PAGES: 110
BIG AREA: Engenharias
AREA: Engenharia de Produção
SUBÁREA: Pesquisa Operacional
SPECIALTY: Programação Linear, Não-Linear, Mista e Dinâmica
SUMMARY:

The management of healthcare for patients living with HIV presents complex challenges that encompass not only clinical aspects but also social, economic, and structural dimensions of the health system. In this context, multicriteria decision support emerges as a promising approach to classify and prioritize care, ensuring a more efficient allocation of available resources. This study proposes the development of a multicriteria analysis model, based on the FITradeoff method, to optimize the classification of care for HIV patients in a Specialized Care Service (SAE). The model considers clinical, social, economic, and operational criteria, enabling fairer decisions aligned with the specific needs of each patient. The methodology was grounded in the principles of Value-Focused Thinking (VFT), with problem structuring based on fundamental decision-making values, careful definition of evaluation criteria, development of archetypal patient profiles, and application of the FITradeoff method for weight elicitation and construction of a scoring system. The model resulted in a decision matrix capable of assigning priority levels to patients, organizing them into three distinct levels: high, medium, and low priority. The results showed that the combination of criteria such as detectable viral load, presence of comorbidities, advanced stage of infection, and poor treatment adherence significantly influenced care prioritization. The scoring system developed allows for the rapid classification of patients based on accessible clinical and social data, contributing to more agile decisions aligned with the principle of equity in Brazil’s Unified Health System (SUS). As a practical impact, the model is applicable to the routine of specialized services, assisting managers in resource allocation, appointment scheduling, and implementation of personalized protocols. Moreover, its use may enhance treatment adherence, reduce adverse outcomes, and promote health system savings by prioritizing preventive and more effective interventions. Finally, the study highlights the relevance of multicriteria methods as strategic tools for public policy formulation and management optimization in contexts marked by vulnerability and resource scarcity.

COMMITTEE MEMBERS:
Interno - 1086657 - JOELTON FONSECA BARBOSA
Interno - 4859773 - RICARDO PIRES DE SOUZA
Externo à Instituição - IRAMI ARAUJO FILHO - UnP
Externo à Instituição - RODRIGO JOSE PIRES FERREIRA - UFPE