Extension of a POMDM model for cervical cancer screening policies in Colombia
In Colombia, Cervical cancer is the second most common cancer and the first cancer cause of death in women. Nowadays, there are different known screening tests that can be performed in order to prevent this disease. Even though Colombia's government tries to increase health coverage, low-income...
- Autores:
-
Arboleda Alaguna, Juan David
- Tipo de recurso:
- Fecha de publicación:
- 2016
- Institución:
- Universidad de los Andes
- Repositorio:
- Séneca: repositorio Uniandes
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.uniandes.edu.co:1992/13492
- Acceso en línea:
- http://hdl.handle.net/1992/13492
- Palabra clave:
- Neoplasmas del cuello uterino - Investigaciones - Colombia - Estudio de casos
Investigación operacional - Investigaciones
Procesos de Markov - Investigaciones
Cáncer - Diagnóstico - Toma de decisiones - Investigaciones
Ingeniería
- Rights
- openAccess
- License
- https://repositorio.uniandes.edu.co/static/pdf/aceptacion_uso_es.pdf
| Summary: | In Colombia, Cervical cancer is the second most common cancer and the first cancer cause of death in women. Nowadays, there are different known screening tests that can be performed in order to prevent this disease. Even though Colombia's government tries to increase health coverage, low-income communities and people from rural areas are not having access to these tests easily. Therefore, women from some communities are not following Colombian screening policies as they should. This problem was addressed by Namen et al. in 2014 and they formulated a POMDP model that incorporates different elements of the detection process. However, this model presents some limitations for implementing it according Colombian context. Our main goal is to solve those limitations and extend the model, so it can be evaluated and compared with Colombian current guidelines. We addressed the problems, one by one, and developed a set of tools that helped to improve the evaluation of any policy for cervical cancer. We changed the graphic representation of the solution for a decision tree that allows doctors and patients to see future possible actions and make better decisions. By including co-testing as a possible action, we made the model comparable with current policies. Using Monte Carlo simulation, we generated many random patients and random paths for those patients, so different cervical cancer screening policies could be analyzed and compared with some statistical support. Our new model screening strategies show an improvement regarding costs and total expected quality-adjusted life years (QALYs), compared with existing guidelines |
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