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The Linear Programming to evaluate the performance of Oral Health in Primary Care

OBJECTIVE: To show the use of Linear Programming to evaluate the performance of Oral Health in Primary Care. METHODS: This study used data from 19 municipalities of Santa Catarina city that participated of the state evaluation in 2009 and have more than 50,000 habitants. A total of 40 indicators wer...

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Detalles Bibliográficos
Autores principales: Colussi, Claudia Flemming, Calvo, Maria Cristina Marino, de Freitas, Sergio Fernando Torres
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Instituto Israelita de Ensino e Pesquisa Albert Einstein 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4872975/
https://www.ncbi.nlm.nih.gov/pubmed/23579751
http://dx.doi.org/10.1590/S1679-45082013000100017
Descripción
Sumario:OBJECTIVE: To show the use of Linear Programming to evaluate the performance of Oral Health in Primary Care. METHODS: This study used data from 19 municipalities of Santa Catarina city that participated of the state evaluation in 2009 and have more than 50,000 habitants. A total of 40 indicators were evaluated, calculated using the Microsoft Excel 2007, and converted to the interval [0, 1] in ascending order (one indicating the best situation and zero indicating the worst situation). Applying the Linear Programming technique municipalities were assessed and compared among them according to performance curve named “quality estimated frontier”. Municipalities included in the frontier were classified as excellent. Indicators were gathered, and became synthetic indicators. RESULTS: The majority of municipalities not included in the quality frontier (values different of 1.0) had lower values than 0.5, indicating poor performance. The model applied to the municipalities of Santa Catarina city assessed municipal management and local priorities rather than the goals imposed by pre-defined parameters. In the final analysis three municipalities were included in the “perceived quality frontier”. CONCLUSION: The Linear Programming technique allowed to identify gaps that must be addressed by city managers to enhance actions taken. It also enabled to observe each municipal performance and compare results among similar municipalities.