Rocha Thiago Augusto Hernandes, de Almeida Dante Grapiuna, do Amaral Pedro Vasconcelos Maia, da Silva Núbia Cristina, Thomaz Erika Bárbara Abreu Fonseca, Queiroz Rejane Christine de Sousa, Barbosa Allan Claudius Queiroz, Vissoci João Ricardo Nickenig
Organização Pan-Americana da Saúde (OPAS) Organização Pan-Americana da Saúde (OPAS) Brasília(DF) Brasil Organização Pan-Americana da Saúde (OPAS), Brasília (DF), Brasil.
Medomai Informática Medomai Informática Belo Horizonte(MG) Brasil Medomai Informática, Belo Horizonte (MG), Brasil.
Rev Panam Salud Publica. 2019 May 24;43:e47. doi: 10.26633/RPSP.2019.47. eCollection 2019.
To present a methodology for the empirical evaluation of primary health care (PHC) through the construction of digital representations of potential PHC coverage areas.
In this methodological study, potential areas were constructed by combinatorial analysis between census tracts and the location of basic health units with working PHC teams in Brazil. Six rules were used to parameterize the algorithm for the construction of potential areas. Thus, six restrictions were applied to enable the model: the selection of census tracts near the basic health unit; contiguous sectors; mutually exclusive sectors; sectors located in the same municipality of basic health units; sum of 4 500 users per health team in each unit; and volume of population ascribed proportional to the number of PHC teams allocated to the unit. Based on 316 594 census tracts and 39 758 basic health units, a neighborhood matrix was developed. To that matrix, a graph algorithm was applied to test combinations of sectors that simultaneously met the stipulated rules.
A total of 1 901 114 arcs were defined, connecting 30 351 census tracts, allowing the construction of 26 907 potential areas. Based on these results, intra-municipal analyses can be performed to monitor PHC indicators. Customizable algorithm parameters can be adjusted to accommodate different sets of rules which may be adapted to different countries.
The use of geoprocessing approaches creates conditions for the assessment of PHC impact, based on secondary databases at various levels, such as intra-municipal, basic health unit, and even at the team level.
通过构建初级卫生保健(PHC)潜在覆盖区域的数字表示,提出一种对初级卫生保健进行实证评估的方法。
在这项方法学研究中,通过对巴西人口普查区与配备有初级卫生保健工作团队的基层卫生单位的位置进行组合分析,构建潜在区域。使用六条规则对潜在区域构建算法进行参数化。因此,应用了六项限制条件以使模型生效:选择靠近基层卫生单位的人口普查区;相邻区域;相互排斥的区域;位于与基层卫生单位同一市的区域;每个单位每个卫生团队有4500名用户的总和;以及分配给该单位的初级卫生保健团队数量成比例的人口数量。基于316594个人口普查区和39758个基层卫生单位,开发了一个邻域矩阵。对该矩阵应用图算法来测试同时满足规定规则的区域组合。
总共定义了1901114条弧,连接了30351个人口普查区,从而构建了26907个潜在区域。基于这些结果,可以进行市内分析以监测初级卫生保健指标。可定制的算法参数可以进行调整,以适应不同的规则集,这些规则集可能适用于不同的国家。
地理处理方法的使用为基于市级、基层卫生单位甚至团队层面等各级二级数据库评估初级卫生保健影响创造了条件。