[Automated geospatial model for health services strategic planning]

Area of Science:

• Health Services Research
• Geospatial Analysis
• Public Health Planning

Background:

• Mexico's new healthcare model requires efficient operational regionalization for planning health service networks.
• Existing manual regionalization methods may not be optimal for healthcare access.

Purpose of the Study:

• To develop an automated geospatial model for operational regionalization.
• To improve the planning of health service networks under Mexico's Modelo Integrador de Servicios de Salud (MIDAS).

Main Methods:

• A geospatial model was developed using 2005 and 2007 data for Mexico.
• The model estimated potential catchment areas based on travel time to health facilities.
• Results were compared against a manually derived operational regionalization (ERO) study in Oaxaca.

Main Results:

• The geospatial model demonstrated greater efficiency compared to the ERO study.
• The ERO model assigned 48% of villages to more distant health centers.
• 23% of health centers in the ERO study referred patients to more distant hospitals.

Conclusions:

• The automated geospatial model provides a more efficient regionalization than the ERO model.
• The model minimizes travel time for accessing health services.
• The Mexican Ministry of Health adopted this model for the Health Sector Infrastructure Master Plan.