Spatial evaluation of the quality of vital statistics at the departmental level: 'unssable codes' and local autocorrelation in Argentina (2017–2019)
Abstract
Accuracy in the certification of causes of death is fundamental for the design of public policies. However, the statistical classification of the Underlying Cause of Death using "unusable codes" —historically referred to in the literature as "garbage codes" (i.e., non-specific or ill-defined categories)— obscures the true epidemiological profile of subpopulations and perpetuates health inequalities. This article analyzes the quality of vital statistics on mortality in Argentina, aiming to determine whether diagnostic inefficiency stems from socio-geographic determinants (structural vulnerability) or from the state's institutional capacity (governance structure). Mortality records from a three-year period, provided by the Directorate of Health Statistics and Information (DEIS), were analyzed at the departmental level (N=511). The methodological strategy integrated a binomial Generalized Linear Mixed Model (GLMM), controlling for overdispersion through an Observation-Level Random Effect (OLRE), and an Exploratory Spatial Data Analysis (ESDA) using the Bivariate LISA statistic. Results demonstrate that precarious population health coverage at the departmental level places strain on the local health system and significantly increases the probability of miscoding (p < 0.001). Nevertheless, the variance explained by the provincial jurisdiction is more than double that explained by the departmental specificity. While the spatial analysis confirmed a macro-regional cluster of inefficiency in the central-northern part of the country, bivariate spatial autocorrelation revealed atypical cases of "institutional resilience" (e.g., Pirané, Formosa), where administrative micro-management achieves high diagnostic specificity in contexts of high vulnerability. We conclude that statistical invisibility essentially constitutes a deficit in provincial state capacity, which can be mitigated through targeted administrative interventions.
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Anexo
Declaración de disponibilidad de datos
Los datos de mortalidad fueron provistos por la Dirección de Estadísticas e Información de Salud (DEIS) del Ministerio de Salud de la Nación Argentina ante una solicitud. El listado exhaustivo de los códigos de la CIE-10 considerados como "códigos poco útiles" según nivel de importancia para la política pública, se encuentra alojado para su libre acceso y reproducibilidad en el repositorio Zenodo bajo el DOI: https://doi.org/10.5281/zenodo.18789861
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