Science and Technology Production

EPIO - CONSTRUCCIÓN DE UN ÍNDICE MULTIDIMENSIONAL PARA MEDIR EL ACCESO A LOS BIENES Y SERVICIOS DE SALUD DE LAS PERSONAS MAYORES EN UNA LOCALIDAD DE LA PROVINCIA DE BUENOS AIRES

Congress

Authorship:

Gonzalez Gisela Paula ; Geri Milva ; Moscoso Nebel Silvana ; Lago fernando

Date:

2023

Publishing House and Editing Place:

Universidad Nacional de La Pampa

ISSN:

978-987-47251-4-1

Summary *

The purpose of this paper is to build multidimensional indices of access to health goods and services for those over 60 years of age in the city of Bahía Blanca (Buenos Aires Province, Argentina) incorporating all dimensions of this phenomenon. The data comes from a survey carried out between December 2021 and March 2022 on a sample of 200 older adults from the Bahía Blanca district affiliated with an insurer. For the processing of the indices, the Categorical Principal Component Analysis (CATPCA)technique was used, whose main advantage has to do with the fact that it allows dealing with variables of a different nature. Likewise, it does not require assuming that the relationship between the variables analyzed is necessarily linear. Taking into consideration the theoretical framework of reference, 21 variables were selected from the database to reflect the different dimensions of the phenomenon. They were treated according to their nature (nominal categorical and ordinal categorical). Four main components were analyzed based on the consideration of the eigenvalues and percentage of explained variance, each of which was then interpreted as a multidimensional index. Those variables whose sum of assumed factor loads in each squared component (VAF) was less than 0.25 were sequentially eliminated (16 variables were finally selected). Once it was verified that the VAF of all the variables was equal to or higher than 0.25, it was determined in which principal component each of them presented the highest factorial load. Then, each of the four multidimensional indices was interpreted. For each main component, the categories of the variables that presented the highest relative weight with respect to the other components were eliminated from the analysis. Immediately after, the assumed scores were multiplied by the transformed value that each category assumes by the factorial load of the variable to which they correspond in the component under study. All the categories that scored the highest in each case were analyzed, determining whether they are indices of obstacles or facilitators of access to health goods and services. This is the text. Two indices of facilitators and two of barriers to healthcare access were formulated, of which only two (one of each type) were validated. The validated facilitator index involves aspects related to the dimensions of accessibility (in its three subdimensions) and adequacy. It is negatively correlated with the presence of obstacles to access. The other validated index refers to barriers to healthcare access and is linked to the stages of seeking and using health care. Likewise, it is related to the dimensions of adaptation and accessibility (both administrative, organizational and economic). This index is positively correlated with the presence of barriers to access. Keywords: STATISTICS - MULTIDIMENSIONAL INDEX - ACCESS TO HEALTH SERVICES - OLDER ADULTS.Estadística 64REFERENCIAS ADAY, L. A., & ANDERSEN, R. (1974): ?A framework for the study of access to medical care?. Health services research, 9(3), 208. CHANDRA, R (2016): ?Cities and the questions of health equity: A study of multidimensional healthcare access in India?. In European Journal of Public Health (Vol 26, pp 371-371). GRECO, S., ISHIZAKA, A., TASIOU, M., & TORRISI, G. (2019): ?On the methodological framework of composite indices: A review of the issues of weighting, aggregation, and robustness?. Social indicators research, 141(1), 61-94. LINTING, M., & VAN DER KOOIJ, A. (2012): ?Nonlinear principal components analysis with CATPCA: a tutorial?. Journal of personality assessment, 94(1), 12-25. SAUKANI, N., & ISMAIL, N. A. (2019): ?Identifying the components of social capital by categorical principal component analysis (CATPCA)?. Social Indicators Research, 141(2), 631-655. Information provided by the agent in SIGEVA