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Early characterization of an adult population at an insurer's point of entry as an opportunity to identify hospitalization risk

Vargas-Díaz, Lorena María; Pachón Arciniegas, Olga Patricia; Osorio Rojas, Santiago; Manrique-Hernández, Edgar Fabián; Bermon Angarita, Anderson.
Artículo en Inglés | LILACS, BDENF - Enfermería, COLNAL - Colombia-Nacional | ID: biblio-1553397

Introduction:

Health Benefit Plan Administrators must manage the health risk of their members. Therefore, health characterization is performed from enrollment to support decision-making and timely intervention.

Objective:

To analyze the historical results of characterizing the adult population on admission to the insurance company in relation to the demand for all-cause and psychiatric hospitalization services. Materials and

Methods:

An observational cross-sectional study with members over 18 years of age, in which an analysis was made of the characterization of the adult population of the insurer and its association with the use of medical consultation services in primary care and all-cause and psychiatric hospitalizations. Bivariate and multivariate analysis was made, and odds ratios (OR) were calculated in logistic regression.

Results:

Variables significantly associated with having an all-cause hospitalization were identified having referred history of heart disease OR=1.71(95%CI 1.33; 2.20), respiratory disease OR= 1. 30(95%CI 1.04; 1.61), chronic kidney disease OR=1.66(95%CI 1.13; 2.45), cancer OR=1.65(95%CI 1.14; 2.40), taking any medication permanently OR=1.35(95%CI 1.174; 1.56) and smoking OR=1.44(95%CI 1.12; 1.85). For psychiatric hospitalizations, a history of discouragement, depression, or little hope was relevant with OR=5.12(95%CI 1.89; 13.87).

Discussion:

The characterization of patients during enrolment allowed the identification of predictor variables of hospitalization, guiding management from the primary care level minimizing costs and catastrophic health events.

Conclusion:

The timely identification of specific patient profiles allows timely actions to minimize health costs and catastrophic health events.
Biblioteca responsable: CO646.1