Abstract
OBJECTIVE: To analyse a prediction model for admissions and hospital emergencies based on Clinical Risk Groups, in a population of complex chronic patients demanding primary care. DESIGN: A multicentric retrospective observational study, of a cohort of chronic patients with comorbidity, from January until December 2013. PLACE: The study population was assigned to the Santa Pola and Raval health centres from the Health Department of Elche. PARTICIPANTS: Cohort of chronic patients with comorbidity, from January to December 2013. INTERVENTIONS: Data about the number of admissions, reasons and complexity level associated with the admission were collected by the review of medical records. MAIN MEASURES: To determine the level of complexity, the classification included in the chronicity strategy of the Valencian Community based on Clinical Risk Groups was used. RESULTS: Five hundred and four patients were recruited with a high complexity degree (N3) and 272 with moderate/low complexity (N1-N2). A higher comorbidity was observed in N3 patients with high complexity [Charlson 2.9 (DE 1.8) vs. 1.9 (DE 1.3); P<.001], and higher dependence degree for basic diary activities [Barthel 16.1 (n=81) vs. 7.3 (n=20); P<.001]. Association between the number of admissions [0.4 (DE 0.8) vs. 0.1 (DE 0.5); P<.001] and emergency visits [0.8 (DE 1.5) vs. 0.3 (DE 0.8), P<.001] was significatively higher in patients from N3 group than N1-N2 groups. CONCLUSIONS: The predictive capacity of CRG grouper showed high sensibility for the patient classification with a high degree of complexity. Its specificity and positive predictive value were lower for the association of the N3 complexity stratum.