A Sicras-Mainar1. 1. Dirección de Planificación, Badalona Servicios Asistenciales S.A. Badalona, Barcelona, España. asicras@bsa.gs
Abstract
OBJECTIVE: To evaluate retrospectively the application of adjusted clinical groups (ACGs) at a primary care centre. DESIGN: Descriptive, retrospective examination. SETTING: Urban. PARTICIPANTS: All patients seen by the team in 2000 were included in the study. Those who moved or died during the study period were excluded. MAIN MEASUREMENTS: Universal variables (age and sex), dependant variables (visits, episodes, and costs), and case-mix or comorbidity variables (ACGs 2.0) were measured. The model of cost per patient was established by distinguishing the costs of the PCC from the variables. The ICPC was converted to the ICD-9-CM and a multiple linear regression analysis was performed to predict the models. RESULTS: The total number of patients studied was 15 983, with an average of 5.0+/-3.2 episodes and 8.0+/-7.7 visits during the year. The power of explanation of the variability of the classification between the number of episodes was 71.9%; of the visits, 50.0% (with refinement, 56.3%); and cost, 30.2% (with refinement, 55.0%) (P=.000). CONCLUSIONS: ACGs were shown to be an acceptable system for classifying patients according to the consumption of resources used in primary care. In addition, the methodology used was adequate for integrating clinical and economic information at the PCC.
OBJECTIVE: To evaluate retrospectively the application of adjusted clinical groups (ACGs) at a primary care centre. DESIGN: Descriptive, retrospective examination. SETTING: Urban. PARTICIPANTS: All patients seen by the team in 2000 were included in the study. Those who moved or died during the study period were excluded. MAIN MEASUREMENTS: Universal variables (age and sex), dependant variables (visits, episodes, and costs), and case-mix or comorbidity variables (ACGs 2.0) were measured. The model of cost per patient was established by distinguishing the costs of the PCC from the variables. The ICPC was converted to the ICD-9-CM and a multiple linear regression analysis was performed to predict the models. RESULTS: The total number of patients studied was 15 983, with an average of 5.0+/-3.2 episodes and 8.0+/-7.7 visits during the year. The power of explanation of the variability of the classification between the number of episodes was 71.9%; of the visits, 50.0% (with refinement, 56.3%); and cost, 30.2% (with refinement, 55.0%) (P=.000). CONCLUSIONS: ACGs were shown to be an acceptable system for classifying patients according to the consumption of resources used in primary care. In addition, the methodology used was adequate for integrating clinical and economic information at the PCC.
Authors: Alba Aguado; Elisabet Guinó; Bhramar Mukherjee; Antoni Sicras; Josep Serrat; Mateo Acedo; Juan Jose Ferro; Victor Moreno Journal: BMC Health Serv Res Date: 2008-03-04 Impact factor: 2.655