OBJECTIVES: To study and analyse the Out-Patient Care Groups (OCGs), and evaluate how they affect use of health resources. DESIGN: An observational, retrospective study. SETTING: Ciudad Jardín Health Centre, Málaga. PARTICIPANTS: 2999 patients with a clinical history opened before 31.12.95, chosen from 5 of the 17 medical lists at the Health Centre, were included. RESULTS: The statistical analysis was performed with the SPSS software package of the Calculation Centre at Málaga University. A descriptive test produced the following results: 33% of the patients were classified in OCG 41 (combination of 2 or 3 out-patient diagnosis groups in people over 34); 19% belonged to groups of stable or unstable chronic illnesses (OCGs 8, 9 and 10); and 9% had acute children's diseases. Then multiple regression constructed a model with the OCGs as independent variable and annual visits, further tests performed and referral to specialists as dependent variables. In this model the OCGs were able to explain 20.3% of resource consumption. CONCLUSIONS: In the retrospective study and with a limited sample of 2999 patients, the OCGs are able to explain 20.3% of resource consumption. However, it does seem a valid model for discriminating between normal and over-using patients.
OBJECTIVES: To study and analyse the Out-Patient Care Groups (OCGs), and evaluate how they affect use of health resources. DESIGN: An observational, retrospective study. SETTING: Ciudad Jardín Health Centre, Málaga. PARTICIPANTS: 2999 patients with a clinical history opened before 31.12.95, chosen from 5 of the 17 medical lists at the Health Centre, were included. RESULTS: The statistical analysis was performed with the SPSS software package of the Calculation Centre at Málaga University. A descriptive test produced the following results: 33% of the patients were classified in OCG 41 (combination of 2 or 3 out-patient diagnosis groups in people over 34); 19% belonged to groups of stable or unstable chronic illnesses (OCGs 8, 9 and 10); and 9% had acute children's diseases. Then multiple regression constructed a model with the OCGs as independent variable and annual visits, further tests performed and referral to specialists as dependent variables. In this model the OCGs were able to explain 20.3% of resource consumption. CONCLUSIONS: In the retrospective study and with a limited sample of 2999 patients, the OCGs are able to explain 20.3% of resource consumption. However, it does seem a valid model for discriminating between normal and over-using patients.
Authors: F A Alonso López; C J Cristos; A Brugos Larumbe; F García Molina; L Sánchez Perruca; A Guijarro Eguskizaga; A Ruiz Téllez; M Medina Peralta; F A Alonso López Journal: Aten Primaria Date: 2000-11-15 Impact factor: 1.137