[Influence of the unit of analysis on the studies of the factors of primary care resource utilization].
OBJECTIVE
To identify the characteristics of the patient that influence a different cost of his care, specifically, the different behaviour of these factors depending on the unit considered: encounter, episode or patient.


METHODS
Observational study with the voluntary participation of 13 physicians (9 general practitioners and 4 paediatricians) and nursing staff. During 7 months all diagnoses and interventions to a sample of attended patients were gathered. The cost of care was calculated and aggregated depending on the three units, and four models of multiple lineal regression were built with the following explanatory variables: age, gender, morbidity (ambulatory diagnosis groups), comorbidity and psychosocial conditions.


RESULTS
1,868 adult patients (more than 14 years) made 11.146 consults which belong to 4,772 episodes. The 895 paediatric patients made 6,254 consults that belonged to 3,416 episodes. Morbidity is the variable that shows a major increase in all units. Overall, the capacity to explain cost variations are: 0.03 for the encounter, 0.14 for the episode and 0.44 for the patient.


CONCLUSIONS
The patients variables considered in the study explain very little the resource utilization of the encounter, more the episode, and rather more the patient. Those results indicate that the assessment or comparison of the effectiveness, efficiency, or quality of the encounters will be very difficult considering only the commonly used variables to control the patient factors. The patient classification systems that group with a similar complexity that use the visits as the unit, should, consequently, consider additional variables of the process of care in contrast with the others units. This have implications in the collection and availability of the information.
Juncosa
S
S
Unitat d'Investigació Centre, Institut Català de la Salut, Terrassa, Barcelona, 08027, España.
Bolíbar
B
B
Roset
M
M
Martínez
C
C
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000553:Ambulatory Care / Q000191:economics / Q000706:statistics & numerical data; D002648:Child; D002675:Child, Preschool; D015897:Comorbidity; D003625:Data Collection / Q000379:methods; D003953:Diagnosis-Related Groups; D005194:Family Practice / Q000706:statistics & numerical data; D005260:Female; D017048:Health Care Costs / Q000706:statistics & numerical data*; D006295:Health Resources / Q000191:economics / Q000706:statistics & numerical data*; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D009017:Morbidity / Q000639:trends; D015999:Multivariate Analysis; D009819:Office Visits / Q000191:economics / Q000706:statistics & numerical data; D010361:Patients / Q000145:classification / Q000523:psychology; D010372:Pediatrics / Q000706:statistics & numerical data; D011320:Primary Health Care / Q000191:economics / Q000706:statistics & numerical data*; D012044:Regression Analysis; D012107:Research Design; D012959:Socioeconomic Factors; D013030:Spain / Q000453:epidemiology