[Use of outpatient services in Pelotas, Rio Grande do Sul State, Brazil: factors related to above-average number of physician visits].
This cross-sectional, population-based study including males and females 20 to 69 years of age from the urban area of Pelotas, Rio Grande do Sul State, Brazil, aimed to verify characteristics associated with above-average number of medical consultations. The mean number of physician consultations in the previous year was 3.2, with a standard deviation of 5.5. The analysis considered two outcomes: individuals with more than eight physician visits per year (one SD above the mean) and more than 14 consultations (two SD above the mean). In the sample of 1,962 individuals, 183 (9.3%) reported more than eight physician consultations in the previous year. Logistic regression compared the outcomes with the following variables: sex, age, diabetes mellitus, hypertension, chronic bronchitis, minor psychiatric disorders, and hospitalization in the previous year. There were 57 individuals (2.9%) with more than 14 consultations during the year. Logistic regression showed significant differences for sex, hypertension, minor psychiatric disorders, and hospitalization in the previous year. The high demand does not always mean inadequate health services, and restricting the demand could result in policies that limit access to care, causing suffering to patients with serious conditions.
Dias-da-Costa
Juvenal Soares
JS
Faculdade de Medicina, Universidade Federal de Pelotas, Pelotas, Brasil. episoares@terra.com.br
Olinto
Maria Teresa Anselmo
MT
Gigante
Denise Petrucci
DP
Menezes
Ana Maria Baptista
AM
Macedo
Silvia
S
Daltoé
Tiago
T
Santos
Iná da Silva dos
Ida S
Fuchs
Sandra Costa
SC
D000328:Adult; D000368:Aged; D000553:Ambulatory Care / Q000191:economics / Q000706:statistics & numerical data*; D001938:Brazil; D002908:Chronic Disease; D003430:Cross-Sectional Studies; D005260:Female; D005102:Health Expenditures / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D008875:Middle Aged; D012044:Regression Analysis; D012959:Socioeconomic Factors; D014505:Urban Population