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Med Care ; 37(8): 738-47, 1999 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-10448717

RESUMO

OBJECTIVE: This study assesses the effects of competing demands, such as poor health habits or new medical problems, on health-habit counseling during a primary care visit. METHODS: We surveyed a consecutive sample of 1,259 patients visiting primary care clinicians at an academic VA medical center. Before the visit, patients reported their health status, health habits, and sociodemographics; immediately after the visit, patients reported reasons for the visit and whether they had been counseled about specific health habits. We scored visit acuity ranging from visits for unscheduled walk-in care or new medical problems to scheduled visits for check-ups or old problems. We defined counseling "triggers" as clinical indications for counseling about particular health habits (e.g., smoking). We developed a logistic model predicting primary care provider counseling during a visit. RESULTS: Over two-thirds of patients (68.9%) received some health habit counseling. Controlling for other independent variables, patients with more triggers were more likely to report being counseled. Counseling rates went up as visit acuity went down; patients with the lowest visit acuity having 67% greater odds of being counseled than patients with the highest visit acuity. CONCLUSIONS: Physicians set priorities for health-habit counseling during a visit based on patients' health habit problems or triggers; whether the visit is scheduled or walk-in; and whether the patient has new or acute problems. Future research about primary care performance of health habit counseling should account for these patient and visit characteristics, and prevention-oriented health care organizations should ensure access to scheduled "check-up" visits.


Assuntos
Aconselhamento/estatística & dados numéricos , Hábitos , Comportamentos Relacionados com a Saúde , Necessidades e Demandas de Serviços de Saúde/estatística & dados numéricos , Atenção Primária à Saúde/estatística & dados numéricos , Idoso , California , Estudos de Coortes , Humanos , Funções Verossimilhança , Modelos Logísticos , Estudos Longitudinais , Masculino , Pessoa de Meia-Idade , Razão de Chances , Inquéritos e Questionários , Estados Unidos , United States Department of Veterans Affairs
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