Obesity and medical visits in family medicine - A retrospective analysis of medical records

Background: Controlling the number of medical visits consumed by primary care patients is essential to cost containment; therefore, identification of patients likely to be frequent users of medical visits is required. Obesity has not often been used as a marker for selecting patients for disease management efforts. Methods: This study was a retrospective analysis of information abstracted from the medical records of 1405 adult patients who were treated in family medicine practices in Rochester, Minnesota, USA, and referred to specialists. Patients were sorted into two groups - frequent visitors and others - with patients in the highest quartile of use being classified as frequent visitors. Multiple logistic regression analysis was used to test the relationship between body mass index (BMI) and frequency of visits, after adjustment for co-morbidities and demographic characteristics. Results: Multiple logistic regression analysis revealed that, in comparison with patients with a BMI of 0-24.9 kg/m(2), patients with a BMI >= 35 kg/m(2) had greater odds of being frequent visitors, after adjusting for co-morbidity, age, marital status, and gender (adjusted odds ratio [AOR] = 1.51; 95% CI 1.01, 2.26; p = 0.04). AORs for being a frequent visitor were also significantly greater for subjects with Charlson co-morbidity scores of 1 (AOR = 2.10; 95% CI 1.50, 2.95; p < 0.01) and >= 2 (AOR = 4.45; 95% CI 3.17, 6.25; p < 0.01) than for those with no co-morbid diseases and were lower for married patients than those who were unmarried (AOR = 0.71; 95% CI 0.52, 0.96; p = 0.03). The BMI categories of 25-29.9 kg/m(2) and 30-34.9 kg/m(2) were not independently related to the frequency of medical visits. Conclusions: In our sample of patients who attended family medicine practices and were referred to specialists, having a BMI >= 35 kg/m(2) was an independent risk factor for frequent utilization of medical visits. Referral to weight management programs might be an effective utilization management strategy.