Purpose: This article uses an interactional analysis instrument to characterize patient-centered care in the primary care setting and to examine its relationship with health care utilization.Methods: Five hundred nine new adult patients were randomized to care by family physicians and general internists. An adaption of the Davis Observation Code was used to measure a patient-centered practice style. The main outcome measures were their use of medical services and related charges monitored over 1 year.Results: Controlling for patient sex, age, education, income, self-reported health status, and health risk behaviors (obesity, alcohol abuse, and smoking), a higher average amount of patient-centered care recorded in visits throughout the 1-year study period was related to a significantly decreased annual number of visits for specialty care (P ‫؍‬ .0209), less frequent hospitalizations (P ‫؍‬ .0033), and fewer laboratory and diagnostic tests (P ‫؍‬ .0027). Total medical charges for the 1-year study were also significantly reduced (P ‫؍‬ .0002), as were charges for specialty care clinic visits (P ‫؍‬ .0005), for all patients who had a greater average amount of patient-centered visits during that same time period. For female patients, the regression equation predicted 15.47% of the variation in total annual medical charges compared with male patients, for whom 31.18% of the variation was explained by the average percent of patient-centered care, controlling for sociodemographic variables, health status, and health risk behaviors.Conclusions

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In a nationally representative sample, higher patient satisfaction was associated with less emergency department use but with greater inpatient use, higher overall health care and prescription drug expenditures, and increased mortality.

Female physicians were more likely to deliver female prevention procedures, but few other physician gender differences in primary care were observed. Physician-patient gender concordance was a key determinant of encounters.

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Objective: This study investigated differences in the use of health care services and associated costs between obese and nonobese patients. Research Methods and Procedures: New adult patients (N ϭ 509) were randomly assigned to primary care physicians at a university medical center. Their use of medical services and related charges was monitored for 1 year. Data collected included sociodemographics, self-reported health status using the Medical Outcomes Study Short Form-36, evaluation for depression using the Beck Depression Index, and measured height and weight to calculate BMI.

Our purpose was to explore why women are more likely than men to be diagnosed as depressed by their primary care physician. Women were found to have more depressive symptoms as self-reported on the Beck Depression Inventory (BDI). Women having high BDI scores (reflecting significant depression) were more likely than men with high BDI scores to be diagnosed by their primary care physician (p = 0.0295). Female patients made significantly more visits to the clinic than men. For both sexes, patients with greater numbers of primary care clinic visits were more likely to be diagnosed as depressed. Logistic regression revealed that gender has both a direct and indirect (through increased use) effect on the likelihood of being diagnosed as depressed. Patient BDI score, clinic use, educational level, and marital status were all significantly related to the diagnosis of depression. Controlling all other independent variables, women were 72% more likely than men to be identified as depressed, but this effect did not achieve statistical significance (p = 0.0981). In gender-specific analyses, BDI and clinic use were again significantly related to the diagnosis of depression for both sexes. However, educational and marital status predicted depression diagnosis only for women. Separated, divorced, or widowed women were almost five times as likely to be diagnosed as depressed as those who were never married, all other factors being equal. Clinic use and BDI scores were found to be important correlates of the diagnosis of depression. There was some evidence of possible gender bias in the diagnosis of depression.

Results: Regression equations were estimated relating obesity to visit length, each of the 20 individual DOC codes, and the six DOC Physician Practice Behavior Clusters, controlling for patient health status and sociodemographics. Obesity was not significantly associated with the length of the visit, but influenced what happened during the visit. Physicians spent less time educating obese patients about their health (p ϭ 0.0062) and more time discussing exercise (p ϭ 0.0075). Obesity was not related to discussions regarding nutrition. Physicians spent a greater portion of the visit on technical tasks when the patient was obese (p ϭ 0.0528). Mean pre-visit general satisfaction for obese patients was significantly lower than for non-obese patients (p ϭ 0.0069); however, there was no difference in post-visit patient satisfaction. Discussion: Patient obesity impacts the medical visit. Further research can promote a greater understanding of the relationships between obese patients and their physicians.