Ambulatory Training Program to Expand Procedural Skills in Primary Care.

INTRODUCTION: Outpatient procedures are an important component of primary care, yet few programs incorporate procedural training into their curriculum. We examined a 4-year procedural curriculum to improve understanding of ambulatory procedures and increase the number of procedures performed. METHODS: A total of 56 resident and 8 faculty physicians participated in a procedural curriculum directed at joint injections (knee, shoulder, elbow, trochanteric bursa, carpal tunnel, wrist, and ankle), subdermal contraceptive insertion/removal, skin biopsies, and ultrasound use in primary care. We administered annual surveys and used generalized estimating equations to model changes. RESULTS: Across the 4 years, there was an average 96% response rate. Mean comfort level with the indications for procedures increased for both resident (62.5 to 78.8; P < .0001) and faculty physicians (61.5 to 94.8; P < .0001). Similarly, mean comfort with performing procedures increased for both resident (32.1 to 62.3; P < .0001) and faculty physicians (42.2 to 85.4; P < .0001). Residents' comfort level performing procedures increased for all individual procedures measured. The mean number of procedures performed per year increased for resident (1.9 to 8.2; P < .0001) and faculty physicians (14.7 to 25.2; P = .087). CONCLUSIONS: A longitudinal ambulatory-based procedural curriculum can increase resident and faculty physician understanding and comfort performing primary-care-based procedures. This, in turn, increased the total number of procedures performed.

Factors Associated With Resident Continuity in Ambulatory Training Practices.

BACKGROUND: Continuity of care is a critical element of residents' educational experience in primary care programs. OBJECTIVE: We examined how continuity in resident practices compares to nonteaching practices, identified factors associated with increased continuity, and explored the association between continuity and quality measures. METHODS: We analyzed 117 235 patient visits to 4 resident practices (26 resident teams in internal medicine, pediatrics, family medicine, and medicine-pediatrics) and 270 242 visits to nonteaching community practices between July 2013 and May 2014. We defined continuity from both clinician and patient perspectives, and used logistic regression models to examine the influence of factors on continuity while controlling for postgraduate year, patient age, gender, race, and insurance. RESULTS: Continuity was greater at nonteaching sites compared to resident practices (87.3% versus 56.2%, P < .001). Resident continuity ranged from 33.1% to 83.7% among resident sites. Factors associated with improved resident continuity included absence of advanced practice providers (71.5% versus 52.3%); consistent use of scheduling protocols (77.5% versus 33.1%); rescheduling policies (71.5% versus 41.3%); increased faculty clinical time (71.5% versus 46.3%); and dismissal policies for excessive missed appointments (71.5% versus 62.5%, P < .001 for all). Increased continuity was associated with improved rates of diabetic control (62.8% versus 54.6%); hypertension control (82.8% versus 57.5%); screening colonoscopy (69.2% versus 31.9%); and mammography (74.8% versus 38.2%, P < .001 for all). CONCLUSIONS: Increased clinical faculty time, scheduling protocols, and absence of advanced practice providers were most strongly associated with increasing continuity. Increased continuity was associated with improved quality measures.

Factors Associated with the Accurate Diagnosis of Obesity.

Obesity is a growing epidemic, yet few patients with obesity receive a clinical diagnosis of obesity or appropriate counseling. We examined the socioeconomic and demographic factors associated with the accurate diagnosis of obesity during ambulatory care visits. We used data from the National Hospital Ambulatory and National Ambulatory Medical Care Surveys (NHAMCS and NAMCS) to determine if a patient with obesity had been clinically diagnosed with obesity during the visit by either of the following: (1) a diagnosis listed in the patient's record; or (2) the provider's answer to the question "despite the diagnoses listed, does this patient have obesity?" We used multivariate models to examine the association between the accurate diagnosis of obesity and socioeconomic and demographic factors. We examined 885,291,770 weighted office visits involving individuals 5 years of age and older between 2006 and 2010. Providers were less likely to diagnose obesity at office visits involving children (5-12 years) with obesity (23.4 %) than at visits for adolescents (13-21 years; 39.7 %), young adults (22-34 years; 45.4 %), adults (35-64 years; 43.9 %) or elderly adults (≥65 years; 39.6 %; P < 0.001 for all). Individuals with obesity residing in more highly educated areas were more likely to be diagnosed than those living in less highly educated areas (44.2 vs. 40.9 %; AOR 1.4; 95 % CI 1.2-1.6). Males with obesity were less likely to be diagnosed than females with obesity (36.1 vs. 45.8 %; AOR 0.7; 95 % CI 0.6-0.8). After controlling for socioeconomic-status we did not find a consistent difference in the diagnosis of obesity by race. The diagnosis of obesity was made at less than half of all office visits involving patients with obesity. Children, adolescents, elderly, males, and those living in less educated areas were less likely to be accurately diagnosed with obesity.

Overweight children and adolescents: a risk group for iron deficiency.

BACKGROUND: The prevalence of obesity has increased at an epidemic rate, and obesity has become one of the most common health concerns in the United States. A few small studies have noted a possible association between iron deficiency and obesity. OBJECTIVE: To investigate the association between weight status, as measured by body mass index (BMI), and iron deficiency in a nationally representative sample of children and adolescents. DESIGN: National Health and Nutrition Examination Survey III (1988-1994) provides cross-sectional data on children 2 to 16 years of age. Recorded measures of iron status included transferrin saturation, free erythrocyte protoporphyrin levels, and serum ferritin levels. Children were considered iron-deficient if any 2 of these values were abnormal for age and gender. With the use of age- and gender-specific BMI percentiles, at risk for overweight was defined as a BMI of > or =85th percentile and <95th percentile, and overweight was defined as a BMI of > or =95th percentile. The prevalence of iron deficiency was compared across weight groups. Logistic regression was used to estimate the association between iron status and overweight, controlling for age, gender, ethnicity, poverty status, and parental education level. RESULTS: In this sample of 9698 children, 13.7% were at risk for overweight and 10.2% were overweight. Iron deficiency was most prevalent among 12- to 16-year-old subjects (4.7%), followed by 2- to 5-year-old subjects (2.3%) and then 6- to 11-year-old subjects (1.8%). Overweight 2- to 5-year-old subjects (6.2%) and overweight 12- to 16-year-old subjects (9.1%) demonstrated the highest prevalences of iron deficiency. Overall, the prevalence of iron deficiency increased as BMI increased from normal weight to at risk for overweight to overweight (2.1%, 5.3%, and 5.5%, respectively), and iron deficiency was particularly common among adolescents (3.5%, 7.2%, and 9.1%, respectively). In a multivariate regression analysis, children who were at risk for overweight and children who were overweight were approximately twice as likely to be iron-deficient (odds ratio: 2.0; 95% confidence interval: 1.2-3.5; and odds ratio: 2.3; 95% confidence interval: 1.4-3.9; respectively) as were those who were not overweight. CONCLUSIONS: In this national sample, overweight children demonstrated an increased prevalence of iron deficiency. Given the increasing numbers of overweight children and the known morbidities of iron deficiency, these findings suggest that guidelines for screening for iron deficiency may need to be modified to include children with elevated BMI.