Michael Grover

Identifying Patients at Risk for Obstructive Sleep Apnea in a Primary Care Practice

Purpose: The purpose of this study was to determine (1) whether our review of systems (ROS) form facilitates identification of sleep complaints; (2) how frequently department physicians investigate these sleep complaints; (3) the prevalence of our family practice patients at increased risk for obstructive sleep apnea (OSA); and (4) how well ROS responses function as diagnostic tests to identify OSA risk. Methods: We used a prospectively collected sample of consecutive adult patients undergoing preventive examinations at 2 family medicine clinics. Patients completed ROS forms and the Berlin Questionnaire to determine OSA risk level. Physicians at only one site used ROS forms during care. Results: Two hundred forty-nine of 382 eligible patients (65%) completed forms and underwent examinations. Thirty-seven percent responded positively to sleep-related ROS questions. Physicians documented 24% of those complaints. ROS form use affected documentation (31% with use vs 5% without; P = .03). Thirty-three percent of all patients had increased OSA risk. Fifty-seven percent of high-risk patients responded affirmatively to an ROS question as opposed to 27% for those at lower risk (P < .001). ROS responses were 57% sensitive and 73% specific for increased OSA risk. Conclusions: Sleep symptoms were common and were recognized significantly more often when our physicians used a ROS form. However, few complaints were investigated. Our current ROS sleep questions are not sufficiently sensitive to identify increased OSA risk. Physicians should prioritize evaluation of sleep dysfunction because of the association with OSA.

Urinary Tract Infection in Women Over the Age of 65: Is Age Alone a Marker of Complication?

Background: We were interested to know if our older female patients with urinary tract infections (UTIs) might have differing pathogens or rates of Escherichia coli antibiotic sensitivity and if our physicians managed them in a manner similar or dissimilar to the care provided to younger patients with no complications. Methods: This was a secondary analysis from patients excluded from a previous retrospective study regarding uncomplicated UTIs. Results: Twenty-six percent of total patients with UTIs were older than 65 and otherwise medically uncomplicated whereas 21% were older patients who did have complicating factors. E. coli was a pathogen in 81% of uncomplicated elders’ and 54% of complicated elders’ cultures. E. coli sensitivity rate to sulfamethoxazole-trimethoprim (SMX/TMP) in both groups was 86%. Physicians were significantly less likely to prescribe SMX/TMP for complicated older patients with complications than for young patients with an uncomplicated UTI (P = .017); there was a significant trend of physicians to be less likely to prescribe SMX/TMP with advancing age in a patient and complications across all 3 groups (P = .011). Antibiotics rarely needed to be changed after cultures. Conclusions: The presence of E. coli on culture in patients with a UTI changes based on medical complications, not age. Being medically complex did not result in reduced sensitivity of E. coli to SMX/TMP but was associated with increased rates of the presence of other pathogens. In our setting, treatment employed with SMX/TMP and without the use of culture and sensitivity may be effective for appropriately selected older women. Prospective studies are needed to determine the optimal approach to management.

Increased Osteoporosis Screening Rates Associated with the Provision of a Preventive Health Examination

Objectives: We determined the frequencies of (1) female patients aged 65 years and older having bone density measurement performed and (2) prescription therapy use among osteoporotic women. Methods: We completed a retrospective chart audit to assess our adherence to Physician Quality Reporting Initiative guidelines. Women aged 65 to 75 with an office visit between June 1 to November 30, 2007, were divided into 3 subgroups: those who had a recent preventive general medical examination (GME), those who received one in the last 10 years, and those who had not. We determined osteoporosis screening rates for all 3 groups. The first group then underwent electronic medical record review to obtain patient demographics, determine bone mineral density results, and review if those with osteoporosis were receiving prescription treatment. Results: Ninety-six percent of 305 female patients seen for a GME during the study period had completed bone mineral density testing. This was a screening rate significantly greater than that for patients with an earlier GME and those who never had one in our offices (70% and 50%, respectively). Seventy-seven percent of recent GME patients had abnormal T scores. Low weight and body mass index were significantly associated with osteoporotic T scores. Seventy-four percent of patients whose latest T scores were less than −2.5 were receiving prescription therapy. Conclusions: Female patients who completed a recent GME had extraordinarily high rates of screening for osteoporosis. We believe this demonstrates the importance of a dedicated preventive health examination as well as the increased significance that physicians and patients currently place on this behavior.

Family Medicine Panel Size with Care Teams: Impact on Quality

Purpose: The demand for comprehensive primary health care continues to expand. The development of team-based practice allows for improved capacity within a collective, collaborative environment. Our hypothesis was to determine the relationship between panel size and access, quality, patient satisfaction, and cost in a large family medicine group practice using a team-based care model. Methods: Data were retrospectively collected from 36 family physicians and included total panel size of patients, percentage of time spent on patient care, cost of care, access metrics, diabetic quality metrics, patient satisfaction surveys, and patient care complexity scores. We used linear regression analysis to assess the relationship between adjusted physician panel size, panel complexity, and outcomes. Results: The third available appointments (P < .01) and diabetic quality (P = .03) were negatively affected by increased panel size. Patient satisfaction, cost, and percentage fill rate were not affected by panel size. A physician-adjusted panel size larger than the current mean (2959 patients) was associated with a greater likelihood of poor-quality rankings (≤25th percentile) compared with those with a less than average panel size (odds ratio [OR], 7.61; 95% confidence interval [CI], 1.13–51.46). Increased panel size was associated with a longer time to the third available appointment (OR, 10.9; 95% CI, 1.36–87.26) compared with physicians with panel sizes smaller than the mean. Conclusions: We demonstrated a negative impact of larger panel size on diabetic quality results and available appointment access. Evaluation of a family medicine practice parameters while controlling for panel size and patient complexity may help determine the optimal panel size for a practice.