BMI, Physical Activity, and Health Care Utilization/Costs among Medicare Retirees

Objective : To examine the influence of physical activity (PA) and BMI on health care utilization and costs among Medicare retirees. Research Methods and Procedures : This cross‐sectional study was based on 42, 520 Medicare retirees in a U.S.‐wide manufacturing corporation who participated in indemnity/perferred provider and one health risk appraisal during the years 2001 and 2002. Participants were assigned into one of the three weight groups: normal weight, overweight, and obese. PA behavior was classified into three levels: sedentary (0 time/wk), moderately active (1 to 3 times/wk), and very active (4+ times/wk). Results : Generalized linear models revealed that the moderately active retirees had $1456,$1731, and $1177 lower total health care charges than their sedentary counterparts in the normal‐weight, overweight, and obese groups, respectively ( p < 0.01). The very active retirees had$1823, $581, and$1379 lower costs than the moderately active retirees. Health care utilization and specific costs showed similar trends with PA levels for all BMI groups. The total health care charges were lower with higher PA level for all age groups ( p < 0.01). Discussion : Regular PA has strong dose‐response effects on both health care utilization and costs for overweight/obese as well as normal‐weight people. Promoting active lifestyle in this Medicare population, especially overweight and obese groups, could potentially improve their well‐being and save a substantial amount of health care expenditures. Because those Medicare retirees are hard to reach in general, more creative approaches should be launched to address their needs and interests as well as help reduce the usage of health care system.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/93683/1/oby.2005.175.pd

Glucose testing and insufficient follow-up of abnormal results: a cohort study

BACKGROUND: More than 6 million Americans have undiagnosed diabetes. Several national organizations endorse screening for diabetes by physicians, but actual practice is poorly understood. Our objectives were to measure the rate, the predictors and the results of glucose testing in primary care, including rates of follow-up for abnormal values. METHODS: We conducted a retrospective cohort study of 301 randomly selected patients with no known diabetes who received care at a large academic general internal medicine practice in New York City. Using medical records, we collected patients' baseline characteristics in 1999 and followed patients through the end of 2002 for all glucose tests ordered. We used multivariate logistic regression to measure associations between diabetes risk factors and the odds of glucose testing. RESULTS: Three-fourths of patients (78%) had at least 1 glucose test ordered. Patient age (≥45 vs. <45 years), non-white ethnicity, family history of diabetes and having more primary care visits were each independently associated with having at least 1 glucose test ordered (p < 0.05), whereas hypertension and hyperlipidemia were not. Fewer than half of abnormal glucose values were followed up by the patients' physicians. CONCLUSION: Although screening for diabetes appears to be common and informed by diabetes risk factors, abnormal values are frequently not followed up. Interventions are needed to trigger identification and further evaluation of abnormal glucose tests

Documentation of body mass index and control of associated risk factors in a large primary care network

<p>Abstract</p> <p>Background</p> <p>Body mass index (BMI) will be a reportable health measure in the United States (US) through implementation of Healthcare Effectiveness Data and Information Set (HEDIS) guidelines. We evaluated current documentation of BMI, and documentation and control of associated risk factors by BMI category, based on electronic health records from a 12-clinic primary care network.</p> <p>Methods</p> <p>We conducted a cross-sectional analysis of 79,947 active network patients greater than 18 years of age seen between 7/05 - 12/06. We defined BMI category as normal weight (NW, 18-24.9 kg/m²), overweight (OW, 25-29.9), and obese (OB, ≥ 30). We measured documentation (yes/no) and control (above/below) of the following three risk factors: blood pressure (BP) ≤130/≤85 mmHg, low-density lipoprotein (LDL) ≤130 mg/dL (3.367 mmol/L), and fasting glucose <100 mg/dL (5.55 mmol/L) or casual glucose <200 mg/dL (11.1 mmol/L).</p> <p>Results</p> <p>BMI was documented in 48,376 patients (61%, range 34-94%), distributed as 30% OB, 34% OW, and 36% NW. Documentation of all three risk factors was higher in obesity (OB = 58%, OW = 54%, NW = 41%, p for trend <0.0001), but control of all three was lower (OB = 44%, OW = 49%, NW = 62%, p = 0.0001). The presence of cardiovascular disease (CVD) or diabetes modified some associations with obesity, and OB patients with CVD or diabetes had low rates of control of all three risk factors (CVD: OB = 49%, OW = 50%, NW = 56%; diabetes: OB = 42%, OW = 47%, NW = 48%, p < 0.0001 for adiposity-CVD or diabetes interaction).</p> <p>Conclusions</p> <p>In a large primary care network BMI documentation has been incomplete and for patients with BMI measured, risk factor control has been poorer in obese patients compared with NW, even in those with obesity and CVD or diabetes. Better knowledge of BMI could provide an opportunity for improved quality in obesity care.</p

How and why community hospital clinicians document a positive screen for intimate partner violence: a cross-sectional study

BACKGROUND: This two-part study examines primary care clinicians' chart documentation and attitudes when confronted by a positive waiting room screen for intimate partner violence (IPV). METHODS: Patients at community hospital-affiliated health centers completed a screening questionnaire in waiting rooms that primary care providers (PCPs) were subsequently given at the time of the visit. We first reviewed the medical records of patients who screened positive for IPV, evaluating the presence and quality of documentation. Next we administered a survey to PCPs that measured their knowledge, attitudes and practice regarding IPV. RESULTS: Seventy-two percent of charts contained some documentation of IPV, however only 10% contained both a referral and safety plan. PCPs were more likely to refer patients (p < .05) who screened positively for mood or anxiety disorders, disclosed that they feared for their safety or were economically disadvantaged. Those that feared for their safety or endorsed mood or anxiety disorders were more likely to have notation of a safety plan in their records. When surveyed, 81.6% of clinicians strongly agreed that it is their role to inquire about IPV, but only 68% expressed confidence in their ability to manage it. In contrast, 93% expressed confidence in managing depression. Sixty-seven percent identified time constraints as a barrier to care. Predictors of PCP confidence in treating patients who have experienced IPV (p < .05) included hours of recent training and clinical experience with IPV. CONCLUSION: Mandatory waiting room screening for IPV does not result in high levels of referral or safety planning by PCPs. Despite the implementation of a screening process, clinicians lack confidence and time to address IPV in their patient populations suggesting that alternative methods of training and supporting PCPs need to be developed

Monitoring county-level chlamydia incidence in Texas, 2004 – 2005: application of empirical Bayesian smoothing and Exploratory Spatial Data Analysis (ESDA) methods

<p>Abstract</p> <p>Background</p> <p>Chlamydia continues to be the most prevalent disease in the United States. Effective spatial monitoring of chlamydia incidence is important for successful implementation of control and prevention programs. The objective of this study is to apply Bayesian smoothing and exploratory spatial data analysis (ESDA) methods to monitor Texas county-level chlamydia incidence rates by examining spatiotemporal patterns. We used county-level data on chlamydia incidence (for all ages, gender and races) from the National Electronic Telecommunications System for Surveillance (NETSS) for 2004 and 2005.</p> <p>Results</p> <p>Bayesian-smoothed chlamydia incidence rates were spatially dependent both in levels and in relative changes. Erath county had significantly (p < 0.05) higher smoothed rates (> 300 cases per 100,000 residents) than its contiguous neighbors (195 or less) in both years. Gaines county experienced the highest relative increase in smoothed rates (173% – 139 to 379). The relative change in smoothed chlamydia rates in Newton county was significantly (p < 0.05) higher than its contiguous neighbors.</p> <p>Conclusion</p> <p>Bayesian smoothing and ESDA methods can assist programs in using chlamydia surveillance data to identify outliers, as well as relevant changes in chlamydia incidence in specific geographic units. Secondly, it may also indirectly help in assessing existing differences and changes in chlamydia surveillance systems over time.</p

Screening Patients with a Family History of Colorectal Cancer

OBJECTIVES: To compare screening practices and beliefs in patients with and without a clinically important family history. DESIGN: We mailed a brief questionnaire asking about family history and a second, longer survey asking about knowledge of and beliefs about colorectal cancer to all respondents with a family history and a random sample of respondents without a family history of colorectal cancer. We reviewed electronic medical records for screening examinations and recording of family history. PARTICIPANTS: One thousand eight hundred seventy of 6,807 randomly selected patients ages 35–55 years who had been continuously enrolled in a large multispecialty group practice for at least 5 years. MEASUREMENTS: Recognition of increased risk, screening practices, and beliefs—all according to strength of family history and patient’s age. RESULTS: Nineteen percent of respondents reported a family history of colorectal cancer. In 11%, this history was strong enough to warrant screening before age 50 years. However, only 39% (95% CI 36, 42) of respondents under the age of 50 years said they had been asked about family history and only 45% of those with a strong family history of colorectal cancer had been screened appropriately. Forty-six percent of patients with a strong family history did not know that they should be screened at a younger age than average risk people. Medical records mentioned family history of colorectal cancer in 59% of patients reporting a family history. CONCLUSIONS: More efforts are needed to translate information about family history of colorectal cancer into the care of patients

Time to definitive diagnosis of breast cancer in Latina and non-Hispanic white women: the six cities study

Time delay after an abnormal screening mammogram may have a critical impact on tumor size, stage at diagnosis, treatment, prognosis, and survival of subsequent breast cancer. This study was undertaken to evaluate disparities between Latina and non-Hispanic white (NHW) women in time to definitive diagnosis of breast cancer after an abnormal screening mammogram, as well as factors contributing to such disparities. As part of the activities of the National Cancer Institute (NCI)-funded Redes En Acción research network, clinical records of 186 Latinas and 74 NHWs who received abnormal screening mammogram results were reviewed to determine the time to obtain a definitive diagnosis. Data was obtained from participating clinics in six U.S. cities and included demographics, clinical history, and mammogram characteristics. Kaplan-Meier estimates and Cox proportional hazards models were used to test differences in median time to definitive diagnosis by ethnicity after adjusting for clinic site, demographics, and clinical characteristics. Time-to-event analysis showed that Latinas took 2.2 times longer to reach 50% definitively diagnosed with breast cancer relative to NHWs, and three times longer to reach 80% diagnosed (p=0.001). Latinas’ median time to definitive diagnosis was 60 days compared to 27 for NHWs, a 59% gap in diagnosis rates (adjusted Hazard Ratio [aHR] = 1.59, 95% CI = 1.09, 2.31; p=0.015). BI-RADS-4/5 women’s diagnosis rate was more than twice that of BI-RADS-3 (aHR = 2.11, 95% CI = 1.18, 3.78; p=0.011). Disparities in time between receipt of abnormal screening result and definitive diagnosis adversely affect Latinas compared to NHWs, and remain significant after adjusting for demographic and clinical variables. With cancer now the leading cause of mortality among Latinos, a greater need exists for ethnically and culturally appropriate interventions like patient navigation to facilitate Latinas’ successful entry into, and progression through, the cancer care system