A Survey of Obesity Education and Training in United States Pharmacy Schools.

OBJECTIVE: To assess how obesity is addressed in Doctor of Pharmacy (PharmD) schools and colleges, identify the extent to which core obesity competencies are covered in the curricula, and identify opportunities for expanding obesity management training. METHODS: An online survey was conducted with PharmD program leaders in the United States. Respondents answered questions regarding obesity education in their pharmacy school curricula. Data were analyzed in aggregate, using descriptive statistics. RESULTS: We collected responses from 75 of 150 (50%) PharmD programs. One-third (32%) of respondents thought their graduating students were very prepared to discuss obesity pharmacotherapy (anti-obesity medication) options with patients. A total of 45% reported obesity pharmacological treatment was covered to a great extent. Few respondents (19%) were very familiar with anti-obesity medications; 21% thought their students were similarly familiar. No programs covered weight stigma and discrimination to a great extent. Most respondents (88%) believed obesity education was fairly/very important to include in PharmD curricula, and 96% thought it was similarly appropriate to include. But 72% indicated that expanding obesity education was not a priority/low priority. Lack of room in the curricula was cited as the greatest barrier, with 60% of PharmD programs reporting this to be a large barrier. CONCLUSION: Pharmacists, as medication experts, are key members of the care team. However, obesity management/pharmacotherapy is not emphasized in most pharmacy schools. Therefore, pharmacists are not well-prepared to provide counseling on medications for obesity. Leveraging guidance on core obesity competencies and available resources could help expand obesity education in pharmacy schools.

Clinical and Cost Benefits of Anti-Obesity Medication for US Veterans Participating in the MOVE! Weight Management Program.

Abstract This study investigated the clinical and economic impact of anti-obesity medications (AOMs; orlistat, liraglutide, phentermine/topiramate extended-release [ER], naltrexone ER/bupropion ER) among United States Veterans with obesity participating in Motivating Overweight/Obese Veterans Everywhere! (MOVE!), a government-initiated weight management program. The study population was identified from electronic medical records of the Veterans Health Administration (2010-2020). Clinical indices of obesity and health care resource utilization and costs were evaluated at 6, 12, and 24 months after the initial dispensing of an AOM in the AOM+MOVE! cohort (N = 3732, mean age 57 years, 79% male) or on the corresponding date of an inpatient or outpatient encounter in the MOVE! cohort (N = 7883, mean age 58 years, 81% male). At 6 months postindex, the AOM+MOVE! cohort had better cardiometabolic indices (eg, systolic blood pressure, diastolic blood pressure, total cholesterol, low-density lipoprotein cholesterol, hemoglobin A1c) than the MOVE! cohort, with the trends persisting at 12 and 24 months. The AOM+MOVE! cohort was significantly more likely than the MOVE! cohort to have weight decreases of 5%-10%, 10%-15%, and >15% and lower body mass index at 6, 12, and 24 months. The AOM+MOVE! cohort also had fewer inpatient and emergency department visits than the MOVE! cohort, which was associated with lower mean total medical costs including inpatient costs. These results suggest that combining AOM treatment with the MOVE! program could yield long-term cost savings for the Veterans Affairs network and meaningful clinical improvements for Veterans with obesity.

Impact of Sustained Weight Loss on Cardiometabolic Outcomes.

Obesity increases the risk of developing type 2 diabetes, hypertension, and hyperlipidemia. We sought to determine the impact of obesity maintenance, weight regain, weight loss maintenance, and magnitudes of weight loss on future risk and time to developing these cardiometabolic conditions. This was a retrospective cohort study of adults receiving primary care at Geisinger Health System between 2001 and 2017. Using electronic health records, patients with ≥3-weight measurements over a 2-year index period were identified and categorized. Obesity maintainers (OM) had obesity (body mass index ≥30 kg/m²) and maintained their weight within ±3% from baseline (reference group). Both weight loss rebounders (WLR) and weight loss maintainers (WLM) had obesity at baseline and lost >5% body weight in year 1; WLR regained ≥20% of weight loss by end of year 2 and WLM maintained ≥80% of weight loss. Incident type 2 diabetes, hypertension, and hyperlipidemia, and time-to-outcome were determined for each study group and by weight loss category for WLM. Of the 63,567 patients included, 67% were OM, 19% were WLR, and 14% were WLM. The mean duration of follow-up was 6.6 years (SD, 3.9). Time until the development of electronic health record-documented type 2 diabetes, hypertension, and hyperlipidemia was longest for WLM and shortest for OM (log-rank test p <0.0001). WLM had the lowest incident type 2 diabetes (adjusted hazard ratio [HR] 0.676 [95% confidence interval [CI] 0.617 to 0.740]; p <0.0001), hypertension (adjusted HR 0.723 [95% CI 0.655 to 0.799]; p <0.0001), and hyperlipidemia (adjusted HR 0.864 [95% CI 0.803 to 0.929]; p <0.0001). WLM with the greatest weight loss (>15%) had a longer time to develop any of the outcomes compared with those with the least amount of weight loss (<7%) (p <0.0001). In an integrated delivery network population, sustained weight loss was associated with a delayed onset of cardiometabolic diseases, particularly with a greater magnitude of weight loss.

Effects of sustained weight loss on outcomes associated with obesity comorbidities and healthcare resource utilization.

OBJECTIVE: Determine the impact of long-term non-surgical weight loss maintenance on clinical relevance for osteoarthritis, cancer, opioid use, and depression/anxiety and healthcare resource utilization. METHODS: A cohort of adults receiving primary care within Geisinger Health System between 2001-2017 was retrospectively studied. Patients with ≥3 weight measurements in the two-year index period and obesity at baseline (BMI ≥30 kg/m2) were categorized: Obesity Maintainers (reference group) maintained weight within +/-3%; Weight Loss Rebounders lost ≥5% body weight in year one, regaining ≥20% of weight loss in year two; Weight Loss Maintainers lost ≥5% body weight in year one, maintaining ≥80% of weight loss. Association with development of osteoarthritis, cancer, opioid use, and depression/anxiety, was assessed; healthcare resource utilization was quantified. Magnitude of weight loss among maintainers was evaluated for impact on health outcomes. RESULTS: In total, 63,567 patients were analyzed including 67% Obesity Maintainers, 19% Weight Loss Rebounders, and 14% Weight Loss Maintainers; median follow-up was 9.7 years. Time until osteoarthritis onset was delayed for Weight Loss Maintainers compared to Obesity Maintainers (Logrank test p <0.0001). Female Weight Loss Maintainers had a 19% and 24% lower risk of developing any cancer (p = 0.0022) or obesity-related cancer (p = 0.0021), respectively. No significant trends were observed for opioid use. Weight loss Rebounders and Maintainers had increased risk (14% and 25%) of future treatment for anxiety/depression (both <0.0001). Weight loss maintenance of >15% weight loss was associated with the greatest decrease in incident osteoarthritis. Healthcare resource utilization was significantly higher for Weight Loss Rebounders and Maintainers compared to Obesity Maintainers. Increased weight loss among Weight Loss Maintainers trended with lower overall healthcare resource utilization, except for hospitalizations. CONCLUSIONS: In people with obesity, sustained weight loss was associated with greater clinical benefits than regained short-term weight loss and obesity maintenance. Higher weight loss magnitudes were associated with delayed onset of osteoarthritis and led to decreased healthcare utilization.

Associations of weight loss with obesity-related comorbidities in a large integrated health system.

AIMS: To determine the health outcomes associated with weight loss in individuals with obesity, and to better understand the relationship between disease burden (disease burden; ie, prior comorbidities, healthcare utilization) and weight loss in individuals with obesity by analysing electronic health records (EHRs). MATERIALS AND METHODS: We conducted a case-control study using deidentified EHR-derived information from 204 921 patients seen at the Cleveland Clinic between 2000 and 2018. Patients were aged ≥20 years with body mass index ≥30 kg/m2 and had ≥7 weight measurements, over ≥3 years. Thirty outcomes were investigated, including chronic and acute diseases, as well as psychological and metabolic disorders. Weight change was investigated 3, 5 and 10 years prior to an event. RESULTS: Weight loss was associated with reduced incidence of many outcomes (eg, type 2 diabetes, nonalcoholic steatohepatitis/nonalcoholic fatty liver disease, obstructive sleep apnoea, hypertension; P < 0.05). Weight loss >10% was associated with increased incidence of certain outcomes including stroke and substance abuse. However, many outcomes that increased with weight loss were attenuated by disease burden adjustments. CONCLUSIONS: This study provides the most comprehensive real-world evaluation of the health impacts of weight change to date. After comorbidity burden and healthcare utilization adjustments, weight loss was associated with an overall reduction in risk of many adverse outcomes.

Effectiveness of Combining Antiobesity Medication With an Employer-Based Weight Management Program for Treatment of Obesity: A Randomized Clinical Trial.

Importance: The clinical efficacy of antiobesity medications (AOMs) as adjuncts to lifestyle intervention is well characterized, but data regarding their use in conjunction with workplace wellness plans are lacking, and coverage of AOMs by US private employers is limited. Objective: To determine the effect of combining AOMs with a comprehensive, interdisciplinary, employer-based weight management program (WMP) compared with the WMP alone on weight loss, treatment adherence, and work productivity and limitations. Design, Setting, and Participants: This 1-year, single-center, open-label, parallel-group, real-world, randomized clinical trial was conducted at the Cleveland Clinic's Endocrinology and Metabolism Institute in Cleveland, Ohio, from January 7, 2019, to May 22, 2020. Participants were adults with obesity (body mass index [BMI; calculated as weight in kilograms divided by height in meters squared] ≥30) enrolled in the Cleveland Clinic Employee Health Plan. Interventions: In total, 200 participants were randomized 1:1, 100 participants to WMP combined with an AOM (WMP+Rx), and 100 participants to WMP alone. The WMP was the Cleveland Clinic Endocrinology and Metabolism Institute's employer-based integrated medical WMP implemented through monthly multidisciplinary shared medical appointments. Participants in the WMP+Rx group initiated treatment with 1 of 5 US Food and Drug Administration-approved medications for chronic weight management (orlistat, lorcaserin, phentermine/topiramate, naltrexone/bupropion, and liraglutide, 3.0 mg) according to standard clinical practice. Main Outcomes and Measures: The primary end point was the percentage change in body weight from baseline to month 12. Results: The 200 participants were predominately (177 of 200 [88.5%]) women, had a mean (SD) age of 50.0 (10.3) years, and a mean (SD) baseline weight of 105.0 (19.0) kg. For the primary intention-to-treat estimand, the estimated mean (SE) weight loss was -7.7% (0.7%) for the WMP+Rx group vs -4.2% (0.7%) for the WMP group, with an estimated treatment difference of -3.5% (95% CI, -5.5% to -1.5%) (P < .001). The estimated percentage of participants achieving at least 5% weight loss was 62.5% for WMP+Rx vs 44.8% for WMP (P = .02). The rate of attendance at shared medical appointments was higher for the WMP+Rx group than for the WMP group. No meaningful differences in patient-reported work productivity or limitation measures were observed. Conclusions and Relevance: Clinically meaningful superior mean weight loss was achieved when access to AOMs was provided in the real-world setting of an employer-based WMP, compared with the WMP alone. Such results may inform employer decisions regarding AOM coverage and guide best practices for comprehensive, interdisciplinary employer-based WMPs. Trial Registration: ClinicalTrials.gov Identifier: NCT03799198.

Benchmarking of provider competencies and current training for prevention and management of obesity among family medicine residency programs: a cross-sectional survey.

BACKGROUND: U.S. physicians lack training in caring for patients with obesity. For family medicine, the newly developed Obesity Medicine Education Collaborative (OMEC) competencies provide an opportunity to compare current training with widely accepted standards. We aimed to evaluate the current state of obesity training in family medicine residency programs. METHODS: We conducted a study consisting of a cross-sectional survey of U.S. family medicine residency program leaders. A total of 735 directors (including associate/assistant directors) from 472 family medicine residency programs identified from the American Academy of Family Physicians public directory were invited via postal mail to complete an online survey in 2018. RESULTS: Seventy-seven program leaders completed surveys (16% response rate). Sixty-four percent of programs offered training on prevention of obesity and 83% provided training on management of patients with obesity; however, 39% of programs surveyed reported not teaching an approach to obesity management that integrates clinical and community systems as partners, or doing so very little. Topics such as behavioral aspects of obesity (52%), physical activity (44%), and nutritional aspects of obesity (36%) were the most widely covered (to a great extent) by residency programs. In contrast, very few programs extensively covered pharmacological treatment of obesity (10%) and weight stigma and discrimination (14%). Most respondents perceived obesity-related training as very important; 65% of the respondents indicated that expanding obesity education was a high or medium priority for their programs. Lack of room in the curriculum and lack of faculty expertise were reported as the greatest barriers to obesity education during residency. Only 21% of the respondents perceived their residents as very prepared to manage patients with obesity at the end of the residency training. CONCLUSION: Family medicine residency programs are currently incorporating recommended teaching to address OMEC competencies to a variable degree, with some topic areas moderately well represented and others poorly represented such as pharmacotherapy and weight stigma. Very few program directors report their family medicine residents are adequately prepared to manage patients with obesity at the completion of their training. The OMEC competencies could serve as a basis for systematic obesity training in family medicine residency programs.

Job Absenteeism Costs of Obesity in the United States: National and State-Level Estimates.

OBJECTIVE: To estimate the causal effect of obesity on job absenteeism and the associated lost productivity in the United States, both nationwide and by state. METHODS: We conducted a retrospective pooled cross-sectional analysis using the 2001 to 2016 Medical Expenditure Panel Survey and estimated two-part models of instrumental variables. RESULTS: Obesity, relative to normal weight, raises job absenteeism due to injury or illness by 3.0 days per year (128%). Annual productivity loss due to obesity ranges from $271 to $542 (lower/upper bound) per employee with obesity, with national productivity losses ranging from $13.4 to $26.8 billion in 2016. Trends in state-level estimates mirror those at the national level, varying across states. CONCLUSIONS: Obesity significantly raises job absenteeism. Reductions in job absenteeism should be included when calculating the cost-effectiveness of interventions to prevent or reduce obesity among employed adults.

Building Successful Models in Primary Care to Improve the Management of Adult Patients with Obesity.

Although several obesity clinical practice guidelines are available and relevant for primary care, a practical and effective medical model for treating obesity is necessary. The aim of this study was to develop and implement a holistic population health-based framework with components to support primary care-based obesity management in US health care organizations. The Obesity Care Model Collaborative (OCMC) was conducted with guidance and expertise of an advisory committee, which selected participating health care organizations based on prespecified criteria. A committee comprising obesity and quality improvement specialists and representatives from each organization developed and refined the obesity care framework for testing and implementing guideline-based practical interventions targeting obesity. These interventions were tracked over time, from an established baseline to 18 months post implementation. Ten geographically diverse organizations, treating patients with diverse demographics, insurance coverage, and health status, participated in the collaborative. The key interventions identified for managing obesity in primary care were applicable across the 4 OCMC framework domains: community, health care organization, care team, and patient/family. Care model components were developed within each domain to guide the primary care of obesity based on each organization's structure, resources, and culture. Key interventions included development of quality monitoring systems, training of leadership and staff, identifying clinical champions, patient education, electronic health record best practice alerts, and establishment of community partnerships, including the identification of external resources. This article describes the interventions developed based on the framework, with a focus on implementation of the model and lessons learned.

Direct medical costs of obesity in the United States and the most populous states.

BACKGROUND: After a dramatic increase in prevalence over several decades, obesity has become a major public health crisis in the United States. Research to date has consistently demonstrated a correlation between obesity and higher medical costs for a variety of U.S. subpopulations and specific categories of care. However, by examining associations rather than causal effects, previous studies likely underestimated the effect of obesity on medical expenditures. OBJECTIVE: To estimate the causal effect of obesity on direct medical care costs at the national and state levels. METHODS: This study is a pooled cross-sectional analysis of retrospective data from the 2001-2016 Medical Expenditure Panel Surveys. Adults aged 20-65 years with a biological child living in the household were included in the study sample. Primary outcomes were individual-level medical expenditures due to obesity, overall, as well as separately by type of payer and category of medical care. Results were reported at the national level and separately for the 20 most populous states. The expenditure estimates were obtained from 2-part models of instrumental variables in which the respondent's body mass index (BMI) was instrumented using the BMI of their biological child. RESULTS: Adults with obesity in the United States compared with those with normal weight experienced higher annual medical care costs by $2,505 or 100%, with costs increasing significantly with class of obesity, from 68.4% for class 1 to 233.6% for class 3. The effects of obesity raised costs in every category of care: inpatient, outpatient, and prescription drugs. Increases in medical expenditures due to obesity were higher for adults covered by public health insurance programs ($2,868) than for those having private health insurance ($2,058). In 2016, the aggregate medical cost due to obesity among adults in the United States was $260.6 billion. The increase in individual-level expenditures due to obesity varied considerably by state (e.g., 24.0% in Florida, 66.4% in New York, and 104.9% in Texas). CONCLUSIONS: The 2-part models of instrumental variables, which estimate the causal effects of obesity on direct medical costs, showed that the effect of obesity is greater than suggested by previous studies, which estimated only correlations. Much of the aggregate national cost of obesity-$260.6 billion-represents external costs, providing a rationale for interventions to prevent and reduce obesity. DISCLOSURES: Novo Nordisk financed the development of the study design, analysis, and interpretation of data, as well as writing support of the manuscript. Cawley, Biener, and Meyerhoefer received financial support from Novo Nordisk to conduct the research study on which this manuscript is based. Smolarz and Ramasamy are employees of Novo Nordisk. Ding and Zvenyach have no conflicts to declare. Our research has been presented as a poster at the 2020 Academy Health Annual Research Meeting (Virtual), July 28-August 6, 2020.

Economic value of nonsurgical weight loss in adults with obesity.

BACKGROUND: Obesity imposes a substantial economic burden on the United States. The short-term value of nonsurgical weight loss (WL) and nonsurgical sustained WL (i.e., WL not resulting from bariatric surgery) is poorly understood. OBJECTIVES: To assess short-term (1 year) effect of nonsurgical WL and sustained nonsurgical WL (i.e., approximately 2 years) on per-patient-per-month (PPPM) total all-cause health care costs among adults with obesity in the United States. METHODS: In this retrospective cohort study, we analyzed data from the IBM MarketScan Explorys Claims-EMR Data Set from January 1, 2012, through June 30, 2018. Adults aged 18-64 years with a body mass index (BMI) measurement ≥ 30 kg/m2 on the index date and BMI measurements at 12, 24, and 36 months were classified into weight-gain (≥ 3%), no-weight-change (within ± 3%), and WL (≥ 3%-≤ 5%, > 5%-≤ 10%, and > 10%-≤ 20%) cohorts based on the change from first to second BMI measurements (baseline), and sustained nonsurgical WL based on WL during baseline and < 3% weight gain from second to third BMI measurement. PPPM all-cause health care costs were calculated for baseline, first year, and second year of follow-up. Generalized linear models were used to examine if PPPM all-cause health care cost change (ΔPPPM) from baseline to follow-up differed significantly between nonsurgical WL/sustained WL and no-weight-change cohorts. Analyses were stratified by index obesity class (class 1: BMI 30- < 34.9 kg/m2, class 2: BMI 35- < 39.9 kg/m2, class 3: BMI ≥ 40 kg/m2). Specific nonsurgical WL treatments used by individuals in the study were not studied. RESULTS: The sample included 20,488 adults who were grouped as follows: weight-gain cohort (24.8%), no-weight-change cohort (56.6%), ≥ 3%- ≤ 5% WL cohort (8.2%), > 5%- ≤ 10% WL cohort (7.7%), and > 10%- ≤ 20% WL cohort (2.8%). Compared with the no-weight-change cohort, adjusted mean ΔPPPM all-cause health care cost from baseline to first year of follow-up was lower in all WL cohorts (≥ 3%- ≤ 5% WL: -$57.36, > 5%- ≤ 10% WL: -$135.35 [P < 0.05], > 10%- ≤ 20% WL: -$193.54 [P < 0.05]). In the second year of follow-up (n = 15,307), the cohorts were weight-gain (43.4%), no-weight-change (59.4%), ≥ 3%- ≤ 5% sustained WL (7.3%), ≥ 5%- ≤ 10% sustained WL (6.3%), and > 10%- ≤ 20% sustained WL (1.8%). Adjusted mean ΔPPPM all-cause health care cost was lower in all sustained WL groups (-$26.38, -$157.41 [P < 0.05], and -$185.41 for ≥ 3%- ≤ 5%, ≥ 5%- ≤ 10%, and > 10%- ≤ 20% WL, respectively). Greater nonsurgical WL and sustained nonsurgical WL were generally associated with larger reduction in short-term all-cause health care costs. Results stratified by index obesity class were mixed, due to small samples. CONCLUSIONS: Substantial all-cause health care cost savings were observed 1 year after nonsurgical WL and after sustained (on average for 2 years) nonsurgical WL in adults with obesity, with greater nonsurgical WL and sustained nonsurgical WL associated with greater cost savings. Comprehensive solutions to chronic weight management, including improved access to antiobesity medications in combination with lifestyle interventions, could be valuable to patients, employers, and payers. DISCLOSURES: This study was sponsored by Novo Nordisk, which also purchased the data. Blanchette is an employee of Novo Nordisk. Smolarz and Ramasamy are employees of Novo Nordisk and hold equity in Novo Nordisk. Ding, Fan, and Weng were employees of Novo Nordisk at the time this study was conducted. The findings from this study were previously presented at Obesity Week 2019; November 3-7, 2019; Las Vegas, NV.

Medicine Residents are Unprepared to Effectively Treat Patients with Obesity: Results from a U.S. Internal Medicine Residency Survey.

BACKGROUND: In an obesity epidemic, physicians are unprepared to treat patients with obesity. The objective of this study was to understand how obesity is currently addressed in United States (U.S.) Internal Medicine (IM) residency programs and benchmark the degree to which curricula incorporate topics pertaining to the recently developed Obesity Medicine Education Collaborative (OMEC) competencies. METHODS: Invitations to complete an online survey were sent via postal mail to U.S IM residency programs in 2018. Descriptive analyzes were performed. RESULTS: Directors/associate directors from 81 IM residencies completed the online survey out of 501 programs (16.2%). Although obesity was an intentional educational objective for most programs (66.7%), only 2.5% of respondents believed their residents are "very prepared" to manage obesity. Formal rotation opportunities in obesity are limited, and at best, only one-third (34.6%) of programs reported any one of the core obesity competencies are covered to "a great extent." Many programs reported psychosocial components of obesity (40.7%), weight stigma (44.4%), etiological aspects of obesity (64.2%) and pharmacological treatment of obesity (43.2%) were covered to "very little extent" or "not at all." Lack of room in the curriculum and lack of faculty expertise are the greatest barriers to integrating obesity education; only 39.5% of residency programs have discussed incorporating or expanding formal obesity education. CONCLUSIONS: Our study found the current obesity curricula within U.S. IM residency programs do not adequately cover important aspects that address the growing obesity epidemic, suggesting that obesity education is not enough of a priority for IM residency programs to formalize and implement within their curricula.

Low priority of obesity education leads to lack of medical students' preparedness to effectively treat patients with obesity: results from the U.S. medical school obesity education curriculum benchmark study.

BACKGROUND: Physicians are currently unprepared to treat patients with obesity, which is of great concern given the obesity epidemic in the United States. This study sought to evaluate the current status of obesity education among U.S. medical schools, benchmarking the degree to which medical school curricula address competencies proposed by the Obesity Medicine Education Collaborative (OMEC). METHODS: Invitations to complete an online survey were sent via postal mail to 141 U.S. medical schools compiled from Association of American Medical Colleges. Medical school deans and curriculum staff knowledgeable about their medical school curriculum completed online surveys in the summer of 2018. Descriptive analyses were performed. RESULTS: Forty of 141 medical schools responded (28.4%) and completed the survey. Only 10.0% of respondents believe their students were "very prepared" to manage patients with obesity and one-third reported that their medical school had no obesity education program in place and no plans to develop one. Half of the medical schools surveyed reported that expanding obesity education was a low priority or not a priority. An average of 10 h was reported as dedicated to obesity education, but less than 40% of schools reported that any obesity-related topic was well covered (i.e., to a "great extent"). Medical students received an adequate education (defined as covered to at least "some extent") on the topics of biology, physiology, epidemiology of obesity, obesity-related comorbidities, and evidence-based behavior change models to assess patient readiness for counseling (range: 79.5 to 94.9%). However, in approximately 30% of the schools surveyed, there was little or no education in nutrition and behavioral obesity interventions, on appropriate communication with patients with obesity, or pharmacotherapy. Lack of room in the curriculum was reported as the greatest barrier to incorporating obesity education. CONCLUSIONS: Currently, U.S. medical schools are not adequately preparing their students to manage patients with obesity. Despite the obesity epidemic and high cost burden, medical schools are not prioritizing obesity in their curricula.

The Societal Value of Broader Access to Antiobesity Medications.

OBJECTIVE: Obesity and its complications place an enormous burden on society. Yet antiobesity medications (AOM) are prescribed to only 2% of the eligible population, even though few individuals can sustain weight loss using other strategies alone. This study estimated the societal value of greater access to AOM. METHODS: By using a well-established simulation model (The Health Economics Medical Innovation Simulation), the societal value of AOM for the cohort of Americans aged ≥ 25 years in 2019 was quantified. Four scenarios with differential uptake among the eligible population (15% and 30%) were modeled, with efficacy from current and next-generation AOM. Societal value was measured as monetized quality of life, productivity gains, and savings in medical spending, subtracting the costs of AOM. RESULTS: For the 217 million Americans aged ≥ 25 years, AOM generated $1.2 trillion in lifetime societal value under a conservative scenario (15% annual uptake using currently available AOM). The introduction of next-generation AOM increased societal value to $1.9 to $2.5 trillion, depending on uptake. Finally, societal value was higher for younger individuals and Black and Hispanic individuals compared with White individuals. CONCLUSIONS: This study suggests that AOM provide substantial gains to patients and society. Policies promoting broader clinical access to and use of AOM warrant consideration to reach national goals to reduce obesity.

Direct, Absenteeism, and Disability Cost Burden of Obesity Among Privately Insured Employees: A Comparison of Healthcare Industry Versus Other Major Industries in the United States.

OBJECTIVE: To compare obesity-related costs of employees of the healthcare industry versus other major US industries. METHODS: Employees with obesity versus without were identified using the Optum Health Reporting and Insights employer claims database (January, 2010 to March, 2017). Employees working in healthcare with obesity were compared with employees of other industries with obesity for absenteeism/disability and direct cost differences. Multivariate models estimated the association between industries and high costs compared with the healthcare industry. RESULTS: Obesity-related absenteeism/disability and direct costs were higher in several US industries compared with the healthcare industry (adjusted cost differences of $-1220 to $5630). Employees of the government/education/religious services industry (GERS) with obesity (BMI of 30 or greater) had significantly higher odds of direct costs at the 80th percentile and above (odds ratio vs healthcare industry = 2.20; P < 0.05). CONCLUSIONS: Relative to the healthcare industry, employees of other industries, especially GERS, incurred higher obesity-related costs.

Direct and Indirect Cost of Obesity Among the Privately Insured in the United States: A Focus on the Impact by Type of Industry.

OBJECTIVE: To evaluate obesity-related costs and body mass index (BMI) as a cost predictor among privately insured employees by industry. METHODS: Individuals with/without obesity were identified using the Optum Health Reporting and Insights employer claims database (January, 2010 to March, 2017). Direct/indirect costs were reported per-patient-per-year (PPPY). Multivariate models were used to estimate the association between obesity and high costs (more than or equal to 80th percentile) by industry. RESULTS: Overall (N = 86,221), direct and absenteeism/disability cost differences between class I obesity (BMI 30.0 to 34.9) and reference were $1,775 and $617 PPPY, respectively (P < 0.05). Among employees with obesity (BMI more than or equal to 30), highest total costs were observed in the government/education/religious services, food/entertainment services, and technology industries. Class I obesity increased the odds of high costs (more than or equal to 80th percentile) within each industry (odds ratios vs reference = 1.09-5.17). CONCLUSIONS: Obesity (BMI more than or equal to 30) was associated with high costs among employees of major US industries.

Effect of Weight Change on Economic Outcomes Among Persons with Type 2 Diabetes Mellitus in the United States: Beyond Glycemic Control.

BACKGROUND: Previous studies report weight loss to be associated with significantly lower total health care costs among patients with type 2 diabetes mellitus (T2DM). The effect of weight change on health care costs, independent of glycemic control and after controlling for time-varying covariates among T2DM patients, remains unknown. OBJECTIVE: To evaluate the effect of weight change, independent of glycemic control, on all-cause and T2DM-related health care resource utilization (HCRU) and costs among T2DM patients in the United States. METHODS: A retrospective cohort study was conducted using a linked data extract composed of IQVIA's RWI Data Adjudicated Claims-US and Ambulatory Electronic Medical Record data. Adults (aged ≥ 18 years) with T2DM receiving ≥ 1 oral antidiabetic drug (OAD) medication, glucagon-like peptide-1 receptor agonist (GLP-1RA), and/or short- or long-acting insulin between January 1, 2010, and December 31, 2014 were included (the date of the first observed medical claim with a diagnosis code or medication prescription claim was the index date). Baseline characteristics were evaluated in the 6-month pre-index period. Weight loss (3%, 5%, or 7% from baseline) was evaluated over two 6-month periods (months 1-6 and 7-12) following the index date. Covariates included time-varying weight, hemoglobin A1c (A1c), costs, and HCRU within each 6-month period. Outcomes of interest (all-cause and T2DM-related HCRU and costs) were evaluated in the 6-month (months 13-18) and 12-month (months 13-24) periods following the initial 1- to 6-month and 7- to 12-month post-index periods. Structural nested mean models were used to evaluate the effect of weight change on these outcomes, independent of glycemic control. RESULTS: 1,407 patients were included (mean age = 55 years; 55% male), with a mean baseline weight of 102.2 kg (median = 99.7 kg) and a mean baseline A1c of 7.4% (median = 6.9%). In adjusted analysis, weight loss was associated with significantly lower all-cause and T2DM-related annual total health care costs. Compared with those showing no weight change, a 3%, 5%, and 7% weight loss resulted in approximately $500, $800, and $1,100 in savings, respectively, in all-cause annual total health care costs per patient in the year following the weight loss. Similarly, compared with those with no weight change, a 3%, 5%, and 7% weight loss resulted in approximately $200, $300, and $400 in savings, respectively, in T2DM-related annual total health care costs per patient in the following year. Even greater savings (up to ~$2,000 and ~$800 in all-cause and T2DM-related annual costs per patient, respectively) were experienced by those who lost weight compared with those who gained weight. CONCLUSIONS: After accounting for glycemic control, this study found that weight loss was associated with additional significant reductions in all-cause and T2DM-related annual total health care costs. Understanding the role of weight loss in T2DM may provide useful evidence for decision makers as they evaluate therapy options for T2DM. DISCLOSURES: This study was funded by Novo Nordisk. Dang-Tan, Smolarz, and Iyer are employees of Novo Nordisk. Karkare and DeKoven (employees of IQVIA) and Fridman (employed by AMF Consulting) were contracted by Novo Nordisk to conduct this study. Fridman also reports personal fees from Shire, GSK, and CSL Behring, outside of the submitted work. Lu, an employee of IQVIA, accessed the database and conducted the statistical analysis for this study.

Persistence of newer anti-obesity medications in a real-world setting.

AIMS: Evaluate real-world data on persistence with anti-obesity medications (AOMs) and explore associated patient factors. METHODS: Truven Health MarketScan® data were analyzed to evaluate utilization of AOMs approved for long-term use between 4/2015 and 3/2016. Kaplan-Meier survival analyses were used to evaluate treatment persistence. A multivariate analysis was performed to identify associations between persistence and relevant factors. RESULTS: In total, 26,522 adult patients were identified as newly prescribed naltrexone/bupropion (44.0%, mean age 47.1, 80.5% female), lorcaserin (24.8%, 48.5, 79.3%), phentermine/topiramate extended release (15.8%, 46.7, 82.2%) or liraglutide 3.0 mg (15.4%, 46.9, 72.4%). At 6 months, 41.8% of patients were still on liraglutide 3.0 mg, compared to 15.9% lorcaserin (p < 0.001), 18.1% naltrexone/bupropion (p < 0.001), and 27.3% phentermine/topiramate (p < 0.001). After adjusting for baseline factors, patients on liraglutide 3.0 mg had significantly lower risk of discontinuation compared to those on lorcaserin (HR = 0.46, p < 0.0001), naltrexone/bupropion (HR = 0.48, p < 0.0001), and phentermine/topiramate (HR = 0.64, p < 0.0001) over the course of follow-up (mean follow-up duration, 342-427 days). Older age, male gender, having hyperlipidemia, and no prior phentermine use were associated with higher persistence. Over 95% of study patients had commercial insurance. CONCLUSIONS: In a real-world setting, patients on liraglutide 3.0 mg had the highest persistence rate of the four AOMs studied.

Use of International Classification of Diseases, Ninth Revision Codes for Obesity: Trends in the United States from an Electronic Health Record-Derived Database.

Obesity is a potentially modifiable risk factor for many diseases, and a better understanding of its impact on health care utilization, costs, and medical outcomes is needed. The ability to accurately evaluate obesity outcomes depends on a correct identification of the population with obesity. The primary objective of this study was to determine the prevalence and accuracy of International Classification of Diseases, Ninth Revision (ICD-9) coding for overweight and obesity within a US primary care electronic health record (EHR) database compared against actual body mass index (BMI) values from recorded clinical patient data; characteristics of patients with obesity who did or did not receive ICD-9 codes for overweight/obesity also were evaluated. The study sample included 5,512,285 patients in the database with any BMI value recorded between January 1, 2014, and June 30, 2014. Based on BMI, 74.6% of patients were categorized as being overweight or obese, but only 15.1% of patients had relevant ICD-9 codes. ICD-9 coding prevalence increased with increasing BMI category. Among patients with obesity (BMI ≥30 kg/m2), those coded for obesity were younger, more often female, and had a greater comorbidity burden than those not coded; hypertension, dyslipidemia, type 2 diabetes mellitus, and gastroesophageal reflux disease were the most common comorbidities. KEY FINDINGS: US outpatients with overweight or obesity are not being reliably coded, making ICD-9 codes undependable sources for determining obesity prevalence and outcomes. BMI data available within EHR databases offer a more accurate and objective means of classifying overweight/obese status.

Positive predictive value between medical-chart body-mass-index category and obesity versus codes in a claims-data warehouse.

OBJECTIVE: To evaluate the positive predictive value of claims-based V85 codes for identifying individuals with varying degrees of BMI relative to their measured BMI obtained from medical record abstraction. METHODS: This was a retrospective validation study utilizing administrative claims and medical chart data from 1 January 2009 to 31 August 2015. Randomly selected samples of patients enrolled in a Medicare Advantage Prescription Drug (MAPD) or commercial health plan and with a V85 claim were identified. The claims-based BMI category (underweight, normal weight, overweight, obese class I-III) was determined via corresponding V85 codes and compared to the BMI category derived from chart abstracted height, weight and/or BMI. The positive predictive values (PPVs) of the claims-based BMI categories were calculated with the corresponding 95% confidence intervals (CIs). RESULTS: The overall PPVs (95% CIs) in the MAPD and commercial samples were 90.3% (86.3%-94.4%) and 91.1% (87.3%-94.9%), respectively. In each BMI category, the PPVs (95% CIs) for the MAPD and commercial samples, respectively, were: underweight, 71.0% (55.0%-87.0%) and 75.9% (60.3%-91.4%); normal, 93.8% (85.4%-100%) and 87.8% (77.8%-97.8%); overweight, 97.4% (92.5%-100%) and 93.5% (84.9%-100%); obese class I, 96.9 (90.9%-100%) and 97.2% (91.9%-100%); obese class II, 97.0% (91.1%-100%) and 93.0% (85.4%-100%); and obese class III, 85.0% (73.3%-96.1%) and 97.1% (91.4%-100%). CONCLUSIONS: BMI categories derived from administrative claims, when available, can be used successfully particularly in the context of obesity research.