Quality Measurement Gaps and Future Directions in the Assessment of Obesity.

PURPOSE OF REVIEW: The disease of obesity continues to increase in prevalence and severity yet obesity care, treatment, and coverage are scarce. Progress has been made in the development and implementation of quality measures in clinical practice and organizational performance. However, major gaps and limitations exist in the context of measuring guideline-based clinical care for obesity. RECENT FINDINGS: Obesity quality measures have entered various stages of testing and development, but only a select few are included in reporting and payment programs. One process measure for adults, "Preventive Care and Screening: Body Mass Index (BMI) Screening and Follow-Up Plan" is used in Medicare. One process measure for pediatrics, "Weight Assessment and Counseling for Nutrition and Physical Activity in Children and Adolescence" is used in Medicare, health insurance plans, and Medicaid. No outcome or digital quality measure exists for the disease of obesity. One quality measure development project is underway that is testing the performance of four measures, including outcome measures for obesity. The general absence of quality measures for obesity means that there are no objective measures to address the quality of obesity care or its outcome. More meaningful efforts are needed to seriously integrate obesity with quality performance measurement and value in healthcare payment programs.

Assessing opportunities to advance quality measures in adult obesity.

OBJECTIVES: To evaluate the methodological soundness and performance of 3 obesity quality measures aimed at promoting improvements in obesity care. STUDY DESIGN: Retrospective, clinical, and administrative data-based observational research study to evaluate scientific soundness, feasibility, and performance of obesity quality measures. METHODS: Four test sites (clinicians/clinician groups) submitted clinical and administrative health data including patient demographics, diagnoses, and encounter information for patient panels encompassing individuals aged 18 to 79 years with at least 1 ambulatory visit between July 1, 2017, and June 30, 2018 (measurement period). Clinician/clinician group data were supplemented by an Optum data set contributing patient information from 21 health care organizations with approximately 6 million qualifying patients to assess the impact of using a larger data set for measure testing. Patients were excluded if they met any of the following criteria: were pregnant during the measurement period or in the 6 months prior to the measurement period, had died during the measurement year, or had evidence of palliative or hospice care during the measurement period. RESULTS: This study resulted in the identification of a clinician/clinician group-level measure, Documentation of Obesity Diagnosis, as being feasible and reliable; however, the measure requires additional evaluation and potential adjustments to determine validity. Other measures included in our evaluation had feasibility and methodological challenges due to data capture and coding limitations. CONCLUSIONS: Findings of our current study suggest that there are emerging opportunities to capture data and advance obesity measurement incrementally. A process measure focused on obesity diagnosis has the most potential for immediate implementation by clinicians, and additional measures focused on change in body mass index over time and use of evidence-based obesity treatment remain challenging to implement due to data capture and benefit coverage.

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.

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.

Simulating the Fiscal Impact of Anti-Obesity Medications as an Obesity Reduction Strategy.

While substantial public health investment in anti-smoking initiatives has had demonstrated benefits on health and fiscal outcomes, similar investment in reducing obesity has not been undertaken, despite the substantial burden obesity places on society. Anti-obesity medications (AOMs) are poorly prescribed despite evidence that weight loss is not sustained using other strategies alone.We used a simulation model to estimate the potential impact of 100% uptake of AOMs on Medicare and Medicaid spending, disability payments, and taxes collected relative to status quo with negligible AOM use. Relative to status quo, AOM use simulation would result in Medicare and Medicaid savings of $231.5 billion and $188.8 billion respectively over 75 years. Government tax revenues would increase by $452.8 billion. Overall, the net benefit would be $746.6 billion. Anti-smoking efforts have had substantial benefits for society. A similar investment in obesity reduction, including broad use of AOMs, should be considered.

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.

Ten-year Medicare budget impact of increased coverage for anti-obesity intervention.

Aims: To estimate the long-term budget impact of expanding Medicare coverage of anti-obesity interventions among adults aged 65 and older in the US. Materials and methods: This study analyzed a representative sample of Medicare beneficiaries from the combined 2008-2016 National Health and Nutrition Examination Surveys. Population characteristics, cost and effectiveness of anti-obesity interventions, and the sustainability of weight loss in real-life were modeled to project the budgetary impact on gross Medicare outlay over 10 years. Hypothetical scenarios of 50% and 67% increases in intervention participation above base case were used to model moderate and extensive Medicare coverage expansion of intensive behavior therapy and pharmacotherapy. Results: For each Medicare beneficiary receiving anti-obesity treatment, we estimate Medicare savings of $6,842 and $7,155 over 10 years under moderate and extensive coverage utilization assumptions, respectively. The average cost of intervention is $1,798 and $1,886 per treated participant. Taking the entire Medicare population (treated and untreated) into consideration, the estimated 10-year budget savings per beneficiary are $308 and $339 under moderate and extensive assumptions, respectively. Sensitivity analysis of drug adherence rate and weight-loss efficacy indicated a potential variation of budget savings within 7% and 22% of the base case, respectively. Most of the projected cost savings come from lower utilization of ambulatory services and prescription drugs. Limitations: Due to the scarcity of studies on the efficacy of pharmacotherapy among older adults with obesity, the simulated weight loss and long-term maintenance effects were derived from clinical trial outcomes, in which older adults were mostly excluded from participation. The model did not include potential side-effects from anti-obesity medications and associated costs. Conclusions: This analysis suggests that expanding coverage of anti-obesity interventions to eligible individuals could generate $20-$23 billion budgetary savings to Medicare over 10 years.

Where can obesity management policy make the largest impact? Evaluating sub-populations through a microsimulation approach.

BACKGROUND: There is a critical need to focus limited resources on sub-groups of patients with obesity where we expect the largest return on investment. This paper identifies patient sub-groups where an investment may result in larger positive economic and health outcomes. METHODS: The baseline population with obesity was derived from a public survey database and divided into sub-populations defined by demographics and disease status. In 2016, a validated model was used to simulate the incidence of diabetes, absenteeism, and direct medical cost in five care settings. Research findings were derived from the difference in population outcomes with and without weight loss over 15 years. Modeled weight loss scenarios included initial 5% or 12% reduction in body mass index followed by a gradual weight regain. Additional simulations were conducted to show alternative outcomes from different time courses and maintenance scenarios. RESULTS: Univariate analyses showed that age 45-64, pre-diabetes, female, or obesity class III are independently predictive of larger savings. After considering the correlation between these factors, multivariate analyses projected young females with obesity class I as the optimal sub-group to control obesity-related medical expenditures. In contrast, the population aged 20-35 with obesity class III will yield the best health outcomes. Also, the sub-group aged 45-54 with obesity class I will produce the biggest productivity improvement. Each additional year of weight loss maintained showed increased financial benefits. CONCLUSIONS: This paper studied the heterogeneity between many sub-populations affected by obesity and recommended different priorities for decision-makers in economic, productivity, and health realms.

Health Care Quality: Measuring Obesity in Performance Frameworks.

OBJECTIVE: Obesity affects over one-third of Americans and leads to several chronic and costly comorbid conditions. The national movement toward value-based care calls for a refocusing of efforts to address the US obesity epidemic. To help set the stage, the current landscape of obesity-specific quality measures was evaluated. METHODS: Seven quality measure databases and nine professional societies were searched. Inclusion and exclusion criteria were applied. Measures were then classified by domain and by implementation in national public programs. RESULTS: Eleven obesity-specific quality measures in adults were identified (nine process and two outcome). Three measures received National Quality Forum (NQF) endorsement. Two measures were actively used within Centers for Medicare and Medicaid Services (CMS) programs. Only one measure was both NQF-endorsed and used by CMS. CONCLUSIONS: Limitations exist with respect to obesity-specific quality metrics. Such gaps provide opportunities for obesity care specialists to engage and offer valuable insights and pragmatic approaches toward quality measurement.

Obesity and government.

PURPOSE OF REVIEW: Despite much effort, obesity prevalence and disease severity continues to worsen. The purpose of this review is to describe the leading government supported food and nutrition interventions and policies to prevent and address obesity in the USA. The review also summarizes obesity interventions and policies that the government plays a role in, but further development is warranted. RECENT FINDINGS: The government's role in obesity has largely focused on interventions and policies such as national surveillance, obesity education and awareness, grant-based food subsidy programs, zoning for food access, school-based nutrition programs, dietary guidelines, nutrition labeling, and food marketing and pricing policies. The government has played a lesser role in obesity interventions and policies that provide access to evidence-based obesity care to people affected by the disease. SUMMARY: Given the magnitude of the obesity epidemic, the government should explore multiple evidence-based interventions and policies across prevention and clinical care.

Obesity as a Disease: Current Policies and Implications for the Future.

The recognition of obesity as a chronic disease is increasing. However, there is variable acknowledgment of it as a disease in health policies across the USA. The objective of this review is to describe how obesity meets the definition of a disease, explain its interpretation in current health policies, and explore implications for obesity in future health policy adoption and development. Perspectives are presented from scientific evidence, clinical practice, and health policy areas including Medicare, Medicaid, the Affordable Care Act, federal government agency guidance, and healthcare quality.