Non-classical measurement error in instrumental variables estimation: An application to the medical care costs of obesity.

Estimates of the impact of body mass index and obesity on health and labor market outcomes often use instrumental variables estimation (IV) to mitigate bias due to endogeneity. When these studies rely on survey data that include self- or proxy-reported height and weight, there is non-classical measurement error due to the tendency of individuals to under-report their own weight. Mean reverting errors in weight do not cause IV to be asymptotically biased per se, but may result in bias if instruments are correlated with additive error in weight. We demonstrate the conditions under which IV is biased when there is non-classical measurement error and derive bounds for this bias conditional on instrument strength and the severity of mean-reverting error. We show that improvements in instrument relevance alone cannot eliminate IV bias, but reducing the correlation between weight and reporting error mitigates the bias. A solution we consider is regression calibration (RC) of endogenous variables with external validation data. In simulations, we find IV estimation paired with RC can produce consistent estimates when correctly specified. Even when RC fails to match the covariance structure of reporting error, there is still a reduction in asymptotic bias.

Comparison of Estimated No Surprises Act Qualifying Payment Amounts and Payments to In-Network and Out-of-Network Emergency Medicine Professionals.

Importance: The No Surprises Act (NSA), which took effect on January 1, 2022, applies a qualifying payment amount (QPA) as an out-of-network payment reference point. An understanding of how QPA measures compare with the in-network and out-of-network payments physicians received before the NSA implementation may be useful to policy makers and stakeholders. Objective: To estimate the QPA for geographic and funding markets and compare QPA estimates with in-network and out-of-network payments for 2019 emergency medicine claims. Design, Setting, and Participants: This cross-sectional study of US commercial insurance claims assessed the Health Care Cost Institute's 2019 commercial professional emergency medicine claims (Current Procedural Terminology [CPT] codes 99281-99285 and 99291) and included enrollees in commercial health maintenance organizations, exclusive provider organizations, point of service, and preferred provider organizations self-funded and fully insured through Aetna, Humana, and some Blue Health Intelligence plans. Claims with missing or inconsistent data fields were excluded. Data were analyzed November 1, 2021, to April 7, 2022. Main Outcomes and Measures: The QPA was calculated as the median allowed amount of all observed claims within strata defined by geographic region, CPT code, and funding market. For each stratum, the ratio of mean in-network allowed amounts to QPAs and mean out-of-network allowed amounts to QPAs were calculated. Then the volume-weighted mean of these ratios was computed across CPT codes within each geographic and funding market stratum. Results: The analytic sample included 7 556 541 professional emergency claims with a mean (SD) allowed amount of $313 ($306) and mean (SD) QPA of $252 ($133). Among the 650 geographic and market strata in the sample, the mean in-network allowed amounts were 14% (ratio, 0.96) higher than the estimated QPA. For the subset of strata with a sufficient sample of out-of-network claims (n = 227), the mean out-of-network payments were 112% (ratio, 2.12) higher than the QPA. More generous out-of-network payments were from self-funded plans (120% [ratio, 2.20] higher than the QPA estimate) vs fully insured plans (43% [ratio, 1.43] higher than the QPA estimate). Mean in-network allowed amounts for nonphysician clinicians were 4% (ratio, 1.04) lower than the QPA, whereas mean in-network allowed amounts for physicians were 15% (ratio, 1.15) higher than the QPA estimates. These differences remained after adjusting for geographic region. Conclusions and Relevance: The findings of this cross-sectional study of US commercial insurance claims suggest that the NSA may have heterogeneous implications for out-of-network payments and negotiating leverage experienced by emergency medicine physicians in different geographic markets, with the potential for greater implications in the self-funded market.

Methenamine hippurate compared with trimethoprim for the prevention of recurrent urinary tract infections: a randomized clinical trial.

INTRODUCTION AND HYPOTHESIS: The objective was to find an alternative treatment to a low-dose antibiotic for the prevention of recurrent urinary tract infections (UTI) and to evaluate the difference in rates of reinfection within 1 year when treated with methenamine hippurate for prophylaxis compared with trimethoprim. METHODS: We present a non-blinded randomized trial comparing methenamine hippurate with trimethoprim for the prevention of recurrent UTI at 12 months after starting treatment. Women over 18 who had at least two culture-positive UTI in the prior 6 months or three in the prior year were included. Ninety-two patients met enrollment criteria and were randomized to receive daily prophylaxis with methenamine hippurate or trimethoprim for a minimum of 6 months. Both intent-to-treat and per-protocol analyses if patients received the alternative drug after randomization were analyzed using Student's t test, Mann-Whitney U test, Kaplan-Meier curves, log-rank test, and a logistic and multivariate regression model. The primary outcome of this study was culture-proven UTI recurrence by 12 months after initiating prophylaxis. RESULTS: In the intent-to-treat analysis, we found no difference between groups in recurrent UTI, with a 65% (28 out of 43) recurrence in the trimethoprim group versus 65% (28 out of 43) in the methenamine hippurate group (p = 1.00). In the per-protocol analysis, 65% (26 out of 40) versus 65% (30 out of 46) of patients had UTI recurrences in the trimethoprim group versus the methenamine hippurate group (p = 0.98). CONCLUSIONS: Methenamine hippurate may be an alternative for the prevention of recurrent UTI, with similar rates of recurrence and adverse effects to trimethoprim.

Emergency Physicians Recover A Higher Share Of Charges From Out-Of-Network Care Than From In-Network Care.

Surprise medical bills occur when a patient unexpectedly or involuntarily receives care from an out-of-network provider and is billed for the amount not covered by insurance. Past studies were unable to observe whether bills for such care were sent to patients and, if so, how much patients paid directly to out-of-network providers. We used data from the Medical Expenditure Panel Survey to measure how much privately insured emergency patients paid when they likely received a surprise bill and how much physicians received in these situations. Physicians collected 65 percent of the charged amount for likely surprise bills compared with 52 percent for other cases. Patients who likely received a surprise out-of-network bill for emergency care paid physicians more than ten times as much as other emergency patients paid, on average.

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.

Do Racial and Ethnic Disparities in Mental Health Treatment Vary With Underlying Mental Health?

A long line of studies document substantial and persistent racial and ethnic disparities in the use of mental health services. Many recent studies follow the Institute of Medicine's definition of disparities, adjusting only for differences in health and mental health status across groups. However, controlling for mental health may mask important changes in the magnitudes of disparities at different levels of mental health need. We extend the previous literature by explicitly estimating how differences in treatment use across groups change at different levels of psychological distress. We used detailed data on sociodemographic characteristics, health insurance coverage, treatment, and the K6 psychological distress scale from the 2010 to 2015 Medical Expenditure Panel Survey to estimate nonlinear models of ambulatory and prescription drug mental health treatment. We find that in contrast to physical health treatment, Black-White and Hispanic-White disparities in any mental health treatment use widen with higher levels of psychological distress.

The medical care costs of obesity and severe obesity in youth: An instrumental variables approach.

This paper is the first to use the method of instrumental variables to estimate the impact of obesity and severe obesity in youth. on U.S. medical care costs. We examine data from the Medical Expenditure Panel Survey for 2001-2015 and instrument for child BMI using the BMI of the child's biological mother. Instrumental variables estimates indicate that obesity in youth raises annual medical care costs by $907 (in 2015 dollars) or 92%, which is considerably higher than previous estimates of the association of youth obesity with medical costs. We find that obesity in youth significantly raises costs in all major categories of medical care: outpatient doctor visits, inpatient hospital stays, and prescription drugs. The costs of youth obesity are borne almost entirely by third-party payers, which is consistent with substantial externalities of youth obesity, which in turn represents an economic rationale for government intervention.

Annual Report on Children's Healthcare: Healthcare Access and Utilization by Obesity Status in the United States.

OBJECTIVE: To examine access to care and utilization patterns across a set of healthcare measures by obesity status and socio-demographic characteristics among children. METHODS: Nationally representative data from the Medical Expenditure Panel Survey (2010-2015) provides data on obesity status, well-child visits, access to a usual source of care provider, preventive dental visits, and prescription medication fills in the past year. RESULTS: Uninsured adolescents with obesity were less likely to have a usual source of care provider relative to children without obesity (73% vs 65%). Among younger children, children with obesity were less likely to report a well-child visit (difference of 8 percentage points). Younger children with obesity who lived in the Northeast were more than twice as likely as those living in the West to have a well-child visit. Children with obesity were less likely to report preventive dental use relative to their nonobese counterparts. Obesity status was associated with more prescription medication fills for adolescents, but not for younger children. CONCLUSIONS: Our findings provide a baseline assessment for examining obesity and utilization trends among children in the future, especially as coverage patterns change with potential changes in childhood insurance coverage access through the Child Health Insurance Programs and Medicaid programs. Our findings highlight new directions for future research, particularly regarding the lower rates of preventive dental care among children with obesity.

Characteristics of office-based providers associated with secure electronic messaging use: Achieving meaningful use.

OBJECTIVES: To identify characteristics of office-based provider used as a usual source of care (USC) associated with secure electronic messaging (SM) use. DATA SOURCE: 2015 Medical Expenditure Panel Survey Household Component and the supplemental Medical Organizations Survey. STUDY DESIGN: Cross-sectional analysis. EXTRACTION METHODS: Patients are linked to characteristics of their usual source of care provider. MAIN FINDINGS: We found that 89 percent of patients whose USC had electronic health records were able to exchange secure messages with their provider. Patients whose USC reported being patient-centered medical homes (PCMHs) or that used other health information technology (HIT) were also more likely to have been able to exchange SM with their provider. Patients of independent group or solo practices were less likely to have been able to exchange SM relative to patients whose USC practice was hospital owned. CONCLUSIONS: Patients were more likely to have visited a USC that exchanged SMs if that practice also used other electronic health records functionalities. Study findings suggest that while patients' USC practices were likely to exchange secure messages, there is a disparity in SM use between physician-owned practices, and hospital-owned practices.

Do racial and ethnic disparities in health care use vary with health?

OBJECTIVE: To determine the relationship between health status and the magnitude of black-white and Hispanic-white disparities in the likelihood of having any office-based or hospital outpatient department visits, as well as number of visits. DATA SOURCE: 2010-2014 Medical Expenditure Panel Survey. STUDY DESIGN: The probability of having a visit is modeled using a Probit model, and the number of visits using a negative binomial model. We use a nonlinear rank-and-replace method to adjust minority health status to be comparable to that of whites, and predict utilization at different levels of health by fixing an indicator of health status. We compare estimated differences in predicted utilization across racial/ethnic groups for each level of health status to map out the relationship between the racial/ethnic disparity and health status, also stratifying by health insurance coverage. EXTRACTION METHODS: We subset to nonelderly adults. PRINCIPAL FINDINGS: We find that Hispanic-white differences in the probability of having an office-based or hospital outpatient department were widest among adults in excellent health (27 percentage points, 95% CI: [23, 31]) and narrowest when reporting poor or fair health (15 p.p. [13, 17]). Black-white and Hispanic-white differences in the number of visits were wider for adults who report poor or fair health (5.3 visits [4.0, 6.6] and 5.7 [4.3, 7.0], respectively) compared to excellent health (1.7 [1.2, 2.1] and 1.5 [1.1, 2.0], respectively) among adults who are full-year privately insured. CONCLUSIONS: The magnitudes of racial/ethnic disparities vary with level of health.

Impact of Recent Medicaid Expansions on Office-Based Primary Care and Specialty Care among the Newly Eligible.

OBJECTIVE: To quantify the effect of Medicaid expansions on office-based care among the newly eligible. DATA SOURCE: 2008-2014 Medical Expenditure Panel Survey. STUDY DESIGN: The main sample is adults age 26-64 with incomes ≤138% of poverty who were not eligible for Medicaid prior to the Affordable Care Act. For this population, difference-in-differences linear probability models compare utilization between expansion and nonexpansion states and between 2008-2013 and 2014. EXTRACTION METHODS: Medicaid eligibility is simulated using data on family relationships, state of residence, and income. PRINCIPAL FINDINGS: Relative to comparable adults in nonexpansion states, newly eligible adults in expansion states were 9.1 percentage points more likely to have any office-based primary care physician visit in 2014, a 21.4% increase from 2013 (p-value = .004); 6.9 percentage points more likely to have a specialist visit, a 25.2% increase from 2013 (p-value = .036); and 5.1 percentage points more likely to have a visit with a nurse practitioner, nurse, or physician assistant, a 34.5% increase from 2013 (p-value = .016). CONCLUSIONS: State Medicaid expansions in 2014 were associated with greater likelihoods of visits with a variety of office-based providers. The estimated effects are larger among newly eligible compared with previous estimates on broader populations of low-income adults.

The Impact of Obesity on Medical Care Costs and Labor Market Outcomes in the US.

BACKGROUND: The prevalence of obesity has risen dramatically in most countries of the world, and the economic consequences of obesity are not well understood. METHODS: We analyzed data from the Medical Expenditure Panel Survey (MEPS) for 2001-2015 and estimated the percentage of healthcare costs that were associated with adult obesity, both for the US as a whole and for the most populous states. We also reviewed the literature on the impact of obesity on economic outcomes such as medical care costs, employment, and wages. RESULTS: The percent of US national medical expenditures devoted to treating obesity-related illness in adults rose from 6.13% in 2001 to 7.91% in 2015, an increase of 29%. Substantial differences existed across states; in 2015, some states (AZ, CA, FL, NY) devoted 5%-6% of medical expenditures to obesity, whereas others (NC, OH, WI) spent >12% of all healthcare dollars on obesity. A review of previous literature that exploited natural experiments to estimate causal effects found that obesity raises medical care costs and lowers wages and the probability of employment. CONCLUSIONS: A substantial and rising percentage of healthcare costs are associated with obesity. This is true for the US, for individual states, for each category of expenditure, and for each type of payer. Previous literature generally found that obesity worsens economic outcomes, such as medical care costs, wages, and employment, and imposes negative external costs that may justify government intervention.

Public And Private Payments For Physician Office Visits.

We used data for 2014-15 from the Medical Expenditure Panel Survey to estimate standardized payments for nonelderly adults' physician office visits by type of insurance. Adults with public insurance, especially Medicaid, had substantially lower provider payments, out-of-pocket spending, and third-party payments than their peers with employer-sponsored or Marketplace insurance. Quantifying public-private payment differences can help clarify choices for financing health care among low-income Americans.

Savings in Medical Expenditures Associated with Reductions in Body Mass Index Among US Adults with Obesity, by Diabetes Status.

BACKGROUND: The prevalence of obesity has more than doubled in the USA in the past 30 years. Obesity is a significant risk factor for diabetes, cardiovascular disease, and other clinically significant co-morbidities. This paper estimates the medical care cost savings that can be achieved from a given amount of weight loss by people with different starting values of body mass index (BMI), for those with and without diabetes. This information is an important input into analyses of the cost effectiveness of obesity treatments and prevention programs. METHODS: Two-part models of instrumental variables were estimated using data from the Medical Expenditure Panel Survey (MEPS) for 2000-2010. Models were estimated for all adults as well as separately for those with and without diabetes. We calculated the causal impact of changes in BMI on medical care expenditures, cost savings for specific changes in BMI (5, 10, 15, and 20 %) from starting BMI levels ranging from 30 to 45 kg/m(2), as well as the total excess medical care expenditures caused by obesity. RESULTS: In the USA, adult obesity raised annual medical care costs by $US3,508 per obese individual, for a nationwide total of $US315.8 billion (year 2010 values). However, the relationship of medical care costs over BMI is J-shaped; costs rise exponentially in the range of class 2 and 3 obesity (BMI ≥35). The heavier the obese individual, the greater the reduction in medical care costs associated with a given percent reduction in BMI. Medical care expenditures are higher, and rise more with BMI, among individuals with diabetes than among those without diabetes. CONCLUSIONS: The savings from a given percent reduction in BMI are greater the heavier the obese individual, and are greater for those with diabetes than for those without diabetes. The results provide health insurers, employers, government agencies, and health economists with accurate estimates of the change in medical care expenditures resulting from weight loss, which is important information for calculating the cost effectiveness of interventions to prevent and treat obesity.