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Measuring consumer responsiveness to medical care prices is a central issue in health economics and a key ingredient in the optimal design and regulation of health insurance markets. We leverage a natural experiment at a large self-insured firm that required all of its employees to switch from an insurance plan that provided free health care to a nonlinear, high-deductible plan. The switch caused a spending reduction between 11.8% and 13.8% of total firm-wide health spending. We decompose this spending reduction into the components of (i) consumer price shopping, (ii) quantity reductions, and (iii) quantity substitutions and find that spending reductions are entirely due to outright reductions in quantity. We find no evidence of consumers learning to price shop after two years in high-deductible coverage. Consumers reduce quantities across the spectrum of health care services, including potentially valuable care (e.g., preventive services) and potentially wasteful care (e.g., imaging services). To better understand these changes, we study how consumers respond to the complex structure of the highdeductible contract. Consumers respond heavily to spot prices at the time of care, reducing their spending by 42% when under the deductible, conditional on their true expected end-of-year price and their prior year end-of-year marginal price. There is no evidence of learning to respond to the true shadow price in the second year post-switch.

Enrollment in high-deductible health plans (HDHPs) has greatly increased in recent years. Policy makers and other stakeholders need the best available evidence about how these plans may affect health care cost and utilization, but the literature has not been comprehensively synthesized. We performed a systematic review of methodologically rigorous studies that examined the impact of HDHPs on health care utilization and costs. The plans were associated with a significant reduction in preventive care in seven of twelve studies and a significant reduction in office visits in six of eleven studies-which in turn led to a reduction in both appropriate and inappropriate care. Furthermore, bivariate analyses of data extracted from the included studies suggested that the plans may be associated with a reduction in appropriate preventive care and medication adherence. Current evidence suggests that HDHPs are associated with lower health care costs as a result of a reduction in the use of health services, including appropriate services.

Background Despite the substantial burden of obesity in the United States (US), data on the comprehensive range of comorbidities in different age groups is limited. This study assessed the prevalence of various comorbidities among people diagnosed with obesity (as per ICD-10 diagnosis code) across age cohorts and compared how they differ from people without obesity. Methods This cross-sectional study analyzed individuals from all four regions (Midwest, Northeast, South, and West) of the US who had continuous insurance coverage from 2018 to 2020, using a large health insurance claims database (Merative™ MarketScan ® ). Identification of disorders relied on ICD-10 diagnosis code in patient claims and their prevalence was calculated. Results Of 6,935,911 individuals, people with a diagnosis of obesity accounted for 22.0%, 33.6%, and 34.4% in the 18–39 years, 40–64 years, and ≥ 65 years age groups, respectively. Within age strata, the mean age of people with obesity was comparable with those without obesity. Comorbidity burden was significantly higher among people with obesity, but increased with age in both obesity and non-obesity groups. Comorbidities with highest prevalence in people with obesity included: (i) hypertension (18–39 years: 29.0%, 40–64 years: 66.2%, ≥ 65 years: 89.4%), (ii) dyslipidemia (18–39 years: 28.1%, 40–64 years: 65.4%, ≥ 65 years: 88.0%), (iii) depression or anxiety (18–39 years: 44.1%, 40–64 years: 39.0%, ≥ 65 years: 38.9%), and (iv) prediabetes (18–39 years: 17.1%, 40–64 years: 32.2%, ≥ 65 years: 35.3%). Notably, increased prevalence of cardiometabolic risk factors such as hypertension and dyslipidemia began at an earlier age in people with obesity as compared with those without obesity. Ratio of prevalence between obesity and non-obesity groups was highest for the 18–39 years age group, as compared to older groups. Disorders such as obstructive sleep apnea, osteoarthritis, type 2 diabetes, metabolic dysfunction-associated steatotic liver disease, coronary heart diseases (CHD), and chronic kidney diseases also exhibited substantial burden among those with obesity. Conclusions In this claims study, hypertension and dyslipidemia were the leading comorbidities in people with obesity, with an increasing prevalence with age. The burden of cardiometabolic comorbidities among the younger age group suggested potential risk for early onset of CHD in later life. Understanding the range of obesity-related comorbidities seen in this claims data may encourage healthcare professionals and healthcare systems to systematically diagnose and better manage these disorders. Further research using additional data sources can offer a more accurate view of the prevalence of obesity and its impact.

The Affordable Care Act was designed to provide financial protection to Americans in their use of the health care system. This required addressing two intertwined problems: cost barriers to accessing coverage and care, and barriers to comprehensive risk protection provided by insurance. We reviewed the evidence on whether the law was effective in achieving these goals. We found that the Affordable Care Act generated substantial, widespread improvements in protecting Americans against the financial risks of illness. The coverage expansions reduced uninsurance rates, especially relative to earlier forecasts; improved access to care; and lowered out-of-pocket spending. The insurance market reforms also made it easier for people to get and stay enrolled in coverage and ensured that those who were insured had true financial risk protection. But subsequent court decisions and congressional and executive branch actions have left millions uninsured and allowed the risk of inadequate insurance to resurface.

The share of employer-sponsored health insurance enrollment in self-funded plans grew from 55 percent in 2015 to 60 percent in 2021. Growth was concentrated in states with an initially low share but was widespread across most states (88.0 percent saw growth) and counties (78.2 percent saw growth). There were substantial differences in plan types in the self-funded and fully insured markets.The most common form of health insurance in the US is employersponsored health insurance (ESI), whether self-funded or fully insured.1,2 In self-funded arrangements, employers bear the financial risk of health expenditures (as opposed to insurers). This distinction is critical from a policy perspective, as self-funded plans are not subject to any state insurance regulations (for example, coverage requirements). Recent reports highlight the growing nationwide prevalence of self-funded ESI,3 but little is otherwise known about this critically important market. This article describes the growth of self-funded ESI enrollmentover time and its variation by geography, insurers and third-party administrators (TPAs), and plan types.The share of ESI enrollment in self-funded plans rose from 55 percent in 2015 to 60 percent in 2021 (exhibit 1), amounting to an approximate 2.8 million increase in enrollment in this market. Growth was concentrated in states where the share of ESI enrollment was below 50 percent in 2015. In these states, the self-funded share rose from 41 percent in 2015 to 55 percent in 2021. See online appendix 1 for state-level enrollment numbers in 2015 and 2021.

It is unknown to what extent rising drug costs are due to inflation in the prices of existing drugs versus the entry of new products. We used pricing data from First Databank and pharmacy claims from UPMC Health Plan to quantify the contribution of new versus existing drugs to the changes in costs of oral and injectable drugs used in the outpatient setting in 2008-16. The costs of oral and injectable brand-name drugs increased annually by 9.2 percent and 15.1 percent, respectively, largely driven by existing drugs. For oral and injectable specialty drugs, costs increased 20.6 percent and 12.5 percent, respectively, with 71.1 percent and 52.4 percent of these increases attributable to new drugs. Costs of oral and injectable generics increased by 4.4 percent and 7.3 percent, respectively, driven by new drug entry. The rising costs of generic and specialty drugs were mostly driven by new product entry, whereas the rising costs of brand-name drugs were due to existing drug price inflation.

Abstract Objectives The purpose of this analysis was to assess the frequency of inadequate response (IR) over 1 year from biologic initiation among Crohn’s disease (CD) patients in the United States using a claims-based algorithm. Baseline factors associated with IR to a biologic were also analyzed. Methods This was a retrospective cohort study using claims data from the HealthCore Integrated Research Database. Adult patients with CD who initiated a biologic (TNFi: adalimumab, certolizumab, infliximab; non-TNFi: natalizumab, ustekinumab, and vedolizumab) from 7/1/2016 to 8/31/2018 and had continuous enrollment ≥6 months before and ≥12 months after index date (date of first biologic claim) were included. The index biologic was defined as the first biologic prescribed during the study time period. The claims-based algorithm used in this study to identify IR was originally developed and validated in rheumatoid arthritis and was modified for CD patients. Patients were identified as having IR to their index biologic if during the 12 months after index date they had one or more of the following: low adherence (defined as proportion of days covered (PDC)<80%), switched/added new biologic, added a new conventional therapy, increased dose/frequency of biologic, addition or dose increase of oral glucocorticoids, used a new pain medication, or had surgery for CD. Baseline patient characteristics were compared between responders and IRs using Chi-square tests for categorical variables and t-tests for continuous variables. A multivariable logistic regression model was constructed to identify baseline characteristics associated with IR to the index biologic. Results A total of 2,437 CD patients were included in this analysis. Mean age was 41 years, 53% were female, 81% initiated a TNFi, and 19% initiated a non-TNFi as their index biologic (Table 1). Over the 1-year follow-up period, 62% of CD patients had an IR to their biologic: 41% of patients had low adherence, 14% switched/added a new biologic, 13% added a new conventional therapy, 12% had a dose/frequency increase of their index biologic, 12% had an addition/dose increase of oral glucocorticoids, 8% used a new pain medication, and 5% had surgery. Inadequate responders were more likely to be female (odds ratio (OR)=1.36; p<0.001), have historical use of TNFi (OR=1.94; p<0.001), and be on a consumer-driven health plan (OR=1.28; p<0.001); while patients with baseline use of conventional therapy were more likely to be responders (OR=0.72; p<0.001) (Table 2). Conclusion Over 62% of CD patients had an inadequate response to their index biologic within 1 year after initiation, mostly driven by low adherence. This modified claims-based algorithm for CD appears useful to classify inadequate responders in health plan claims data. Additional research is needed to further validate this algorithm in a clinical setting.

To mark the 30th anniversary of The American Journal of Managed Care (AJMC), each issue in 2025 includes a special feature: reflections from a thought leader on what has changed-and what has not-over the past 3 decades and what's next for managed care. The October issue features a conversation with Ge Bai, PhD, CPA, professor of accounting at Johns Hopkins Carey Business School and professor of health policy and management at Johns Hopkins Bloomberg School of Public Health in Baltimore, Maryland.

The growing awareness of the wide variation in health care prices, increased availability of price data, and increased patient cost sharing are expected to drive patients to shop for lower-cost medical services. We conducted a nationally representative survey of 2,996 nonelderly US adults who had received medical care in the previous twelve months to assess how frequently patients are price shopping for care and the barriers they face in doing so. Only 13 percent of respondents who had some out-of-pocket spending in their last health care encounter had sought information about their expected spending before receiving care, and just 3 percent had compared costs across providers before receiving care. The low rates of price shopping do not appear to be driven by opposition to the idea: The majority of respondents believed that price shopping for care is important and did not believe that higher-cost providers were of higher quality. Common barriers to shopping included difficulty obtaining price information and a desire not to disrupt existing provider relationships.