The U.S. Medicare Disproportionate Share Hospital program and capacity planning

Barnes, Beau Grant; Harp, Nancy L.

doi:10.1016/j.jaccpubpol.2018.07.005

Cited by 12 publications

(7 citation statements)

References 36 publications

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“…However, several empirical studies and gray literature sources provide evidence to the contrary. [30][31][32][33][34][35][36][37] In fact, hospitals participating since the Affordable Care Act-which dramatically increased the returns to the program by allowing participants to dispense outpatient prescriptions through an unlimited number of contract pharmacies 38 -appear to manipulate the DSH patient percentage to gain eligibility. 39 These post-2010 participants tend to be smaller and provide little more uncompensated care than nonparticipants.…”

Section: Challenges To Estimating the Causal Effect Of 340b Particimentioning

confidence: 99%

“…A challenge with this design is that it assumes hospitals cannot alter their adjusted DSH patient percentage. However, several empirical studies and gray literature sources provide evidence to the contrary 30‐37 . In fact, hospitals participating since the Affordable Care Act—which dramatically increased the returns to the program by allowing participants to dispense outpatient prescriptions through an unlimited number of contract pharmacies 38 —appear to manipulate the DSH patient percentage to gain eligibility 39 .…”

Section: Introductionmentioning

confidence: 99%

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Relationship between initiation of 340B participation and hospital safety‐net engagement

Nikpay

Buntin

Conti

2020

Health Services Research

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Objective The 340B program allows safety‐net hospitals to acquire discounted outpatient drugs and charge payers full price. We examined whether 340B participation increases safety‐net engagement. Data Sources 340B participation data, Medicare hospital cost reports, American Hospital Association Survey, and Schedule 990 nonprofit hospital tax returns. Study Design Quasi‐experimental difference‐in‐differences design comparing 340B hospitals (the “treatment” group) before and after participating to changes over time to three alternative “control” groups: all other nonprofit and public hospitals, hospitals that are not participating during our study, and hospitals that were not‐yet‐participating but started after 2015. Outcome measures include a range of safety‐net care measures that are alternatives to the standard uncompensated care: charity care, community benefit spending, charity care policies, and low‐profit service‐line provision. Data Extraction We extracted data on all nonprofit and public hospitals from 2011 to 2015. We linked 340B participation data to Medicare hospital cost reports and American Hospital Association data using Medicare hospital identifiers. 990 Data was linked on name and address. Principal Findings New 340B participation was not associated with a change in uncompensated care, but was associated with a 28.9 percent increase in charity care spending (SE = 8.8), or about $880,000 per hospital. However, total community benefit spending (including charity care) did not change. 340B was associated with an increase in the probability of offering discounted care (4.3 percentage points, SE = 1.6) from 84 to 88 percent and an increase in the income eligibility limit for discounted care (18.9 percentage points, SE = 5.6) from 294 to 313 percent. Participation was not associated with the probability of offering low‐profit medical care services. Conclusions Alternative measures show that newly participating hospitals may increase charity care, potentially through offering more patients discounted care. However, increases appear to be fully offset by reductions in other community benefit programs.

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Section: Challenges To Estimating the Causal Effect Of 340b Particimentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Relationship between initiation of 340B participation and hospital safety‐net engagement

Nikpay

Buntin

Conti

2020

Health Services Research

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“…3 For example, if earnings levels are replaced with earnings changes or consensus analyst forecast errors, then the same model describes earnings management to avoid earnings decreases (Burgstahler and Dichev, 1997) or to meet or beat analyst forecasts (Degeorge et al, 1999), respectively. Discontinuities in debt covenant slack ratios (Dichev and Skinner, 2002), insurance loss reserve ratios (Gaver and Paterson, 2004), working capital ratios (Dyreng et al, 2017), reported hedge fund monthly returns (Bollen and Pool, 2009), Medicare reimbursements (Barnes and Harp, 2018), baseball batting averages (Pope and Simonsohn, 2011), SAT scores among test re-takers (Pope and Simonsohn, 2011), reported tumor sizes (Samoylova et al, 2017), labor income (Chetty et al, 2011;Kleven and Waseem, 2013), size-contingent audit and disclosure requirements (Gao et al, 2009;Kausar et al, 2016;Bernard et al, 2018), marathon running times (Allen et al, 2017), reported statistical significance levels (Brodeur et al, 2016;Basu and Park, 2016), and perceived retail prices (e.g., Ginzberg, 1936;Stiving and Winer, 1997) are amenable to similar analysis. To apply the model to a given metric (e.g., reported liver tumor size around the 2 cm threshold for a patient's inclusion on the liver transplant waiting list in Samoylova et al, 2017), the dependent variable should be defined as the deviation from the relevant benchmark, and it should be scaled appropriately (Burgstahler and Chuk, 2015).…”

Section: Main Model Componentsmentioning

confidence: 99%

“…Our method generalizes to other distribution discontinuity scenarios where a decision-maker has both an opportunity and an incentive to move from just below to just above a benchmark or vice versa, including Medicare reimbursements (Barnes and Harp, 2018), labor tax avoidance (Chetty et al, 2011), marathon running times (Allen et al, 2017), and reported tumor sizes at the eligibility thresholds for the liver transplant waiting list (Samoylova et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Modeling the Determinants of Meet-or-Beat Behavior in Distribution Discontinuity Tests

Byzalov,

Basu

2018

SSRN Journal

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We develop new tests of distribution discontinuity conditional on multiple explanatory variables, which can be used to analyze meet-or-beat behavior around benchmarks. These tests combine Burgstahler and Dichev's (1997) intuition on benchmark-driven earnings management with a flexible statistical model that addresses important limitations of the existing distribution discontinuity tests. Our conditional discontinuity method offers large improvements in test performance relative to both histogram-based tests of the existence of distribution discontinuity and logit-based tests of the determinants of distribution discontinuity, and it changes some of the major findings in the earnings discontinuity literature. Our method is robust and easy to implement in standard statistical software. Future research in many fields could benefit by adopting our distribution discontinuity tests.

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“…We also contribute to recent studies that examine how health-related regulatory policies affect managerial decisions. Barnes and Harp (2018) find that Medicare statutory formulas influence bed capacity planning policies in urban hospitals, while Belina et al (2019) examine whether the new MLR provisions affected the stickiness of selling, general and administrative (SG&A) costs for publicly traded health insurers. They provide evidence that SG&A cost stickiness declined in the post-ACA period and conclude that the MLR provisions encourage managers to exhibit more cost cutting behavior in revenue decreasing periods.…”

Section: Introductionmentioning

confidence: 99%

Do Health Insurers Manage Their Medical Loss Ratios? At What Cost?

Plummer¹,

Wempe²

2021

JIR

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We use plan-level data to examine a reporting incentive unique to health insurers—the federal Affordable Care Act’s (ACA’s) Medical Loss Ratio (MLR) provisions—which require that health plans spend a specified percentage of premiums on claims or else pay policyholder rebates. While there are no penalties for noncompliance with the MLR provisions, incentives for insurers to comply include avoiding political and reputation costs, reducing administrative burdens, and eliminating rebate payments. We find that health plans with pre-managed MLRs— i.e., the MLRs that would be reported without reporting discretion—below the required MLR overstate claims, thereby increasing their MLRs and reducing or eliminating rebate payments. Overall, results suggest that overstating claims reduced rebate payments by approximately $190 million to $325 million for 20112013; i.e., about 10–17% of total rebates actually paid. We also find that plans with pre-managed MLRs significantly greater than the minimum required MLR understate claims, thereby improving plan earnings while still complying with the MLR provisions. These understatements average between 14–34% of plans’ pre-tax earnings.

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The U.S. Medicare Disproportionate Share Hospital program and capacity planning

Cited by 12 publications

References 36 publications

Relationship between initiation of 340B participation and hospital safety‐net engagement

Relationship between initiation of 340B participation and hospital safety‐net engagement

Modeling the Determinants of Meet-or-Beat Behavior in Distribution Discontinuity Tests

Do Health Insurers Manage Their Medical Loss Ratios? At What Cost?

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