Predicting inpatient hospital payments in the United States: a retrospective analysis (original) (raw)
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PloS one, 2016
In 2013 the United States spent $2.9 trillion on health care, more than in any previous year. Much of the debate around slowing health care spending growth focuses on the complicated pricing system for services. Our investigation contributes to knowledge of health care spending by assessing the relationship between charges and payments in the inpatient hospital setting. In the US, charges and payments differ because of a complex set of incentives that connect health care providers and funders. Our methodology can also be applied to adjust charge data to reflect actual spending. We extracted cause of health care encounter (cause), primary payer (payer), charge, and payment information for 50,172 inpatient hospital stays from 1996 through 2012. We used linear regression to assess the relationship between charges and payments, stratified by payer, year, and cause. We applied our estimates to a large, nationally representative hospital charge sample to estimate payments. The average amo...
Private insurers pay widely varying prices for inpatient care across hospitals. Previous research indicates that certain hospitals use market clout to obtain higher payment rates, but there have been few in-depth examinations of the relationship between hospital characteristics and pricing power. This study used private insurance claims data to identify hospitals receiving inpatient prices significantly higher or lower than the median in their market. High-price hospitals, compared to other hospitals, tend to be larger; be major teaching hospitals; belong to systems with large market shares; and provide specialized services, such as heart transplants and Level I trauma care. High-price hospitals also receive significant revenues from nonpatient sources, such as state Medicaid disproportionate-share hospital funds, and they enjoy healthy total financial margins. Quality indicators for high-price hospitals were mixed: High-price hospitals fared much better than low-price hospitals did in U.S. News & World Report rankings, which are largely based on reputation, while generally scoring worse on objective measures of quality, such as postsurgical mortality rates. Thus, insurers may face resistance if they attempt to steer patients away from high-price hospitals because these facilities have good reputations and offer specialized services that may be unique in their markets.
We use a panel of hospitals from Washington state to examine the impact of government reimbursement on a provider's costs. We find that providers change their relative patient mix when Medicare and Medicaid lower reimbursement rates. On a percentage change basis, the magnitudes of these changes are small; however, the overall economic impacts are quite large. Additionally, our findings indicate that a number of other factors significantly influence a provider's costs, including patient demographics, initial illness severity and input market conditions facing the firm. We thank two anonymous reviewers for their helpful comments. We also thank William Greene for valuable econometric advice when making revisions to this manuscript. Remaining errors are our own.
Health services research, 2018
To examine the impact of the Affordable Care Act's coverage expansion on safety-net hospitals (SNHs). Nine Medicaid expansion states. Differences-in-differences (DID) models compare payer-specific pre-post changes in inpatient stays of adults aged 19-64 years at SNHs and non-SNHs. 2013-2014 Healthcare Cost and Utilization Project State Inpatient Databases. On average per quarter postexpansion, SNHs and non-SNHs experienced similar relative decreases in uninsured stays (DID = -2.2 percent, p = .916). Non-SNHs experienced a greater percentage increase in Medicaid stays than did SNHs (DID = 13.8 percent, p = .041). For SNHs, the average decrease in uninsured stays (-146) was similar to the increase in Medicaid stays (153); privately insured stays were stable. For non-SNHs, the decrease in uninsured (-63) plus privately insured (-33) stays was similar to the increase in Medicaid stays (105). SNHs and non-SNHs experienced a similar absolute increase in Medicaid, uninsured, and privat...
Journal of Health Economics, 1996
In an interesting and important policy paper, Avi examine whether hospital inpatients with different types of insurance are treated differently. They find that marginal cost differ substantially across payers. However, we demonstrate that their estimates of marginal costs are implausibly low, on average, and conflict with other well-established knowledge about hospital costs and markets. We also find that hospitals treat patients nearly uniformly, regardless of payment source, using an alternative measure of service intensity or quality. JEL classification: I11; L15; L13
—Recently hospitals struggle to control the cost of care while maintaining optimal outcomes. To respond to this challenge, we developed an interactive web platform which utilizes a multiple linear regression model. The user can create and furthermore alter a clinical scenario, during a patient hospitalization to see the dynamic prediction of total charges, via interactive sessions. The R 2 value of our model is 0.655 and the standard error of the estimate is $38,732. Predictors with high coefficient scores include the cardioverter implantation, mechanical ventilation, implant of pulsation balloon and hospital-acquired conditions such as staphylococcus aureus septicemia. Our findings indicate that (a) integration of predictive models into clinical decision support systems is feasible and use of regression methods provide direct feedback on the effect of any clinical practice to the in-hospital charges (b) medical claims data can provide a useful estimation of the in-hospital charges (c) hospital acquired conditions have significant impact on the in-hospital charges.
THE PRICE AIN'T RIGHT? HOSPITAL PRICES AND HEALTH SPENDING ON THE PRIVATELY INSURED
We use insurance claims data covering 28 percent of individuals with employer-sponsored health insurance in the US to study the variation in health spending on the privately insured, examine the structure of insurer-hospital contracts, and analyze the variation in hospital prices across the nation. Health spending per privately insured beneficiary differs by a factor of three across geographic areas and has a very low correlation with Medicare spending. For the privately insured, half of the spending variation is driven by price variation across regions and half is driven by quantity variation. Prices vary substantially across regions, across hospitals within regions, and even within hospitals. For example, even for a near homogenous service such as lower-limb MRIs, about a fifth of the total case-level price variation occurs within a hospital in the cross-section. Hospital market structure is strongly associated with price levels and contract structure. Prices at monopoly hospitals are 12 percent higher than those in markets with four or more rivals. Monopoly hospitals also have contracts that load more risk on insurers (e.g. they have more cases with prices set as a share of their charges). In concentrated insurer markets the opposite occurs -hospitals have lower prices and bear more financial risk. Examining the 366 mergers and acquisitions that occurred between 2007 and 2011, we find that prices increased by over 6 percent when the merging hospitals were geographically close (e.g. 5 miles or less apart), but not when the hospitals were geographically distant (e.g. over 25 miles apart). JEL Codes: I11, L10, L11. for outstanding research assistance. The opinions expressed in this paper and any errors are those of the authors alone. More details on our analysis and downloadable data, including our roster of hospital mergers, can be found online at www.healthcarepricingproject.org. 1 Our discussion of Medicare is focused on the traditional, publicly administered Medicare program. See Curtu et al. (2017) for a comparison of the traditional, public Medicare program and the privately administered Medicare Advantage program. The remainder of the population have coverage from the Medicaid program, other payers (e.g. the Veterans Administration), or are uninsured.
Profile of Insurance Coverage in a National Inpatient Sample
American Journal of Public Health Research, 2013
To identify the hospitals most strongly impacted by health insurance trends, this study investigated the relationships between hospital characteristics and patterns of insurance coverage in a national inpatient sample. Data from the 2007 Nationwide Inpatient Sample of the Healthcare Cost and Utilization Project were used to examine hospital characteristics, aggregated patient characteristics, and payer mix (defined as rates of Medicare, Medicaid, private insurance, and uninsured). Medicare was expected to cover nearly half of all inpatient admissions; however, hospitals showed a wide range of percentages for all payers, and some facilities reported up to 61.5% of visits from uninsured patients. Significant multivariate differences in insurance coverage resulted from bed size, location, region, and patient age, gender, racial, and socioeconomic distributions. Results suggest that reimbursement policy changes may disproportionally impact certain hospitals based on their characteristics and/or patient distribution and may be particularly informative in the current era of potential system-wide reform.