22 research outputs found

    Analysis of variation in charges and prices paid for vaginal and caesarean section births: a cross-sectional study

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    This is the publisher's version. To view the original publication, see http://bmjopen.bmj.comThis article aims to examine the between-hospital variation of charges and discounted prices for uncomplicated vaginal and caesarean section deliveries, and to determine the institutional and market-level characteristics that influence adjusted charges. Using data from the California Office of Statewide Health Planning and Development (OSHPD), we conducted a cross-sectional study of all privately insured patients admitted to California hospitals in 2011 for uncomplicated vaginal delivery (diagnosis-related group (DRG) 775) or uncomplicated caesarean section (DRG 766). Hospital charges and discounted prices were adjusted for each patient's clinical and demographic characteristics. We analysed 76,766 vaginal deliveries and 32,660 caesarean sections in California in 2011. After adjusting for patient demographic and clinical characteristics, we found that the average California woman could be charged as little as US3,296orasmuchasUS3,296 or as much as US37,227 for a vaginal delivery and US8,312US8,312–US70,908 for a caesarean section depending on which hospital she was admitted to. The discounted prices were, on an average, 37% of the charges. We found that hospitals in markets with middling competition had significantly lower adjusted charges for vaginal deliveries, while hospitals with higher wage indices and casemixes, as well as for-profit hospitals, had higher adjusted charges. Hospitals in markets with higher uninsurance rates charged significantly less for caesarean sections, while for-profit hospitals and hospitals with higher wage indices charged more. However, the institutional and market-level factors included in our models explained only 35–36% of the between-hospital variation in charges. These results indicate that charges and discounted prices for two common, relatively homogeneous diagnosis groups—uncomplicated vaginal delivery and caesarean section—vary widely between hospitals and are not well explained by observable patient or hospital characteristics

    Variation in charges for 10 common blood tests in California hospitals: A cross-sectional analysis

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    Objectives: To determine the variation in charges for 10 common blood tests across California hospitals in 2011, and to analyse the hospital and market-level factors that may explain any observed variation. Design setting and participants: We conducted a cross-sectional analysis of the degree of charge variation between hospitals for 10 common blood tests using charge data reported by all non-federal California hospitals to the California Office of Statewide Health Planning and Development in 2011. Outcome measures: Charges for 10 common blood tests at California hospitals during 2011. Results: We found that charges for blood tests varied significantly between California hospitals. For example, charges for a lipid panel ranged from US10toUS10 to US10 169, a thousand-fold difference. Although government hospitals and teaching hospitals were found to charge significantly less than their counterparts for many blood tests, few other hospital characteristics and no market-level predictors significantly predicted charges for blood tests. Our models explained, at most, 21% of the variation between hospitals in charges for the blood test in question. Conclusions: These findings demonstrate the seemingly arbitrary nature of the charge setting process, making it difficult for patients to act as true consumers in this era of ‘consumer-directed healthcare.

    Price effects of a hospital merger: Heterogeneity across health insurers, hospital products, and hospital locations

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    In most studies on hospital merger effects, the unit of observation is the merged hospital, whereas the observed price is the weighted average across hospital products and across payers. However, little is known about whether price effects vary between hospital locations, products, and payers. We expand existing bargaining models to allow for heterogeneous price effects and use a difference-in-differences model in which price changes at the merging hospitals are compared with price changes at comparison hospitals. We find evidence of heterogeneous price effects across health insurers, hospital products and hospital locations. These findings have implications for ex ante merger scrutiny

    THE AFFORDABLE CARE ACT AND AMBULANCE RESPONSE TIMES

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    This study contributes to the literature on supply-side adjustments to insurance expansions by examining the effect of the Affordable Care Act (ACA) on ambulance response times. Exploiting temporal and geographic variation in the implementation of the ACA as well as pre-treatment differences in uninsured rates, we estimate that the expansions of private and Medicaid coverage under the ACA combined to slow ambulance response times by an average of 19%. We conclude that, through extending coverage to individuals who, in its absence, would not have availed themselves of emergency medical services, the ACA added strain to emergency response systems

    Variation in charges for emergency department visits across California

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    Study objective Previous studies have shown that charges for inpatient and clinic procedures vary substantially; however, there are scant data on variation in charges for emergency department (ED) visits. Outpatient ED visits are typically billed with current procedural terminology-coded levels to standardize the intensity of services received, providing an ideal element on which to evaluate charge variation. Thus, we seek to analyze the variation in charges for each level of ED visits and examine whether hospital- and market-level factors could help predict these charges. Methods Using 2011 charge data provided by every nonfederal California hospital to the Office of Statewide Health Planning and Development, we analyzed the variability in charges for each level of ED visits and used linear regression to assess whether hospital and market characteristics could explain the variation in charges. Results Charges for each ED visit level varied widely; for example, charges for a level 4 visit ranged from 275to275 to 6,662. Government hospitals charged significantly less than nonprofit hospitals, whereas hospitals that paid higher wages, served higher proportions of Medicare and Medicaid patients, and were located in areas with high costs of living charged more. Overall, our models explained only 30% to 41% of the between-hospital variation in charges for each level of ED visits. Conclusion Our findings of extensive charge variation in ED visits add to the literature in demonstrating the lack of systematic charge setting in the US health care system. These widely varying charges affect the hospital bills of millions of uninsured patients and insured patients seeking care out of network and continue to play a role in many aspects of health care financing. © 2014 by the American College of Emergency Physicians

    Variation in charges for 10 common blood tests in California hospitals: A cross-sectional analysis

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    Objectives: To determine the variation in charges for 10 common blood tests across California hospitals in 2011, and to analyse the hospital and market-level factors that may explain any observed variation. Design setting and participants: We conducted a cross-sectional analysis of the degree of charge variation between hospitals for 10 common blood tests using charge data reported by all non-federal California hospitals to the California Office of Statewide Health Planning and Development in 2011. Outcome measures: Charges for 10 common blood tests at California hospitals during 2011. Results: We found that charges for blood tests varied significantly between California hospitals. For example, charges for a lipid panel ranged from US10toUS10 to US10 169, a thousand-fold difference. Although government hospitals and teaching hospitals were found to charge significantly less than their counterparts for many blood tests, few other hospital characteristics and no market-level predictors significantly predicted charges for blood tests. Our models explained, at most, 21% of the variation between hospitals in charges for the blood test in question. Conclusions: These findings demonstrate the seemingly arbitrary nature of the charge setting process, making it difficult for patients to act as true consumers in this era of ‘consumer-directed healthcare.
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