title: Assessing the Complex and Evolving Relationship between Charges and Payments in US Hospitals: 1996 - 2012.
abstract: BACKGROUND
  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.
  
  
  METHODS
  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.
  
  
  RESULTS
  The average amount paid per $1 charged varies significantly across three dimensions: payer, year, and cause. Among the 10 largest causes of health care spending, average payments range from 23 to 55 cents per dollar charged. Over time, the amount paid per dollar charged is decreasing for those with private or public insurance, signifying that inpatient charges are increasing faster than the amount insurers pay. Conversely, the amount paid by out-of-pocket payers per dollar charged is increasing over time for several causes. Applying our estimates to a nationally representative hospital charge sample generates payment estimates which align with the official US estimates of inpatient spending.
  
  
  CONCLUSIONS
  The amount paid per $1 charged fluctuates significantly depending on the cause of a health care encounter and the primary payer. In addition, the amount paid per charge is changing over time. Transparent accounting of hospital spending requires a detailed assessment of the substantial and growing gap between charges and payments. Understanding what is driving this divergence and generating accurate spending estimates can inform efforts to contain health care spending.
authors.affiliation: Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America.
authors.forename: Hannah
authors.initials: H
authors.lastname: Hamavid
authors.affiliation: Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America.
authors.forename: Maxwell
authors.initials: M
authors.lastname: Birger
authors.affiliation: Global Health Group, University of California San Francisco, San Francisco, United States of America.
authors.forename: Anne G
authors.initials: AG
authors.lastname: Bulchis
authors.affiliation: Northwell Health, Great Neck, New York, United States of America.
authors.forename: Liya
authors.initials: L
authors.lastname: Lomsadze
authors.affiliation: Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America.
authors.forename: Jonathan
authors.initials: J
authors.lastname: Joseph
authors.affiliation: Global Health Group, University of California San Francisco, San Francisco, United States of America.
authors.forename: Ranju
authors.initials: R
authors.lastname: Baral
authors.affiliation: David Geffen School of Medicine, University of California Los Angeles, Los Angeles, United States of America.
authors.forename: Anthony L
authors.initials: AL
authors.lastname: Bui
authors.affiliation: Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America.
authors.forename: Cody
authors.initials: C
authors.lastname: Horst
authors.affiliation: Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America.
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Johnson
authors.affiliation: Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America.
authors.forename: Joseph L
authors.initials: JL
authors.lastname: Dieleman
mesh_terms: D016208:Databases, Factual; D003695:Delivery of Health Care; D004469:Economics, Hospital; D017048:Health Care Costs; D005102:Health Expenditures; D006761:Hospitals; D006801:Humans; D007348:Insurance, Health; D018803:Models, Economic; D015233:Models, Statistical; D012044:Regression Analysis; D014481:United States