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Factors Associated With Increases in US Health Care Spending, 1996-2013.
Dieleman, Joseph L; Squires, Ellen; Bui, Anthony L; Campbell, Madeline; Chapin, Abigail; Hamavid, Hannah; Horst, Cody; Li, Zhiyin; Matyasz, Taylor; Reynolds, Alex; Sadat, Nafis; Schneider, Matthew T; Murray, Christopher J L.
Afiliação
  • Dieleman JL; Institute for Health Metrics and Evaluation, Seattle, Washington.
  • Squires E; Institute for Health Metrics and Evaluation, Seattle, Washington.
  • Bui AL; David Geffen School of Medicine, University of California, Los Angeles.
  • Campbell M; Institute for Health Metrics and Evaluation, Seattle, Washington.
  • Chapin A; Institute for Health Metrics and Evaluation, Seattle, Washington.
  • Hamavid H; Institute for Health Metrics and Evaluation, Seattle, Washington.
  • Horst C; Institute for Health Metrics and Evaluation, Seattle, Washington.
  • Li Z; Institute for Health Metrics and Evaluation, Seattle, Washington.
  • Matyasz T; Institute for Health Metrics and Evaluation, Seattle, Washington.
  • Reynolds A; Institute for Health Metrics and Evaluation, Seattle, Washington.
  • Sadat N; Institute for Health Metrics and Evaluation, Seattle, Washington.
  • Schneider MT; Institute for Health Metrics and Evaluation, Seattle, Washington.
  • Murray CJL; Institute for Health Metrics and Evaluation, Seattle, Washington.
JAMA ; 318(17): 1668-1678, 2017 11 07.
Article em En | MEDLINE | ID: mdl-29114831
ABSTRACT
Importance Health care spending in the United States increased substantially from 1995 to 2015 and comprised 17.8% of the economy in 2015. Understanding the relationship between known factors and spending increases over time could inform policy efforts to contain future spending growth.

Objective:

To quantify changes in spending associated with 5 fundamental factors related to health care spending in the United States population size, population age structure, disease prevalence or incidence, service utilization, and service price and intensity. Design and

Setting:

Data on the 5 factors from 1996 through 2013 were extracted for 155 health conditions, 36 age and sex groups, and 6 types of care from the Global Burden of Disease 2015 study and the Institute for Health Metrics and Evaluation's US Disease Expenditure 2013 project. Decomposition analysis was performed to estimate the association between changes in these factors and changes in health care spending and to estimate the variability across health conditions and types of care. Exposures Change in population size, population aging, disease prevalence or incidence, service utilization, or service price and intensity. Main Outcomes and

Measures:

Change in health care spending from 1996 through 2013.

Results:

After adjustments for price inflation, annual health care spending on inpatient, ambulatory, retail pharmaceutical, nursing facility, emergency department, and dental care increased by $933.5 billion between 1996 and 2013, from $1.2 trillion to $2.1 trillion. Increases in US population size were associated with a 23.1% (uncertainty interval [UI], 23.1%-23.1%), or $269.5 (UI, $269.0-$270.0) billion, spending increase; aging of the population was associated with an 11.6% (UI, 11.4%-11.8%), or $135.7 (UI, $133.3-$137.7) billion, spending increase. Changes in disease prevalence or incidence were associated with spending reductions of 2.4% (UI, 0.9%-3.8%), or $28.2 (UI, $10.5-$44.4) billion, whereas changes in service utilization were not associated with a statistically significant change in spending. Changes in service price and intensity were associated with a 50.0% (UI, 45.0%-55.0%), or $583.5 (UI, $525.2-$641.4) billion, spending increase. The influence of these 5 factors varied by health condition and type of care. For example, the increase in annual diabetes spending between 1996 and 2013 was $64.4 (UI, $57.9-$70.6) billion; $44.4 (UI, $38.7-$49.6) billion of this increase was pharmaceutical spending. Conclusions and Relevance Increases in US health care spending from 1996 through 2013 were largely related to increases in health care service price and intensity but were also positively associated with population growth and aging and negatively associated with disease prevalence or incidence. Understanding these factors and their variability across health conditions and types of care may inform policy efforts to contain health care spending.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Risk_factors_studies Limite: Female / Humans / Male País/Região como assunto: America do norte Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Risk_factors_studies Limite: Female / Humans / Male País/Região como assunto: America do norte Idioma: En Ano de publicação: 2017 Tipo de documento: Article