Evidence map›Paper›PMID 25634500›Full record

ArticleThe European journal of health economics : HEPAC : health economics in prevention and care2016

Is the United States in the middle of a healthcare bubble?

Wen-Yi Chen, Yia-Wun Liang, Yu-Hui Lin

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Article in The European journal of health economics : HEPAC : health economics in prevention and care, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Healthcare debts in the United States: a silent fight.Annals of medicine and surgery (2012) · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Wen-Yi ChenDepartment of Senior Citizen Service Management, National Taichung University of Science and Technology, 193, Sec 1, Sanmin Road, Taichung, 40343, Taiwan, ROC. chenwen@nutc.edu.tw.
Yia-Wun LiangDepartment of Senior Citizen Service Management, National Taichung University of Science and Technology, 193, Sec 1, Sanmin Road, Taichung, 40343, Taiwan, ROC. ywliang@nutc.edu.tw.
Yu-Hui LinDepartment of Business Administration, NanKai University of Technology, 568 Chung Cheng Road, Tsao Tun, Nan Tou, 54243, Taiwan, ROC. lin2138@nkut.edu.tw.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study investigates the possibility of multiple healthcare bubbles in the US healthcare market.

methodsWe first applied the newly developed Generalized Sup ADF test to locate multiple healthcare bubble episodes and then estimated the switching regression model specifying multiple healthcare bubble periods to evaluate to what extent macroeconomic variables (such as the interest rate, public debt, and fiscal deficit) and public financing healthcare programs influence the magnitude of healthcare bubbles in terms of the deviation of the medical care price inflation from either the overall price inflation or the money wage growth.

resultsOur results show that expansionary monetary and fiscal policies play important roles in determining the deviation of the medical care price inflation from the overall price inflation and that the net government debt has a positive impact on the deviation of the medical care price inflation from the money wage growth. The US healthcare market is now in the middle of a healthcare bubble, and this healthcare bubble has developed slowly and has lasted for approximately 3 decades, mirroring an increased societal preference for healthcare.

conclusionsPolicymakers in the US should cautiously consider the fact that healthcare bubbles must imply a misallocation of resources into healthcare, leading to negative consequences on the sustainability of the healthcare system.

Indexed as

PolicyCosts and Cost AnalysisHealth Care SectorHumansInflation, EconomicModels, EconometricUnited StatesGeneralized Sup ADF testHealthcare bubbleSwitching regression model

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.