Evidence map›Paper›PMID 38551735›Full record

ArticleInternational journal of health economics and management2024

Contribution of high-technology procedures to public healthcare expenditures: the case of ischemic heart disease in Portugal, 2002-2015.

Wenkang Ma, Ana Timóteo, Vanessa Ribeiro, Céu Mateus, Julian Perelman

Abstract read
In one paragraph

Article in International journal of health economics and management, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Wenkang MaDepartment of Economics and Related Studies, University of York, York, England, UK.ORCID http://orcid.org/0000-0003-1633-3187
Ana TimóteoNova Medical School, Nova University of Lisbon, Lisbon, Portugal.
Vanessa RibeiroCentral Administration of the Health System, Lisbon, Portugal.
Céu MateusLancaster University, Lancaster, England, UK.
Julian PerelmanComprehensive Health Research Center, Nova University of Lisbon, Lisbon, Portugal. JPerelman@ensp.unl.pt.ORCID http://orcid.org/0000-0001-6634-9000

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The magnitude of the impact of technological innovations on healthcare expenditure is unclear. This paper estimated the impact of high-technology procedures on public healthcare expenditure for patients with ischemic heart disease (IHD) in Portugal. The Blinder-Oaxaca decomposition method was applied to Portuguese NHS administrative data for IHD discharges during two periods, 2008-2015 vs. 2002-2007 (N = 434,870). We modelled per episode healthcare expenditures on the introduction of new technologies, adjusting for GDP, patient age, and comorbidities. The per episode healthcare expenditure was significantly higher in 2008-2015 compared to 2002-2007 for IHD discharges. The increase in the use of high-technology procedures contributed to 28.6% of this growth among all IHD patients, and to 18.4%, 6.8%, 11.1%, and 29.2% for acute myocardial infarction, unstable angina, stable angina, and other IHDs, respectively. Changes in the use of stents and embolic protection and/or coronary brachytherapy devices were the largest contributors to expenditure growth. High-technology procedures were confirmed as a key driver of public healthcare expenditure growth in Portugal, contributing to more than a quarter of this growth.

Indexed as

Health ExpendituresMyocardial IschemiaAgedFemaleHumansMaleMiddle AgedPortugalDecomposition methodsHealth expenditureIschemic heart diseaseMedical technologyPortugal

Identifiers

PMID38551735
PMCPMC11445372

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.