Evidence map›Paper›PMID 35762465›Full record

ArticleHealth economics2022

How real can we get in generating real world evidence? Exploring the opportunities of routinely collected administrative data for evaluation of medical devices.

Benedetta Pongiglione, Aleksandra Torbica

Open access · hybridAbstract read
In one paragraph

Article in Health economics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.9field-weighted citation impact, top 10% of its field
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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

2 authors at 1 institution in 1 country.

Benedetta PongiglioneCentre for Research on Health and Social Care Management, Bocconi University, Milano, Lombardia, Italy.ORCID 0000-0001-8539-1554
Aleksandra TorbicaCentre for Research on Health and Social Care Management, Bocconi University, Milano, Lombardia, Italy.
Bocconi University · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Real-world data are considered a potentially valuable source of evidence for assessing medical technologies in clinical practice, but their widespread use is hampered by numerous challenges. Using the case of coronary stents in Italy, we investigate the potential of administrative databases for estimating costs and health outcomes associated with the use of medical devices in real world conditions. An administrative dataset was created ad hoc by merging hospital records from patients admitted between 2013 and 2019 for stent implantations with ambulatory records, pharmaceutical use data and vital statistics. Health outcomes were multifold: all-cause and cardiac mortality and myocardial infarction, within 30 days, 1, 2, 5 years. Costs were estimated from the National Health System perspective. We used multivariable Cox models and propensity score (PS) methods (PS matching; stratification on PS; inverse probability of treatment weighting using PS; PS adjustment). 257,907 coronary stents were implanted in 113,912 patients. For all health outcomes and follow-up times, and across all methods, patients receiving drug-eluting stents (DES) presented lower risk. For all-cause mortality, the DES patient advantage over bare-metal stent (BMS) patients declined over time but remained significant even at 5 years. For myocardial infarction, results remained quite stable. The DES group presented lower cumulative total costs (ranging from 3264 to 2363 Euros less depending on methods). Our results confirm the consolidated evidence of the benefits of DES compared to BMS. The consistency of results across methods suggests internal validity of the study, while highlighting strengths and limitations of each depending on research context. Administrative data yield great potential to perform comparative effectiveness and cost-effectiveness analysis of medical devices provided certain conditions are met.

Indexed as

Datasets as TopicDrug-Eluting StentsHumansItalyMyocardial InfarctionProportional Hazards ModelsRisk FactorsStentsTreatment Outcomeadministrative datamedical devicepropensity scorereal-world datareal-world evidence

Identifiers

PMID35762465
PMCPMC9796733
OpenAlexW4283650669

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.