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Record W4413992600 · doi:10.1080/13696998.2025.2555144

Real world evidence on health care resource utilization and economic burden of arrhythmias in patients with COPD

2025· article· en· W4413992600 on OpenAlexaff
Pierantonio Russo, Ramaa Nathan, Juliana Poh, Harjeet Singh, Brent Wright, Ken Boyle, Erik Hendrickson

Bibliographic record

VenueJournal of Medical Economics · 2025
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsEVERSANA (Canada)
FundersiRhythm Technologies
KeywordsMedicineCOPDReal world evidenceHealth careIntensive care medicineResource (disambiguation)Internal medicineEconomic growth

Abstract

fetched live from OpenAlex

AIMS: Cardiac arrhythmias are common in chronic obstructive pulmonary disease (COPD) and are associated with poor outcomes. Their impact on healthcare resource utilization (HCRU) and costs is increasingly recognized. The incremental economic burden of arrhythmias in patients with COPD and the impact of early detection using ambulatory electrocardiogram (AECG) monitors remain unknown. This real-world analysis quantified incremental HCRU and costs associated with arrhythmia in COPD, and the impact of early detection through AECG monitoring. METHODS: We conducted a retrospective claims analysis using the Merative MarketScan database (2006-2024) to identify patients with COPD aged ≥ 18 years. We examined three sub-cohort pairs of these patients, with and without arrhythmia, and those who underwent AECG monitoring, comparing demographics, hospitalization rates, all-cause readmissions within 30 days, emergency room visits, and total care costs. Each cohort pair was reweighted using entropy balancing on the following baseline variables: age, sex, region, insurance type, and comorbidities. The HCRU and cost drivers were analyzed over 24 months from the index date, and significance was assessed using Tweedie distributions for costs and zero-inflated binomial distributions for HCRU rates. RESULTS: Healthcare costs and HCRU were significantly higher in the 71,585 patients with COPD and arrhythmia than in the 261,188 matched patients without arrhythmia. In the second comparison, patients with COPD and arrhythmia who were monitored using AECG had a higher utilization rate than their counterparts who did not have arrhythmia. In the third comparison, patients with COPD and arrhythmia who were monitored using AECG had lower utilization than their counterparts who were never monitored. LIMITATIONS: As a retrospective analysis of claims data, this study was limited by the population under investigation and the availability of the measured variables. CONCLUSIONS: Arrhythmias in COPD substantially increase healthcare utilization and costs. Early detection by AECG monitoring may mitigate this burden.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.034
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.328
Teacher spread0.304 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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