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Record W7038323936

Healthcare Costs And Resource Utilization In Chronic Pain Patients Treated With Extended-Release Formulations Of Tapentadol, Oxycodone, Or Morphine Stratified By Type Of Pain: A Retrospective Claims Analysis, 2012–2016

2019· other· en· W7038323936 on OpenAlexaboutno aff

Bibliographic record

VenueDove Medical Press (Taylor and Francis Group) · 2019
Typeother
Languageen
FieldComputer Science
TopicParallel Computing and Optimization Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsRetrospective cohort studyChronic painMedical prescriptionHealth careOxycodoneCohortEmergency departmentMedicare Advantage
DOInot available

Abstract

fetched live from OpenAlex

Vladimir Zah,1 Rowe B Brookfield,2 Martina Imro,1 Simona Tatovic,1 Jovana Pelivanovic,1 Djurdja Vukicevic1 1Health Economics and Outcomes Research Department, ZRx Outcomes Research Inc, Mississauga, Ontario, Canada; 2Field Medical Affairs, Depomed, Inc, Newark, CA, USACorrespondence: Vladimir ZahHealth Economics and Outcomes Research Department, ZRx Outcomes Research Inc., 3373 Cawthra Road, Mississauga, Ontario, CanadaTel/fax +14169534427Email vzah@outcomesresearch.caPurpose: Chronic pain treatment imposes a substantial economic burden on US society. Treatment costs may vary across subgroups of patients with different types of pain. The aim of our study was to compare healthcare costs (HC) and resource utilization in musculoskeletal (MP), neuropathic (NP), and cancer pain (CaP) patients treated with long-acting opioids (LAO), using real-world evidence.Patients and methods: We compared total HC and resource utilization in subgroups of chronic pain patients (MP, NP or CaP) treated with three LAO alternatives: morphine-sulfate extended-release (MsER), oxycodone ER (OxnER) and tapentadol ER (TapER). Retrospective claims data were analyzed in the IBM Truven Health MarketScan® Commercial Claims Database (October 2012 through March 2016). All patients were continuously health plan enrolled for at least 12 months before the index date (first LAO prescription date) and during the LAO-treatment period. The cohorts were propensity-score matched.Results: A total of 2824 TapER-treated patients were matched to 16,716 OxnER-treated patients, while 2827 TapER patients were matched to 16,817 MsER patients. The average monthly total HC were lower in the TapER than in the OxnER cohort ($2510 vs. $3720, p<0.001), reflecting significantly lower outpatient, inpatient and emergency department visit rates in the TapER cohort. Similarly, the TapER cohort exhibited a lower average monthly total HC ($2520 vs. $2900, p<0.05) than MsER cohort, with significantly fewer inpatient and outpatient visits in the TapER cohort. TapER demonstrated significantly lower total HC than OxnER in patients with NP and MP, and similar to OxnER in CaP patients. TapER costs were similar to MsER costs in all pain-type subpopulations.Conclusion: Based on real-world evidence, the TapER treatment for chronic pain was associated with significantly lower HC compared with MsER or OxnER. When categorized by type of pain, TapER remained a less costly strategy in comparison with OxnER for MP and NP.Keywords: long-acting opioids, real-world evidence, administrative database, cost analysis, subgroup analysis

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)0.001
metaresearch head score (Gemma)0.004
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 score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.284
Teacher spread0.262 · 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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