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Record W7084177383

Prevalence, Incidence, and Treatment Characteristics of Primary Open-Angle Glaucoma Among Medicare Fee-for-Service Beneficiaries

2025· article· en· W7084177383 on OpenAlexaff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicUnemployment and Economic Growth
Canadian institutionsGlobal Affairs Canada
Fundersnot available
KeywordsMedical prescriptionPharmacyGlaucomaRetrospective cohort studyMedicare AdvantageMedicare Part BCohortGlaucoma medicationMedicare Part D
DOInot available

Abstract

fetched live from OpenAlex

Jonathan S Myers,1 Elizabeth A Donckels,2 Tigwa H Davis,2 Scott B Robinson,2 Zulkarnain Pulungan,2 Teresa L Brevetti,3 Joel Fain,3 Abhishek A Nair4 1Glaucoma Service, Wills Eye Hospital, Philadelphia, PA, USA; 2Insights, Inovalon, Bowie, MD, USA; 3Medical Affairs, Bausch + Lomb U.S., Bridgewater, NJ, USA; 4Global Health Economics and Outcomes Research, Bausch + Lomb U.S., Bridgewater, NJ, USACorrespondence: Abhishek A Nair, Global Health Economics and Outcomes Research, Bausch + Lomb U.S., Bridgewater, NJ, USA, Email Abhishek.Nair@bausch.comPurpose: This study aimed to describe Medicare FFS beneficiaries with prevalent and incident POAG, and to determine their demographic characteristics. Secondary objectives included describing POAG prescription rates, prescribers of POAG therapy, and dry eye disease rates among POAG prevalent beneficiaries.Patients and Methods: The study was a retrospective cohort analysis using de-identified Medicare FFS medical and pharmacy claims and enrollment data (Parts A/B/D) spanning from January 1, 2016, to December 31, 2021. Medicare FFS beneficiaries were included in the analysis if they were diagnosed or treated for POAG, 65 years of age or older, and continuously enrolled for at least 24 months. Beneficiaries were identified between January 1, 2017, and December 31, 2021, allowing for a 12-month baseline to categorize patients as incident or prevalent. Comorbid dry eye disease and prescription POAG therapies were also identified. Prescriber NPIs were used to classify prescriber types.Results: From 2017 to 2021, 5.5– 6.2% of Medicare FFS beneficiaries were identified with prevalent POAG, with ~1% categorized as incident. A higher proportion of POAG beneficiaries were older and/or Black. At least 81% received POAG prescription therapy each year, with ophthalmologists as most frequent prescribers. Comorbid dry eye was documented in 16.4– 18.7% of beneficiaries with prevalent POAG, and in 11.8– 13.6% of beneficiaries with incident POAG.Conclusion: A significant proportion of Medicare FFS beneficiaries have POAG. While most people with POAG received some type of prescription therapy each year, a notable proportion of individuals had no form of prescription POAG therapy identified. Given higher rates of dry eye disease in people with glaucoma, dry eye disease screening and care among beneficiaries with POAG should be promoted. Future research should evaluate treatment patterns and outcomes among Medicare FFS beneficiaries with comorbid POAG and dry eye disease.Keywords: dry eye, glaucoma, race/ethnicity, prevalence, medicare, topical therapy

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.156
GPT teacher head0.428
Teacher spread0.272 · 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 teacher head, not a consensus.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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