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Record W4224436887 · doi:10.1016/j.jsxm.2022.01.098

86 Direct-to-Consumer vs. Traditional Prescriptions of PDE5 inhibitors: A Contemporary Cost-Analysis

2022· article· en· W4224436887 on OpenAlexaboutno aff
D Schneider, C Loeb, F el-Khatib, L Jenkins, F Yafi

Bibliographic record

VenueThe Journal of Sexual Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Quality and Counterfeiting
Canadian institutionsnot available
Fundersnot available
KeywordsMedical prescriptionPharmacyReimbursementFamily medicineMedicineBusinessTelehealthHealth careTelemedicineNursingPolitical science

Abstract

fetched live from OpenAlex

ABSTRACT Introduction After a text screen and focused telehealth visit, patients can now have access to phosphodiesterase inhibitor (PDEi) prescriptions through online direct to consumer (DTC) healthcare companies. Prescription of PDEis has unknown costs relative to the traditional office visit, especially with the availability of online discounts. Objective This study seeks to quantify the cost of DTC PDEi treatment compared to a traditional physician visit and local pharmacy prescription fulfillment. Methods Nine pharmacies were included, including two DTC companies, two compounding pharmacies with national reach, three online Canadian pharmacies licensed by the Canadian International Pharmacy Association, and sixteen American pharmacy chains, representing all locally available chains. National pharmacies which are subsidiaries were grouped together. Prices for chains were determined using their publicly available price on GoodRx® with coupons in Irvine, CA (92612), Cleveland, OH (44101), New York, NY (10001), Dallas, TX (75201), and Birmingham, AL (35201). Cost of physician visit was determined using 2020 CMS reimbursement for a level 3 new patient visit. Prices for DTC companies were acquired from direct communication with the company. Where offerings did not align with 90 dose regimens, price per pill was determined and price for 90 doses was calculated. Results For a 90-dose supply of sildenafil 20mg, a physician visit and local prescription cost a mean of $191.51 with a low of $125.45, compounding pharmacy prescription cost a mean of $218.28 with a low of $144.35, and Canadian pharmacy prescription cost a mean of $240.25 with a low of $169.34, compared to a mean of $220.00 and a low of $180.00 for online DTC. For sildenafil 100mg, a physician visit and local prescription had a mean cost of $524.11 with a low cost of $137.16, compounding pharmacy prescription a mean cost of $401.78 with a low cost of $289.35, and Canadian pharmacy prescription a mean cost of $262.63 with a low cost of $200.36, compared to a mean and low cost of $900.00 for DTC. For tadalafil 5mg, a physician visit and local prescription cost a mean of $205.79 with a low of $125.80, compounding pharmacy prescription cost a mean of $179.33 with a low of $169.35, and “Canadian” pharmacy prescription cost a mean of $207.59 with a low of $195.34, compared to an average and low of $720.00 for DTC. Finally, for tadalafil 20mg, a physician visit and local prescription cost a mean of $643.70 with a low of $161.00, compounding pharmacy prescription cost a mean of $359.33 with a low of $289.35, and Canadian pharmacy prescription cost a mean of $291.74 with a low of $229.00, compared to a mean of $3420.00 and a low of $2880.00 for DTC (Table 1). Conclusions Our findings suggest that local pharmacies, in conjunction with online coupons, consistently provide a markedly less expensive option for fulfillment of PDEi prescriptions than online DTC services, compounding, or Canadian pharmacies, in addition to the established benefits of physician visits for screening. This is most pronounced if patients have flexibility in where they fill their prescriptions and can use the available local prices. Disclosure Any of the authors act as a consultant, employee or shareholder of an industry for: FY: Coloplast (consultant), Cynosure (consultant) LJ: Hims (consultant)

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.507
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.185
GPT teacher head0.374
Teacher spread0.189 · 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 designNot applicable
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
Published2022
Admission routes1
Has abstractyes

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