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Record W4411933628 · doi:10.3899/jrheum.2025-0314.10

Compounding for Rheumatologists: A Glimpse Inside the Black Box of Pricing to Patients

2025· article· en· W4411933628 on OpenAlexaffvenueabout
Inioluwa Adeboye, Stephen Williams, Aurore Fifi‐Mah

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical studies and practices
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCompoundingPharmacyMedicineDiclofenacPharmacistReimbursementFamily medicineMarketingBusinessPharmacologyHealth careEconomics

Abstract

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Objectives Drug compounding is the combining, mixing, or alteration of active pharmaceutical ingredients (API) into doses or dosage forms for individual patients.[1] While often prescribed by rheumatologists, the methodology behind drug compound pricing by pharmacies remains unclear to most rheumatologists. In this study, we reviewed the approach to pricing 1 of the most prescribed compounds: 100 grams of diclofenac 10% in PLO. Methods The constituent costs of a drug compound were determined by interviewing members of the Alberta Pharmacist’s Association. API and excipient ingredient costs were determined by reviewing listed wholesaler prices. Published insurance plan information was used for dispensing fees and insurer permitted mark-ups.[2] These mark-ups are at the pharmacy’s discretion if a patient pays cash. Price quotes were attained by calling pharmacies across Alberta. Independent, chain, and compounding pharmacies were called to ensure representation from the different pharmacy types. Only 1 pharmacy from each brand/banner was called. Results A comprehensive overview of price constituents for diclofenac 10% in PLO is seen in Figure 1. Using the information available, we determined the theoretical lowest cost for this compound was $31.78. Contextually, the cost per 10g of diclofenac (amount needed to make compound) ranged from $2.92-$17.92 The cost per 90g of PLO (amount needed to make compound) ranged from $8.67-$13.86. Mark-up and dispensing were the largest contributor to final price. The real price varied considerably by pharmacy. The average price for 100g of 10% diclofenac was $50.54 (range: 38.42-55.82) at chains, $88.36 (range: 37.83-205.00) at compounding pharmacies, and $94.63 (range: 55.75-170.00) at independent pharmacies. Conclusion A wide range of prices for the same compound were determined. Several factors contribute to the large price variations. The most important be summarized as follows: 1. Differing acquisition costs from wholesalers for the active pharmaceutical ingredient and excipients (diclofenac, PLO), 2. Mark-ups, which can be changed at the pharmacy’s discretion for patients without insurance 3. Dispensing fees 4. Hidden repackaging costs (charges associated with a non-compounding pharmacy acquiring compounds from another pharmacy). It is important to note that items 1-3 provide profit to the pharmacy after covering labor and material costs. These findings have important implications for prescribing rheumatologists and patients without adequate insurance who may be exposed to elevated prices without their knowledge. A range of prices from $33.55 to $205.00 a product costing $31.78 to make highlights the need for greater price transparency. Rheumatologists are well-situated as prescribers to advocate on behalf of patients. [1.] Alberta Blue Cross. Reference guide for Alberta pharmacies. 2023. [Internet.] Available from: https://www.ab.bluecross.ca/pdfs/82477-ab-pharmacy-reference-guide.pdf . [2.] Telus Health. Submission and eligibility guidelines for compounds. 2022. [Internet.] Available from: https://page.telushealth.com/rs/655-URY-133/images/supportdoc_compound-eligibility-en.pdf?_ga=2.232875934.1641613068.1625517315-1146326151.1613664105 .

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)0.023
metaresearch head score (Gemma)0.053
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.053
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0020.007
Scholarly communication0.0100.016
Open science0.0020.005
Research integrity0.0030.009
Insufficient payload (model declined to judge)0.0230.007

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 head0.044
GPT teacher head0.371
Teacher spread0.328 · 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
Published2025
Admission routes3
Has abstractyes

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