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Record W2342848062 · doi:10.18553/jmcp.2016.22.5.539

Impact of Patient Reimbursement Timing and Patient Out-of-Pocket Expenses on Medication Adherence in Patients Covered by Private Drug Insurance Plans

2016· article· en· W2342848062 on OpenAlexaffabout
François Després, Amélie Forget, Fatima‐Zohra Kettani, Lucie Blais

Bibliographic record

VenueJournal of Managed Care & Specialty Pharmacy · 2016
Typearticle
Languageen
FieldMedicine
TopicMedication Adherence and Compliance
Canadian institutionsHôpital du Sacré-Cœur de MontréalUniversité de Montréal
Fundersnot available
KeywordsReimbursementMedicineDeductibleMedical prescriptionQuartileRetrospective cohort studyCohortFamily medicineEmergency medicineHealth careInternal medicineActuarial scienceNursingConfidence interval

Abstract

fetched live from OpenAlex

BACKGROUND: Adherence to prescribed medications used in the treatment of chronic diseases is suboptimal, and drug insurance plans can have an impact on adherence. There is little evidence on the impact of patient reimbursement timing on medication adherence. OBJECTIVE: To compare adherence to prescribed medications in privately insured patients from Quebec, Canada, with different patient reimbursement timing and levels of patient out-of-pocket expenses. METHODS: A retrospective cohort was constructed by selecting privately insured patients aged 18-64 years from the reMed database (2008-2012) who filled at least 1 prescription for a medication belonging to 1 of the 10 most prescribed drug classes for chronic diseases. Patient reimbursement timing was classified as immediate (immediate patient reimbursement at the point of service of the portion of the medication cost covered by the insurer) or deferred (patient reimbursement at a later time). Patient outof-pocket expenses related to the medication under study at cohort entry (available only for the immediate patient reimbursement group), which included the deductible and the coinsurance, were categorized into 5 levels (null category and quartiles): $0, $0.01-$3.59, $3.60-$8.11, $8.12-$14.40, and $14.41-$89.99. Adherence was measured with the proportion of days covered (PDC) over 1 year among new users of the medication under study. Linear regression models were used to estimate the adjusted mean difference of PDC between groups. RESULTS: There was no difference in medication adherence between the immediate (n = 1,345) and deferred patient reimbursement (n = 437; difference, 0.0%; 95% CI, -3.0 to 3.0). Patients with the highest patient out-of-pocket expenses were less adherent than those with the lowest patient out-of-pocket expenses (difference, -19.0%; 95% CI, -24.0 to -13.0); however, patients with no patient out-of-pocket expenses were less adherent than those with low patient out-of-pocket expenses (difference, -9.0%; 95% CI, -15.0 to -2.0). CONCLUSIONS: Medication adherence appeared to be unaffected by patient reimbursement timing but was affected by the level of patient out-of-pocket expenses. The absence of a correlation between medication adherence and timing of patient reimbursement might be explained by the relatively rapid reimbursement of expenses by insurance companies in Canada. Subjects with no patient out-of-pocket expenses at the point of service might be less adherent because they place less value on their medications than do patients who must pay even a small amount. DISCLOSURES: This study was funded by Pfizer Canada, Montréal, Québec, Canada. Blais received research grants or honorarium from AstraZeneca, Pfizer Canada, Sanofi, Novartis, Almirall, GlaxoSmithKline, and Merck for research projects and co-chairs the AstraZeneca Endowment Pharmaceutical Chair in Respiratory Health. Després, Kettani, and Forget have no competing interests to declare. All authors contributed to the concept and design of the study. Data were collected by Blais and Forget. Data analysis was conducted by Després. The manuscript was written by Després and revised by all authors.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.354
Threshold uncertainty score0.471

Codex and Gemma teacher scores by category

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

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 head0.030
GPT teacher head0.334
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 teacher head, 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

Citations19
Published2016
Admission routes2
Has abstractyes

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