MétaCan
Menu
Back to cohort
Record W2187411263 · doi:10.18553/jmcp.2010.16.9.680

Evaluation of Health Plan Member Use of an Online Prescription Drug Price Comparison Tool

2010· article· en· W2187411263 on OpenAlexaboutno aff
Norman V. Carroll, Matthew P. Mitchell, H Eric Cannon, Bryan W York York, Robert Oscar

Bibliographic record

VenueJournal of Managed Care Pharmacy · 2010
Typearticle
Languageen
FieldMedicine
TopicMedication Adherence and Compliance
Canadian institutionsnot available
Fundersnot available
KeywordsCopaymentMedicinePharmacyQuarter (Canadian coin)Medical prescriptionPrescription drugFamily medicineDemographicsHealth careDemographyNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Health plans have implemented tiered copayment systems to incentivize members to use less expensive medications. However, members need drug price information to make comparisons among therapeutic alternatives. Many health plans and pharmacy benefit management companies have implemented online prescription drug price comparison tools to provide such information. There has been little published evaluation of these tools. OBJECTIVE: To evaluate use of an online price comparison tool- MyPharmacyTools (MPT)- by the measures of (a) the extent to which the tool was used, (b) changes in use over the first year after implementation, and (c) the types of members who were most likely to use the tool. METHODS: Data were provided by a 500,000-member integrated health plan with approximately 156,250 enrolled families. The sample included only families with continuous eligibility for all members from July 1, 2006, through June 30, 2008; use of 1 of 7 common copayment structures; and use of the pharmacy benefit in every quarter of the study period. Data collected on each member, using pharmacy claims for the time period July 1, 2007, through June 30, 2008, included annual drug costs (total, out-of-pocket, plan-paid, and mail order) and number of unique drugs and unique generic drugs taken during the third quarter of 2007. Data collected also included whether the member had each of several selected chronic diseases (as inferred from drug claims for the third quarter of 2007) and demographics. Age, gender, and family size were taken from eligibility files. Other demographic data were imputed to members from the demographics of the ZIP code in which they resided. MPT was made available to members on July 1, 2007. Use of MPT was measured as the number of times members logged into the site for each quarter during the subsequent year. Statistical analyses were conducted at the family rather than at the individual level, and families were defined as users if any family member used MPT at least once during the year. Between-group comparisons were evaluated with t-tests, Pearson chi-square tests, and analyses of variance. RESULTS: Data were analyzed for 8,909 families composed of 28,537 health plan members, of which 464 (5.2%) families used MPT at least once between July 2007 and June 2008. A total of 141 families used MPT in the first quarter it was available, 170 families used it in the second quarter, 185 families in the third quarter, and 182 families during the fourth quarter. Users had significantly higher mean [SD] total drug costs ($4,477 [$9,647] vs. $2,848 [$3,473], P < 0.001) and used significantly more unique drug products (7.7 [5.7] vs. 5.9 [4.5], P < 0.001) and unique generic drug products (5.0 [3.9] vs. 3.9 [3.2], P < 0.001) than did nonusers. Users were significantly more likely than nonusers to use drugs for behavioral diseases (47.0% vs. 39.7%, P = 0.002), hypercholesterolemia (35.8% vs. 27.0%, P < 0.001), gastric disorders (32.8% vs. 23.0%, P < 0.001), diabetes (18.3% vs. 12.8%, P < 0.001), epilepsy (21.1% vs. 10.6%, P < 0.001), cardiovascular problems (48.3% vs. 37.5%, P < 0.001), and asthma (14.0% vs. 10.7%, P = 0.025). Families that used MPT were less likely to have a female subscriber than were nonusers (39.7% vs. 49.0%, P < 0.001). Otherwise, here were no statistically significant demographic differences between users and nonusers. Families using MPT in more quarters of the year had higher out-of-pocket (P < 0.001) and mail order drug costs (P < 0.001), took a larger number of drugs (P = 0.003) and generic drugs (P = 0.019), were more likely to use drugs for diabetes (P = 0.049) and cardiovascular disease (P = 0.013), and used drugs for a greater number of chronic diseases (P = 0.049), compared with less frequent MPT users. CONCLUSIONS: About 5% of families in a sample from a large integrated health plan used an online prescription drug cost comparison tool during the first year it was available. Use increased over the year. Users were more likely to have several chronic diseases, took more prescription drugs, and had higher drug costs than nonusers. Further, users with more chronic diseases and more prescriptions were more likely to use the tool consistently throughout the year. These results indicate that the tool was successful in reaching health plan members who could most benefit from comparative prescription drug price information.

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)0.002
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.787
Threshold uncertainty score0.630

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0010.000

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 head0.282
GPT teacher head0.455
Teacher spread0.173 · 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 designOther design
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

Citations3
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Managed Care PharmacySame topicMedication Adherence and ComplianceFrench-language works237,207