ArticleMedical care2016
Who Were the Early Adopters of Dabigatran?: An Application of Group-based Trajectory Models.
Article in Medical care, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Barriers and facilitators to the uptake of new medicines into clinical practice: a systematic review.BMC health services research · 2021Pooled it
- Second-Line Therapy for Type 2 Diabetes Management: The Treatment/Benefit Paradox of Cardiovascular and Kidney Comorbidities.Diabetes care · 2021Article
- Emergency Department and Ambulatory Care Visits in the First Twelve Months of Coverage Under Medicaid Expansion: A Group-Based Trajectory Analysis.Annals of emergency medicine · 2021Observational
- A Bayesian hierarchical model for characterizing the diffusion of new antipsychotic drugs.Biometrics · 2021Article
- Patient Perspectives on Factors Affecting Direct Oral Anticoagulant Use for Stroke Prevention in Atrial Fibrillation.Patient preference and adherence · 2021Article
- Adoption of New Glucose-Lowering Medications in the U.S.-The Case of SGLT2 Inhibitors: Nationwide Cohort Study.Diabetes technology & therapeutics · 2019Article
- Factors affecting general practitioners' decisions to adopt new prescription drugs - cohort analyses using Australian longitudinal physician survey data.BMC health services research · 2019Article
- Using the Beta distribution in group-based trajectory models.BMC medical research methodology · 2018Article
- Medicare part D prescribing for direct oral anticoagulants in the United States: Cost, use and the "rubber effect".PloS one · 2018Article
- The Patterns of Non-vitamin K Antagonist Oral Anticoagulants (NOACs) Use in Patients with Atrial Fibrillation in Seven Balkan Countries: a Report from the BALKAN-AF Survey.Advances in therapy · 2017Article
- Influences on the start, selection and duration of treatment with antibiotics in long-term care facilities.CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne · 2017Article
- New chronic disease medication prescribing by nurse practitioners, physician assistants, and primary care physicians: a cohort study.BMC health services research · 2016Article
- Regional Variation in Physician Adoption of Antipsychotics: Impact on US Medicare Expenditures.The journal of mental health policy and economics · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
backgroundVariation in physician adoption of new medications is poorly understood. Traditional approaches (eg, measuring time to first prescription) may mask substantial heterogeneity in technology adoption.
objectiveApply group-based trajectory models to examine the physician adoption of dabigratran, a novel anticoagulant.
methodsA retrospective cohort study using prescribing data from IMS Xponent™ on all Pennsylvania physicians regularly prescribing anticoagulants (n=3911) and data on their characteristics from the American Medical Association Masterfile. We examined time to first dabigatran prescription and group-based trajectory models to identify adoption trajectories in the first 15 months. Factors associated with rapid adoption were examined using multivariate logistic regressions. OUTCOMES: Trajectories of monthly share of oral anticoagulant prescriptions for dabigatran.
resultsWe identified 5 distinct adoption trajectories: 3.7% rapidly and extensively adopted dabigatran (adopting in ≤3 mo with 45% of prescriptions) and 13.4% were rapid and moderate adopters (≤3 mo with 20% share). Two groups accounting for 21.6% and 16.1% of physicians, respectively, were slower to adopt (6-10 mo post-introduction) and dabigatran accounted for <10% share. Nearly half (45.2%) of anticoagulant prescribers did not adopt dabigatran. Cardiologists were much more likely than primary care physicians to rapidly adopt [odds ratio (OR)=12.2; 95% confidence interval (CI), 9.27-16.1] as were younger prescribers (age 36-45 y: OR=1.49, 95% CI, 1.13-1.95; age 46-55: OR=1.34, 95% CI, 1.07-1.69 vs. >55 y).
conclusionsTrajectories of physician adoption of dabigatran were highly variable with significant differences across specialties. Heterogeneity in physician adoption has potential implications for the cost and effectiveness of treatment.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.