ArticleCanadian family physician Medecin de famille canadien2014
Patient-specific academic detailing for smoking cessation: feasibility study.
Article in Canadian family physician Medecin de famille canadien, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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
4 citing papers in PubMed.
- From Good to Great: The Role of Performance Coaching in Enhancing Tobacco-Dependence Treatment Rates.Annals of family medicine · 2018Trial
- Enhancing Naloxone Distribution for Opioid Users in the USA: A Cost-Utility Analysis of Academic Detailing to Clinicians.Applied health economics and health policy · 2025Article
- Can Academic Detailing Move the Needle for Patients with Diabetes in a State-Based Prescription Drug Benefit Program?American health & drug benefits · 2019Article
- Key Features of Academic Detailing: Development of an Expert Consensus Using the Delphi Method.American health & drug benefits · 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
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo describe and to determine the feasibility of a patient-specific academic detailing (PAD) smoking cessation (SC) program in a primary care setting.
designDescriptive cohort feasibility study.
settingHamilton, Ont.
participantsPharmacists, physicians, nurse practitioners, and their patients.
interventionsIntegrated pharmacists received basic academic detailing training and education on SC and then delivered PAD to prescribers using structured verbal education and written materials. Data were collected using structured forms.
main outcome measuresFive main feasibility criteria were generated based on Canadian academic detailing programs: PAD coordinator time to train pharmacists less than 40 hours; median time of SC education per pharmacist less than 20 hours; median time per PAD session less than 60 minutes for initial visit; percentage of prescribers receiving PAD within 3 months greater than 50%; and number of new SC referrals to pharmacists at 6 months more than 10 patients per 1.0 full-time equivalent (FTE) pharmacist (total of approximately 30 patients).
resultsEight pharmacists (5.8 FTE) received basic academic detailing training and education on SC PAD. Forty-eight physicians and 9 nurse practitioners consented to participate in the study. The mean PAD coordinator training time was 29.1 hours. The median time for SC education was 3.1 hours. The median times for PAD sessions were 15 and 25 minutes for an initial visit and follow-up visit, respectively. The numbers of prescribers who had received PAD at 3 and 6 months were 50 of 64 (78.1%) and 57 of 64 (89.1%), respectively. The numbers of new SC referrals at 3 and 6 months were 11 patients per FTE pharmacist (total of 66 patients) and 34 patients per FTE pharmacist (total of 200 patients), respectively.
conclusionThis study met the predetermined feasibility criteria with respect to the management, resources, process, and scientific components. Further study is warranted to determine whether PAD is more effective than conventional academic detailing.
Indexed as
Identifiers
24452574PMC3994822What 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.