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Record W2563413628 · doi:10.1002/jppr.1295

Emerging roles for pharmacists – all in a day's work

2016· article· en· W2563413628 on OpenAlexaboutno aff
Lisa Nissen, Esther Lau

Bibliographic record

VenueJournal of Pharmacy Practice and Research · 2016
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsnot available
FundersQueensland University of Technology
KeywordsMedicinePharmacistVaccinationPharmacyFamily medicineHealth careNursingMeaslesImmunology

Abstract

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The value to public health outcomes of pharmacist-administered vaccinations is undeniable and the numbers speak for themselves. Australia's first pharmacist vaccination pilot in Queensland (QPIP) saw over 35 000 vaccinations administered to adults in community pharmacies in just over 2 years. The overwhelmingly positive uptake of this service, and consistently positive feedback from patients after the first year (QPIP1), saw the pilot extended from influenza vaccinations to include pertussis and measles vaccinations. The data collected during the pilot paved the way for pharmacist-administered vaccinations across the whole of Australia. Being a pharmacist was traditionally considered, and in many instances still is, a very 'hands off' profession. Only 3 years ago, most pharmacists would never have dreamed of being able to vaccinate. Yet who would have thought that simply penetrating someone's skin with a sharp metal object would so significantly change their relationship and trust in you? Certainly, the success of the pilot was due to the trust the community places in pharmacists, as well as pharmacists' accessibility, as key healthcare professionals. In the QPIP pilot, almost 14% of patients had never had an influenza vaccination before, and another 15% indicated they would not have received an influenza vaccine if the QPIP service was not available. This indicates pharmacists have an important role to play in increasing the uptake of vaccines in the community, particularly in reaching people who would not have otherwise been vaccinated. This is also especially important in rural, regional or remote regions where access to healthcare services is more difficult. Consistent with findings from QPIP1, the vast majority of people in QPIP2 were also happy to receive their vaccination from a pharmacy in the future (99.4%), and would recommend the QPIP service to other people (99.5%). Patients applauded the convenience and accessibility of the pharmacist in community pharmacies. The fact that they could receive a vaccination without an appointment was seen as a positive by patients. The impact pharmacists can have on increasing the overall vaccination rates in the community through accessibility alone must be recognised. These figures are not unique to Australia, as similar statistics have been noted in other jurisdictions around the world where pharmacists are immunisers, e.g. Canada, United Kingdom, United States, and New Zealand.1-5 The ability of pharmacists to safely and effectively administer injectable medication and manage adverse drug reactions, points to an opportunity for pharmacists to further contribute to delivering public health services beyond that of influenza vaccinations. This is of particular importance as suboptimal uptake of vaccinations is an ongoing issue in many areas of the community (e.g. at-risk groups), and an expansion of pharmacist vaccination services will help to achieve more effective herd immunity.6 Pharmacists can help to increase the uptake of other vaccines, such as for human papilloma virus (HPV), hepatitis A and/or B, adults who require catch-up or booster vaccines, travel vaccines, and also those with gaps in their childhood immunisation record. However, the opportunity for wider delivery of healthcare services to people in the community extends to that beyond vaccinations per se. These include application of our administration skills too, e.g. depot injections (such as contraception, anti-psychotics), vitamin B12 injections, and possibly in patients' homes, e.g. antibiotic infusions/home IV. So the value for pharmacists as immunisers is clear. As a profession, it is time for pharmacists to roll up our sleeves and ask, what's next?

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)0.019
metaresearch head score (Gemma)0.038
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.037
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.038
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0080.008
Scholarly communication0.0150.015
Open science0.0040.018
Research integrity0.0170.021
Insufficient payload (model declined to judge)0.0370.014

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 head0.339
GPT teacher head0.596
Teacher spread0.257 · 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 designNot applicable
Domainnot available
GenreCommentary

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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Citations6
Published2016
Admission routes1
Has abstractyes

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