ArticleJournal of pharmacy practice2025
Prescription for Digital Evolution: Transformative Recommendations for Pharmacy Practice in the Digital Age.
Article in Journal of pharmacy practice, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed.
- Exploring Community Pharmacists' Awareness, Attitudes, and Experiences with Digital Health Technologies: A Focus on Mobile Applications for Diabetes Mellitus Self-Management.Pharmacy (Basel, Switzerland) · 2026Article
- Exploring community pharmacy manager/ pharmacist perceptions and responses to China's dual-channel policy for improving access and rational use of innovative drugs: a qualitative study.International journal of clinical pharmacy · 2025Article
- Detection of Adverse Medicine Events by Pharmacists in Residential Aged Care Facilities: Secondary Analysis of Data From ReMInDAR Trial.Pharmacoepidemiology and drug safety · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Increased administrative tasks, evolving expectations of care and advancement in practice scope have rapidly advanced digital health. Health policy has acknowledged the need for evaluation to determine the technological needs of clinicians, including pharmacists, to practice to full and top of scope. There is an emergent need for recommendations to address the technological transformation to enable community pharmacists' practice. This study aimed to develop digital health recommendations, through expert consensus, for the government, pharmacy professional associations, pharmacy enterprises and software vendors, to facilitate community pharmacists' practice. A modified Delphi survey was conducted online in February-March 2024. Pharmacists with digital health expertise were purposively recruited. Participants were asked to rate their level of agreement with the initial 24 research-derived statements in round 1. Consensus was defined a priori as ≥80% of participants strongly agreeing or agreeing with a statement and a standard deviation of ≤1.00. Review of participants' free-text comments progressively reduced and refined the statements. All 22 participants completed the modified Delphi study in 3 survey rounds. Participants represented every Australian jurisdiction. Eighteen participants had more than 10 years of professional experience. Sixteen recommendations emerged: 6 for government, 2 for pharmacy professional associations, 4 for pharmacy enterprises and 4 for software vendors. The majority of recommendations require financial investment and harmonization of legislation across jurisdictions. Adoption of these recommendations, with significant investment across partners in the healthcare system and technology providers, will enable pharmacists to more effectively and safely practice utilizing technology solutions.
Indexed as
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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.