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A model for a drug distribution system in remote Australia as a social determinant of health using event structure analysis

Overview of attention for article published in BMC Health Services Research, September 2017
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Title
A model for a drug distribution system in remote Australia as a social determinant of health using event structure analysis
Published in
BMC Health Services Research, September 2017
DOI 10.1186/s12913-017-2629-x
Pubmed ID
Authors

John P. Rovers, Michelle D. Mages

Abstract

The social determinants of health include the health systems under which people live and utilize health services. One social determinant, for which pharmacists are responsible, is designing drug distribution systems that ensure patients have safe and convenient access to medications. This is critical for settings with poor access to health care. Rural and remote Australia is one example of a setting where the pharmacy profession, schools of pharmacy, and regulatory agencies require pharmacists to assure medication access. Studies of drug distribution systems in such settings are uncommon. This study describes a model for a drug distribution system in an Aboriginal Health Service in remote Australia. The results may be useful for policy setting, pharmacy system design, health professions education, benchmarking, or quality assurance efforts for health system managers in similarly remote locations. The results also suggest that pharmacists can promote access to medications as a social determinant of health. The primary objective of this study was to propose a model for a drug procurement, storage, and distribution system in a remote region of Australia. The secondary objective was to learn the opinions and experiences of healthcare workers under the model. Qualitative research methods were used. Semi-structured interviews were performed with a convenience sample of 11 individuals employed by an Aboriginal health service. Transcripts were analyzed using Event Structure Analysis (ESA) to develop the model. Transcripts were also analyzed to determine the opinions and experiences of health care workers. The model was comprised of 24 unique steps with seven distinct components: choosing a supplier; creating a list of preferred medications; budgeting and ordering; supply and shipping; receipt and storage in the clinic; prescribing process; dispensing and patient counseling. Interviewees described opportunities for quality improvement in choosing suppliers, legal issues and staffing, cold chain integrity, medication shortages and wastage, and adherence to policies. The model illustrates how pharmacists address medication access as a social determinant of health, and may be helpful for policy setting, system design, benchmarking, and quality assurance by health system designers. ESA is an effective and novel method of developing such models.

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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 105 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 105 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 21 20%
Student > Ph. D. Student 13 12%
Researcher 11 10%
Student > Doctoral Student 8 8%
Student > Bachelor 7 7%
Other 10 10%
Unknown 35 33%
Readers by discipline Count As %
Nursing and Health Professions 13 12%
Medicine and Dentistry 10 10%
Social Sciences 9 9%
Engineering 8 8%
Pharmacology, Toxicology and Pharmaceutical Science 7 7%
Other 20 19%
Unknown 38 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 October 2017.
All research outputs
#14,962,064
of 23,931,731 outputs
Outputs from BMC Health Services Research
#5,351
of 8,014 outputs
Outputs of similar age
#181,143
of 322,938 outputs
Outputs of similar age from BMC Health Services Research
#72
of 107 outputs
Altmetric has tracked 23,931,731 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,014 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one is in the 30th percentile – i.e., 30% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 322,938 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 107 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.