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Record W2159843355 · doi:10.1186/1472-6963-13-418

Developing a medication communication framework across continuums of care using the Circle of Care Modeling approach

2013· article· en· W2159843355 on OpenAlexaff
Nicole Kitson, Morgan Price, Francis Lau, Grey Showler

Bibliographic record

VenueBMC Health Services Research · 2013
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsUniversity of British ColumbiaUniversity of Victoria
Fundersnot available
KeywordsHealth informaticsHealth administrationNursing researchMedicinePublic healthHealth carePain medicineNursingPsychiatryAnesthesiology

Abstract

fetched live from OpenAlex

BACKGROUND: Medication errors are a common type of preventable errors in health care causing unnecessary patient harm, hospitalization, and even fatality. Improving communication between providers and between providers and patients is a key aspect of decreasing medication errors and improving patient safety. Medication management requires extensive collaboration and communication across roles and care settings, which can reduce (or contribute to) medication-related errors. Medication management involves key recurrent activities (determine need, prescribe, dispense, administer, and monitor/evaluate) with information communicated within and between each. Despite its importance, there is a lack of conceptual models that explore medication communication specifically across roles and settings. This research seeks to address that gap. METHODS: The Circle of Care Modeling (CCM) approach was used to build a model of medication communication activities across the circle of care. CCM positions the patient in the centre of his or her own healthcare system; providers and other roles are then modeled around the patient as a web of relationships. Recurrent medication communication activities were mapped to the medication management framework. The research occurred in three iterations, to test and revise the model: Iteration 1 consisted of a literature review and internal team discussion, Iteration 2 consisted of interviews, observation, and a discussion group at a Community Health Centre, and Iteration 3 consisted of interviews and a discussion group in the larger community. RESULTS: Each iteration provided further detail to the Circle of Care medication communication model. Specific medication communication activities were mapped along each communication pathway between roles and to the medication management framework. We could not map all medication communication activities to the medication management framework; we added Coordinate as a separate and distinct recurrent activity. We saw many examples of coordination activities, for instance, Medical Office Assistants acting as a liaison between pharmacists and family physicians to clarify prescription details. CONCLUSIONS: Through the use of CCM we were able to unearth tacitly held knowledge to expand our understanding of medication communication. Drawing out the coordination activities could be a missing piece for us to better understand how to streamline and improve multi-step communication processes with a goal of improving patient safety.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.544
Threshold uncertainty score0.769

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.345
GPT teacher head0.567
Teacher spread0.222 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations19
Published2013
Admission routes1
Has abstractyes

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