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Record W2579875579 · doi:10.1186/s12911-016-0404-2

Naturalistic study of guideline implementation tool use via evaluation of website access and physician survey

2017· article· en· W2579875579 on OpenAlexaff
Melissa J. Armstrong, Gary Gronseth, Richard Dubinsky, Sonja Potrebic, Rebecca Penfold Murray, Thomas S.D. Getchius, Carol Rheaume, Anna R. Gagliardi

Bibliographic record

VenueBMC Medical Informatics and Decision Making · 2017
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsUniversity Health Network
FundersAmerican Academy of Neurology
KeywordsHealth informaticsGuidelineMedicineComputer scienceFamily medicinePublic healthNursingPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Clinical guidelines support decision-making at the point-of-care but the onus is often on individual users such as physicians to implement them. Research shows that the inclusion of implementation tools in or with guidelines (GItools) is associated with guideline use. However, there is little research on which GItools best support implementation by individual physicians. The purpose of this study was to investigate naturalistic access and use of GItools produced by the American Academy of Neurology (AAN) to inform future tool development. METHODS: Website accesses over six months were summarized for eight AAN guidelines and associated GItools published between July 2012 and August 2013. Academy members were surveyed about use of tools accompanying the sport concussion guideline. Data were analyzed using summary statistics and the Chi-square test. RESULTS: The clinician summary was accessed more frequently (29.0%, p < 0.001) compared with the slide presentation (26.8%), patient summary (23.2%) or case study (20.9%), although this varied by guideline topic. For the sport concussion guideline, which was accompanied by a greater variety of GItools, the mobile phone quick reference check application was most frequently accessed, followed by the clinician summary, patient summary, and slide presentation. For the sports concussion guideline survey, most respondents (response rate 21.8%, 168/797) were aware of the guideline (88.1%) and had read the guideline (78.6%). For GItool use, respondents indicated reading the reference card (51.2%), clinician summary (45.2%), patient summary (28.0%), mobile phone application (26.2%), and coach/athletic trainer summary (20.2%). Patterns of sports concussion GItool use were similar between respondents who said they had and had not yet implemented the guideline. CONCLUSIONS: Developers faced with resource limitations may wish to prioritize the development of printable or mobile application clinician summaries, which were accessed significantly more than other types of GItools. Further research is needed to understand how to optimize the design of such GItools.

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)0.009
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.790
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.493
GPT teacher head0.616
Teacher spread0.123 · 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.

Study designObservational
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

Citations7
Published2017
Admission routes1
Has abstractyes

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