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Record W1607320869 · doi:10.18438/b83915

Topic-specific Infobuttons Reduce Search Time but their Clinical Impact is Unclear

2009· article· en· W1607320869 on OpenAlexvenueno aff
Shandra Protzko

Bibliographic record

VenueEvidence Based Library and Information Practice · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHealthcare Systems and Technology
Canadian institutionsnot available
Fundersnot available
KeywordsSession (web analytics)MedicineRandomized controlled trialHealth careIntervention (counseling)World Wide WebComputer scienceNursingSurgery

Abstract

fetched live from OpenAlex

A Review of:
 Del Fiol, Guilherme, Peter J. Haug, James J. Cimino, Scott P. Narus, Chuck Norlin, and Joyce A. Mitchell. ‚Effectiveness of Topic-specific Infobuttons: A Randomized Controlled Trial.‛ Journal of the American Medical Information Association 15.6 (2008): 752-9.
 
 Objective – To assess whether infobutton links that direct users to specific content topics (‚topic links‛) are more effective in answering clinical questions than links that direct users to general overview content (‚nonspecific links‛).
 
 Design – Randomized control trial.
 
 Setting – Intermountain Healthcare, an integrated system of 21 hospitals and over 120 outpatient clinics located in Utah and southeastern Idaho.
 
 Subjects – Ninety clinicians and 3,729 infobutton sessions.
 
 Methods – To ensure comparable group composition, subjects were paired and randomly allocated to the study groups. Clinicians in the intervention group had access to topic links, while those in the control group had access to nonspecific links. All subjects at Intermountain Healthcare use a Web-based electronic medical record system (EMR) called HELP2 Clinical Desktop with integrated infobutton links. An Infobutton Manager application defines the content topics and resources; in this case, Micromedex® (Thomson Healthcare, Englewood, CO) provided access to the topic links. The medication order entry module, the most popular of the outpatient modules, was selected to test the two configurations of infobuttons. A focus group of seven HELP2 users aided the researchers in determining the most salient topics to be displayed as a part of the intervention group's user-interface. The study measured infobutton session duration, or time spent seeking information, the number of infobutton sessions conducted, and the outcome and impact of the information seeking. A post-session questionnaire displayed randomly in 30% of sessions measured outcome and impact. The study was conducted between May and November, 2007. This project was funded in part by the National Library of Medicine.
 Main Results – Subjects in the intervention group spent 17.4% less time seeking information than those in the control group (35.5 seconds vs. 43 seconds, p = 0.008). The intervention group used infobuttons 20.5% more often (22 sessions vs. 17.5 sessions, p = 0.21) than those in the control group, a difference that was not statistically significant. Twenty-five subjects answered the post-session survey at least once for a total of 115 (9.9%) responses out of 1,161 possible sessions. The information seeking success rate was equally high in both groups (87.2% intervention vs. 89.4% control, p = .099). Subjects reported high positive clinical impact (i.e., decision enhancement or learning) in 62% of successful sessions. Subjects conveyed a moderate or high level of frustration in 80% of responses associated with unsuccessful sessions.
 
 Conclusion – Topic links provide a slight advantage in the clinical decision-making process by reducing the amount of time spent searching. But while the session length difference between the control and intervention groups is statistically significant, it is less clear whether the difference is clinically meaningful. As previous studies have indicated, infobuttons are able to answer clinical medication questions with a high success rate. It is unclear whether topic links have a clinically significant impact, or rather, whether they are more effective than nonspecific links. The authors believe that the study results ‚should generalize to high-frequency, medication-related infobutton users in other institutions‛ (758).

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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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.867
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.161
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.046
GPT teacher head0.330
Teacher spread0.283 · 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 designNot applicable
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

Citations1
Published2009
Admission routes1
Has abstractyes

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