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Record W1598736293 · doi:10.18438/b8pd03

Personalized Information Service for Clinicians: Users Like It

2008· article· en· W1598736293 on OpenAlexvenueno aff
Gale G. Hannigan

Bibliographic record

VenueEvidence Based Library and Information Practice · 2008
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsnot available
Fundersnot available
KeywordsService (business)PublicityMedicineObservational studyFocus groupMedical recordMedical educationElectronic medical recordFamily medicineRelevance (law)Business

Abstract

fetched live from OpenAlex

A Review of:
 Jerome, Rebecca N., Nunzia Bettinsoli Giuse, S. Trent Rosenbloom, and Patrick G. Arbogast. “Exploring Clinician Adoption of a Novel Evidence Request Feature in an Electronic Medical Record System.” Journal of the Medical Library Association 96.1 (Jan. 2008): 34-41, with online appendices. 
 
 
 Abstract
 
 Objective – To examine physician use of an Evidence-Based Medicine (EBM) literature request service available to clinicians through the institution’s electronic medical record system (EMR). Specifically, the authors posed the following questions: 1) Did newly implemented marketing and communication strategies increase physicians’ use of the service? 2) How did clinicians rate the relevance of the information provided? 3) How was the information provided used and shared? 
 
 Design – Ten-month, prospective, observational study employing a questionnaire, statistics, a focus group, and a “before and after marketing intervention” analysis.
 
 Setting – Adult primary care outpatient clinic in an academic medical centre.
 
 Subjects – Forty-eight attending and 89 resident physicians.
 
 Methods – In 2003, a new service was introduced that allowed physicians in the Adult Primary Care Center clinic to request evidence summaries from the library regarding complex clinical questions. Contact with the library was through the secure messaging feature of the institution’s electronic medical record (EMR). From March through July 2005, the librarian employed “standard” publicity methods (e-mail, flyers, posters, demonstrations) to promote the service. A focus group in July 2005 provided feedback about the service as well as recommendations about communicating its availability and utility. New communication methods were implemented, including a monthly electronic “current awareness” newsletter, more frequent visits by the librarian during resident clinic hours, and collaborations between the librarian and residents preparing for morning report presentations. At the end of the study period, a 25-item Web-based questionnaire was sent to the 137 physicians with access to the service. 
 
 Main Results – During the 10-month study period, 23 unique users submitted a total of 45 questions to the EBM Literature Request Service. More questions were from attending physicians than residents: 36 (80%) vs. 9 (20%). At least one of the 23 users asked 12 (26%) of the questions. Utilization did not significantly change after the mid-study intervention. At the end of the study, 48 physicians (35%) completed the survey (32 attending physicians and 16 residents). While 94% of the respondents indicated awareness of the service, only 40% indicated using it. The 19 who used the service, on average, agreed that the information provided was relevant and “sometimes leads to a change in my clinical practice” (p.37). Those who indicated that they shared the information (n=15) mostly did so with other attending physicians and residents, but also mentioned sharing with fellows, patients, and nurses. Information was typically shared verbally but also by distributing a printout, forwarding by e-mail, and forwarding within the EMR message system. The information was used primarily for general self-education, instruction of trainees, and confirmation of a current plan. 
 
 Conclusion – The newly implemented marketing and communication strategies did not significantly increase the use of the EBM Literature Request Service. Those who used the service found it relevant and often shared the information with others. Based on a small number of respondents and survey information, the librarian-provided EBM Literature Request Service was “well-received” (39).

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)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.300
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.301
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 head0.149
GPT teacher head0.458
Teacher spread0.310 · 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
GenreCommentary

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
Published2008
Admission routes1
Has abstractyes

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