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Electronic Procedure Logs

2002· article· en· W2072605808 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAcademic Medicine · 2002
Typearticle
Languageen
FieldComputer Science
TopicICT in Developing Communities
Canadian institutionsFoothills Medical CentreUniversity of Calgary
Fundersnot available
KeywordsMEDLINEComputer scienceChemistry

Abstract

fetched live from OpenAlex

OBJECTIVE: To create an electronic procedural logbook with enhanced user interactivity and usefulness as an educational resource. DESCRIPTION: From our own work on electronic student logbooks and other studies, it is clear that compliance with complete and valid data entry remains a challenge. Without direct and visible benefit, students are reluctant to spend time logging all their cases. We developed an interactive procedural logbook using Microsoft Embedded Visual Basic and Metrowerks CodeWarrior. Interface design focused on rapid data entry with minimum requirement for text, and field-level automation where possible. We loaded it onto a mixed platform of personal digital assistants (PDAs)--Compaq iPaq Pocket PCs and HandEra 330 PalmOS devices. Our rural residents were supplied with the devices of their choice. Various built-in educational reference resources included: (1) contextual help options about each procedure, which contained diagrams and pictures; (2) diagnostic and fee coding so they could see how poorly some procedures pay; and (3) Quick Tips relevant to each procedure, which can be easily modified by the preceptor. Preceptor evaluations and comments can be entered rapidly. Using built-in database conduits, data are automatically collected from each device on every HotSync with the desktop. Data can then be collated and analyzed using Microsoft Access or via secure Web access. DISCUSSION: Improved compliance has been dramatic-one resident logged 250 procedures in just two months. However, not all residents have been successful in establishing seamless synchronization, and the resulting data loss has caused frustration. The evidence indicates the need to implement central data collection and backup right from the outset. Central data collection provides many advantages. The program director has better information for future applications. Preceptor evaluations are now spread over many interactions and yet can be collated and analyzed. Quick Tips have been very popular-we have been able to collect the tips and redistribute them. Focus-group feedback from the residents has shown that the rich data in the logbook's reference component improved its usefulness and popularity as an educational tool. Choice of device type is important for user acceptance because devotees of one platform are reluctant to switch to another. Cross-platform development does slow the process but is increasingly easy with the latest software design tools, such as AppForge. These new tools have enabled us to explore further improvements in data entry. Digital ink provides the ability to capture annotated diagrams and preceptor signatures. Voice input is built in with these devices, and our software now allows for voice annotation for more detailed commentary by preceptors or student. The compressed digital sound file is collected along with the data and transcribed centrally (on-device voice recognition is not feasible yet). Point-of-care accessibility has been the key attraction of using these devices for logging encounter data. This project demonstrates that it is important to explore all multimodal interactive capabilities to provide a truly rich educational tool.

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.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.838
Threshold uncertainty score0.450

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.042
GPT teacher head0.273
Teacher spread0.231 · 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