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Activities Identification for Activity-Based Cost/Management Applications of the Diagnostics Outpatient Procedures

2011· article· en· W2140971939 on OpenAlexaff
Abdalla Alrashdan, Amer Momani, Tamador Ababneh

Bibliographic record

VenueJournal for Healthcare Quality · 2011
Typearticle
Languageen
FieldHealth Professions
TopicQuality and Safety in Healthcare
Canadian institutionsArtificial Intelligence in Medicine (Canada)
Fundersnot available
KeywordsIdentification (biology)Computer scienceTask (project management)Schema (genetic algorithms)Process (computing)Health careRisk analysis (engineering)Process managementOperations managementMedicineEngineeringMachine learningSystems engineering

Abstract

fetched live from OpenAlex

One of the most challenging problems facing healthcare providers is to determine the actual cost for their procedures, which is important for internal accounting and price justification to insurers. The objective of this paper is to find suitable categories to identify the diagnostic outpatient medical procedures and translate them from functional orientation to process orientation. A hierarchal task tree is developed based on a classification schema of procedural activities. Each procedure is seen as a process consisting of a number of activities. This makes a powerful foundation for activity-based cost/management implementation and provides enough information to discover the value-added and non-value-added activities that assist in process improvement and eventually may lead to cost reduction. Work measurement techniques are used to identify the standard time of each activity at the lowest level of the task tree. A real case study at a private hospital is presented to demonstrate the proposed methodology.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.570
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
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 head0.293
GPT teacher head0.525
Teacher spread0.232 · 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

Citations6
Published2011
Admission routes1
Has abstractyes

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