Clinical coding internationally: A comparison of the coding workforce in Australia, America, Canada and England
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.
Bibliographic record
Abstract
Recently, researchers in Australia, America, England and Canada have conducted national surveys of clinical coders in their respective countries. In Australia in 2002, the National Centre for Classification in Health (NCCH) in collaboration with the Health Information Management Association of Australia and the Clinical Coders’ Society of Australia conducted the National Clinical Coder Workforce survey, a study of clinical coders and coding managers . In America in 2002, the American Health Information Management Association (AHIMA) commissioned an independent national workforce research study to the Centre for Health Workforce Studies (CHWS), State University of New York at Albany to provide a picture of health information management roles today and forecast through 2010 . In England in 2003, the National Health Service Information Authority (NHSIA) conducted a national clinical coder survey, along with a survey of coding managers, in a similar format to that completed by Australia . In Canada, in 2002, a study was conducted by the Canadian Health Record Association (CHRA) (currently known as the Canadian Health Information Management Association (CHIMA)) and Thiinc iMi, which provided information regarding the various roles health record professionals have in the healthcare sector, the qualifications of health record professionals and their salaries . While these surveys have been conducted independently, they have addressed similar issues in terms of coders' salaries, educational backgrounds, roles and responsibilities, resources, experience, and continuing education needs. While several papers/reports have been generated from the individual research at a national level, there has been no systematic comparison of the coder workforce at an international level to date. This paper will describe the findings of each of the national surveys, and seeks to identify similarities and differences in important aspects of the coder workforce at an international level.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it