Clinical coding internationally: A comparison of the coding workforce in Australia, America, Canada and England
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.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.013 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".