MétaCan
Menu
Back to cohort

A Curriculum in Medical Economics for Residents

2002· article· en· W1997091440 on OpenAlexaboutno aff
R. Jeffrey Kohlwes, Calvin L. Chou

Bibliographic record

VenueAcademic Medicine · 2002
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicaidReimbursementHealth careCurriculumGovernment (linguistics)SyllabusMedical educationMedicineManaged careCredentialingPublic relationsNursingPolitical science

Abstract

fetched live from OpenAlex

Objectives: In today's changing marketplace, it is increasingly difficult for physicians to be both effective clinicians and practice managers. The plethora of insurance and reimbursement plans, with their confusing language of acronyms and abbreviations, intimidates most practicing physicians. However, understanding the various plans is critical in enabling resident physicians to successfully navigate the medical marketplace and make informed career decisions. To develop residents' understanding of the current American health care system, we created a curriculum to introduce the principles of medical economics. Description: At the University of California, San Francisco, the UCSF-VA PRIME program instituted a series of seminars in health economics, taught by local experts in the field. Residents were given a syllabus of articles before each class, and they were expected to participate actively in each of the seven 90-minute seminars. The topics covered were (1) an introductory history of American medical economics and the development of work-based health insurance; (2) how government-sponsored health care systems (Medicare, Medicaid, and the VA) developed, who qualifies for care, and what problems may arise with funding these programs; (3) the creation of Blue Cross and Blue Shield, and their prominence in the current health care system; (4) medical reimbursement programs (including health maintenance organizations, preferred provider organizations, and independent provider organizations) and variations on these systems; (5) single-payer plans, using the Canadian health care system as a paradigm and assessing how its implementation in the United States would affect American medicine; (6) health care quality; and (7) the role of legislation and government in medical policy, using the failed Clinton health care plan as an example. There were three types of interactive seminars. Most commonly, questions based on assigned readings acted as starting points for discussion. Some seminars were case-based. One particularly effective session on the topic of health care quality used role-play exercises where different seminar members depicted practitioners, clinic managers, and health plan representatives to illustrate different perspectives of the same problems. Discussion: Our residents reported a high degree of interest in and enthusiasm for our pilot curriculum. Dynamic seminars with leaders who promoted discussion by direct participation, such as during the role-play exercises, were the most successful. Interestingly, however, the reading assignments were less effective, since residents were unlikely to read long, dense articles. The most highly rated readings were the medical economics features from The New England Journal of Medicine, as they seemed the most concise and accessible. We feel that, with continued revisions and by creatively increasing interactivity in each session, this innovative curriculum meets important educational needs of our residents, and that it is easily exportable. Long-term outcome assessments include rating residents' abilities to become successful patient advocates, participation in research or fellowship programs in health care quality, and future career development into leaders in health economics and policy.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.063
Threshold uncertainty score0.210

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0630.022

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 head0.106
GPT teacher head0.334
Teacher spread0.228 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations4
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueAcademic MedicineSame topicHealthcare Policy and ManagementFrench-language works237,207