Reconsidering the Harvard Medical Practice Study Conclusions about the Validity of Medical Malpractice Claims
Bibliographic record
Abstract
Over fifteen years after first reporting to the State of New York, the Harvard Medical Practice Study (HMPS) continues to have a significant impact in medical malpractice policy debates. In those debates the HMPS has come to stand for four main propositions. First, “medical injury… accounts for more deaths than all other kinds of accidents combined” and “more than a quarter of those were caused by substandard care.” Second, the vast majority of people who are injured as result of substandard care do not file a claim. Third, “a substantial majority of malpractice claims filed are not based on provider carelessness or even iatrogenic injury.” Fourth, “whether negligence or a medical injury had occurred… bore little relation to the outcome of the claims.” Medical malpractice researchers have long known that the HMPS provides far stronger support for the first two of these propositions than for the last two; the HMPS was not designed or powered to reach strong conclusions about the validity of medical malpractice claims.
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 | 0.385 | 0.666 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.017 | 0.009 |
| Science and technology studies | 0.013 | 0.081 |
| Scholarly communication | 0.019 | 0.030 |
| Open science | 0.015 | 0.013 |
| Research integrity | 0.030 | 0.025 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".