Papanicolaou Tests in Canada and the US - Does Type of Insurance Matter?
Bibliographic record
Abstract
Objectives: The health care systems in the United States and Canada differ quite dramatically. Canadians are covered by a universal health care system while residents of the United States, if they are insured, obtain their insurance from various private or public sources. This study examines how the use of Papanicolaou test by women differs in the United States and Canada using data from Joint Canada/United States Survey of Health (JCUSH). Methodology: The probability of having the Pap smear is estimated separately for Canadian and American women using probit regressions. A question arises as to whether differences in the probability of the pap test are a result of (1) differences in the demographics between Canadian and American women or (2) differences in the estimated coefficients. A Blinder/Oaxaca type decomposition is used to determine the influence of each. Gomulka and Stern expanded this methodology for a dichotomous dependent variable using probit estimation. In their analysis, the probit estimates are transformed into changes arising from a change in the coefficients and changes arising from a change in the population. The Gomulka and Stern method is applied to this data. The analysis has two parts. The first part examines the full sample of American and Canadian women between the ages of 18 to 65 and a subsample of those under age 30. In the full sample, 87% of the Canadians have had a pap smear in the past 3 years (60% in the past year) compared to 93% of the American women (71% within the past year). However, for women under age 30, where the recommendation is for a pap smear every year, the differences are reversed with 79% of Canadians and 76% of Americans receiving the test. In the second analysis, privately insured Americans are compared to Canadians. This allows us to compare how the Canadian national health insurance and US private insurance differ in their influence the use of pap smears. Results: For the full sample, the decomposition shows that the differences between the Canadian and US women mostly occur because of differences in coefficients and not the distributions. For women less than 30 years old, the differences are due to both differences in distributions and coefficients. For insured US women the coefficient effect was even stronger. The only significant difference between US and Canadian women who did not have the test was that 6% of the Canadian women reported that they did not know where to go for the test (vs. 1% of the US). Also 91% of the US women compared to 85% of the Canadian women reported that their doctor recommended the test. Conclusions: Overall, women in the US health care system are more likely to have pap smears and the main driver is differences in the coefficients. Given that fewer Canadian physicians recommend the test, the differences can be attributed to differences in how the systems value the test.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.011 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".