Bibliographic record
Abstract
This thesis comprises three essays that empirically explore two important areas in health economics and policy: the valuation of medical innovations, and access to healthcare. The first essay explores the role of new medical technologies in improving labor market outcomes by conducting a case study of a class of drugs used in the treatment of arthritis called Cox-2 inhibitors. Cox-2 drugs make an excellent case study for investigating the labor supply effects of medical innovation because the potential labor supply effects are large, and the market introduction of these drugs generates plausibly exogenous variation in their use. Using data from the Health and Retirement Study (HRS) and applying a difference-in-differences approach that compares individuals with arthritis to individuals without arthritis, I find that the introduction of Cox-2 drugs had a positive and significant impact on the probability of working among individuals with long-term arthritis. The effects are stronger among older individuals, the less-educated, and those working in physical occupations. These results highlight the importance of evaluating economic outcomes such as labor supply as part of an assessment of the overall benefits of medical technology. The second essay builds on work by Allin et al. (2010) and Hurley et al. (2011) that systematically analyzes the relationship between subjective unmet need and healthcare utilization. However, unlike previous work that uses cross-sectional data, I use panel data from the National Population Health Survey (NPHS) to control for fixed unobserved individual heterogeneity. In addition, healthcare utilization is modeled using latent class models for panel data, which outperform traditional hurdle models. The results of this study confirm previous findings of different patterns of healthcare utilization among individuals with system-related unmet needs, personal-related unmet needs, and no unmet needs. Individuals with personal-related unmet needs tended to use the same amount of services as expected based on their needs. On the other hand, individuals with system-related unmet needs were found to not only be high users of GP and specialist visits, they were also higher-than-expected users. The third essay examines long-term changes in socioeconomic inequality and inequity in influenza immunization in Canada. The concentration index framework is applied using data from the following two Statistics Canada surveys: the cross-sectional component of the 1996/97 National Population Health Survey (NPHS), and the 2007/08 Canadian Community Health Survey (CCHS). The results show large variations in both coverage and inequity across provinces. In addition, increases in coverage levels across many provinces seem to have drawn disproportionately from those of higher socioeconomic status, contributing to a growing pro-rich inequity in utilization. These results highlight the need for more targeted efforts to help reduce inequities in vaccination.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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".