Chronic Obstructive Pulmonary Disease. Health Disparity and Inequity
Bibliographic record
Abstract
The Centers for Disease Control and Prevention describes health disparities that “negatively affect groups of people who have systematically experienced greater social or economic obstacles to health” and inequity as a “difference or disparity in health outcomes that is systematic, avoidable, and unjust” (1). Despite being the only major leading cause of death that continues to increase (2), chronic obstructive pulmonary disease (COPD) is rarely a disease championed by celebrities or the public. COPD is not the subject of viral social media campaigns, such as the recent ice-bucket challenge to fund research for Amyotrophic Lateral Sclerosis, a disease that often afflicts younger, otherwise healthy individuals. The face of the patient with COPD is typically older, of lower socioeconomic status, and in the view of many, suffering from self-inflicted injury. The insidious onset and gradual decline in health and functional status that is characteristic of COPD does not typically garner the public support of conditions that are rapidly fatal, such as lung cancer, nor does treatment lead to rapid improvements in health and functional status, such as with low-ejection fraction heart failure. In turn, COPD has received relatively scant attention from primary care clinicians, funders of researchers, and policy makers (3, 4). Nihilism for what can be done for patients with COPD remains rampant, despite a robust evidence base to the contrary (5). By all accounts, patients with COPD represent the paradigm of a group of people at risk for health disparity and inequity. In this issue of AnnalsATS, Gershon and colleagues (pp. 1195–1202) describe a white cloud, but one with a foreboding shadow (6). Using data collected as part of the Provincial Health Ministry from Ontario, Canada, Gershon and colleagues demonstrate that from 1996 to 2011–2012, the COPD population became older and included a greater number of women. In addition, the authors report that among patients with COPD, the standardized mortality decreased 35% during this 16-year period. Although this is encouraging, the reduction in mortality was not shared equitability among patients. Across quintiles of income, patients in the lowest quintiles of income experienced the least mortality benefit. These results are important especially within the United States, where COPD mortality has been flat or continues to rise relative to that of other conditions. Although there are many possible explanations, an obvious difference between patients with COPD in Ontario and those in the United States is the difference in access to healthcare. Unlike in the United States, where health insurance is provided through a porous patchwork of sources, the ability to purchase insurance is not a barrier to healthcare access in Canada, where health insurance coverage is nearly universal. Mortality among patients with COPD is not the same as mortality attributed to COPD. Among patients with COPD, the leading cause of death is attributed to disease comorbidity, not COPD itself. Only among a minority of patients with severe disease does respiratory failure become a leading cause of mortality. One important reason that patients with COPD are at risk for health disparity is most likely not the COPD treatment itself but, instead, modifying COPD comorbidity. Depending on the severity of COPD, the leading cause of death is either cardiovascular disease or lung cancer. Tobacco use, which causes death from both these conditions, has decreased more among patients of higher socioeconomic than lower socioeconomic status. Likewise, other factors associated with early mortality, such as limited access to healthy foods and obesity, are also significantly higher among patients of lower socioeconomic status. The results of Gershon’s article also imply that solving the insurance issue alone may not solve the access or health delivery issue for patients with COPD. Several other factors may represent barriers to receipt of quality care for COPD, such as that patients with limited socioeconomic means often live in more rural areas or within urban environments with significant barriers to transportation (7). Missing work may also have a significant effect on an individual’s income, leading to the decision to forego both preventative and ongoing healthcare. Similarly, being health literate is essential to gain access to complex healthcare systems and to be adherent to multiple medical therapies, both for
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.028 | 0.002 |
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".