Health Care Contact Days Among Older Cancer Survivors
Bibliographic record
Abstract
PURPOSE: Health care contact days-days spent receiving health care outside the home-represent an intuitive, practical, and person-centered measure of time consumed by health care. METHODS: We linked 2019 Medicare Current Beneficiary Survey and traditional Medicare claims data for community-dwelling older adults with a history of cancer. We identified contact days (ie, spent in a hospital, emergency department, skilled nursing facility, or inpatient hospice or receiving ambulatory care including an office visit, procedure, treatment, imaging, or test) and described patterns of total and ambulatory contact days. Using weighted Poisson regression models, we identified factors associated with contact days. RESULTS: We included 1,168 older adults representing 4.51 million cancer survivors (median age, 76.4 years, 52.8% women). The median (IQR) time from cancer diagnosis was 65 (27-126) months. In 2019, these adults had mean (standard deviation) total contact days of 28.4 (27.6) and ambulatory contact days of 24.2 (23.6). These included days for tests (8.0 [8.8]), imaging (3.6 [4.1]), visits with any clinicians (12.4 [11.5]), and visits with primary care clinicians (4.4 [4.7]), and nononcology specialists (7.1 [9.4]) specifically. Sixty-four percent of days with a nonvisit ambulatory service (eg, a test) were not on the same day as a clinician visit. Factors associated with more total contact days included younger age, lower income, more chronic conditions, poor self-rated health, and tendency to "go to doctor as soon as feel bad." CONCLUSION: Older adult cancer survivors spent nearly 1 month of the year receiving health care outside the home. This care was largely ambulatory, often delivered by nononcologists, and varied by factors beyond clinical characteristics. These results highlight the need to recognize patient burdens and improve survivorship care delivery, including through care coordination.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".