The uses of provincial administrative health databases for research on palliative care: Insights from British Columbia, Canada
Bibliographic record
Abstract
BACKGROUND: Research indicating that people increasingly prefer to die at home suggests that palliative care is likely to play a more prominent role in the future of Canada's health care system. Unfortunately, at a time when research evidence should be informing policy and service delivery, little is known about health service utilization by Canadians at the end of life. One existing mechanism that can help address this gap is provincial administrative health data. The purpose of this study was to explore the potential of administrative health data to identify characteristics of palliative care users, patterns of formal service utilization and predictors of palliative care use. METHODS: Bivariate and multivariate analyses were used to examine data from the Capital Health Region, British Columbia Linked Health Databases for the period 1992/93 to 1998/99. The databases examined include continuing care, physician claims, hospital separations, and vital statistics. As the name implies, these databases can be linked at the individual level using unique identifiers so that health services utilization can be tracked across sectors. RESULTS: General patterns of service use among palliative care patients suggest that general practitioner and medical specialist visits have decreased over time and the utilization of hospital beds has increased. Utilization of community-based services (i.e. home support and home nursing care) shows an overall pattern of decline. However, when compared to non-palliative care patients, palliative care patients spent fewer nights in hospital, used fewer hours of home support, and had a greater number of home nursing care visits. CONCLUSIONS: Administrative health databases can provide valuable information for examining service utilization patterns over time. However, given that decisions surrounding the designation of palliative care include factors beyond the scope of administrative databases (such as quality of life, personal preferences, social support), these databases should only be seen as one source of information to inform service delivery and policy decision making.
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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 | 0.007 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.035 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".