Patterns of health care use in a high-cost inpatient population in Ottawa, Ontario: a retrospective observational study
Bibliographic record
Abstract
BACKGROUND: A small proportion of patients account for the majority of health care spending. We used detailed clinical and administrative data to explore clinical characteristics, patterns of health care use and changes in cost profiles over time among high-cost inpatients in an acute tertiary care hospital in Ottawa, Ontario. METHODS: We identified all people who had 1 or more inpatient admissions to The Ottawa Hospital between Apr. 1, 2009, and Mar. 31, 2012. We calculated the direct inpatient costs using case-costing information to categorize patients into persistently high-cost, episodic high-cost and non-high-cost groups. Within each group, we used discharge abstracts to measure encounter-level characteristics and patterns of inpatient health care use over time. We also developed transition matrices to explore how inpatient costing states changed over time. RESULTS: During the study period, 100 178 patients had 132 996 hospital admissions. Hospital spending was often limited to a single year for most of the patients (90.2%), with only a small proportion (7.4%) of patients remaining in the high-cost group in the subsequent year. Patients in the persistently (n = 236) and episodic (n = 5062) high-cost groups were often older, had medically complex conditions and generated most of the costs from nursing care and intensive care. Compared with patients in the other cost groups, those in the persistently high-cost group were more likely to have multiple readmissions (43.4%) and multiple placements in an alternate level of care (19.0%) and were high users of health care services outside of the hospital setting. INTERPRETATION: Hospital spending was often limited to a single year for most patients, and only a small proportion of patients remained in the high-cost group in the subsequent year. These persistently high-cost patients had medically complex conditions and often required expensive care. A greater understanding of the circumstances that result in persistent hospital spending remains an area for future work, including an exploration of the potential barriers impeding efficient transition out of acute care for high-risk patients.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 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 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".