Why the US spends more treating high-need high-cost patients: a comparative study of pricing and utilization of care in six high-income countries
Bibliographic record
Abstract
One of the most pressing challenges facing most health care systems is rising costs. As the population ages and the demand for health care services grows, there is a growing need to understand the drivers of these costs across systems. This paper attempts to address this gap by examining utilization and spending of the course of a year for two specific high-need high-cost patient types: a frail older person with a hip fracture and an older person with congestive heart failure and diabetes. Data on utilization and expenditure is collected across five health care settings (hospital, post-acute rehabilitation, primary care, outpatient specialty and drugs), in six countries (Canada (Ontario), France, Germany, Spain (Aragon), Sweden and the United States (fee for service Medicare) and used to construct treatment episode Purchasing Power Parities (PPPs) that compare prices using baskets of goods from the different care settings. The treatment episode PPPs suggest other countries have more similar volumes of care to the US as compared to other standardization approaches, suggesting that US prices account for more of the differential in US health care expenditures. The US also differs with regards to the share of expenditures across care settings, with post-acute rehab and outpatient speciality expenditures accounting for a larger share of the total relative to comparators.
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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) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".