The cost of schizophrenia: lessons from an international comparison.
Bibliographic record
Abstract
BACKGROUND: A number of studies have attempted to estimate the aggregate burden of mental illness in particular countries. It has been observed that the economic costs vary by country. This is particularly true for estimates of the cost of schizophrenia, a severe mental illness that can lead to major psychiatric disability. The reasons for this may be due to differences in populations, measurement methods or quality of care. AIMS OF THE STUDY: This paper reviews three key studies of the cost of schizophrenia in Canada, the United States and the United Kingdom with an emphasis on a US-Canada comparison. The detailed focus allows for an in-depth study of the factors that lead to different cost estimates. A secondary aim of this paper is to illustrate the importance of direct and indirect costs in the measurement of economic burden. METHODS: We explore various hypotheses about why three major studies of the economic burden of schizophrenia suggest large differences in the estimated per capita costs when expressed in the same currency. We discuss adjustments that may be made in the reported cost estimates to account for factors such as higher wages or lower administrative costs, in order to make them more comparable. RESULTS: In spite of the many adjustments, the estimated per capita resources spent on care for people with schizophrenia in Canada is less than half of the corresponding amount in the US (1,122 million dollars compared to 2,306 million dollars). Even though adjusting for per capita income narrows the apparent gap between the Canadian and US figures, it still remains very large. Since adjusting for per capita income almost certainly over-adjusts for resources spent in the US as compared to Canada, it is clear that the true difference is very large. Even though the per capita direct costs in Canada are only about a third as large as the corresponding US figure, the UK figure is less than half of Canada's. Coincidentally, if one assumes that the true prevalence rate in the UK is similar to that estimated for Canada and adjusts figures accordingly, the result is an estimate for direct costs that is quite similar to the Canadian one. DISCUSSION AND LIMITATIONS: With respect to direct costs, a key finding in the paper is the very large difference in the per capita cost of treatment of schizophrenia in Canada and the United States. From the standpoint of Canadian public policy, the worrisome policy question that this raises is whether the findings reflect, on average, a relatively less satisfactory level of treatment for those with schizophrenia in Canada. An important limitation is that we do not analyze quality of care data. Our detailed item by item comparison of the estimates attempts to rule out alternative explanations in order to discover whether a quality difference may actually exist. IMPLICATIONS FOR HEALTH POLICIES: This research reviews US and international estimates of the economic burden of schizophrenia. In the process of summarizing what is known, a remarkable difference in the direct cost of schizophrenia is uncovered. Possible methodological and economic explanations are investigated (e.g., adjustments for different financial currencies and study methodologies). Nevertheless, the results appear robust to a variety of sensitivity analyses. From the standpoint of public policy, the worrisome question that this raises is whether these findings reflect, on average, a relatively lower quality of care for Canadians with schizophrenia or wasteful care for Americans with schizophrenia.
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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 | 0.008 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".