Toward Benchmarks for Tertiary Care for Adults with Severe and Persistent Mental Disorders
Bibliographic record
Abstract
BACKGROUND: Scarce attention has been paid to establishing benchmarks for tertiary care for adults with severe mental disorders. Yet, the availability and efficient utilization of residential resources partly determines the capacity of a comprehensive system of care to avoid clogging ever-shrinking acute care bed facilities. OBJECTIVES: To describe the actual utilization of and projected needs for residential resources, one part of tertiary care, in the catchment area of a psychiatric hospital in east-end Montreal. To compare results obtained against actual utilization and projected needs evaluated in other Canadian provinces and in other countries, with a view to establishing national benchmarks. METHODS: Two surveys were undertaken to establish the number of places in these facilities that were utilized and needed for adults aged 18 to 65 years with severe mental disorders, without a primary diagnosis of mental retardation or organic brain syndrome, and originally from the catchment area. A first survey ascertained the number of places utilized and of those needed for residential care among all long-stay inpatients and all adults in supervised residential facilities. A second survey identified the need for such long-stay hospitalization, nursing homes, and supervised facilities as an alternative or as a complement to hospitalization among acute care inpatients. RESULTS: The actual ratio of places in long-stay hospital units, nursing homes, and supervised residential facilities was 150:100,000 inhabitants. The ideal ratio, according to estimated needs, is 171:100,000. The figure breakdown is as follows: 20:100,000 for long-stay hospital units, 20:100,000 for nursing homes, 40:100,000 for group homes, 40:100,000 for private hostels or foster families, and 51:100,000 for supervised apartments. The needs of this urban, blue-collar population for supervised residential places hovered in the upper range of utilization and standards for European countries and within the proposed standards for Canadian provinces. DISCUSSION: Needs for long-stay hospitalization or for supervised residential facilities cannot be treated as absolute. For example, evaluation conducted in this hospital-led system of psychiatric care may produce higher estimates of institutional care. Comparing actual utilization and projected needs in this urban catchment area with current utilization in other jurisdictions in Canada and Europe should contribute to establishing sound national benchmarks within ranges. CONCLUSIONS: It is possible to establish benchmarks that guide the development of supervised residential settings to best meet the needs of the population of adults with severe and persistent mental disorders. The methods used here to assess needs should serve as guidelines for future research, because they were designed to contain the bias of over- or underprovision of care in the current utilization.
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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 | 0.024 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".