Comprehensive Standardized Assessment for Information Continuity: What Does the Workforce Need
Bibliographic record
Abstract
Introduction: Older adults living with frailty and multimorbidity interact with multiple care providers across different health settings increasing the risk for fragmented care and information discontinuity. Information discontinuity results in workforce inefficiencies and adverse health events, including duplication of assessment and diagnostics, medication errors and increased health service use. Standardized assessments potentiate integrated care by communicating consistent measures of health information between health care sectors and providers. InterRAI assessments facilitate integration through promoting a common language and aligning successive assessments across the care continuum. Description: We used a pragmatic case example of a theoretical medically-complex older adult to illustrate effective use of interRAI standardized assessments throughout the health care journey. The interRAI suite of instruments spans across the age continuum, from pediatrics to geriatrics, and is designed to be used across diverse care settings, including community services, primary care, home care, long-term care, acute care, inpatient and community mental health, and palliative services. The case example represents one patient’s assessment findings, derived from standardized assessment instruments, such as the contact assessment, home care assessment and long-term care facility assessment. Automated and embedded risk algorithms are generated as outputs from the assessment, acting as decision support tools to inform care planning for clinical, functional, and social support needs. Process schematics depict potential workflows, where instruments can guide care strategies and facilitate the flow of information between the care team members. Discussion: Integrating elements such as using a common language, standardized assessment items, and embedded decision support algorithms, can support effective communication and collaboration in the care of older adults between clinical settings. Risk algorithms and scales support real-time identification of care issues, with standardized assessment items allowing for changes in health status to be easily recognized. Operationalizing a suite of standardized assessment instruments across the health system offers advantages for the individual including improved continuity of care, as well as for organizations and the system through use of a consistent measurement of health metrics between health providers and sectors, and evaluating health system performance. Successful adoption of comprehensive assessment tools to support integration requires training, stakeholder engagement and time to embed work and care processes into practice. Conclusion: Standardized language and algorithms used in interRAI comprehensive assessments can increase capacity for integration and continuity of care across the full spectrum of health sectors and settings. Findings from this pragmatic case example demonstrate real-world application and utility of standardized assessments to support an integrated workforce.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.073 | 0.227 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.023 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".