Operationalizing a holistic health definition as a framework to guide comprehensive assessment at the point of care: a modified eDelphi study
Bibliographic record
Abstract
Background: Holistic assessment of client needs is an important component of person-centred care planning. However, the comprehensive nature of some standardized assessment tools from a documentation perspective, such as the internationally validated interRAI Home Care (interRAI HC) assessment tool, can make conducting and experiencing the assessment as a person-centred and conversational process challenging for both the assessor and the client1. Researchers in the Netherlands proposed the Pillars for Positive Health (PPH) as a broader definition of health to support more realistic and meaningful care planning for people living with chronic disease and other life-long health conditions2. To explore the use of PPH as a framework to guide person-centred care assessment and goal-setting conversations in home care, we sought to map PPH domains to assessment elements from the interRAI HC1. Methods: The study utilized a modified eDelphi approach to conduct a domain mapping exercise with a purposively sampled expert panel (n=25). The panel consisted of researchers, health care providers and older adults and caregivers. The eDelphi process was conducted in two stages, with each stage consisting of three survey rounds. In the first stage, the expert panel were asked to map 201 elements from the interRAI HC to the six PPH domains: 1) Bodily Functions; 2) Daily Functioning; 3) Mental Wellbeing; 4) Quality of Life; 5) Participation; and 6) Meaningfulness. The second stage focused on identifying opportunities to adapt or expand comprehensive assessment as it relates to the PPH domains. Results: In Stage 1, 189 of 201 elements reached consensus. These included: 80 assessment elements for Bodily Functions, 32 for Daily Functioning, 32 for Mental Wellbeing, 24 for Quality of Life, 10 for Participation, 1 for Meaningfulness. Ten elements were identified to have no pillar of best fit. The 12 elements that did not reach consensus in stage 1 formed the basis for Stage 2, where expert panel participants proposed four new assessment elements in the meaningfulness and participation pillars and 12 additional descriptors across the six PPH domains. Of these, two elements, each in both the meaningfulness and participation domains, and 10 of the 12 descriptors reached consensus. Learnings: The expert panel reached agreement on mapping 94% of the assessment elements drawn from the interRAI HC to the six domains of the PPH, confirming the potential use of this framework to operationalize comprehensive and person-centred assessment conversations around a broader definition of health, building on existing international best practices in standardized assessment of home care client needs. Findings indicated interRAI HC assessment elements are oriented toward the physical, functional, and mental health PPH domains. Complementary assessment elements and/or tools may be needed to support comprehensive assessment of ‘meaningfulness’ and ‘participation’ domains in home and community care. Additional descriptors may be needed to aid communication about PPH domains. Next Steps: Home care clinicians will be engaged in leveraging study findings to co-design tools and resources to guide person-centred comprehensive assessment conversations, leveraging PPH domains and additional descriptors to structure dialogue around interRAI-HC elements and other potential complementary assessment elements and/or tools.
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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 | 0.125 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".