Recommendations for Medical and Mental Health Care in Assisted Living Based on an Expert Delphi Consensus Panel
Bibliographic record
Abstract
Importance: Assisted living (AL) is the largest provider of residential long-term care in the US, and the morbidity of AL residents has been rising. However, AL is not a health care setting, and concern has been growing about residents' medical and mental health needs. No guidance exists to inform this care. Objective: To identify consensus recommendations for medical and mental health care in AL and determine whether they are pragmatic. Evidence Review: A Delphi consensus statement study was conducted in 2021; as a separate effort, the extent to which the recommendations are reflected in practice was examined in data obtained from 2016 to 2021 (prepandemic). In the separate effort, data were from a 7-state study (Arkansas, Louisiana, New Jersey, New York, Oklahoma, Pennsylvania, Texas). The 19 Delphi panelists constituted nationally recognized experts in medical, nursing, and mental health needs of and care for older adults; dementia care; and AL and long-term care management, advocacy, regulation, and education. One invitee was unavailable and nominated an alternate. The primary outcome was identification of recommended practices based on consensus ratings of importance. Panelists rated 183 items regarding importance to care quality and feasibility. Findings: Consensus identified 43 recommendations in the areas of staff and staff training, nursing and related services, resident assessment and care planning, policies and practices, and medical and mental health clinicians and care. To determine the pragmatism of the recommendations, their prevalence was examined in the 7-state study and found that most were in practice. The items reflected the tenets of AL, the role of AL in providing dementia care, the need for pragmatism due to the diversity of AL, and workforce needs. Conclusions and Relevance: In this consensus statement, 43 recommendations important to medical and mental health care in AL were delineated that are highly pragmatic as a guide for practice and policy.
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 | 0.260 | 0.276 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.005 | 0.013 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".