Examining Satisfaction and Quality in Home- and Community-Based Service Programs in the United States: A Scoping Review
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Long-term services and supports in the United States are increasingly reliant on home- and community-based services (HCBS). Yet, little is known about the quality of HCBS. We conducted a scoping review of the peer-reviewed literature to summarize HCBS consumer, provider, and stakeholder satisfaction with services as a means of assessing quality. RESEARCH DESIGN AND METHODS: We searched PubMed, OVID-MEDLINE, and SCOPUS to identify articles published from 2000 to 2021 that reported on studies describing a U.S.-based study population. Articles were grouped into 3 categories: drivers of positive consumer satisfaction, drivers of negative consumer satisfaction, and provider and stakeholder perspectives on satisfaction. RESULTS: Our final sample included 27 articles. Positive perceptions of quality and reported satisfaction with services were driven by consistent, reliable, and respectful care providers, and adoption of person-centered models of service delivery. Mistreatment of consumers, staff turnover, training, service interruptions, and unmet functional needs were drivers of negative consumer perceptions of quality. Support for caregivers and emphasis on training were identified by providers and stakeholders as important for providing satisfactory services. DISCUSSION AND IMPLICATIONS: Multiple data challenges limit the ability to systematically evaluate HCBS program quality; however, studies examining single programs found that HCBS consumers are more satisfied and associate higher quality with easy-to-navigate programs and professional staff. Efforts to expand HCBS should also include requirements to systematically evaluate quality outcomes.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".