Quality of care of nurse-led and allied health personnel-led primary care clinics.
Bibliographic record
Abstract
OBJECTIVES: To review the literature regarding quality of care of nurse-led and allied health personnel-led primary care clinics with specific attention to the quality indicators for fall prevention, continence care, pulmonary rehabilitation, mental health, pharmaceutical care, and wound care services. DATA SOURCES: Literature search from 1990 to 2010 including Ovid Medline, Cochrane Database, RAND (Research and Development) Corporation Health Database, the ACOVE (Assessing the Care of Vulnerable Elders) project and clinical guidelines from the United Kingdom, Australia, Canada, and the United States. STUDY SELECTION: This review was limited to studies involving adult, primary care patients. Where available, evidence from systematic reviews and meta-analyses were used to synthesise findings. DATA EXTRACTION: Combinations of the following terms (and related terms) were used to identify studies: primary care, clinic, allied-health, nurse-led, fall prevention, continence care, incontinence, chronic obstructive pulmonary disorder, pulmonary disease, respiratory rehabilitation, mental health, mental wellbeing, depression, anxiety, wound care, leg ulcer, venous ulcer, dressings clinic, wound clinic, medication review, pharmacist-led, pharmaceutical care. DATA SYNTHESIS: A total of 21 international guidelines and 33 studies were selected for data synthesis. Despite a lack of consistent outcomes data, it is apparent that certain aspects of organisational structure and clinical care processes are important though not necessarily sufficient indicators of quality of care, because they themselves can influence care outcomes. Seven key factors were identified which seem important determinants of the quality of care provided by nurse- and allied health personnel-led clinics. CONCLUSION: Delivery of primary health care by nurse and allied health personnel-led teams is a well-established model, internationally. Evidence from the literature provides benchmarks for standards of good practice. Knowledge of factors influencing quality of care can assist the planning, implementation, evaluation, and further expansion of such programmes, locally.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".