Patient satisfaction with chronic HIV care provided through an innovative pharmacist/nurse-managed clinic and a multidisciplinary clinic
Bibliographic record
Abstract
BACKGROUND: Pharmacist/nurse-led clinics are an established model for many chronic diseases but not yet for HIV. At our centre, patients with HIV are seen by a multidisciplinary team (physician, nurse, pharmacist, social worker) at least yearly. Some attend an HIV-specialist pharmacist/nurse clinic (or "nonphysician clinic," NPC) for alternate biannual visits. Our objective was to assess patient satisfaction with care received through both clinics. METHODS: The Patient Satisfaction Survey for HIV Ambulatory Care (assesses satisfaction with access to care, clinic visits and quality of care) was administered by telephone to adults who attended either clinic between January and July 2014. Descriptive statistics described patient characteristics and satisfaction scores. Fisher's exact test compared satisfaction scores between the NPC and multidisciplinary clinic (MDC). Multivariate logistic regression examined associations between overall satisfaction with care and clinic type and patient characteristics (e.g., age, disease duration). RESULTS: = 0.6). Patients from both clinics expressed satisfaction with access to care, treatment plan input, their provider's knowledge of the newest developments in HIV care and explanation of medication side effects, with no significant differences noted. Significantly more MDC patients reported being asked about housing/finances, alcohol/drug use and whether they needed help disclosing their status. Patient characteristics were not significantly associated with satisfaction with overall quality of care. CONCLUSION: Patients are satisfied with both clinics, supporting NPC as an innovative model for chronic HIV care. Comparison of outcomes between clinics is needed to ensure high-quality care.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".