Chronic Care Model Decision Support and Clinical Information Systems Interventions for People Living with HIV: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: The Chronic Care Model is an effective framework for improving chronic disease management. There is scarce literature describing this model for people living with HIV. Decision Support (DS) and Clinical Information Systems (CIS) are two components of this model that aim to improve care by changing health care provider behavior. OBJECTIVE: Our aim was to assess the effectiveness of DS and CIS interventions for individuals with HIV, through a systematic literature review. DESIGN: We performed systematic electronic searches from 1996 to February 2011 of the medical (E.g. Medline, EMBASE, CINAHL) and grey literature. Effectiveness was measured by the frequency of statistically significant outcome improvement. Data and key equity indicator extraction and synthesis was completed. PARTICIPANTS AND INTERVENTIONS: We included comparative studies of people living with HIV that examined the impact of DS or CIS interventions on outcomes. MAIN MEASURES: The following measures were assessed: outcome (immunological/virological, medical, psychosocial, economic measures) and health care process/performance measures. KEY RESULTS: Records were screened for relevance (n = 10,169), full-text copies of relevant studies were obtained (n = 123), and 16 studies were included in the review. Overall, 5/9 (55.6%) and 17/41 (41.5%) process measures and 5/12 (41.7%) and 3/9 (33.3%) outcome measures for DS and CIS interventions, respectively, were statistically significantly improved. DS-explicit mention of implementation of guidelines and CIS-reminders showed the most frequent improvement in outcomes. DS-only interventions were more effective than CIS-only interventions in improving both process and outcome measures. Clinical, statistical and methodological heterogeneity among studies precluded meta-analysis. Primary studies were methodologically weak and often included multifaceted interventions that made assessment of effectiveness challenging. CONCLUSIONS: Overall, DS and CIS interventions may modestly improve care for people living with HIV, having a greater impact on process measures compared to outcome measures. These interventions should be considered as part of strategies to improve HIV care through changing provider performance.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".