Case management for dementia in primary health care: a systematic mixed studies review based on the diffusion of innovation model
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to examine factors associated with the implementation of case management (CM) interventions in primary health care (PHC) and to develop strategies to enhance its adoption by PHC practices. METHODS: This study was designed as a systematic mixed studies review (including quantitative and qualitative studies) with synthesis based on the diffusion of innovation model. A literature search was performed using MEDLINE, PsycInfo, EMBASE, and the Cochrane Database (1995 to August 2012) to identify quantitative (randomized controlled and nonrandomized) and qualitative studies describing the conditions limiting and facilitating successful CM implementation in PHC. The methodological quality of each included study was assessed using the validated Mixed Methods Appraisal Tool. RESULTS: Twenty-three studies (eleven quantitative and 12 qualitative) were included. The characteristics of CM that negatively influence implementation are low CM intensity (eg, infrequent follow-up), large caseload (more than 60 patients per full-time case manager), and approach, ie, reactive rather than proactive. Case managers need specific skills to perform their role (eg, good communication skills) and their responsibilities in PHC need to be clearly delineated. CONCLUSION: Our systematic review supports a better understanding of factors that can explain inconsistent evidence with regard to the outcomes of dementia CM in PHC. Lastly, strategies are proposed to enhance implementation of dementia CM in PHC.
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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 | 0.012 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it