A qualitative study of the dissemination and diffusion of innovations: bottom up experiences of senior managers in three health districts in South Africa
Bibliographic record
Abstract
BACKGROUND: In 2012 the South African National Department of Health (SA NDoH) set out, using a top down process, to implement several innovations in eleven health districts in order to test reforms to strengthen the district health system. The process of disseminating innovations began in 2012 and senior health managers in districts were expected to drive implementation. The research explored, from a bottom up perspective, how efforts by the National government to disseminate and diffuse innovations were experienced by district level senior managers and why some dissemination efforts were more enabling than others. METHODS: A multiple case study design comprising three cases was conducted. Data collection in 2012 - early 2014 included 38 interviews with provincial and district level managers as well as non- participant observation of meetings. The Greenhalgh et al. (Milbank Q 82(4):581-629, 2004) diffusion of innovations model was used to interpret dissemination and diffusion in the districts. RESULTS: Managers valued the national Minister of Health's role as a champion in disseminating innovations via a road show and his personal participation in an induction programme for new hospital managers. The identification of a site coordinator in each pilot site was valued as this coordinator served as a central point of connection between networks up the hierarchy and horizontally in the district. Managers leveraged their own existing social networks in the districts and created synergies between new ideas and existing working practices to enable adoption by their staff. Managers also wanted to be part of processes that decide what should be strengthened in their districts and want clarity on: (1) the benefits of new innovations (2) total funding they will receive (3) their specific role in implementation and (4) the range of stakeholders involved. CONCLUSION: Those driving reform processes from 'the top' must remember to develop well planned dissemination strategies that give lower-level managers relevant information and, as part of those strategies, provide ongoing opportunities for bottom up input into key decisions and processes. Managers in districts must be recognised as leaders of change, not only as implementers who are at the receiving end of dissemination strategies from those at the top. They are integral intermediaries between those at the at the coal face and national policies, managing long chains of dissemination and natural (often unpredictable) diffusion.
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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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.009 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".