Determinants of implementation of maternal health guidelines in Kosovo: mixed methods study
Bibliographic record
Abstract
BACKGROUND: One of the challenges to implementing clinical practice guidelines is the need to adapt guidelines to the local context and identify barriers to their uptake. Several models of framework are available to consider for use in guideline adaptation. METHODS: We completed a multiphase study to explore the implementation of maternal health guidelines in Kosovo, focusing on determinants of uptake and methods to contextualize for local use. The study involved a survey, individual interviews, focus groups, and a consensus meeting with relevant stakeholders, including clinicians (obstetricians, midwives), managers, researchers, and policy makers from the national Ministry of Health and the World Health Organization office in Pristina, Kosovo. RESULTS: Participants identified several important barriers to implementation. First, lack of communication between clinicians and ministry representatives was seen as leading to duplication of effort in creating or adapting guidelines, as well as substantial mistrust between clinicians and policy makers. Second, there was a lack of communication across clinical groups that provide obstetric care and a lack of integration across the entire healthcare system, including rural and urban centers. This fragmentation was thought to have directly resulted from the war in 1998 - 1999. Third, the conflict substantially and adversely affected the healthcare infrastructure in Kosovo, which has resulted in an inability to monitor quality of care across the country. Furthermore, the impact on infrastructure has affected the ability to access required medications consistently and to smoothly transfer patients from rural to urban centers. Another issue raised during this project was the appropriateness of including guideline recommendations perceived to be 'aspirational'. CONCLUSIONS: Implementing clinical practice guidelines in low- and middle-income countries (LMICs) requires consideration of several specific barriers. Particularly pertinent to this study were the effects of recent conflict and the resulting fragmentation of healthcare and communication strategies among relevant stakeholders. However, as Kosovo rebuilds and invests in infrastructure after the conflict, there is a tremendous opportunity to create comprehensive, thoughtful strategies to monitor and improve quality of care. To avoid duplication of effort, it may be beneficial for LMICs to share information on assessing barriers as well as on guideline implementation strategies.
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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 | 0.023 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".