Facilitators and barriers of implementing the WHO ICOPE care model in Nepal: A clinical perspective
Bibliographic record
Abstract
• The Integrated Care for Older People (ICOPE) care model is being actively implemented worldwide, including Nepal. • ICOPE implementors in Nepal were surveyed to identify the barriers and facilitators of implementing ICOPE. • Lack of suitable infrastructure, shortage of trained workforce, low priority for geriatric health, lack of guidelines and funding were considered the major barriers. • Continuous government ICOPE training programs, support from the WHO, and motivated healthcare workers were considered the major facilitators. • Lack of systematic dedicated referral system was considered a primary barrier to complete the four steps of ICOPE care model. The Integrated Care for Older People (ICOPE) care model is being actively implemented worldwide, including in low-resource countries like Nepal. We aimed to conduct a survey to understand the major barriers and facilitators of implementing ICOPE in Nepal from a clinical perspective. A survey questionnaire was developed to assess the barriers and facilitators of implementing ICOPE at the micro, meso , and macro levels and the recommended four steps of ICOPE. Relevant suggestions for improving ICOPE were also collected from the implementors. Among the 11 (ICOPE implementors) respondents, four were geriatricians and seven were non-geriatric clinicians. Lack of suitable infrastructure, shortage of trained workforce, comparatively low priority for geriatric health and geriatrics, lack of national guidelines and funding were considered the major barriers for implementing ICOPE in Nepal. Major facilitators for implementing ICOPE in Nepal were motivated healthcare workers, continuous support from the WHO, and government ICOPE training programs. Lack of a systematic referral framework with no provision of electronic health records and a dedicated team were considered as major barriers in completing the recommended four steps of ICOPE. The respondents thought the ICOPE application was feasible in Nepal, which could also serve as a tool to share health records digitally. Additionally, localisation of the ICOPE pathway was suggested. The ICOPE care pathway was considered quite feasible in Nepal by the implementors, although more work is needed to remove the current barriers and embed ICOPE in the existing healthcare system.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".