An examination of the causes, consequences, and policy responses to the migration of highly trained health personnel from the Philippines: the high cost of living/leaving—a mixed method study
Bibliographic record
Abstract
BACKGROUND: Dramatic increases in the migration of human resources for health (HRH) from developing countries like the Philippines can have consequences on the sustainability of health systems. In this paper, we trace the outflows of HRH from the Philippines, map out its key causes and consequences, and identify relevant policy responses. METHODS: This mixed method study employed a decentered, comparative approach that involved three phases: (a) a scoping review on health workers' migration of relevant policy documents and academic literature on health workers' migration from the Philippines; and primary data collection with (b) 37 key stakeholders and (c) household surveys with seven doctors, 329 nurses, 66 midwives, and 18 physical therapists. RESULTS: Filipino health worker migration is best understood within the context of macro-, meso-, and micro-level factors that are situated within the political, economic, and historical/colonial legacy of the country. Underfunding of the health system and un- or underemployment were push factors for migration, as were concerns for security in the Philippines, the ability to practice to full scope or to have opportunities for career advancement. The migration of health workers has both negative and positive consequences for the Philippine health system and its health workers. Stakeholders focused on issues such as on brain drain, gain, and circulation, and on opportunities for knowledge and technology transfer. Concomitantly, migration has resulted in the loss of investment in human capital. The gap in the supply of health workers has affected the quality of care delivered, especially in rural areas. The opening of overseas opportunities has commercialized health education, compromised its quality, and stripped the country of skilled learning facilitators. The social cost of migration has affected émigrés and their families. At the household level, migration has engendered increased consumerism and materialism and fostered dependency on overseas remittances. Addressing these gaps requires time and resources. At the same time, migration is, however, seen by some as an opportunity for professional growth and enhancement, and as a window for drafting more effective national and inter-country policy responses to HRH mobility. CONCLUSIONS: Unless socioeconomic conditions are improved and health professionals are provided with better incentives, staying in the Philippines will not be a viable option. The massive expansion in education and training designed specifically for outmigration creates a domestic supply of health workers who cannot be absorbed by a system that is underfunded. This results in a paradox of underservice, especially in rural and remote areas, at the same time as underemployment and outmigration. Policy responses to this paradox have not yet been appropriately aligned to capture the multilayered and complex nature of these intersecting phenomena.
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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 | 0.037 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".