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Record W4401230870 · doi:10.1016/j.jfma.2024.07.030

Reflection on 30 years of Taiwanese national health insurance: Analysis of Taiwanese health system progress, challenges, and opportunities

2024· review· en· W4401230870 on OpenAlexaff
Sian Hsiang‐Te Tsuei

Bibliographic record

VenueJournal of the Formosan Medical Association · 2024
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsSimon Fraser UniversityUniversity of British Columbia
Fundersnot available
KeywordsMedicineAllocative efficiencyIncentiveHealth careWorkforceHealth economicsPublic healthActuarial scienceFinanceEconomic growthNursingBusinessEconomics

Abstract

fetched live from OpenAlex

On the eve of Taiwan's National Health Insurance's 30th birthday, this study reviews the policy and performance trajectory of the Taiwanese health system. Taiwan has controlled their health spending well and grown increasingly reliant on private financing. The floating-point global budget payment preferentially rewards outpatient-based services, but this has not affected the hospital-centric market composition, which persists despite several primary-care friendly developments. The outcomes suggest improving health care workforce and resource availability, good patient-centredness, respectable technical efficiency, and impressive patient care satisfaction. However, there are worrisome trends for financial barriers to access and allocative efficiency. Evidence on clinical quality suggests that hospitals are performing well though the primary care setting might not be. Overall, the public remains satisfied despite signs of lagging improvement in health outcomes, worsening maternal mortality rate, and persistently incomplete financial risk protection. Identifying what drives the worsening financial barriers of access and persistent financial risk is necessary for further discussions on potential financing adjustments. Improving allocative efficiency could draw on a combination of supporting the functions and quality of primary care alongside patient-oriented education and incentives. Further data on causes of slow health status improvement and rebounding maternal mortality rate is necessary.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.979
Threshold uncertainty score0.535

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.173
GPT teacher head0.381
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations15
Published2024
Admission routes1
Has abstractyes

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