Systematic Literature Review on NLP for Outpatient Referral Triage, 10 Studies

Angela Lim Fung's systematic review and narrative synthesis, published on figshare in 2026, analyzes the use of Natural Language Processing for triaging outpatient referrals. The review screened 4,225 titles and abstracts, ultimately extracting data from 10 studies across specialties like surgery and radiology. It synthesizes findings on model performance, dataset preprocessing, and clinical applicability.

Use Cases

• Benchmarking NLP model performance for referral urgency prioritization based on the review's synthesis of accuracy outcomes.
• Informing dataset preprocessing and augmentation strategies for clinical text based on the review's summarized key differences.
• Assessing the feasibility and clinical applicability of triage models based on the review's narrative synthesis of study results.

Strengths

• Includes a systematic review of 4,225 titles and abstracts, providing a broad survey of recent literature.
• Data extraction and synthesis is based on 10 studies, offering a focused analysis of relevant work.
• Risk of bias was assessed using PROBAST-AI and Technology Readiness scales, indicating a structured evaluation.

Limitations

• The dataset is a 160.5 KB PDF, containing only the review article, not the underlying primary data from the 10 studies.
• Row count and column-level documentation for any primary data are unknown.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Angela Lim Fung via figshare.

Collection Method

Systematic literature review and narrative synthesis of studies from Medline, Embase, Web of Science, and CINAHL up to February 17, 2024.

Time Range

Studies published within the 5 years prior to the search date of February 17, 2024.

Freshness

Last updated 2026-04 05:22:31; freshness should be verified.

Geography

null