# Search Strategy Formulation for Systematic Reviews: issues, challenges and opportunities

arXiv: https://arxiv.org/abs/2112.09424 · HTML: https://mlsanity.com/paper/2112.09424/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Dec 2021.

## Built on by (most cited first, 6 of 6)

- [Can ChatGPT Write a Good Boolean Query for Systematic Review Literature Search?](https://mlsanity.com/paper/2302.03495/) (2023)
- [Neural Rankers for Effective Screening Prioritisation in Medical Systematic Review Literature Search](https://mlsanity.com/paper/2212.09017/) (2022)
- [Can Open-Source LLMs Compete with Commercial Models? Exploring the Few-Shot Performance of Current GPT Models in Biomedical Tasks](https://mlsanity.com/paper/2407.13511/) (2024)
- [Is ChatGPT a Biomedical Expert? -- Exploring the Zero-Shot Performance of Current GPT Models in Biomedical Tasks](https://mlsanity.com/paper/2306.16108/) (2023)
- [The Impact of LLM-Assistants on Software Developer Productivity: A Systematic Review and Mapping Study](https://mlsanity.com/paper/2507.03156/) (2025)
- [A New Dataset for Topic-Based Paragraph Classification in Genocide-Related Court Transcripts](https://mlsanity.com/paper/2204.02712/) (2022)

## Abstract (arXiv)

Systematic literature reviews play a vital role in identifying the best available evidence for health and social care policy. The resources required to produce systematic reviews can be significant, and a key to the success of any review is the search strategy used to identify relevant literature. However, the methods used to construct search strategies can be complex, time consuming, resource intensive and error prone. In this review, we examine the state of the art in resolving complex structured information needs, focusing primarily on the healthcare context. We analyse the literature to identify key challenges and issues and explore appropriate solutions and workarounds. From this analysis we propose a way forward to facilitate trust and transparency and to aid explainability, reproducibility and replicability through a set of key design principles for tools to support the development of search strategies in systematic literature reviews.