Issue #2 Week of Jul 13, 2026 – Jul 27, 2026
This issue centers on clinical decision support, with four papers testing how AI tools assist nurses in specific tasks: comparing large language models on oncology nursing scenarios, building a delirium-screening agent for ICU settings, reviewing AI use across clinical pharmacy, and developing a machine learning model to flag financial toxicity in stroke patients. A second thread looks at extracting information from unstructured text, including a review of AI for automated ICD coding and a generative AI approach to finding fall risk factors in aged care nursing notes. Workflow redesign also appears, through a voice documentation pilot and a co-designed initial assessment form.
Papers dropped from 49 to 10, and the leading topic shifted from Workforce & Education (29 papers last issue) to Clinical Decision Support (4 papers this issue), with education's share falling to just two papers, one a review protocol not yet reporting findings. The clinical decision support thread continues from last issue but shifts focus, moving from triage and risk-prediction tools toward LLM-based agents and screening support. Documentation and generative AI threads also continue, echoed in the voice documentation pilot and text-extraction studies. Patient-facing AI tools and AI ethics papers, both present last issue, do not appear this issue.
How this digest is made: Papers retrieved bi-weekly from the community-configured sources (PubMed, arXiv, medRxiv, and/or CINAHL — see Digest Settings for this issue's exact sources) using search terms agreed at AINurse-26. Results are restricted to English-language papers; both title and abstract are checked independently, and either being predominantly non-English excludes the paper. Papers are then classified against the community's chosen topics — anything that doesn't clearly match is left out of the issue rather than shown as "Other." Summaries are generated by Claude Sonnet, constrained to report only what the abstract states, with no speculation or inference. The "At a Glance" section above is written under the same constraints — the model synthesizes themes only from the summaries included in this issue, and every number in it (counts, changes since the previous issue) is computed directly from the archive, not by the model. Flagged items indicate incomplete abstracts or unverified peer-review status.