{"title":"Using ChatGPT‑4.0 to Address Nurse Scheduling Challenges in a Cardiology Clinic.","authors":"Kimberly Rusk, Rosemary Slotkus, Ozioma Abaribe, Jenny O'Rourke","doi":"10.1097/NNA.0000000000001715","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Evaluate ChatGPT‑4.0 as a decision‑support tool for an outpatient cardiology nurse scheduling problem.</p><p><strong>Background: </strong>Flexible schedules (4×10) may support retention but often conflict with clinic workflows and coverage needs.</p><p><strong>Methods: </strong>A qualitative case study used constraint mapping and iterative prompt engineering with human oversight to generate and validate schedules against role, full-time equivalent status, and clinic needs.</p><p><strong>Results: </strong>A hybrid 4×10/5×8 model met daily coverage 5 Outpatient Care Center (OCC), 1 Heart Center (HC), and maintained equity, but provided no redundancy for absences; human review resolved role‑specific gaps.</p><p><strong>Conclusions: </strong>ChatGPT can accelerate option generation and quickly solve challenges for nurse managers. Safe and effective use requires clear parameters and rigorous human validation.</p>","PeriodicalId":50108,"journal":{"name":"Journal of Nursing Administration","volume":"56 4","pages":"224-227"},"PeriodicalIF":1.8000,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Nursing Administration","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/NNA.0000000000001715","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/3/23 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"NURSING","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: Evaluate ChatGPT‑4.0 as a decision‑support tool for an outpatient cardiology nurse scheduling problem.
Background: Flexible schedules (4×10) may support retention but often conflict with clinic workflows and coverage needs.
Methods: A qualitative case study used constraint mapping and iterative prompt engineering with human oversight to generate and validate schedules against role, full-time equivalent status, and clinic needs.
Results: A hybrid 4×10/5×8 model met daily coverage 5 Outpatient Care Center (OCC), 1 Heart Center (HC), and maintained equity, but provided no redundancy for absences; human review resolved role‑specific gaps.
Conclusions: ChatGPT can accelerate option generation and quickly solve challenges for nurse managers. Safe and effective use requires clear parameters and rigorous human validation.
期刊介绍：
JONA™ is the authoritative source of information on developments and advances in patient care leadership. Content is geared to nurse executives, directors of nursing, and nurse managers in hospital, community health, and ambulatory care environments. Practical, innovative, and solution-oriented articles provide the tools and data needed to excel in executive practice in changing healthcare systems: leadership development; human, material, and financial resource management and relationships; systems, business, and financial strategies. All articles are peer-reviewed, selected and developed with the guidance of a distinguished group of editorial advisors.
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