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Using an AI-Powered Solution to Transform Nursing Workflow and Improve Inpatient Care: A Retrospective Observational
Luana Llagostera Sillano Gentil1, Vanessa Aparecida Luz Pires, Jéssica Andrade-Silva
1Luana Llagostera Sillano Gentil is the hospital director of the Municipal Hospital Moyses Deutsch in São Paulo, Brazil. Vanessa Aparecida Luz Pires is a nursing coordinator, Jéssica Andrade-Silva is an innovation consultant, Youri Eliphas Almeida is a former innovation consultant, and Claudia Regina Laselva is a hospital unit director, all at the Hospital Israelita Albert Einstein in São Paulo, Brazil. Paulo Gurgel Pinheiro is chief executive officer and Claudio Gurgel Pinheiro is chief operations officer of HOOBOX Robotics in São Paulo. Contact author: Jéssica Andrade-Silva, bio.jandrades@gmail.com. The authors have disclosed no potential conflicts of interest, financial or otherwise.
Background:
Nurses face an escalating workload, including tasks not directly related to patient care, such as responding to patients' requests for water or extra blankets, and adjusting room conditions like air conditioning, which can contribute to burnout and pose potential risks for both professionals and patients.
Purpose:
We aimed to evaluate an artificial intelligence (AI)-driven technology that automates patient requests and directs them to the appropriate teams in other departments instead of to the nurses' station, thereby eliminating the need for nursing intervention.
Methods:
This retrospective observational study, conducted in the surgical clinic of a large hospital over 30 days, examined data gathered from patients occupying 16 beds (as our focus was on the volume and type of patient requests generated per bed rather than per patient, patient turnover did not affect the study). During this period, the AI-driven platform, known as Neonpass Room, was implemented in addition to the traditional bell-activation request system.
Results:
During the 30-day implementation of Neonpass Room, 2,113 requests were recorded, mostly from patients, and the AI-powered system directed 35.4% of those requests, which required clinical attention, to the nursing staff. The remaining requests were routed to other appropriate teams, such as housekeeping or maintenance, according to the nature of the requests. Among the top 10 most frequent request types, only two were explicitly directed to the nursing team: "check IV fluids" and "support with restroom use." The AI platform also measured the response times among the various departments (the nursing team had the shortest response time and the cleaning staff the longest) and enabled the visualization of patterns in patient-initiated requests by request type over a 24-hour period. The AI solution effectively reduced the nursing team's workload by nearly three out of five patient requests, resulting in considerable time savings for nurses.
Conclusion:
Neonpass Room allowed the nursing staff to improve their focus on patient care by optimizing task delegation. Once integrated into the hospital's operations, an AI-driven platform like Neonpass Room would provide managers with valuable strategic insights into the allocation of hospital services.
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Nursing Clinical Information System
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Critical attributes of NCIS include:
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Flow Sheet
Here's a closer look at the examples of flowsheets commonly used by nurses:
Graphic Sheet Documentation:
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