ArticleNursing & health sciences2026
The Impact of Real-Time Data Analytics on Infection Prevention and Control Practices in Ophthalmology: A Nursing Perspective on Patient Outcomes and Cost-Effectiveness.
Article in Nursing & health sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
4 authors.
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Abstract
Ophthalmic surgeries pose infection risks. Traditional control methods rely on manual monitoring, creating a need for more precise, data-driven nursing models. This study evaluated the effectiveness of real-time data analysis in improving ophthalmic infection prevention and control outcomes. This study was designed as a single-center retrospective study. We analyzed 213 patients (2022-2024). The conventional group (n = 105) received conventional care, while the real-time data analytics group (n = 108) received real-time data-driven infection prevention and control. Measured outcomes included infection rates, complications, visual acuity, quality of life, visual function, pain scores, costs, and cost-effectiveness. The real-time data analytics group showed significantly better outcomes: lower infection rates (p = 0.032), better visual acuity (p = 0.042), and less pain (p = 0.024). They also had higher quality of life (p = 0.036) and visual function scores (p = 0.032). Direct medical costs and nursing costs were significantly lower (p < 0.001), with the ICER was -11656.22 yuan/QALY, indicating a dominant economic result. Real-time data analysis enables dynamic risk monitoring and precise interventions in ophthalmic nursing. This approach reduces infections, improves visual outcomes, lowers costs, and enhances cost-effectiveness, supporting standardized quality improvement in infection prevention and control.
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