Transformative Insights into Community-Acquired Pressure Injuries Among the Elderly: A Big Data Analysis.

Area of Science:

• Gerontology
• Data Science in Healthcare
• Nursing Research

Background:

• Community-acquired pressure injuries (CAPIs) are a significant concern in older populations.
• Effective detection and prevention strategies are crucial for improving patient outcomes and reducing healthcare burdens.

Purpose of the Study:

• To leverage big data analytics to identify novel patient characteristics associated with CAPIs in older adults.
• To inform the development of data-driven approaches for CAPI detection and prevention.

Main Methods:

• Retrospective analysis of electronic medical records from 44,449 internal medicine inpatients across two medical centers (2016-2018).
• Data engineers curated and coded nursing assessments, while data scientists analyzed patient characteristics, CAPI details, vital signs, and lab results within 36 hours of admission.

Main Results:

• CAPIs were most prevalent on the buttocks (56.9%), sacrum (11.8%), and ankle (10.8%).
• Injury severity ranged from first-degree (31%) to third-degree (18%).
• Novel associated patient characteristics include age, oxygen use, intestinal function, sensory perception (heat/pain), albumin levels, red cell distribution width (RDW), and systolic blood pressure.

Conclusions:

• Data-driven identification of novel CAPI indicators enhances early detection and prevention strategies.
• Integrating these new insights into clinical practice, particularly in community nursing, can improve care quality and safety for the elderly.