Hidden big data analytics issues in the healthcare industry

Area of Science:

• Health Informatics
• Data Science
• Empirical Research

Background:

• Big data analysis is increasingly vital for healthcare research.
• Identifying challenges in healthcare big data analytics is crucial for reliable empirical studies.
• Existing literature highlights common issues, but deeper problems may persist.

Purpose of the Study:

• To identify significant big data analysis issues impacting empirical healthcare research.
• To synthesize key problems affecting quantitative big data analysis in health studies.
• To propose solutions for critical challenges in healthcare big data analytics.

Main Methods:

• Literature review of big data keywords in peer-reviewed journals since 2011.
• Analysis of topics, methods, techniques, strengths, and weaknesses.
• Interviews with subject matter experts using systems thinking action research.

Main Results:

• Identified common big data analysis issues in healthcare research.
• Validated findings with subject matter experts.
• Discovered three previously undetected, critical issues in healthcare big data analysis.

Conclusions:

• Healthcare big data analysis faces significant methodological and statistical challenges.
• Three fatal issues were identified that require specific attention.
• Proposed methodical and statistical control solutions to address these critical healthcare big data issues.