Healthcare Analytics Challenges: A Three-Pillar Framework Connecting Analytics Maturity, Workforce Agility, and...

Area of Science:

• Healthcare Informatics
• Knowledge Management
• Natural Language Processing

Background:

• Healthcare organizations face "Institutional Amnesia" due to low analytics maturity, workforce instability, and technical barriers.
• Leadership turnover and informatics specialist shortages erase crucial tacit knowledge, hindering data navigation and knowledge capture.
• The "Socialization Failure" in knowledge creation models, caused by high turnover, makes traditional informatics apprenticeship unsustainable.

Purpose of the Study:

• To address the crisis of "Institutional Amnesia" in healthcare organizations.
• To develop a socio-technical framework, Human-in-the-Loop Knowledge Governance (HITL-KG), to mitigate knowledge loss.
• To shift organizational knowledge from human memory to durable semantic artifacts.

Main Methods:

• A Design Science Research (DSR) approach was employed, synthesizing evidence from healthcare informatics, knowledge management, and natural language processing.
• Developed the Human-in-the-Loop Knowledge Governance (HITL-KG) framework, creating "Validated Query Triples" (natural language intent, SQL, rationale).
• Introduced a Three-Pillar Assessment Rubric to identify organizational vulnerabilities in analytics, workforce, and technical enablement.

Main Results:

• The HITL-KG framework embeds knowledge capture into daily query workflows, converting ephemeral analytics into permanent institutional assets.
• "Validated Query Triples" serve as durable semantic artifacts, storing knowledge independent of individual tenure.
• The "Validator Paradox" is addressed by reframing validation as establishing "Standard Work," preventing knowledge regression.

Conclusions:

• HITL-KG offers a novel socio-technical solution to combat "Institutional Amnesia" in healthcare.
• The framework decouples analytical capability from individual tenure, enabling continuous advancement of analytics maturity.
• HITL-KG facilitates knowledge retention and transfer, ensuring institutional memory persists despite workforce evolution.