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Digital Health Transformation: The Good, the Bad, and the Ugly - the strategic role of CMIO

Lutfan Lazuardi

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Aspect

Health Reform

Health Transformation

Scope

Targeted changes within existing systems

Comprehensive overhaul of the entire system

Approach

Incremental adjustments

Holistic redesign

Focus

Improve specific areas like access, cost, quality

Integrate new technologies, shift to personalized care

Challenges

Stakeholder resistance, policy complexity

Cultural shift, technology adoption, investment

Impact

Measurable but limited improvements

Potential for a resilient, patient-centered system

Reformation versus Transformation

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Why Digital Health Transformation Fails?

1. Treated as an IT project, not a clinical transformation

2. Lack of clinical leadership in digital decisions

3. Focus on compliance rather than clinical value

4. Weak digital governance and vendor dependency

5. Poor change management and workforce readiness

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1. Technology Is Not the Primary Cause of Failure

McKinsey & Company

“Up to 70% of digital transformations fail — largely due to organizational and people-related issues, not technology.”

2. Poor Clinical Engagement and Workflow Misalignment

HIMSS emphasizes that EHR and digital health failures often result from:

  • Systems designed without deep clinical input
  • Ignoring real clinical workflows
  • Treating digital projects as IT projects, not clinical transformation

3. Absence of Clinical Digital Leadership (CMIO Gap)

WHO highlights that many digital health initiatives fail because:

  • No clinical leadership for digital health
  • Digital health treated as a technology project
  • Weak integration into care delivery

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From electronic medical record to lifetime health record and medical data liberation

EMR

EHR

PHR

ELHR

Data Ownership

Single Institution/Provider

Healthcare Providers (Shared Access)

The Patient/Individual

The Patient (Primary custodian of the lifelong record)

Data Scope

Limited: Only data from a single practice/clinic

Comprehensive: Data from multiple providers and facilities

Personal: EHR Data + Self-Monitored Data (Wearables/Lifestyle)

Ultimate: The entire health history from birth to end-of-life

Primary Focus

Digitization of internal medical charts

Interoperability and coordinated care across institutions

Patient Empowerment and personal health management

Permanent and fully integrated record

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Why Human & Organizational Factors Matter More Than Technology in Hospitals?

1. Technology does not change care — clinicians do

2. Organizational culture determines digital adoption

3. Leadership alignment matters more than system features

4. Change management is not optional in healthcare

5. Technology maturity follows organizational maturity

Digital health success = 70% people & organization + 20% process + 10% technology

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Diffusion of innovation and leadership style

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CMIO - a new leader for the health system

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Why CMIO (Chief Medical Information Officer)?

  1. Bridging Clinical Practice and Technology
  2. Ensuring Information Systems Support Quality and Patient Safety
  3. Leading Hospital Digital Transformation
  4. Supporting Data Governance and Regulatory Compliance
  5. Optimizing Data Use for Clinical Care and Management
  6. Managing Change and Clinician Resistance
  7. Holding a Strategic Position within Hospital Leadership

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AI-Driven Precision Medicine:

Evolving Legacy Infrastructure with EHR, Biobank, Genomics and Proteomics at UGM

2015 - 2022

Foundations of AI in Healthcare

Data Sources: EMR/EHR, biobanks, genomic data, HDSS (population health data).

Technologies: Big data analytics, medical technologies, connectivity tools

Governance and Ethics

Key Stakeholders: Governments, professionals, academia, industry, society.

Focus Areas:

  • Data sovereignty and security.
  • Bioethics and policy-making.
  • Personalized education for health professionals.

2020 - 2024

2024-2026

Core application

Precision Medicine:�Personalized care based on integrated health data.

Public Health:�Predictive analytics and population health insights.

Device Development

2026-2030

AI integration

AI as a hub for:

  • Data Integration
  • Decision-Making: Support for clinical procedures and public health strategies.
  • Personalized Healthcare: Focusing on predictive, preventive, participatory, and personalized care.

2030-Beyond

UGM contribution

Innovation Centers: Advanced Tech Labs for Global Health.

Digital Solutions:

  • Health information system interoperability.
  • Self-screening apps and personal health records.

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It’s you

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