Regulations, Technology, and the Future of Pathology

What Every Pathology Resident Should Know About LIS and IMS

Peter Gershkovich, MD. MHA
Yale University School of Medicine | April 2025

Conflict of Interest Disclosure

  • Consultant for Applicate Technologies Inc.
  • This presentation is intended solely for educational purposes. It is designed to inform and engage learners in current practices, regulatory frameworks, and emerging trends in Laboratory Information Systems (LIS) and Digital Pathology and AI Orchestration Systems. All content reflects the presenter’s independent views and does not represent the official position of any institution or regulatory agency.

Learning Objectives

By the end of this session, you should be able to:

  • Understand key external regulations affecting LIS and IMS
  • Recognize the role of HIPAA, FDA, and internal validation in laboratory systems
  • Comprehend how regulations shape software and organizational design
  • Explore the informatician's role in digital transformation
  • Appreciate the growing importance of enterprise analytics

Why It Matters

  • Pathology is increasingly digital
  • Systems like LIS and IMS are core to your workflow
  • Regulation shapes what tools we can use, how we use them, and how fast we can change
  • YOU are the next generation of pathologists: be informed, be involved

Digital Pathology: The practice of converting glass slides into digital images for viewing, analysis, storage, and management.

LIS (Laboratory Information System): Software that manages sample processing, results reporting, and workflow in clinical laboratories.

IMS (Image Management System): Software for storing, managing, and viewing digital pathology images.

Key External Regulations

HIPAA

Patient privacy and data security

CLIA

Governs lab testing standards

FDA

Software as a Medical Device (SaMD)

CAP & JCAHO

Accreditation and compliance

NIST

Cybersecurity best practices for software

Insurance

Reimbursement and reporting rules

Internal

Institutional policies, procedures, and training

HIPAA & Data Protection

  • What HIPAA covers: PHI, access control, audit trails
  • Relevance to LIS/IMS: patient data, annotations, sign-outs
  • Encryption, secure storage, and transmission
  • Case study: breach example and its impact

HHS Breach Portal: Types & Locations

HHS Breach Portal: States & Entities

HIPAA: Office for Civil Rights (OCR)

HHS Office for Civil Rights

Key HIPAA Resources from OCR:

  • HIPAA Privacy Rule - Governs the use and disclosure of PHI
  • HIPAA Security Rule - Sets standards for securing electronic PHI
  • HIPAA Breach Notification Rule - Requirements for reporting breaches
  • HIPAA Enforcement - Compliance and audit programs

Source: HHS.gov

HIPAA: Permitted Uses & Disclosures

Treatment

Exchange of PHI for patient treatment purposes

Health Care Operations

Quality assessment, business planning, training

Public Health

Disease reporting, surveillance, interventions

Health Oversight

Audits, investigations, inspections by agencies

Source: HealthIT.gov

HIPAA De-identification Methods

Safe Harbor Method

Removal of 18 specific identifiers:

  • Names
  • Geographic < state
  • Dates (except year)
  • Phone/fax
  • Email
  • SSN
  • Medical record #
  • Health plan #
  • Account #
  • Certificate/license #
  • Vehicle identifiers
  • Device IDs
  • Web URLs
  • IP address
  • Biometric IDs
  • Photos
  • Unique characteristics
  • Other unique codes
Name: John SmithDOB: 04/15/1975
Address: 123 Main St, New Haven, CT (203) 555-1234
Diagnosis: AdenocarcinomaTreatment: Surgical resection

Expert Determination Method

A qualified expert applies statistical methods to ensure:

  • Very small risk that data could identify an individual
  • Risk assessment based on statistical principles
  • Methods and results documented
Name: John Smith
DOB: 04/15/1975
Address: 123 Main St, New Haven, CT
Phone: (203) 555-1234
Diagnosis: Adenocarcinoma
Treatment: Surgical resection
Feature Safe Harbor Expert Determination
Implementation Straightforward, rule-based Complex, requires expertise
Data Utility Lower (more data removed) Higher (tailored approach)
Cost Lower Higher (expert fees)

Source: HHS.gov

CLIA & Laboratory Oversight

  • Role in ensuring test accuracy and reproducibility
  • LIS as part of a compliant testing environment
  • Pre-analytic, analytic, post-analytic phases
  • Validation of informatics tools for lab use

FDA and Software Regulation

  • SaMD and the FDA: what qualifies?
  • IMS increasingly under scrutiny
  • LDTs (Laboratory Developed Tests) vs FDA-cleared tests
  • Risk-based approach: Class I-III software
  • Recent examples (e.g., AI-assisted diagnosis)

Office of the National Coordinator (ONC)

Key Responsibilities

  • National health IT strategy and policy
  • Standards for health information exchange
  • Certification of health IT products
  • Promotion of interoperability

Impact on Pathology

  • Influences LIS certification requirements
  • Shapes interoperability standards for lab data
  • Drives digital pathology adoption through policy

Learn more: HealthIT.gov

Trusted Exchange Framework (TEFCA)

  • Universal governance for nationwide interoperability
  • Simplified connectivity for secure information exchange
  • Ability for individuals to gather their healthcare information
  • Common technical and legal requirements for sharing electronic health information
TEFCA Components
Trusted Exchange Framework
Common Agreement
Qualified Health Information Networks (QHINs)

Source: HealthIT.gov

Internal Validation: What, When, Why

  • Internal validation vs. vendor claims
  • Documentation and reproducibility
  • Human factors & usability validation
  • Example: validation of a new image viewer or LIS module

FDA Approval of Digital Pathology Systems

Philips IntelliSite Pathology Solution (2017)

  • First FDA-approved whole slide imaging system
  • Approved as a complete system: scanner, software, and display
  • Required extensive clinical validation (2,000+ cases)
  • De novo pathway for novel technology

Regulatory Impact on Adoption

  • Delayed U.S. implementation vs. Europe and Canada
  • COVID-19 led to temporary regulatory flexibility
  • Holistic approach: scanner + viewer + monitors as one diagnostic package
  • Validation burden on institutions

Source: FDA, April 2017

AI Regulation in Pathology

Paige Prostate (2021)

  • First FDA-authorized AI for pathology
  • Identifies areas suspicious for cancer
  • 7.3% improvement in cancer detection
  • Adjunctive tool: pathologist must review

Implementation Considerations

  • On-label use: AI as assistant to pathologist
  • Off-label potential: screening out benign cases
  • Workflow implications: efficiency vs. oversight
  • Future: potential for fewer subspecialists needed

Source: FDA, September 2021

Digital Pathology: Then and Now

Traditional Workflow

  • Glass slides
  • Manual microscopy
  • Physical storage
  • Limited sharing capabilities

Digital Workflow

  • Whole slide imaging
  • Digital viewing
  • Cloud storage
  • Remote consultation
  • AI-assisted analysis

AI and Decision Support Systems

Transformation of System Roles

  • From documentation tools to diagnostic assistants
  • Image analysis algorithms and pattern recognition
  • Quantitative measurements replacing subjective assessments
  • Suggestion of diagnoses and differential considerations

Regulatory Implications

  • Higher scrutiny for diagnostic vs. documentation systems
  • FDA classification based on risk to patients
  • Required documentation of AI's role in diagnosis
  • Continuous monitoring of performance in clinical use

Ethical and Practical Challenges

  • Psychological barrier to contradicting AI suggestions
  • Hidden biases in training data affecting outcomes
  • Unclear impact on trainee development and skills
  • Need for automated validation tools to ensure quality

Risk Mitigation Strategies

  • Transparency in AI decision-making processes
  • Clear documentation of AI's role in diagnosis
  • Regular revalidation with new data
  • Maintaining human oversight and final authority

Enterprise Analytics: The Backbone of Modern Healthcare

Regulatory Compliance & Validation

  • Automated documentation of system usage
  • Continuous monitoring of diagnostic accuracy
  • Validation of AI algorithm performance over time
  • Error tracking and quality improvement metrics

Cost-Benefit Analysis

  • Quantifiable metrics for digital transformation ROI
  • Administrative burden measurement
  • Throughput and efficiency calculations
  • Resource utilization optimization

The Hidden Cost of Healthcare

  • For every clinician, 5-10 non-clinical staff
  • Compliance, cybersecurity, credentialing armies
  • Multiple insurance and liability costs
  • Only automation and analytics can address this imbalance

"Without rigorous analytics, we cannot prove the value of digital transformation or meet regulatory requirements. Analytics running in the background can automatically validate systems, monitor performance, and guide evidence-based decisions."

Key Takeaways

Regulations exist to ensure patient safety and data integrity
Understanding regulatory frameworks helps you advocate for better systems
Digital transformation requires both technical and organizational change
Pathologists must be active participants in informatics decisions
Be proactive: your voice matters in digital transformation
The future of pathology is not just digital. It is shaped by YOU.

Questions & Discussion

Please feel free to ask any questions

We've covered a lot of ground today in pathology informatics

Email

peter.gershkovich@yale.edu

Resources

Slide deck available on department website

Thank you for your attention!