Comprehensive Cost/Benefit Analysis and Business Case for ICT and IoT-Based Solutions for Lab Test Redo and Recalls at eHA Clinics

Introduction

Maintaining the accuracy of lab results is essential to ensure effective patient care, minimize errors, and uphold healthcare quality standards. This analysis explores automation opportunities to enhance the processes of lab test re-dos and recalls, focusing on reducing the redo rate to 5% or less in alignment with JCI Standard AOP 6.1.1 and ISO 15189 Standard 7.4.1.8. While some automation already exists at eHA Clinics, further innovations may optimize efficiency and compliance.

Health Care Quality Benchmark: Lab Test Redo and Recalls

Key Areas:

  1. Error Identification: Detect quality markers indicating potential errors before results are published.
  2. Redo Workflow: Automate the creation of redo requests while archiving questionable results.
  3. Recall Process: Streamline notifications to care providers when test results are recalled.

Current QA/QC Processes:

  • Results flagged for quality issues are archived before publication, and a redo request is generated in the EMR.
  • Providers receive automatic notifications when a test is recalled via the EMR.
  • For manual systems (e.g., PHCs), re-dos are documented in a book, and recalls require physical or verbal communication.

Automation Potential: Low to Medium

  • Some automation already exists, but additional enhancements may improve error detection and reduce manual intervention.

Proposed ICT and IoT Solutions

  1. AI-Driven Error Detection System:
    • Product: PathAI Diagnostics.
    • Functionality: Uses AI to flag abnormal trends or data inconsistencies in lab results.
    • Benefits: Proactively identifies potential issues, reducing manual reviews and errors.
  2. Integrated Workflow Automation in EMR:
    • Platform: Odoo Lab Invoicing Module with custom addons.
    • Functionality: Enhances existing automation by integrating real-time error flags and enabling seamless redo workflows.
    • Benefits: Reduces manual input and ensures timely completion of re-dos and recalls.
  3. IoT-Based Quality Monitoring Devices:
    • Device: LoRaWAN-Enabled Quality Sensors.
    • Functionality: Tracks critical environmental parameters (e.g., reagent temperature) that might affect test accuracy.
    • Benefits: Prevents errors caused by suboptimal conditions, reducing the need for re-dos.
  4. BLE-Integrated Notification System:
    • Device: Wiliot BLE Tags.
    • Functionality: Alerts lab staff when flagged tests require review or re-runs.
    • Benefits: Streamlines communication between devices and the EMR.
  5. Integration with Home Assistant for Alerts:
    • Functionality: Enables audiovisual alerts for flagged tests requiring re-dos or recalls.
    • Applicability: Particularly useful for decentralized facilities with shared workspaces.
  6. Manual Alternatives for PHCs:
    • Use mobile apps or SMS-based notifications where internet access or EMR systems are unavailable.
    • Provide lab attendants with logbooks for documenting re-dos and recalls.

Cost Analysis

  1. Initial Investment:
    • AI Error Detection System: ~$10,000 for initial setup and training.
    • Odoo Addon Development: ~$5,000 (one-time).
    • IoT Quality Sensors: ~$150 per sensor. For 20 sensors: ~$3,000.
    • BLE Tags: ~$25 per tag. For 50 tags: ~$1,250.
    • Home Assistant Setup: ~$1,000 for hardware and configuration.
  2. Operational Costs:
    • System Maintenance: ~$750 annually.
    • Cloud Storage for AI System: ~$500 annually.

Total Estimated Initial Cost: ~$20,250

Annual Operational Cost: ~$1,250

Benefit Analysis

  1. Quality Improvement (QI):
    • Proactive Detection: AI reduces the likelihood of incorrect results reaching providers.
    • Streamlined Processes: Automation minimizes delays in re-runs and recalls.
  2. Quality Assurance (QA) and Quality Control (QC):
    • Enhanced Traceability: Digital logs ensure compliance with JCI and ISO standards.
    • Improved Consistency: IoT sensors detect environmental factors affecting accuracy.
  3. Operational Efficiency:
    • Time Savings: Reduces manual effort in identifying and documenting re-dos.
    • Seamless Notifications: BLE and EMR integration improve communication.
  4. Financial Benefits:
    • Cost Savings: Minimizes waste from invalid tests by up to 10%.
    • Reduced Liability: Accurate results decrease legal risks and improve patient trust.
  5. Compliance and Reputation:
    • Global Standards Alignment: Demonstrates adherence to JCI and ISO benchmarks.
    • Patient Confidence: Ensures reliability and accuracy in diagnostic services.

Return on Investment (RoI) and Marketing Language

ROI Messages:

  • Error Reduction: AI systems reduce manual errors by 25%, minimizing costly recalls.
  • Efficiency Gains: Automated workflows save 5-7 hours per month per lab.
  • Cost Savings: Preventing invalid tests reduces reagent wastage by up to $1,000 annually.

Marketing Language: "Enhance diagnostic accuracy at eHA Clinics with intelligent automation. From proactive error detection to seamless recall workflows, our innovative solutions ensure compliance, efficiency, and trust—because every test counts."

Industry Best Practices and Innovations

  1. AI for Error Detection:
    • Globally, labs are adopting AI to identify potential errors in real-time.
    • Applicability: Improves detection of abnormal trends in test results.
  2. Blockchain for Test Result Validation:
    • Ensures traceable, tamper-proof logs of lab test re-dos and recalls.
    • Applicability: Useful for high-stakes diagnostics or audits.
  3. IoT for Environmental Monitoring:
    • IoT sensors ensure optimal lab conditions to prevent reagent degradation.
    • Applicability: Critical for labs with temperature-sensitive reagents.
  4. Mobile-Friendly Alternatives:
    • SMS-based or mobile app notifications improve accessibility in rural PHCs.
    • Applicability: Suitable for facilities without robust digital infrastructure.

Viability in the Nigerian Context

  1. Cost-Effectiveness: Affordable IoT and BLE solutions offer a high RoI with low upfront costs.
  2. Scalability: Modular systems can be gradually rolled out across multiple facilities.
  3. Infrastructure Compatibility: Works well in urban clinics and can be adapted for rural PHCs with mobile solutions.
  4. Ease of Adoption: Training staff on enhanced EMR capabilities ensures smooth implementation.

Conclusion

The automation of lab test re-dos and recalls presents a medium-priority investment opportunity for eHA Clinics. While existing systems already offer partial automation, incorporating AI, IoT sensors, and BLE devices can further enhance efficiency and accuracy. These technologies are cost-effective, scalable, and adaptable to Nigeria’s healthcare context, delivering measurable RoI while ensuring compliance with JCI and ISO standards.

Next Steps

  1. Pilot Program: Implement AI and IoT solutions in a single facility to assess impact.
  2. Integration Development: Customize Odoo for advanced redo and recall workflows.
  3. Staff Training: Train lab teams on new tools and automated workflows.
  4. Evaluate Outcomes: Measure reductions in redo rates, improved efficiency, and patient satisfaction to guide broader adoption.