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Data Use Community
  • HIV Treatment Continuity Technology Intervention Framework (TIF)
    • Outside the Visit
      • Pre Appointment Support Interventions
        • QI-PM Pre Appointment Support
        • Pre-Appointment Reminders (Nigeria)
        • Pre-Appointment Support (South Sudan)
      • Population-Based Scheduling Interventions
        • CMIS Pre Appointment Support & Population Based Scheduling (Eswatini)
      • Congestion Redistribution
        • Lighthouse Trust's Community-based ART Retention and Suppression (CARES) App in Malawi
        • Differentiated Service Delivery Models Support in UgandaEMR
      • Pooling Patient Data
        • Unique Identity (Botswana)
        • Data Analysis and Visualizations (Tanzania)
      • Anticipatory Guidance
    • During the Visit
      • Proactive Adherence Counselling Interventions
        • Missed Appointments Lists (Haiti)
        • AI Predictive Adherence Counseling (South Africa)
        • Machine Learning to Predict Interruption in Treatment (Mozambique)
        • Predictive model for Interruption in Treatment in Patient Treatment Response Dashboard (Nigeria)
      • Reactive Adherence Counseling Interventions
        • Reactive Adherence Counseling (Haiti)
        • Adherence Dashboard (Kenya)
      • Visit Management Interventions
        • EMR Visit Management (Uganda)
    • Missed Appointment Interventions
      • Missed Appointment Reminder
        • Two-way Texting Patient reminders and tracking (Zimbabwe)
        • Patient Reminders and Tracking (Kenya)
        • EMR-ART Missed Appointment Reminder (Ethiopia)
        • Person-Centered Public Health for HIV Treatment (PCPH)
        • Missed Appointment Management (Western Kenya)
        • Rwanda Biomedical Center EMR (RBC EMR)
      • Intensive Outreach Intervention
        • Missed Appointments and Intensive Outreach (Kenya)
        • Patient Tracing (Ethiopia)
        • Identification of Missed Appointments (Malawi)
        • Missed Appointments and Intensive Outreach (Nigeria)
      • Targeted Adherence Support Interventions
        • Enhancing HIV Treatment Continuity: Innovations and Data Use in Kenya's Health Information Systems
  • Patient Identity Management Toolkit
    • Modules
      • Matching Module
        • Background
        • Phase 1
        • Phase 2
        • Phase 3
        • Frequently Asked Questions (FAQ)
      • Biometrics Module
        • Overview
        • Role in Identity Management
        • Choosing Biometric Characteristics and Modalities
          • Reviewing Studies and Comparisons
          • Reviewing Standards and Guidelines
          • Additional Topics to Consider
        • Trends and Developments
          • Current Trends
          • Future Developments
        • Closing
        • References
        • Glossary
    • Learn from Others
      • Visual Representation
      • Reaching Health Standards and Creating Client Registry in Haiti (2021)
      • Introduction to Biometrics for Patient Identity, Presented by Simprints (2022)
      • Utilizing Biometrics for Unique Patient Identification (UPID) in Côte d’Ivoire (2022)
      • Establishing a Unique Patient Identification (UPI) Framework in Kenya (2023)
      • Malawi Master Patient Index (2023)
      • Piloting a Patient Identity Management System (PIMS) in Haiti (2023)
      • Leveraging Biometrics to Scale a Patient Identity Management System (PIMS) in Nigeria (2023)
      • Leveraging Adaptive Machine Learning Algorithms for Patient Identification in Zimbabwe (2023)
      • OpenHIE23 Meeting in Malawi. Patient Identity Management Collaborative Hackathon. (2023)
      • Strengthening Patient Identity Management (PIM) by Integrating a Client Registry in Rwanda (2023)
      • Patient Identity Management Initiatives in Ethiopia (2023)
      • Patient Identity Management Initiatives in Botswana (2024)
    • References
  • How to Provide Feedback and Input on the TIF and Toolkit
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Biometrics Module

In Progress

Purpose

Learning Objectives

At the end of this module, readers should be able to:

  1. Understand biometric technologies and its application in identity matching, including key concepts such as biometric authentication and biometric modalities.

  2. Describe how biometrics has the potential to improve the accuracy, and efficiency of identity matching.

  3. Identify the limitations and risks of biometric technologies, including privacy and security concerns, accuracy issues, and legal and ethical considerations.

  4. Understand the steps involved in implementing a biometric system in a healthcare and public health setting.

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Last updated 1 month ago

This module is in progress and open for Community review and feedback. You are invited to provide feedback in or as a comment in . Please provide your name comments.

This module highlights considerations to implementing biometrics in healthcare and public health programs to support identity management. The document describes key concepts and implementation experiences from community members and other stakeholders. It is intended for program implementers, health IT systems managers, developers, and those working with person level data. If you are in the planning, preparation, or execution phase of using biometrics for healthcare and public health program identity management, this module is intended to help provide you with resources and practices that the , , and subject matter experts have shared.

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