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Informatics Interventions

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Samir Gupta, MD, MSc, FRCPC
Ann McKibbon, BSc, MLS, PhD

Download: Presentation (PDF, 190KB)

Topic Focus

  • Introduction
  • Role of Informatics Interventions in KT:

    • Education
    • Reminder systems
    • Clinical decision support systems
    • Presenting and summarizing data
  • Areas of future research
  • Summary

Introduction

  • Knowledge translation (KT) consists of:

    • Collection
    • Summarization
    • Packaging
    • Delivery

    Of (research) knowledge

  • Informatics interventions:

    • Same concepts, but for information
  • These are natural partners in health care enhancement

How Informatics Can Enhance KT

  • Education:

    • online interactive education, individually tailored education
  • Reminders:

    • lessen “cognitive load” on clinicians
  • Summarizing and presenting data:

    • useful, timely, variety of formats
  • Computerized decision support systems:

    • support clinician decision making

Education

  • Web-based continuing education and patient education: evidence on effectiveness lacking or at best shows weak positive effects
  • Problem: static, one-size-fits-all educational modalities are ineffective
  • Individualized education based on needs assessment → more learning
  • Informatics interventions can improve learning by providing tailored, “as-needed” content

Reminder Systems

  • Reminder systems can reduce the cognitive load for clinicians
  • Computers:

    • Efficiently check data against clinical rules
    • Provide prompts for patient and provider adherence (e.g. screening tests, drug interactions, etc.)
    • Reminder systems free clinicians to concentrate on the needs of each individual patient rather than sorting and processing data
    • Patient reminder systems promote self-directed care and hold promise as well

Summarizing and Presenting Data

  • Computers can store, synthesize, and present data in a user-friendly format
  • Can be used for:

    • online medical education
    • delivering knowledge embedded within information systems
    • individualization: tagging specifications for guidelines can match their content to individual patients in electronic medical records systems (EMRs)
  • Hospital clinicians can use handheld computers for a similar point-of-care function
  • Patients may also use electronic self-management tools directly to present data to physicians in real-time

Clinical Decision Support Systems

  • Providers require “just-in-time” knowledge
  • CDSSs:

    • match patient data to a computerized knowledge database
    • use software algorithms to generate patient-specific recommendations
    • address diagnostic, prevention or screening, drug dosing, or chronic disease management decisions
  • Systematic review of the effectiveness of CDSSs: Garg, et al. reported improved practitioner performance in most studies

Patient Decision Aids

  • Computerized decision aids are a type of CDSS that targets patients
  • Present patients with evidence-based information about personally relevant options and outcomes
  • Enable patients to participate in their own health care decisions

Future Research

  • Needs to broaden the scope of KT informatics interventions
  • Will require:

    • improved technology (e.g. improving information standards and enhancing system interoperability)
    • social sciences (understanding individual needs and characteristics → design easy-to-use interventions
    • business (managing system change with financial integrity)
    • decision makers, health care providers, and patients
    • Personal health records: area of potential – requires qualitative and quantitative interdisciplinary research
    • Future research must also address the effects of informatics and KT interventions on patient and wellness outcomes

Summary

  • Many informatics applications can be effective KT tools, delivering evidence to professionals and patients
  • Informatics interventions that speed KT can be found in:

    • patient and physician education
    • reminder systems
    • systems to summarize and present data
    • decision support
  • These improve education, improve adherence through reminders, collect and present data from multiple sources, and support decision making
  • Effects on health outcomes are less well demonstrated
  • We have yet to harness the full potential of integration of the KT process with informatics applications