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Full benefits of electronic health records only accrue with the implementation of effective retrieval and reuse of clinical information. The scope of analysis of health record data may cover:

  • An individual patient, across time and/or care providers;
  • An individual healthcare worker;
  • Patient groups or cohorts, based on demographics, diagnoses, treatments or interventions;
  • Enterprise groups, based on teams, wards, clinics, institutions or providers;
  • Geographical groups, based on a local area, town, region or country.

Figure 3.2-1 illustrates the three main purposes of analytics with SNOMED CT. These are:

  1. Clinical assessment and treatment;
  2. Population monitoring; and
  3. Research.

 

Figure 3.2-1: Purposes of analytics with SNOMED CT

SNOMED CT may be used to support analytics that:

  • Improves the care of individual patients by enabling:
    • Retrieval of relevant information that better supports clinicians in assessing the condition and needs of a patient
    • Clinical records to be integrated with decision support tools to guide safe, appropriate and effective patient care – for example, allergy checking and potential drug contraindications identified at the point of prescribing
    • Reduction in the duplication of investigations and interventions through the effective retrieval of shared information about the patient
    • Meaning-based sharing of clinical information that is collected by different members of the health care team at different times and places (and potentially in different languages)
    • Identification of patients requiring follow-up or changes to treatment based on updated guidelines
    • Wellness management, for example, using genetic and behavioral risk profiles.
    • Context-sensitive presentation of guidelines and care pathways within the user interface
    • Labor-saving decision support systems for clinicians
    • Adaptive pick lists in clinical user interfaces
    • Professional logs and performance tracking for clinicians
    • Work list generation, for example, patients requiring follow-up based on specific criteria
    • Workload profiling and monitoring.
  • Improves the care of populations by enabling:
    • Epidemiological monitoring and reporting, for example, monitoring of epidemic outbreaks, or hypothesis generation for the causes of diseases
    • Audit of clinical care and service delivery
    • Systems that measure and maximize the delivery of cost-effective treatments and minimize the risk of costly errors
  • Supports evidence-based healthcare and clinical knowledge research by enabling:
    • Identification of clinical trial candidates
    • Research into the effectiveness of different approaches to disease management
    • Clinical care delivery planning, for example, determining optimum discharge time
    • Planning for future service delivery provision based on emerging health trends, perceived priorities and changes in clinical understanding.

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