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Population health management

Identify patients or patient groups for targeted care, prevention and gaps in care across the health and care system to improve patient outcomes and save costs.

Solutions

  • Risk Stratification

    Assesses patients’ risk of adverse outcomes and ranks them according to severity, including risk of emergency admission and level of frailty.

    What it delivers

    An understanding of a patient’s history, including a timeline of interactions with primary and secondary care, to estimate potential use of healthcare services for each member of the population.

    The benefits

    • Identify patients at risk and monitor changes to their risk.
    • Plan care provision based on patients’ risk factors.
    • Effectively manage resources by targeting those in need.
  • Population Segmentation

    Analysis linking primary and secondary care data to understand the patient pathways across different care settings and indicative costs to help inform decisions on transforming patient care.

    What it delivers

    Better understand the most complex, frail patients and those at most risk of an emergency admission to plan the best care service and reduce costs at a health economy level.

    The benefits

    • Focus care management on specific population groups with long-term conditions.
    • Understand the demographic and health needs of the local population to target the right care in the right place the first time.
    • Base decision making on actionable insight rather than anecdotal evidence.
  • Advanced Analytics and Data Science

    Bespoke analytics and data science tailored to specific needs to identify clinical variation, efficiency savings, predict patient risk and improve patient outcomes.

    What it delivers

    A skilled team of experts in advanced healthcare analytics and data science including predicative analytics, machine learning techniques, advanced statistical methods, to investigate issues and transform healthcare services.

    Benefits

    • Access to qualified data scientists, clinicians, statisticians, mathematicians, and economists.
    • Supplement in-house analytical teams with our expert advice and guidance linking, modelling and visualising data and insight.