Using Data Analytics to influence Health Outcomes
  • Introduction
    • Definitions & Acronyms
  • Analytic adoption
    • Opportunities and Enablers
    • Barriers and Obstacles to Data Analytics
    • Guiding Principles for Data Collection and Reporting
  • The Future of Data Analytics
    • Clinical Decision Support
    • Personalized Care
    • Public and Population Health
    • Clinical Operations
    • Policy, Financial and Administrative Decisions
  • Case Scenario
  • Conclusion
  • References

Clinical Operations


·    Wait-time management is amongst the top issues for hospital administrators and in many Western nations the demand for hospital services is increasing and creating public concern that healthcare systems are in crisis (Fitzgerald & Dadich, 2009).

·    Visual analytics is an amalgamation of data computation, visual representation and interactive thinking that can be used to understand complex data sets and situations, detect trends and anomalies, evaluate hypotheses, uncover unexpected connections and encourage users to explore large data sets that might otherwise be daunting (Fitzgerald & Dadich, 2009).

·    In the future, initiatives such as visual analytics may be used to improve patient flow within hospitals, identify areas for improvement and offer viable options to improve these areas to prevent a bottleneck of patient flow before it actually happens (Fitzgerald & Dadich, 2009).




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