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Michelle Cousins



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    OS27 - Integrating the Community Sectors (ID 43)

    • Event: e-Health 2019 Virtual Meeting
    • Type: Oral Session
    • Track: Clinical and Executive
    • Presentations: 1
    • Coordinates: 5/28/2019, 02:30 PM - 03:30 PM, Pod 6
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      OS27.02 - Clinical Value of Standardized Primary Care Data: Learnings from POC (ID 448)

      Michelle Cousins, The eHealth Centre of Excellence; Waterloo/CA

      • Abstract
      • Slides

      Purpose/Objectives:
      The connecting South West Ontario Program?s Primary Care Data Sharing Proof of Concept (PCDS POC) project, funded by eHealth Ontario, enabled a sub-set of primary care electronic medical record (EMR) data to be shared as part of Ontario?s integrated electronic health record (EHR). A key objective of the POC was to support clinicians to improve data quality to enhance data sharing. This presentation demonstrates how structured EMR data can be used to enable clinical and organizational value for primary care providers and their patients


      Methodology/Approach:
      Data quality assessments were completed before and after investments to improve data quality that included chart reviews, surveys and EMR searches. Data quality investments included historical coding of EMR data to ensure coded patient data was current. The eCE consulted with program managers and clinicians to explore how improved data quality could generate value for each organization and developed case studies to demonstrate this value to clinicians.


      Finding/Results:
      During the POC the eCE PCDS project team learned that data quality initiatives, when positioned together with tools developed in line with clinical best practices, generate internal value for contributing organizations and clinicians. Improved EMR data quality allows primary care organizations to: identify patients with specific conditions (including patients who did not have a documented diagnosis); identify complex patients (high-users of the healthcare system); identify and understand patient population (i.e. prevalence of chronic conditions). Overall, findings demonstrated that primary care data quality improvement initiatives promote improved documentation and a more accurate depiction of the patient roster in the EMR, which has allowed primary care providers to be more proactive in the way they manage care internally to their practices as well as through better communication to community and specialist supports.


      Conclusion/Implications/Recommendations:
      The PCDS POC has demonstrated not only that data can be extracted from EMRs and viewed by clinicians across communities and the continuum of care, but generated improved value for clinicians and patients within primary care practices by improving data quality. When EMR data is up-to-date and standardized using codes, practices can identify and mobilize to care for specific patient populations. Moving forward, it is important to invest in a scalable model that can structure and improve primary care data quality and to learn more about the opportunity a high-quality dataset from primary care offers to achieve the quadruple aim (improved patient experience, patient outcomes, system cost, physician experience). For example, EMR tools that incorporate best practice guidelines could be developed in ways that enable clinicians to document specific elements in structured ways that can lead to easier more effective management of patient populations. In addition, those structured fields can be shared with specialists and community supports to support stronger continuity of care.


      140 Character Summary:
      This presentation will demonstrate how quality primary care data can enable clinical and organizational value for primary care providers and their patients.

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