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Presentation

Predicting Progression to Type 2 Diabetes

11:05 AM–11:25 AM May 2, 2019 (US - Eastern)

Great Room 2

Description

The session provides an overview of an initiative to use predictive models to manage patient cost and care at a population level.

Analytics play a key role in the need for accurate risk stratification, predicting patients with rising costs or risks and enabling optimized care pathways for improved outcomes. Converting insights into actionable information is key to bringing value to existing data assets. We highlight success stories and lessons learned in deriving value from big data, and demonstrate how predictive models can drive effective care and promote adherence to current, evidence-based guidelines in chronic disease management.

In one such case, we created a big data framework to optimize care pathways for a precision medicine approach to persons with diabetes or prediabetes. This framework will help clinicians better understand how these conditions can progress and are impacted by factors like environment and prior medical history. It is derived from data on prediabetes and diabetes progression at a population level, generating predictive models based on today’s most advanced analytics tools. Further, we translated these insights into regular clinical workflows, to ensure patients across a population receive a consistent and updated standard of care, per both our owned data and guidelines from the American Diabetes Association.

As more research advancements are made, we hope to enrich clinicians with disease progression patterns in demographically similar patients, accounting for social and environmental risk factors beyond what may appear in health data. This information can enable creation of treatment plans that are powerfully personalized for clinicians and patients alike.

We will illustrate how analytics tools, based on broadly sourced population data and intelligent predictive models, allow clinicians to maintain the highest standard of care delivery while reducing burnout. We will show how incorporating predictive models into healthcare organization’s workflows and systems can enhance care plans, leading to the most optimal health outcomes.

As relevant data becomes more available, analytics will be increasingly crucial to achieving strong outcomes in healthcare. This session will show successful data methodologies and how analytics can be practicable at every point of care.

Describe the new knowledge and additional skills the participant will gain after attending your presentation.: By the end of the presentation the audience will be able to:
-Identify the developing sources of big data in healthcare
-Assess the tangible benefits, value and outcomes of analytics and predictive models
-Apply predictive models to specific healthcare challenges and opportunities, such as managing prediabetes and diabetes at a population level
-Use analytics to achieve the strongest outcomes at various points of care

Authors:

Katherine Khorey, Allscripts
Fatima Paruk (Presenter)
Allscripts

Presentation Materials:

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