Operationalizing Data Analytics

Imagine a workflow that leverages your analytics investment to change the course of your people delivering healthcare as a high reliability organization?

Decision Coordinator takes your data analytics investment and closely integrates it with the diverse range of software applications, devices, and data sources across your organization, through capabilities that merge events and data between sources, workflow, analytics models and machine learning to operationalize new processes that improve patient care.

Decision Coordinator includes unique capability to integrate deeply with multiple software applications in real-time, consuming and modify transactions, work lists and workflows in your health system's existing applications, enabling new workflows and automation to put your data analytics investment into action.

Depending on the process to be improved, activities like these and more become possible with your existing data analytics investment:

  • Events and real-time changes in patient status are fed into your model, and the result used to better drive a patient's care pathway or ensure an action is taken in response to a dire prediction
  • Communicate, track and escalate requests to clinicians through mobile devices, messaging systems, or worklists in systems they use today.
  • Provide an integrated feedback loop for clinicians to acknowledge or reject a prescribed action, to be used to improve your model or training of staff.
  • Monitor information such as orders and appointment scheduling to learn if employees have actually followed prescribed actions.
  • Provide a single presentation layer over existing systems to cause employees to take different actions based on your models, for example, data analytics can enable agents in call centers to better handle inbound calls from patients, care givers and skilled nursing facilities.
  • Bridge the gap between your models, mobile applications and devices used by patients to send or receive information.
  • Extend the reach of your models to skilled nursing and other providers in your network.
  • Schedule follow-up data collection tasks to determine how often and with what result your data analytics investment is being utilized so you can insightfully pursue utilization improvements.

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