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The COVID-19 pandemic makes it more important than ever that we assist our clinicians with a Clinical Decision Support (CDS) solution that is embedded in workflows, offering information at the point of care – where it is has been proven to be 112x more effective.1

Stanson is enhancing our CDS capabilities with COVID-19 content that may assist frontline providers in the identification of patients who are most at risk for severe illness. This is especially important as it would support providers who are working in unfamiliar virtual settings. Additionally, Stanson is developing real-time information based on the NIH COVID-19 Treatment Guidelines focused on the most critically ill patients.

Designed to Support Frontline Providers

in the identification of patients who are most at risk.

COVID-19 CDS Content

Smart Clinical Decision Support

Supporting clinicians as they make complex decisions by helping providers identify patients who are at the highest risk of developing severe symptoms (elderly, multiple comorbidities, other risk factors). This is especially important as it can support providers who may be working in an unfamiliar or virtual setting.

Innovative Technology

Designed to use natural language processing (NLP) and machine learning (ML) to extract data (both structured and unstructured) from the electronic health record (EHR), which can give providers more information to support decision making about potential COVID-19 patients.

Near Real-time Analytics

Use near real-time analytics to get COVID-19 data that may offer insights into ordering and alerting patterns in this uncertain time.

On-demand Analytics

Chart of COVID-19 Panel


Click image to enlarge.
  1. Track COVID-19 Orderables
    • Pull data on orders including COVID-19 orderables.
    • Gain insights into:
      • Volume of orders
      • Name of provider who placed the order
      • Patient department
      • Order set or preference list utilized
      • All modalities including labs and medications
  2. Review COVID-19 Alerts
    • Review COVID-19 alerts and adapt to rapid-cycle changes by reviewing comments, override reasons and the providers triggering the alerts.
  3. Ongoing Support
    • Review high-volume alerts for the key groups impacted by the influx of COVID-19 patients and highlight any quick-win opportunities to reduce alert fatigue.
    • Offer analytics access and training to additional resources that could benefit from this data, such as infection control or analysts involved in the COVID-19 efforts.

Like what you see?

Contact us to update your CDS with COVID-19 content and analytics.

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1Kawamoto K, Houlihan C, Balas E, et al. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ. 2005 Apr 2;330(74794):765 . PMID: 15767266 Available at: Accessed: July 8, 2019.