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ChartWise

Headquarters:

Wakefield Rhode Island, United States

Sector Funding:

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ChartWise's Current COVID-19 Response and Solutions

The following information was supplied by the vendor and has not been validated by KLAS.

COVID-19 AI-Driven Clinical Records Analysis

AI-driven screening and triage tools; predictive clinical analysis and planning

The Covid-19 pandemic is evolving rapidly with potentially hundreds of millions of people throughout the world needing various levels of screening, triage, intensive care and ongoing treatment.

Hospitals and physicians will need smart, data-driven tools and predictive clinical analytics to stay ahead of the crisis and to rapidly and effectively respond to Covid-19 patient needs.


However, because of the vast enormity of documentation that is stored in an Electronic Medical Record (EMR), it is especially difficult for physicians and other clinical team members to quickly and comprehensively search and identify the many complex and co-contributing clinical factors that impact treatment decisions and outcomes for Covid-19 patients.


According to a study by Italy’s National Health Authority, “more than 99% of Italy’s coronavirus fatalities were people who suffered from pre-existing medical conditions. Almost half the victims suffered from at least three prior illnesses and about a fourth had one or two previous medical conditions.”


ChartWise’s NotePath Clinical Validation tools make it easy for physicians and other care givers to access critical clinical information on their patients in real-time, at the point of care so they have the information they need to save lives.


NotePath uses Natural Language Processing and Machine Learning technology to extract and analyze relevant medical information from unstructured text from the entire collection of patient clinical documentation, capturing a wide spectrum of information for signs, symptoms, medications, dose ranges, laboratory results, imaging and anatomic pathology reports, problems, diagnoses and procedures related to Covid-19.

Clinical information collected by NotePath is analyzed by an AI powered rules engine and then provides clinical insights and advice at the point of care so physicians can optimize treatment planning, prevent gaps in care, reduce complications and improve treatment outcomes for Covid-19 patients.

NotePath AI Driven clinical records analysis provides vital diagnostic information to treat Coronavirus and other life-threatening illnesses:

·        Initial patient screening, testing and triage information analysis which identifies:

a)      Potential exposure history

b)     Initial clinical presentation

c)      Risk factors and co-morbid conditions

d)     Information for contact tracing

e)     The actual and predicted number, status and level of care needs of screened patients

      Symptom identification and health risks of co-morbid conditions related to Covid-19 patients

      Projected patient disposition from the underlying co-morbidity data gathered above

      Projected resource requirements and Personal Protective Equipment (PPE)

      Predicted clinical course and clinical outcomes for patient population:

a)      # of required admissions to Hospital

b)     # of required ICU level of care (for those admitted to the hospital)

c)      # of required ventilators advanced life support/ECMO machines (for those admitted to the hospital)

d)     # extubated (taken off the ventilator)

e)     # of discharges to home (for those admitted to the hospital)

f)       # of fatalities



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Software Overall Score Data collected between Jan 2020 - Jan 2021

91.5

 Product
Segment
 

Exceptions

R
Regional Classification
C
Component Products
S
Superseded Products
NP
Not Primary Products
DR
Data Review
MS
Limited Market Share
FR
Data frozen, live data no longer collected.

The following exceptions refer to the number of unique organizations contributing evaluations to the overall score (minimum of 15 required).

# of Unique Organization Evaluations:

0 - 5
L 6 - 14

Segment Position

Segment positions refer to the order in which this product is scored among competitors’ products within its market segment.

In order to be scored in a segment, the product must have sufficient data levels and be equivalent in scope to other products within that segment.

Click the segment positions listed below to learn more.