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Clinical Decision Support

Build predictive models on top of automatically real time extracted information from unstructured documents – enabling data based decision not ever available in past​
01
Extract

Extract in real time information from unstructured text

02
Build

Build a predictive model using the extracted information

03
Get

Get timely and accurate support in clinical decision

Case #1: Predict hospital bed demand by real time analytics of clinical notes
Key factors that influence a patient’s flow (How likely they are to admitted? For how long? For what?):
Volume of arrivals
  • Outpatient
  • Referrals
  • Emergency Room
  • Operation Room
Admission specialty
  • Oncology
  • Hip-replacement
  • Renal Disease
  • Cardiology, …
Timing of arrival
  • Hour of the day
  • Day of the week
  • Holidays
Seasonal variables
  • Flu season
  • Natural disasters
Patient's length of stay
  • per unit (ICU, CVICU, …)
Nurse staffing levels & skill mix:
  • Certified Nurses
  • Licensed N.P.’s
  • Unlicensed Staff
  • Unique certifications
John Snow Labs enabled real-time decision-making and strategic planning, by predicting:
  • Bed demand
  • Safe staffing levels
  • Hospital gridlock
Case #2: Automatic notification of patient aggression risk for psychiatric admitted patients​
NLP system:
  • Input:12 hours past clinical notes
  • Predictions vs. Brøset Violence Checklist:
  • 74% correct score
  • 18% over-score
  • 8% under-score
Case #3: Automatic preparation of Tumor board conference support materials
  • Pathology report
  • Radiology report
  • Lab report
  • Sequencing report
  • OCR
  • Named entities detection
  • Assertions
  • Clinical relations
  • Clinical coding
  • Patient profile
  • Materials for tumor meeting
  • Clinical decision support

Why John Snow Labs?

01

14 records in global accuracy leaderboard

02

The most widely used library in the industry

03

8 out of 10 top pharma our customers

We can train your team to use our software, or build complete solutions per your exact needs.

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