Watson for Patient Record Analytics (aka Watson EMRA)       


Watson for Patient Record Analytics (aka Watson EMRA) - overview

Using Natural Language Processing (NLP) and machine learning to provide intelligent insights from a longitudinal patient record for patient care.

Creating cognitive insights from patient records at the point of care.

Watson for Patient Record Analytics includes:

  • An abstracted patient summary centered around an automatically generated problem list
  • Semantic search that returns clinically meaningful matches on multiple dimensions

The Patient Record

Patient records contain both structured and unstructured data.

Unstructured data is free text – most parts of clinical notes are unstructured data. An older or sicker patient may have hundreds of clinical notes.

Structured data includes medication orders, lab results, procedures, and vitals.

It is typical for a doctor to spend 5 to 10 minutes to review the patient record in order to get a basic understanding of what’s going on with the patient before actually seeing the patient.

Patient Record
Clinical Encounters
Structured Data
Lab Results

Watson Patient Record Analytics

Watson patient record analytics are used on top of the patient record to make sense of the data.

    Watson patient record analytics consist of:
  • NLP: Watson understands the content
  • Synthesis: Watson organizes the data in meaningful ways to help clinicians understand the data
  • Cognitive Insights: Combine patient data and general medical knowledge to provide deeper insight
Watson Patient Record Analysis

Problem-Oriented Medical Record (POMR)

POMR has become the de-facto record keeping standard in most US hospitals.

Problem list is also a mandatory section in the CCD (continuity of care), part of HL7's CDA (clinical document architecture) standard.

Problem-Oriented Medical Record (POMR)

Quality Assessment of Automatically Generated Problem List

On average Watson found 1.2 very important or important problems missed by physicians per patient record (avg. 6 problems)

Quality Assessment

Quick Facts


Amount of U.S. non-federal acute care hospitals that have adopted at least a basic EHR system with clinical notes in 2015

13 - 16 Minutes

The most common amount of time spent with patients as reported by physicians

1.2 Billion

Amount of clinical documents produced in the U.S. each year, comprising 60% of all clinical data


Amount of questions that arise during clinical care that are not pursued at the point of care

Group Members

Murthy Devarakonda
Michele Cestone
Bharath Dandala
Tong-Haing Fin
Sreeram (Venkata Naga) Joopudi
Jennifer Liang
Diwaker Mahajan
Ananya Poddar
John Prager
Preethi Raghavan
Partha Suryanarayanan
Ching-Huei Tsou