The AI Promise

Approx.

USD 150

BILLION

ANNUAL SAVINGS fOR THE US HEALTHCARE  ECONOMY BY 2026

$ 39
Billion

Robot Assisted Surgery**
Can lead to 21% reduction in patients’ length of stay in the hospital following surgery

$ 19
Billion

Virtual Nursing Assistants
Could save 20% of the time nurses spend on patient maintenance tasks

$ 17
Billion

Administrative Workflow Assistance
AI-based technologies, such as voice-to-text transcription, can improve administrative workflows and eliminate time-consuming non-patient-care activities, such as writing chart notes, filling prescriptions, and ordering tests

$ 17
Billion

Fraud Detection
By improving the speed and accuracy of fraud detection in Medicare claims.

$ 15
Billion

Dosage Error Reduction

$ 13
Billion

Connected Machines
AI can help design more efficient IoT networks, ensuring there’s enough capacity without overbuilding and enhancing security.

$ 12
Billion

Clinical Trial Participant Identifier

$ 7
Billion

Preliminary & Automated Image Diagnosis
Radiologists using AI can spot details that escape the human eye.
*Preliminary(5bn), Automated(3bn)

$ 1
Billion

Cyber Security
Could create USD 2 billion in annual savings by reducing health record breaches which can cost around  USD 380 per patient record

Napier’s data approach – An Overview

Napier endeavours to enhance its solutions by providing insight into the data using:

Artificial Intelligence
Deployed –  where deep learning can be deployed to train models over a period of time and generate predictions.

Examples include epidemic prediction, clinical and administrative risk predictor and alerts on impending quality issues

 

 

Artificial Intelligence
Used  – where analytics and insights are drawn from codifying knowledge; instances such as fraud detection and bill rejection.

Decisions made by business managers who need to analyze past data and make better data-driven decisions

 

Napier Artificial Intelligence …on the move

Pneumonia Screening Accelerator

Napier has trained a classification model to accelerate screening of Pneumonia from chest X-ray data. Ability to predict 8 out of 10 cases accurately

iEMR – turning Physician conversations into action

Order entry, capture EMR data using conversations during consultations.
Increased face time with the patients. Can be used to highlight poor prognosis indicators in patients presenting with symptoms of COVID illness.

Napier Assistant (NA)

Is designed to turn conversation (speech) into meaningful action thereby saving time for the user Drives user productivity, better patient experience and overall cost reduction

Predicting The Length Of Stay (PLOS)

Length of stay (LoS) prediction is an important metric of inpatient costs Establishes appropriate healthcare planning and resource allocation necessary for hospital operation while minimizing the cost of healthcare. Data can be used further for treatment plans and predicting bill estimates.

Sepsis Predictor For Patients

Screening tool to assess patient’s risk of developing sepsis or septic shock. Alerts assist in providing timely intervention to save lives

The Pandemic Response Solution

Discovery

Population Health

Analytics
Heat maps
Uses unstructured data

Mitigate

Surveillance

Contact Tracing
Movement management like SHN,
Quarantine

Treat

Care Management

Sepsis, PLOS, Pneumonia, Fraud detection etc.
Virtual Care

AI has the potential to help us tackle the pressing issues raised by pandemic.

: THE CHATBOT FOR ALL NEEDS

  •  Designed to turn conversations (speech) into meaningful actions.
  • It is an interactive tool based on decision tree approach that responds based on predefined queries, performs tasks based on speech inputs.
  • Designed for patients, doctors, nursing staff and administrators.
  • Improves patient experience and increases productivity immediately
  • The key use cases include patient triage, appointments, vitals, responding to queries, bill amounts due, bill and bed status updates
  • User friendly dashboard provides a summary of all the transactions in a session, the results, number of users and the turnaround time for each transaction

iEMR (Interactive EMR)

  • AI driven EMR based on human speech that assists physicians in data entry increasing valuable face time with the patients. This can be expanded to aid medical decision making.
  •  The model listens to voice command, understands intent and can Search or Display data and Complete action.
  • Can enter orders and capture EMR data based on natural conversations during consultations.
  •  Primarily targeted at doctors but can be extended to other clinical staff too
  •  Can be used as an independent application or can be integrated into any other application
  •  iEMR can be used to highlight poor prognosis indicators in patients presenting with symptoms of COVID 19 illness.