ANNUAL SAVINGS fOR THE US HEALTHCARE ECONOMY BY 2026
Robot Assisted Surgery**
Can lead to 21% reduction in patients’ length of stay in the hospital following surgery
Virtual Nursing Assistants
Could save 20% of the time nurses spend on patient maintenance tasks
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
By improving the speed and accuracy of fraud detection in Medicare claims.
Dosage Error Reduction
AI can help design more efficient IoT networks, ensuring there’s enough capacity without overbuilding and enhancing security.
Clinical Trial Participant Identifier
Preliminary & Automated Image Diagnosis
Radiologists using AI can spot details that escape the human eye.
Could create USD 2 billion in annual savings by reducing health record breaches which can cost around USD 380 per patient record
Napier endeavours to enhance its solutions by providing insight into the data using:
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
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 has trained a classification model to accelerate screening of Pneumonia from chest X-ray data. Ability to predict 8 out of 10 cases accurately
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.
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
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.
Screening tool to assess patient’s risk of developing sepsis or septic shock. Alerts assist in providing timely intervention to save lives
Uses unstructured data
Movement management like SHN,
Sepsis, PLOS, Pneumonia, Fraud detection etc.
AI has the potential to help us tackle the pressing issues raised by pandemic.