AGBI Digital HealthTech Grand Challenge

Theme by Virtusa Technologies

Build a predictive chatbot enabled digital assistant, backed by data, that can help surgeons, patients and care teams throughout the patient journey by automating some of the crucial tasks done manually such as decision making, post-surgery planning, tracking and estimating recovery-time, and takes patients' feedback. Can you come up with innovative reporting tools or dashboards for patient data monitoring and Patient engagement by providing customized counseling?

Or use your ML skills to create a bot to Line of Therapy for patients by gathering patient information and suggesting pathway and treatment cost, and prepare an optimized insurance plan for coverage based on the patient's condition and locality.

Theme by Mehta Group of Hospitals

Traditional X-Ray films are bulky and unportable causing patients to leave behind these films when going for follow-up hospital visits, resulting in poorer diagnosis. Currently, the radiology department or diagnostic labs have to print and review the x-ray film and then physically hand it over to the patient/treating doctor for a diagnosis. Help hospitals and diagnostics by enabling better diagnosis and health outcomes, cost savings, the faster mechanism by building a reliable mobile app or lens/scanner that can capture the x-ray image without any loss in image clarity or image distortion.

Theme by Virtusa Technologies

Having an automated system that can predict the volume of sales for a drug year-on-year, estimate the growth rate of the drug market and Identify potential competitor growth rate would reduce human effort and make the process more efficient. Propose a solution to predict revenue of a drug from the time of launch for the next few years and help estimate specific cost requirements with its marketing expenditure to sales revenue and hence determine the time for a drug to be pushed into 1st line of therapy.

Theme by Mehta Group of Hospitals

Currently, hospitals rely on mass marketing campaigns to inform patients of a relevant treatment or drug available to further improve their health. Build applications that can help hospitals, patients, pharmaceutical companies, and health R&D companies with more efficient and effective ways of communication by hospitals for better health outcomes and targeted communication to prime patient groups for a new treatment/drug leveraging the power of data analytics. Your solution needs to manage the database of patient records and discharge summaries to identify patients who are good candidates for newly launched medicines, treatments etc.

Theme by Virtusa Technologies

If image processing and deep learning excites you, you are at the right place!

We rely on your expertise to help doctors and surgeons to identify the associated allergies from capture images of skin, predict the probability of skin cancer, and suggest remedies to prevent further damage. Enabling smart features like connecting with forums offering discussions around the problem or prescribing a skin specialist based on a geographic location will give extra advantages to your solutions!

Theme by Virtusa Technologies

Here’s something exciting for our Alexa and Google developers!

We are looking for solutions that can be integrated to a home device to customize medication packs that capture the medication intake on breaking a printed circuit of the blister pack and remind the user if a medication is missed. The application may send a detailed report to the caregiver and patient's family to track medication adherence and track patient recovery and analyze drug efficacy in chronic disease conditions.

Theme by Virtusa Technologies

Make a difference by building working prototypes on unique industry problems of the Healthcare Space of the United States Market. Interpret, implement, and demonstrate designs and systems that can leverage technologies like AI/ML and deep learning to increase efficiency in the following processes:

• Intake and Pre-Processing Anomaly Detection

Detects anomalies and discrepancies in the healthcare claims intake / acquisition and preprocessing / data loading steps. Example- Data, technical-level, business-logic validations can be done in the pre-processing step in claims processing; or Alerts/ notifications can be sent out in case of table loading errors and where re-submissions are required.

• Overpayment Recovery and Adjustment Analysis

Categorizes claims into groups or builds an adjustments or corrections system to be used whenever Overpayment occurs from the side of the payer in the previous claim payment cycle for a physician/hospital.

• Decision Flagging for Potential Appeals & Grievances Inflow

Based on claim decisions made, build an AI/ML-driven analytics model that flags claims for the potential Appeals & Grievances (A&G) inflow and processing.

• Categorization Based on Provider Payment Preferences
Based on provider payment preferences, build an AIML-driven analytics model that groups claims the Checks and Electronic Fund Transfer (EFT). Based on provider preferences, analytics and decision , support could further be applied on rolling out tailored suggestions and services to providers – to improve provider engagement, experience, and retention.