The solution is built for chronic care management along with medical billing to maximize medical reimbursement. It aims to optimize the financial performance of a healthcare organization by ensuring accurate and timely billing, maximizing reimbursements, reducing claim denials, improving overall revenue, and maintaining high standards of patient care.
The application allows users to purchase medical devices to advance healthcare across the United States. The website has all the major functionalities like product listing, catalogs, add-to-cart, favorite products, purchase options, invoice generation, etc. The platform sells devices to many big hospitals across the USA. Major areas of care- - Compounding pharmacy - Home infusion pharmacy - Infusion - OEM/Private [...]
Real-time automatic mileage tracking app which works continuously in background mode and tracks miles traveled for business and personal logs. It enables you to automatically set & categorize your business mileage based on hours & days you work. This platform automates the entire reimbursement process saving customers & finance department hundreds of hours as it generates mileage & expense reports [...]
A SaaS-based platform that acts as a bridge between the community (clinic/providers) and patients. The platform will cater needs of different types of patients/users- Insured/Uninsured Individual Users and employees. The proposed application will allow site visitors to search providers for consultation (Online, or in person) based on their medical conditions or requirement. They can either consult the provider on an [...]
An online session platform where practitioners create sessions and registered members can register for these sessions as per their interest. This platform empowers practitioners to select multiple categories for the session, schedule as per their availability, set session size (limit on the total number of members attending a session, duration, video required). The payment model for practitioners is based on [...]
This project is based on OCR using python. The data from documents (hand written or scanned), images, excel, CSV is read and converted into structured data using NLP (natural language processing) and natural language tool kit (NLTK). Important data fields related to patient's visit to clinic or hospital are extracted and stored for further analytics.
