Automating the HouseVizit Telemedicine App with Azure Health Bot

Project Overview

HouseVizit works as a comprehensive platform that allows patients to effortlessly find and book appointments with doctors who match their specific requirements. Thousands of patients use this app to set up online telemedicine appointments, streamline the process for both patients and healthcare providers. Patients have to fill out a pre-consultation form that consists of a series of questions regarding their symptoms and medical history. By having access to this detailed information ahead of the appointment, doctors can save valuable time during the consultation and focus on delivering personalized and efficient care.

Key Challenges

Limited Coverage of Diseases

The current app supports only a predefined set of diseases, as each condition requires a specific questionnaire. If a patient's condition is not listed in the app's database, this limitation prevents them from getting the right medical advice.

Static Symptom Questionnaire

The symptom collection process relies on a static, predefined questionnaire, which limits the app's ability to collect complete and nuanced patient information, potentially leaving out important aspects.

Inefficient Use of Consultation Time

Without thorough pre-consultation information, doctors have to spend a significant time during the appointment collecting basic information which reduces the time available for efficient diagnosis and treatment.

Reduced Patient Flow and Care Quality

The process of collecting information during appointments can reduce the number of patients and hamper care quality. This can impact timely and accurate care delivery.

Our Solution

Our team has developed an advanced AI chatbot powered by Generative AI and Natural Language Processing (NLP) to overcome the challenges. This innovative chatbot offers several key features to enhance the user experience and improve the efficiency of telemedicine consultations.

Our AI chatbot engages patients with conversational AI techniques to understand their responses through NLP. It automatically modifies the questions according to the patient’s specific symptoms and medical history, ensuring a comprehensive and customized pre-consultation process. This leads to a better and more accurate information-sharing process.

The AI chatbot chats with patients and summarizes their answers for doctors, saving time during appointments. We have incorporated Azure health bot in our AI chatbot to understand a wide range of health issues. It not only identifies the patient’s condition but also suggests the most appropriate type of doctor for their needs. This ensures that patients are directed to the right specialists, improving the overall quality of care.

Azure Health Bot Service

We set up Azure Health Bot with the help of the Azure portal.
Defined channels – Web Chat and DirectLine from various other options.
Configured the behavior of built-in medical triage with “infermedica” for advanced symptom checking.
Using Azure Health Bot Management Portal, we customized certain settings.
We used Azure for real-time reports on the chatbot, including even the unrecognized phrases to improve user experience.
Incorporated error-handling mechanisms to support technical issues.
Made sure of HIPAA compliance with Azure's robust security features.
Provided easy-to-understand user interfaces for mobile and tablet devices.

Azure Cognitive Services

Enhanced functionality by integrating Azure Cognitive Services.
Improved conversation accuracy with the Language Understanding Model.
Developed and deployed Conversational Language Understanding Model in Language Studio.
Utilized Azure templates for handling unknown statements.

Azure OpenAI

Added Azure OpenAI to cope up with unrecognized statements.
Generated informative responses for unexpected prompts.
Crafted instructions for a wide range of scenarios that can empower the bot to define core behavior.
Improved bot responses and made them more timely by training it continuously on ongoing interactions.

Tech Stack

Flutter

Firebase Authentication

Cloud Firestore

Firebase Analytics

Firebase Crashlytics

Firebase

Framework

Programming Language

Crash Reporting

Cloud Service / AI Framework

SDK (Software Development Kit)

Mobile Operating System / SDK

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