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Crowdsourcing Healthcare Innovation: Learnings from Indegene's ChatGPT Use Case Competition

21 Mar 2023

ChatGPT has been a trending topic for a few months now, for good reason. Its ability to generate conversational human-like responses has made it the fastest app to reach 100 million active users, reaching that milestone in two months.

Generative AI, including models like ChatGPT, has made significant strides in healthcare applications. Initially, basic chatbots assisted with routine inquiries and appointment scheduling. As natural language processing advanced, so did the capabilities of these Artificial Intelligence (AI) systems. Early iterations evolved, promising personalized patient interactions, symptom analysis, and functioning as virtual health assistants adept at comprehending nuanced medical queries. The proficiency of these AI-powered solutions in understanding and generating human-like text also finds its utility in medical research, extracting valuable insights from vast datasets.

The potential Artificial Intelligence holds to transform business processes is enormous, making it a hot topic in various industries. While the life sciences industry is notorious for being slow to adopt technology, there is a lot of buzz around how AI could accelerate digital transformation.

To explore this potential further, at Indegene we ran a competition for ideas on ChatGPT use cases in life sciences. The submissions were outstanding and contain a wealth of inspiration and learning. We are excited to share the Top 3 submissions. 

Submission 1: A smart form for the intake of adverse events, by Adithya Ramesh

What is the current scenario?

Adverse Event (AE) reporting is done through static forms, which are difficult for reporters to use and often capture incomplete information that makes it challenging to evaluate the case. The forms also contain irrelevant fields, leading to a costly follow-up process. One in three AE cases needs multiple follow-ups, and top pharmaceutical companies process over a million cases annually. Additionally, the use of free text in these forms leads to unstructured data that is more challenging to process than structured text.

Solving the problem with ChatGPT

ChatGPT can serve as a responsive "smart form" that dynamically asks questions based on the report's profile (e.g., physician, patient, employee), intelligence extracted from past cases and safety insights, and a case type-based intake. It responds with appropriate follow-up questions based on reporter inputs, capturing the required AE information accurately, reducing follow-ups, and providing a user-friendly experience through layering questions one by one. Additionally, it offers smart response options to users instead of lengthy textual answers, allowing structured information collection.

Submission 2: ChatGPT as a modular content strategist, by Rohit Ayyar

What is the current scenario?

The adoption of Modular Content is rapidly increasing among pharmaceutical and life science organizations to improve content creation, review, and approval processes, and increase content reuse. However, developing a modular content strategy involves identifying key messages, suggesting modules, and determining asset types, which can be a challenge for organizations. It can be time-consuming and resource-intensive, causing delays in content creation and approval timelines.

Solving the problem with ChatGPT

ChatGPT can act as a Modular Content Strategist, providing a high-level plan for developing a modular content strategy. By analyzing large volumes of existing content, ChatGPT can extract key messages and suggest modules that can be used to create relevant content faster. Additionally, ChatGPT can suggest example asset types and storylines for these assets, providing a structured approach to developing modular content. With ChatGPT's assistance, organizations can develop a more effective modular content strategy that can optimize content creation, review, and approval processes, and increase overall efficiency.

Submission 3: Smart chatbot to register patients into a health program, by Sridhivya Veerendran

What is the current scenario?

In the life science industry, registering patients with their personal and demographic information in hospitals or healthcare campaigns is a critical process. However, with large numbers of patients enrolling, it can be a challenging and error-prone task. Additionally, registering patients for health programs involves curating data and fixing formatting and basic errors, which can be time-consuming and tedious for human operators. These challenges can result in errors, delays, and inefficiencies in the patient registration process.

Solving the problem with ChatGPT

ChatGPT can help streamline the patient registration process by acting as a chatbot, prompting patients for their personal and demographic information and registering them in the required format. By leveraging natural language processing (NLP) capabilities, ChatGPT can correct basic formatting and errors in real time, reducing the need for human intervention. With ChatGPT's assistance, healthcare organizations can register patients with greater accuracy and efficiency, reducing errors and saving time and resources.

These ideas highlight just a few of the many ways that AI can be used to transform life sciences. By leveraging the power of machine learning and natural language processing, we can generate insights and predictions that would be impossible for humans alone. With AI-driven solutions, we can speed up drug discovery, optimize clinical trials, and improve patient outcomes.

We hope you are inspired by the winning ideas and will continue to explore the potential of AI to revolutionize healthcare.

To the participants – a big thank you for your enthusiastic participation in our competition! We were blown away by the creativity and insight that you brought to the table, and we are excited to explore how these ideas can be turned into reality.


Pratik Maroo
Pratik Maroo

Insights to build #FutureReadyHealthcare