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Applications of Generative AI in Healthcare

Richard Clements
Richard Clements
Applications of Generative AI in Healthcare

Generative AI Applications in Healthcare

Generative AI has the power to streamline processes across healthcare operations. For example, generative AI platforms can quickly provide accurate, contextual information and insights to questions such as:

  • What is the hospital policy?
    Registered nurses and other practitioners can leverage generative AI to quickly access information on care protocols and policies. For example, a new nurse or a nurse covering for a colleague in a different department can ask a generative AI tool for information policies regarding minimizing hospital-acquired infections, and the solution can quickly provide the details essential to quality care.
  • What’s the optimal way to schedule staff?
    Another impactful application for generative AI in healthcare is assisting managers with scheduling. The platform can analyze hospital capacity and available staff to create a schedule that ensures enough practitioners and employees to provide quality care but avoid burnout due to overscheduling.
  • What’s the answer to this healthcare coverage question?
    Healthcare organizations field numerous questions from patients on their healthcare coverage or other non-clinical topics. Generative AI can provide those answers from a database, saving staff time and allowing them to focus on care and ensuring positive patient outcomes.
  • How can we operate more efficiently?
    One of the most valuable uses for generative AI in healthcare is streamlining the business side of healthcare. It can automate the scheduling of patient care, tracking and restocking inventory, resource allocation, and automated claim processing.
  • Integrations
    Generative AI must be able to connect to data sources, both internal and external, and integrate with the business systems that life sciences and healthcare organizations use, such as Salesforce, Veeva, and Microsoft Teams.

How Generative AI Benefits LHow Can Generative AI in Healthcare Directly Impact Patient Care?ife Sciences

Physicians also explore how generative AI can assist with patient screening, personalizing care, and even diagnoses. This technology has the potential to streamline processes and provide physicians with information more quickly — if the healthcare organization minimizes bias and potential patient privacy and data breaches.The right provider will help healthcare organizations build a strategy for generative AI use that delivers the most significant benefits while minimizing risks. Additionally, healthcare providers can focus on generative AI’s time-saving capabilities, providing 100x faster access to data and insights, which gives organizations more time to focus on individual patients and enhance their experiences.

Generative AI in Healthcare Benefits vs. Traditional Analytics Processes

Generative AI technology will help healthcare organizations take analytics to new levels of speed and efficiency. Generative AI solves common analytics pain points, including:

User autonomy

Traditional analytics processes center on a business intelligence (BI) dashboard. A healthcare employee requests the IT or data team build the dashboard, run the analysis, and generate reports and visualizations. The process can take weeks, slowing progress in different areas of the organization. On the other hand, a generative AI platform allows users to interact without intervention from IT and regardless of their data science expertise. Users simply ask questions conversationally, and the platform searches data and automatically generates the appropriate visualization or provides the answer.

Scalability

Traditional BI dashboards are limited in the number of data sources and the data volumes used in an analysis. With healthcare data growing exponentially, data teams are forced to create new dashboards and piecemeal analyses. A leading generative AI platform for life sciences scales with the organization’s data and analytics needs. They aren’t limited in the number of sources or volumes they can use.

Access to Insights

Healthcare users typically access data analytics insights from dashboard tools. That means they need to open new windows and toggle between the solutions they’re using. Leading generative AI platforms can be embedded into common applications so users can access insights with just a few clicks. Additionally, users can access insights from a PC at a desk or workstation or using tablets or smartphones.

Frequently Asked Questions

What is natural language processing?

Natural language processing (NLP) allows machines to understand human speech and respond in ways people can easily understand. WhizAI includes a hybrid NLP engine that combines sophisticated linguistic techniques with deep learning to enable users to interact with the platform conversationally.

Can WhizAI work with a life sciences company’s current BI dashboard solutions?

Yes. WhizAI is valuable as a standalone solution. However, it can complement companies' investment in business intelligence (BI) dashboards. Our user data shows it can reduce the number of dashboards the company must maintain, on average, from 20 to about 5.

Is coding necessary to configure WhizAI?

WhizAI features a zero-code environment, which allows all users, regardless of their IT or data science expertise, to create dashboards, pin them to their UI, and share them with collaborators without coding.

Does WhizAI limit how we can deploy the platform?

WhizAI’s flexible deployment approach allows companies to implement it with a firewall, on-premises, or in a public or private cloud.

Which public cloud providers can companies use for WhizAI?

WhizAI can be deployed in AWS, Azure, and other popular public clouds.

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