Health tech organizations are increasingly turning to artificial intelligence (AI) to transform data analytics, streamline processes, and ensure they’re providing maximum value to clients. Yet, challenges persist for some.
Lengthy project timelines, high operating costs, and medical coding inaccuracies represent just a few of these difficulties. Organizations that rely heavily on manual workflows may also experience greater instances of human error, among other setbacks.
So, how can you overcome these obstacles and drive innovation?
Check out our latest asset, Leveraging AI to meet client needs: A guide for driving efficiency, maximizing cost effectiveness, and boosting user satisfaction, for a leg up on the competition.
GUIDE
Leveraging AI to meet client needs: A guide for driving efficiency, maximizing cost effectiveness, and boosting user satisfaction
Only have time for an excerpt? Continue reading to learn how AI tools can help your organization minimize manual effort and optimize resource allocation.
To minimize manual effort and optimize resource allocation:
- Embrace AI-driven analysis: Work with a vendor who leverages AI-powered tools to automate the analysis of inputs such as regulatory code set updates and client-provided dictionaries. This allows clinical informatics and code mapping teams to prioritize more complex inputs and act as reviewers for simpler tasks.
- Classify tasks according to difficulty: Partner with a vendor who uses LLMs judiciously, splitting work into easier tasks and complex tasks, and sending only the more complicated or ambiguous ones to the LLM. For basic mapping tasks, look for NLP solutions that can extract clinical concepts from free text data and map clinical entities and structured data to standard codes without running costly, resource-hungry LLMs.
