MedCoder - Coding literal text cause of death information reported on death certificates to ICD-10
Description
Automating the coding of literal text causes of death from death certificates to ICD-10 codes, improving accuracy, efficiency, and timeliness of mortality data for public health surveillance.
Detailed example
MedCoder outputs ICD-10 cause of death codes from literal text on death certificates. It also flags complex or frequently miscoded cases for manual review. The system uses NLP to cleanse and standardize input text before coding.
AI / analytics pattern
Natural Language Processing: AI that processes, interprets, and shares information in human language.
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
MedCoder increased the percentage of deaths that can be automatically and accurately coded from 70-75% to over 85%, resulting in substantial cost savings (hundreds of thousands of dollars) and significantly enhancing the timeliness of data for urgent public health concerns (e.g., COVID, drug overdose deaths), enabling near real-time surveillance.
Controls / human review
ATO: Yes; PIA: Not published
Data needed
Death certificate literal text data, including cause of death statements, and associated demographic information such as sex. Documentation for model training and evaluation data is widely available.