Case Study
Provider automates diagnosis-related coding, improving accuracy and patient timeliness
Results
2x
More than doubled coding-team productivity
30K+
Processed 30K+ coding transactions annually
Better
Improved coding accuracy and patient timeliness
Company Profile
Nonprofit regional integrated health system in the US Midwest, anchors a multi-hospital network plus an affiliated nursing and health-sciences college and a regional health-insurance subsidiary. Thousands of employees and hundreds of physicians, with annual operating revenue in the billions. Distinctive vertical integration of provider and payer at regional scale.
Challenge
Coders extracting and validating diagnosis codes by hand
Every record meant a coder squinting at a document and matching it line by line against the eligible-code list. The diagnosis registration team pulled source docs from the electronic medical record, extracted the ICD codes, validated each against the eligible list, and only then posted it into the registration system. As a result, steady volume, meticulous work, and a steady drip of typos came with doing the same thing thousands of times by hand.
Meanwhile, the pace held back patient timeliness on every downstream process that depends on a registered diagnosis. Therefore, leadership wanted higher accuracy and faster cycle time without expanding the coding team to keep up with growth.
Solution
Automated diagnosis-code extraction and validation at scale
Our client engaged WonderBotz, which leveraged proprietary frameworks and accelerators to rapidly assemble a diagnosis-coding automation tailored to the registration workflow. In short, the automation pulled the encounter identifiers, reached into Cerner to retrieve the diagnosis documents, read the ICD codes assigned by the care team using intelligent document processing, and validated each code against the eligible-code list before posting it to the registration system.
However, where the IDP confidence score was low or a code failed validation, the case routed to a coder for manual review. As a result, the workflow handled 30,000+ transactions a year, more than doubled the coding team’s productivity, and lifted accuracy and patient timeliness on every downstream process that depends on a registered diagnosis.
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