Care Evolution

Whether working with claims, clinical or other health data directly from providers, companies face a fragmented collection of files riddled with duplicate entries and uncoded or poorly coded data. Consolidating these records into a high quality, clean, actionable view of patient health is time consuming, error-prone and typically outside of a health tech company’s core expertise. CareEvolution’s health tech customers have integrated automated tools into their products to ensure high data quality while focusing internal resources on their core business: 

• A health tech company ingests and aggregates patient records from over 600,000 providers and 4,000 hospitals with extensive patient medical histories; individual files average 500 pages and often span 30 or more CDA documents, reaching as high as 700 CDAs full of duplicate, poorly coded and incorrectly formatted information. 

• An insurtech company ingesting and organizing EHR data for its insurance company clients is challenged with managing large records full of duplicate and uncoded information scattered across many files for its clients who underwrite insurance policies and process claims. Read more about how Clareto adopted Convert to expand the use and value of clinical data for life insurance companies

Disorganized records create inefficiencies and increase the risk of errors and misinterpretation of a patient’s state of health. And accuracy is paramount for today’s end user – whether it’s to accurately process claims and underwrite policies or provide a clear picture of patient health to improve care.

How health tech companies have solved their patient data challenges with the Convert API 

• By using the Convert API, one health tech vendor aggregating large volumes of medical records dramatically reduced file sizes and page counts while maintaining data integrity. For instance, one patient’s medical record, originally 7,342 pages, was consolidated into a single, de-duplicated, 600-page PDF. This type of transformation significantly enhanced efficiency for the providers that needed to find relevant patient information, reducing the time spent on medical records reviews.
• The Convert API improved Clareto’s medical record review processes by deduping documents and organizing data into summary tables for conditions, medications, labs and diagnoses so underwriters know where to look. They reported dramatically reduced page counts as a result of the consolidation into a clean, deduped document. This improved the speed and accuracy of their clients’ medical records reviews.

Conclusion  

For health tech companies, APIs are essential to ensuring patient data accuracy and preventing data loss. CareEvolution’s Convert API is part of its Orchestrate technology which works with existing infrastructure to enable rapid and efficient patient data management. Convert can also be utilized from within larger data ecosystems such as Snowflake and Databricks.