	US 12,334,199 B2
	Automated transformation documentation of medical data
Margaret M. Jackson, Collegeville, PA (US); Peter Teunissen, Kansas City, KS (US); Andres Hernandez, Kansas City, KS (US); Steven Ger, Kansas City, KS (US); Daniel Holder, Kansas City, KS (US); and Mark L. Smith, Lee's Summit, MO (US)
Assigned to Cerner Innovation, Inc., Kansas City, MO (US)
Filed by CERNER INNOVATION, INC., Kansas City, KS (US)
Filed on Oct. 8, 2021, as Appl. No. 17/497,324.
Claims priority of provisional application 63/123,850, filed on Dec. 10, 2020.
Prior Publication US 2022/0189596 A1, Jun. 16, 2022
Int. Cl. G16H 15/00 (2018.01); G06F 16/215 (2019.01); G06F 16/25 (2019.01); G16H 10/60 (2018.01)

CPC G16H 15/00 (2018.01) [G06F 16/215 (2019.01); G06F 16/256 (2019.01); G16H 10/60 (2018.01)]

20 Claims

1. A method for documenting transformations of medical data maintained by a healthcare cloud computing platform, the method comprising:

loading medical data from a third-party database into a healthcare cloud computing platform, the medical data comprising a first medical record and a second medical record;

identifying a medical concept included in the medical data, wherein the medical concept includes a first plurality of medical properties in the first medical record and a second plurality of medical properties in the second medical record;

transforming the medical data using a state machine having a state machine definition for the medical concept, to result in transformed medical data, by:

providing the medical data to the state machine;

determining a normalized plurality of medical properties for the medical concept according to the state machine definition; and

normalizing the first plurality of medical properties and the second plurality of medical properties according to the state machine definition to generate a first normalized plurality of medical properties for the first medical record and a second normalized plurality of medical properties for the second medical record;

mapping the transformed medical data to a primary medical record in the healthcare cloud computing platform based on the transformed medical data and the primary medical record being associated with a same patient identifier;

evaluating the first medical record and the second medical record by accessing deduplication rules for the cloud computing platform to determine if the first medical record and the second medical record satisfy a rule set for the medical concept;

if the first medical record and the second medical record satisfy the rule set:

determining whether one of the first medical record and the second medical record is in the primary record;

if the first medical record is in the primary record and the second medical record is not in the primary record: storing the second medical record in a provenance module;

if the first medical record and the second medical record are not in the primary record:

ranking the first medical record and the second medical record to determine a higher-ranking medical record and a lower-ranking medical record;

writing the higher-ranking medical record into the primary medical record; and

writing the lower-ranking medical record into the provenance module;

if the first medical record and the second medical record do not satisfy the rule set:

writing data from the first medical record and the second medical record that is not stored in the primary medical record into the primary medical record; and

storing the determination that the first medical record and the second medical record do not satisfy the rule set in the provenance module.