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Health Factor Selection: We selected HFs Health Factors around Allergy Review around context for Nurse assessing allergies.
We broke down the Health factor Factor statements into chunks that captures the action of what was being performed or requested. Also, we put into consideration that each chunk can exist on its own and still retain its original intent and clarity of meaning.
After the chunking process, we identify the Topics of the ANF statement because they capture the action and are able to stand on their own.
We proceed then proceeded to populate the ANF fields from the chunk data sets.
Highlighted Example:
“VA-VAAES ALG REVIEW-OTHER”
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The different modelers had many similar responses and a few different responses. The ID was only filled out by modeler 1, who reported the health factor Health Factor as the ID. The main differences were present in the topic and associated statement. The topic should specify what is being requested or performed by the AssociatedStatement. The different modelers had differing viewpoints on what the overall topic was that was being referred to. While modelers 1 and 3 chose the Allergy Review as the topic, Modeler 2 chose the Admission screen as the topic. Due to differing answers for the topic, the AssociatedStatement also had differing answers. Modelers 1 and 2 had similar findings referring to the ‘other conducting review’ while modeler 3 had ‘admission screening’. The AssociatedStatement is not as clearly defined within the ANF ballot that described the ANF modeling. The AssociatedStatement should be connected to the topic and allow for further defining of what data is being modeled. Lastly, there is a visible difference in the reporting of the purpose. Modelers 1 and 2 reported the SNOMED terms associated with the ANF statement while Modeler 3 reported insufficient data to capture the purpose.
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