Based on the pairing rules defined, there are two possible outcomes when generating the FHIR resources that represent a condition (e.g., diabetes, MI, HF, etc): the FHIR resource is created, with an 'Active' status (when it is reported as such), or it is just not created otherwise, as there is no such thing as 'Inactive' diabetes, HF, MI, etc.
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* @pairingrule |
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* if diabetes_presence_adu_q_1 = yes in 1A => SNOMED code for active. |
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* else |
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* if diabetes_presence_adu_q_1 = no, and there is a 'yes' on diabetes_followup_adu_q_1 in any of the |
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* follow-up assessments => active. |
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* else |
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* an empty object is returned, as there is no such a thing as 'inactive' diabetes given the |
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* definition used by the profile: Problems with the status 'Inactive' refer to problems that don't |
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* affect the patient anymore or that of which there is no evidence of existence anymore. |
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* |
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*/ |
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export const clinicalStatus = ():object => { |
However, this causes a limitation on the generated data, as there is no way to tell which participants don't have a FHIR Problem/Condition because they explicitly say 'NO' on the related questions, and which don't have it because they didn't answer the related questions (missing data). As there are only two accepted outcomes for the Problem resource the only solution I see for this is to also generate the Problem/FHIR resource for participants that explicitly reported that never had the condition, but setting it as an 'Inactive' one. With this, we will be able to identify three sets for each condition: the ones with the condition, the ones that never had it, and the ones for whom there is no certainty. Knowing the latter would also help when doing data imputation, if needed.
@baukearends could you give me your thoughts on this?
Based on the pairing rules defined, there are two possible outcomes when generating the FHIR resources that represent a condition (e.g., diabetes, MI, HF, etc): the FHIR resource is created, with an 'Active' status (when it is reported as such), or it is just not created otherwise, as there is no such thing as 'Inactive' diabetes, HF, MI, etc.
CDF2Medmij-Mapping-tool/src/lifelines/Diabetes.ts
Lines 46 to 57 in 071cb66
However, this causes a limitation on the generated data, as there is no way to tell which participants don't have a FHIR Problem/Condition because they explicitly say 'NO' on the related questions, and which don't have it because they didn't answer the related questions (missing data). As there are only two accepted outcomes for the Problem resource the only solution I see for this is to also generate the Problem/FHIR resource for participants that explicitly reported that never had the condition, but setting it as an 'Inactive' one. With this, we will be able to identify three sets for each condition: the ones with the condition, the ones that never had it, and the ones for whom there is no certainty. Knowing the latter would also help when doing data imputation, if needed.
@baukearends could you give me your thoughts on this?