We want to announce a new network study:https://github.com/redcdm/RedCohort_v0.1
The full protocol can be found here: https://github.com/redcdm/RedCohort_v0.1/blob/master/extras/REDCDM_OHDSI_Protocol.docx
Our research on REDCDM is being conducted for the following purposes.
The purpose of this study is to examine the number of patients of four rare endocrine diseases (Medullary thyroid carcinoma, idiopathic hypoparathyroidism, pheochromocytoma/ paraganglioma, non-surgical hypophosphatemia) and to identify related comorbidities. This is relatively a simple study to count the number of patients but detecting rare disease in ICD-based database can be a hard task. To overcome this limitation, we created digital phenotyping based on ICD codes plus phenotypic constraints using drugs and procedures, along with digital phenotyping based on SNOMED-CT. We want to see whether this approach works to yield clinically meaningful distribution of numbers of patients with rare endocrine diseases across various institutions. Furthermore, we hope that we can find a suitable approach to rare diseases in electronic medical database system which exists as invisible.
The Specific Aims are to:
- Describe the number of incident patients of rare endocrine diseases by age and gender and compare how the number of incident patients of rare endocrine diseases varies by country, by applying ICD-based and SNOMED-CT based digital phenotypes (operational definitions).
- Examine the top 30% of the most commonly related disease with each rare endocrine disease, during overall observational period or as grouped into pre- and post-index date period.
We hypothesize that the number of incident patients of rare endocrine disorders (Medullary thyroid carcinoma, idiopathic hypoparathyroidism, pheochromocytoma/ paraganglioma, hypophosphatemia) will vary by digital phenotyping (operational definitions) across institutions, and the information itself will help to understand how we need to tailor approach to rare endocrine (or hopefully for other rare disease entities) using CDM.
Participating organizations can help our research by sharing the result file of GitHub’s package.
Please send the result file and questions to email@example.com