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Description	Fig. 4 Laboratory result processing diagram for diabetic biomarker monitoring. Incoming HL7 observations are transformed to denormalized JavaScript Object Notation documents and stored to HDFS. The Prism dataflow ingests streaming JavaScript Object Notation result records and filters hemoglobin A1C results in the “Normal” (<5.7) and “Diabetic” (>6.5) cohorts to the Prism Specimen Surveillance Index in Elastic. Results from CMP/BMP panels (light-green top specimens) are sent to the Prism index. Secure notifications are sent for A1C specimen IDs with related light-green specimen info. BMP: Basic Metabolic Panel, CMP: Comprehensive Metabolic Panel, HbA1c: Hemoglobin A1c; HDFS: Hadoop-Distributed File System, HL7: Health-Level 7, JSON: Java Script Object Notation
Source	Durant, T.J.S.; Gong, G.; Price, N.; Schilz, W.L. (2020). "Bridging the collaboration gap: Real-time identification of clinical specimens for biomedical research". Journal of Pathology Informatics 11: 14. doi:10.4103/jpi.jpi_15_20.
Date	2020
Author	Durant, T.J.S.; Gong, G.; Price, N.; Schilz, W.L.
Permission (Reusing this file)	Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
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+==Summary==
+{{Information
+|Description='''Fig. 4''' Laboratory result processing diagram for diabetic biomarker monitoring. Incoming HL7 observations are transformed to denormalized JavaScript Object Notation documents and stored to HDFS. The Prism dataflow ingests streaming JavaScript Object Notation result records and filters hemoglobin A1C results in the “Normal” (<5.7) and “Diabetic” (>6.5) cohorts to the Prism Specimen Surveillance Index in Elastic. Results from CMP/BMP panels (light-green top specimens) are sent to the Prism index. Secure notifications are sent for A1C specimen IDs with related light-green specimen info. BMP: Basic Metabolic Panel, CMP: Comprehensive Metabolic Panel, HbA1c: Hemoglobin A1c; HDFS: Hadoop-Distributed File System, HL7: Health-Level 7, JSON: Java Script Object Notation
+|Source={{cite journal |title=Bridging the collaboration gap: Real-time identification of clinical specimens for biomedical research |journal=Journal of Pathology Informatics |author=Durant, T.J.S.; Gong, G.; Price, N.; Schilz, W.L. |volume=11 |at=14 |year=2020 |doi=10.4103/jpi.jpi_15_20}}
+|Author=Durant, T.J.S.; Gong, G.; Price, N.; Schilz, W.L.
+|Date=2020
+|Permission=[https://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License]
+}}
 == Licensing ==
 {{cc-by-nc-sa-4.0}}