The following are the instructions for registering with DRH and uploading your CGM data to DRH.
If you are a researcher willing to submit your CGM data, please follow the steps below:
Download and review the MoU
Before you register with us and submit your data, please review our MoU. This document outlines the kind of data expected, secure data sharing methods, data ownership details, and the benefits you, as a researcher, will receive.
Request for SFTP account (For Anchor Researchers)
As a new user to DRH, you must send in a request to researchhub-help@diabetestechnology.org along with the name of your organization to have an SFTP account set up for you. This SFTP account will help you transfer your files securely to DRH.
Based on the above, a new SFTP user account will be created for you.
Once the folder setup and permissions are ready, you shall be informed via the email through which you have sent in your request.
Once you receive your credentials, you can go to the SFTP site and login using your credentials.
You will be able to view the folder created for you. This is where you will be uploading your CGM data.
Note: The file upload through SFTP is for Anchor Researchers only. This will transition to a web-based UI in the near future.
Organize your CGM data in the standard format provided
In order to collect and unify data received from various disparate sources, we have a defined a standard format in which you will have to organize your data before you can upload to SFTP. Your CGM data will have to be organized into the following files. The structure is designed considering that this is a research study.Please note that you will have to use the exact same file names as shown below.a. cgm_tracing_0000n.csv
File Description: The “cgm_tracing_0000n” file typically contains a record of continuous glucose monitoring (CGM) data collected over a specific period of time for a patient from various CGM devices. This is the raw CGM data obtained directly from the CGM device.
Note: You can add a suffix of your choice after cgm_tracing to denote the multiple tracing files. The above suggested suffix ” _0000n ” is only a recommendation.
Accepted CGM Data Formats:
The List below provides information about the different types of CGM data sources, along with their respective manufacturers, sensors, and data formats for each platform:
Manufacturer Sensors Data Format (Platform) File Type Dexcom G6, G7, Stelo Clarity CSV Medtronic Carelink CSV Senseonics CSV Tidepool any Tidepool CSV Glooko any Glooko CSV For each patient, a cgm_tracing file containing CGM data can be provided. The metadata associated with each cgm_tracing file can be linked in the cgm_file_metadata file. The number of cgm_tracing files will increase based on the number of patients included in the study.
You can view a sample in the image below:
b. cgm_file_metadata.csv
File Description: Metadata associated with CGM data files. Given below are the columns that provide additional information about the data in the raw cgm_tracing.csv file. Also, a researcher can choose to add custom columns in addition to the columns given below.
Field Description metadata_id A unique identifier for the record devicename Name of the device device_id Unique identifier for the device source_platform Platform or system from which data originated patient_id Unique identifier for the patient file_name Name of the uploaded file file_format Format of the uploaded file (e.g., CSV, excel) file_upload_date Date when the file was uploaded data_start_date Start date of the data period covered by the file data_end_date End date of the data period covered by the file study_id Unique identifier for the study associated with the data Please download the cgm_file_metadata file for data input by clicking here. You can view a sample in the image below:
c. participant.csv
File Description: Demographic information of study participants/patients.
Field Description participant_id Unique identifier for the participant/patient study_id Unique identifier for the study site_id Identifier for the site where participant is enrolled diagnosis_icd Diagnosis code based on International Classification of Diseases (ICD) system med_rxnorm Medication code based on RxNorm system treatment_modality Modality of treatment for the participant gender Gender of the participant race_ethnicity Race and ethnicity of the participant age Age of the participant bmi Body Mass Index (BMI) of the participant baseline_hba1c Baseline Hemoglobin A1c level of the participant diabetes_type Type of diabetes diagnosed for the participant study_arm Arm or group to which the participant is assigned in the study Please download the participant file for data input by clicking here. You can view a sample in the image below:
d. site.csv
File Description: “Site” typically refers to the physical location or locations where the study is being conducted or where participants are recruited. This file shall contain information related to the site in the context of studying CGM data, including details about the specific facilities, clinics, or hospitals involved in the research, as well as any pertinent characteristics or attributes of these locations.
Field Description study_id Unique identifier for the study site_id Unique identifier for the site site_name Name of the site site_type Type or category of the site (e.g., hospital, clinic) Please download the site file for data input by clicking here. You can view a sample in the image below:
e. study.csv
File Description: The study file typically contains information about a specific research study.
Field Description study_id Unique identifier for the study study_name Name or title of the study start_date Date when the study commences end_date Date when the study concludes treatment_modalities Different modalities or interventions used in the study funding_source Source(s) of funding for the study nct_number ClinicalTrials.gov identifier for the study study_description Description about Study Please download the study file for data input by clicking here. You can view a sample in the image below:
f. investigator.csv
File Description: Details of investigators/researchers involved in the study.
Field Description investigator_id The ID of the investigator / researcher investigator_name Name of the Researcher email Researcher email institution_id Unique identifier for the institution study_id ID for the study associated with the researcher Please download the investigator file for data input by clicking here. You can view a sample in the image below:
g. institution.csv
File Description: This file contains information about institutions involved in a study.
Field Description institution_id Unique identifier for the institution institution_name Name of the institution city City where the institution is located state State where the institution is located country Country where the institution is located Please download the institution file for data input by clicking here.
h. lab.csv
File Description : This file contains information about laboratories involved in a study.
Field Description lab_id Unique identifier for the laboratory lab_name Name of the laboratory lab_pi Principal investigator associated with the lab institution_id Unique identifier of the institution the lab belongs to study_id Unique identifier for the study Please download the lab file for data input by clicking here. You can view a sample in the image below:
i. author.csv
File Description: This file contains information about authors involved in a study publication.
Field Description author_id Unique identifier for the author name Name of the author email Email of the author investigator_id Unique identifier of the investigator the author is associated with study_id Unique identifier for the study Please download the author file for data input by clicking here.You can view a sample in the image below:
j. publication.csv
File Description: This file contains information about publications resulting from a study.
Field Description publication_id Unique identifier for the publication publication_title Title of the publication digital_object_identifier Identifier for the digital object associated with the publication publication_site Publishing site study_id Unique identifier for the study Please download the publication file for data input by clicking here. You can view a sample in the image below:
DRH Data Transformation and local UI setup
This tool allows you to securely convert your CSV files, perform de-identification, and conduct verification and validation (V&V) processes all within your own environment. You can view the results directly on your local system.
Requirements for Previewing the Edge UI:
- Surveilr Tool (use latest version surveilr)
- Deno Runtime (requires
deno
v1.40 or above): Deno Installation Guide
Installation steps may vary depending on your operating system.
Getting Started
Step 1: Navigate to the Folder Containing the Files
- Open the command prompt and navigate to the directory with your files.
- Command:
cd <folderpath>
- Example:
cd D:/DRH-Files
Step 2: Download Surveilr
- Follow the installation instructions at the Surveilr Installation Guide.
- Download latest version
surveilr
from Surveilr Releases to this folder.
Step 3: Verify the Tool Version
- Run the command
surveilr --version
in command prompt and.\surveilr --version
in powershell. - If the tool is installed correctly, it will display the version number.
Step 4 : Execute the commands below
Clear the cache by running the following command:
deno cache --reload https://raw.githubusercontent.com/surveilr/www.surveilr.com/main/lib/service/diabetes-research-hub/drhctl.ts
After clearing the cache, run the single execution command:
deno run -A https://raw.githubusercontent.com/surveilr/www.surveilr.com/main/lib/service/diabetes-research-hub/drhctl.ts 'foldername'
- Replace
foldername
with the name of your folder containing all CSV files to be converted.
Example:
deno run -A https://raw.githubusercontent.com/surveilr/www.surveilr.com/main/lib/service/diabetes-research-hub/drhctl.ts study-files
- After the above command completes execution launch your browser and go to http://localhost:9000/drh/index.sql.
This method provides a streamlined approach to complete the process and see the results quickly.
Step 5 : Verify the Verification Validation Results in the UI
- Check the below section in UI and Perform the steps as in the second image
Image 1
Image 2
- Replace
Submit your converted CGM database using SFTP
Once you have successfully converted your files and verifed them using the above tool, please upload the database after renaming based on your study to the SFTP folder assigned to you.You can login to your SFTP account using the credentials sent to you by DRH via email.
Please note that your data is secure and are available only to you and DRH.