Getting Started

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:

1. 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.

2. 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.

3. 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
   Abbott	Libre2,Libre 3	Freestyle Libre	CSV
   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:

4. 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:

   1. Surveilr Tool (Use the latest version).

   2. Deno Runtime (require Deno 2.0)
      Follow the Deno Installation Guide for step-by-step instructions. If Deno is already installed, upgrade to Deno 2.0 by running the following command as an administrator:

      deno upgrade
      

      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

      1. 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 
         

      2. 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

5. 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.