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.

  1. 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:

    ManufacturerSensorsData Format (Platform)File Type
    AbbottLibre2,Libre 3Freestyle LibreCSV
    DexcomG6, G7, SteloClarityCSV
    MedtronicCarelinkCSV
    SenseonicsCSV
    TidepoolanyTidepoolCSV
    GlookoanyGlookoCSV

    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.

    FieldDescription
    metadata_idA unique identifier for the record
    devicenameName of the device
    device_idUnique identifier for the device
    source_platformPlatform or system from which data originated
    patient_idUnique identifier for the patient
    file_nameName of the uploaded file
    file_formatFormat of the uploaded file (e.g., CSV, excel)
    file_upload_dateDate when the file was uploaded
    data_start_dateStart date of the data period covered by the file
    data_end_dateEnd date of the data period covered by the file
    study_idUnique 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.

    FieldDescription
    participant_idUnique identifier for the participant/patient
    study_idUnique identifier for the study
    site_idIdentifier for the site where participant is enrolled
    diagnosis_icdDiagnosis code based on International Classification of Diseases (ICD) system
    med_rxnormMedication code based on RxNorm system
    treatment_modalityModality of treatment for the participant
    genderGender of the participant
    race_ethnicityRace and ethnicity of the participant
    ageAge of the participant
    bmiBody Mass Index (BMI) of the participant
    baseline_hba1cBaseline Hemoglobin A1c level of the participant
    diabetes_typeType of diabetes diagnosed for the participant
    study_armArm 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.

    FieldDescription
    study_idUnique identifier for the study
    site_idUnique identifier for the site
    site_nameName of the site
    site_typeType 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.

    FieldDescription
    study_idUnique identifier for the study
    study_nameName or title of the study
    start_dateDate when the study commences
    end_dateDate when the study concludes
    treatment_modalitiesDifferent modalities or interventions used in the study
    funding_sourceSource(s) of funding for the study
    nct_numberClinicalTrials.gov identifier for the study
    study_descriptionDescription 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.

    FieldDescription
    investigator_idThe ID of the investigator / researcher
    investigator_nameName of the Researcher
    emailResearcher email
    institution_idUnique identifier for the institution
    study_idID 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.

    FieldDescription
    institution_idUnique identifier for the institution
    institution_nameName of the institution
    cityCity where the institution is located
    stateState where the institution is located
    countryCountry 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.

    FieldDescription
    lab_idUnique identifier for the laboratory
    lab_nameName of the laboratory
    lab_piPrincipal investigator associated with the lab
    institution_idUnique identifier of the institution the lab belongs to
    study_idUnique 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.

    FieldDescription
    author_idUnique identifier for the author
    nameName of the author
    emailEmail of the author
    investigator_idUnique identifier of the investigator the author is associated with
    study_idUnique 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.

    FieldDescription
    publication_idUnique identifier for the publication
    publication_titleTitle of the publication
    digital_object_identifierIdentifier for the digital object associated with the publication
    publication_sitePublishing site
    study_idUnique identifier for the study

    Please download the publication file for data input by clicking here. You can view a sample in the image below:

  2. 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

      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

        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

        vv-image

        Image 1

        vv-steps-image

        Image 2

  3. 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.