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Minimum Data Element

Published: November 2019 (Web posted August 2019)

Read Consensus Statement

The American Society for Radiation Oncology (ASTRO) has determined that defining a minimum set of data elements for radiation therapy is high priority activity. There is a deep and wide interest in leveraging Big Data in the oncology space as shown through the recent New York Times article,New Cancer Treatments Lie Hidden Under Mountains of Paperwork. Identifying a standard set of data elements is an important step in promoting Big Data initiatives.

ASTRO has also received requests for data elements from other societies, database architects, electronic health record (EHR) vendors and the pharmaceutical industry. These requests point to an increasing and shared interest in capturing radiation oncology data within registries, quality measurement, interoperability initiatives and clinical trials. In addition to these technical priorities, this effort can improve overall clinical care for cancer patients by increasing the visibility of radiation oncology treatment in other systems and reducing the time required for data entry by practice staff.

A review of radiation oncology data elements currently in use within national databases, ASTRO programs and resources from other cancer-related societies was conducted to identify possible overlap and priority. This analysis generated a short list of data elements to facilitate the myriad of use cases as well as define the minimum radiation oncology relevant data that should be included in all scenarios. Promoting this list provides an opportunity to educate those outside of the field about what data is necessary to capture and transfer.

Minimum Data Elements

Data ElementDefinitionDetail
Treatment Course Data Elements
DiagnosisIdentify disease(s) relevant to treatmentICD-10
ModalityRadiation type - Records the list of all modalities used during treatment course (Check all that apply)List provided
TechniqueTreatment delivery method - Records the list of all techniques used during treatment course (Check all that apply)List provided
Number of fractions plannedRecords the total number of treatments prescribed in a treatment  
Number of fractions deliveredRecords the total number of treatments delivered in a treatment course 
Start date of treatmentIndicates the date on which the patient commences course of delivered radiation treatmentMMDDYYYY
End date of treatmentIndicates the date on which the patient ends/completes a course of delivered radiation treatmentMMDDYYYY
Prescribed Dose Level Data Elements
Anatomic site of each prescribed dose levelIndicates the primary anatomic site(s) targets for each dose levelReference the Standards for Oncology Registry Entry
Total dose planned for each prescribed dose levelDose prescribed to each dose levelcGy
Total dose delivered for each prescribed dose levelDose delivered to each dose levelcGy
 

ASTRO believes the promotion of these minimum data elements will support many of the organization’s objectives as follows:

  • Research. Currently, many clinical trial datasets merely document administration of radiation therapy as a checkbox. This proposed list provides consistency and clarity in research efforts that can expand the quantity and quality of radiation data in clinical trials. Defining such minimum data elements can also promote the incorporation of radiation oncology into clinical trials and encourage inclusion of radiation oncology earlier in clinical trial timelines.
     
  • Quality. Sharing information across systems, with common definitions, can provide a reduction of duplicated procedures which can be costly and impinge on a patient’s care experience. The common list can safeguard that data has same definition when transferred out of an oncology information system into a more generalized EHR.
     
  • Informatics. A list of data elements allows radiation oncology to have a standard presence in informatics development as the Centers for Medicare and Medicaid Services (CMS) shifts towards interoperability, and patient-data access, within value-based care models.

 

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