Data Element
Tumor Clinical Grade
Description

The degree of abnormality of cancer cells; or the extent to which cancer cells are similar in appearance and function to healthy cells of the same tissue type before any treatment (surgical resection or initiation of any treatment including neoadjuvant).
Submitted By: Wendy Blumenthal / Centers for Disease Control and Prevention (CDC)
Data Element Information
Use Case Description(s)
Use Case Description Cancer comprises a large set of nationally reportable diseases. The Cancer Registries Amendment Act {Public Law 102-515) established national data collection in 1992. Hospitals, physicians and other healthcare facilities and practitioners are required by state or jurisdictional laws to report newly diagnosed cancer cases to population-based cancer registries which are active in every U.S. state, the District of Columbia, Puerto Rico, the Virgin Islands, and the U.S. Pacific Island jurisdictions. Over 5,000 Certified Tumor Registrars (CTRs) (https://www.ncra-usa.org/CTR) review, extract, and manually code the data elements from the facility-level medical record and report these data to the population-based cancer registry. The Centers for Disease Control and Prevention’s (CDC) National Program of Cancer Registries (NPCR) (https://www.cdc.gov/cancer/npcr) and the National Cancer Institute’s (NCI) Surveillance, Epidemiology, and End Results (SEER) (https://seer.cancer.gov/about/overview.html) Program support these population-based registries and receive data to provide official government cancer statistics and public-use data to enable the public, researchers, clinicians, policy makers, and public health professionals to understand cancer on a patient- and population-level. Data on over 1.7 million newly diagnosis cancers are sent from patient care facilities into state cancer registries every year. The North American Association of Central Cancer Registries (NAACCR) (https://www.naaccr.org/) has developed data reporting standards that are used by all national cancer surveillance systems in the United States and Canada to collect, prepare, and exchange data. In the clinical setting, the American College of Surgeons Cancer Programs (https://www.facs.org/quality-programs/cancer) uses the same standardized cancer data to improve cancer patient care and support cancer staging, standards, and quality measures across over 1,500 hospitals, freestanding cancer centers, and cancer program networks accredited by the Commission on Cancer (CoC). At the hospital level, physicians and other healthcare providers use data such as the primary site of the tumor, the tumor histology, and tumor behavior to help determine and design community outreach efforts that are focused on cancer prevention and cancer screening for their patient population. A single data standard is critical for communicating effectively about cancer and to understand and address cancer incidence, survival, and quality of patient care; recruiting for clinical research; and planning and evaluating health services. Within free-standing cancer treatment centers, across regional hospital systems, or at small rural hospitals, the widespread use of standardized data elements would allow healthcare providers to track information that is useful in identifying the equipment and services that are needed for patients across all geographic areas. An interoperable standard incorporated into EHRs, hospital and state cancer registries, pathology laboratories, and other health IT systems would enable more efficient and timely data transmission to accomplish these goals compared to the current state of manual abstraction. The inclusion of these data elements in health IT systems could also improve accuracy of cancer surveillance by enabling capture of cases seen outside of hospitals.

Each of these use cases – population-based surveillance systems and clinical settings as well as patient registries and clinical trials – rely on and exchange Tumor Histologic Type, Tumor Primary Site and Tumor Laterality to communicate about cancer. Tumor Behavior is a critical data element to inform patient treatment and determine reportability to registries. Tumor Clinical Grade is a description of how abnormal the tumor cells appear under a microscope and is seen as a marker of a tumor’s ability to grow and spread.
Estimate the breadth of applicability of the use case(s) for this data element Data collection and transmission on new cancer cases are required by law from all providers [e.g., hospitals (>6000), outpatient physicians, radiation therapy facilities (>2000) and laboratories into state cancer registries (CCRs) and ultimately, into Centers for Disease Control and Prevention’s National Program of Cancer Registries (NPCR) (supports 50 CCRs) and the National Cancer Institute’s (NCI) Surveillance, Epidemiology, and End Results (SEER) Program (supports 20 CCRs). Additionally, The nationally recognized National Cancer Database (NCDB), jointly sponsored by the American College of Surgeons and the American Cancer Society, collects data from over 1,500 Commission on Cancer accredited hospitals and as a required component for quality improvement and assurance. In the United States, 1,701,315 new cases of cancer were reported in the latest year for which incidence data are available.
Link to use case project page https://www.cdc.gov/cancer/uscs/; https://www.cdc.gov/cancer/npcr/index.htm; https://seer.cancer.gov/; http://datadictionary.naaccr.org/default.aspx?Version=21; https://www.facs.org/quality-programs/cancer/coc; https://www.facs.org/quality-programs/cancer
Healthcare Aims
  • Improving patient experience of care (quality and/or satisfaction)
  • Improving the health of populations
  • Reducing the cost of care
  • Improving provider experience of care
Maturity of Use and Technical Specifications for Data Element
Applicable Standard(s) Tumor Histologic Type: International Classification of Diseases for Oncology 3.2, with additional values accepted by the WHO-IARC but not included in the official published documents. SNOMED International, Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT®) U.S. Edition, 2021 Release (month TBD)

Tumor Behavior: International Classification of Diseases for Oncology 3.2

Tumor Primary Site: International Classification of Diseases for Oncology 3.2. SNOMED International, Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT®) U.S. Edition, September 2020 Release

Tumor Laterality: SNOMED International, Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT®) U.S. Edition, September 2020 Release – mCODE Laterality Value Set

Tumor Clinical Grade: North American Association of Central Cancer Registries Grade Clinical
http://www.iacr.com.fr/index.php?option=com_content&view=category&layout=blog&id=100&Itemid=577; https://www.nlm.nih.gov/healthit/snomedct/us_edition.html; http://hl7.org/fhir/us/mcode/ValueSet/mcode-laterality-vs; http://datadictionary.naaccr.org/default
Additional Specifications o HL7 CDA® R2 IG: Reporting to Public Health Cancer Registries from Ambulatory Healthcare Providers, R1, DSTU Release 1.1 - US Realm https://www.hl7.org/implement/standards/product_brief.cfm?product_id=398
o HL7 Implementation Guide for CDA® Release 2: Reporting to Public Health Cancer Registries from Ambulatory Healthcare Providers, Release 1 - US Realm https://www.cdc.gov/phin/resources/guides/documents/implementation_guide_for_ambulatory_healthcare_provider_reporting_to_central_cancer_registries_august_2012.pdf
o IHE Quality Research and Public Health: Structured Data Capture Technical Framework [Internet], 2016. http://ihe.net/uploadedFiles/Documents/QRPH/IHE_QRPH_Suppl_SDC.pdf
o Moldwin R (ed): IHE Structured Data Capture (SDC)Technical Reference Guide (TRG) [Internet], 2020. https://github.com/IHE-SDC-WG/SDC-Schema-Packages/blob/master/Documentation/CAP SDC Technical Reference Guide_v0.42 (Feb 2020).pdf
o HL7 FHIR Implementation Guide: minimal Common Oncology Data Elements (mCODE) Release 1 - US Realm | STU1 (v1.0.0: STU 1) based on FHIR R4 http://hl7.org/fhir/us/mcode/
o College of American Pathologists (CAP) eCC (electronic Cancer Checklists) (https://www.cap.org/laboratory-improvement/proficiency-testing/cap-eccNorth American Association of Central Cancer Registries Version 21 Data Standards and Data Dictionary http://datadictionary.naaccr.org/default.aspx?c=10&Version=21
o Pathology Laboratory Electronic Reporting, Version 5.0 – May 2020 (revised July 2020). https://www.naaccr.org/wp-content/uploads/2020/07/NAACCR-Vol-V_Revised_20200720.pdf
Current Use Extensively used in production environments
Supporting Artifacts Level 2 – at scale, or in more widespread production use (routinely collected already) on several different EHR/HIT systems.
o Data on over 1.7 million newly diagnosis cancers are sent from patient care facilities into state cancer registries every year. Staff at health care facilities abstract data from patients’ medical records, enter it into the facility’s own cancer registry if it has one, and then send the data to the state registry. Other data sources include physicians’ offices, radiation facilities, freestanding surgical centers, and pathology laboratories. https://www.cdc.gov/cancer/uscs/technical_notes/data_sources/index.htm
o These data elements are included in the standards cited for EHR Certification for Transmission to Cancer Registries
 ONC 2015 Edition Final Rule https://www.federalregister.gov/documents/2015/10/16/2015-25597/2015-edition-health-information-technology-health-it-certification-criteria-2015-edition-base
 ONC 2014 Edition Final Rule https://www.federalregister.gov/documents/2012/09/04/2012-20982/health-information-technology-standards-implementation-specifications-and-certification-criteria-for
o Meaningful Use and Promoting Interoperability Programs https://www.cdc.gov/cancer/npcr/meaningful_use.htm https://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms
o The College of American Pathologists (CAP) electronic Cancer Checklists (eCCs) are computer-readable templates for the capture of consistent and complete sets of cancer pathology data elements in EHR and AP-LIS systems. The eCC XML templates are supported by all major vendors of anatomic pathology software systems. Each eCC template is based on a case summary (checklist) inside a CAP Cancer Protocol. Since their first eCC XML release in 2009, eCC use has increased to include 35-40% of North American anatomic pathologists and continues to grow. https://www.cap.org/protocols-and-guidelines/cancer-reporting-tools/cancer-protocol-templates/cancer-protocol-and-ecc-faqs
o IHE Connectathons 2010-2020 (CDA; as part of Cancer Reporting IGs)
o IHE and HL7 FHIR Connectathons 2015-2020 (IHE SDC and SDC on FHIR for eCCs)
o HIMSS Interoperability Showcase 2010-19 (CDA; as part of Cancer Reporting IGs)
o HIMSS Interoperability Showcase 2015-19 (IHE SDC and SDC on FHIR for eCCs)
o Public Health Informatics Conference Interoperability Showcase 2014, 2016, 2018 (CDA; as part of Cancer Reporting IGs)
o Public Health Informatics Conference Interoperability Showcase 2016 and 2018 (IHE SDC for electronic cancer checklists)
o National Association of County and City Health Officials (NACCHO) 360X Interoperability Demonstrations, 2020 (CDA, as part of Cancer Reporting IGs; IHE SDC and SDC on FHIR for eCCs)
https://www.cdc.gov/cancer/uscs/technical_notes/data_sources/index.htm; https://www.cdc.gov/cancer/npcr/meaningful_use.htm; https://www.cap.org/protocols-and-guidelines/cancer-reporting-tools/cancer-protocol-templates/cancer-protocol-and-ecc-faqs
Extent of exchange 5 or more. This data element has been tested at scale between multiple different production environments to support the majority of anticipated stakeholders.
Supporting Artifacts Level 2 – exchanged between 4 or more different EHR/HIT systems. More routinely exchanged between multiple different systems can justify adding to next draft version.
o Data on over 1.7 million newly diagnosis cancers are sent from patient care facilities into state cancer registries every year. Staff at health care facilities manually abstract data from patients’ medical records, enter it into the facility’s own cancer registry if it has one, and then electronically exchange the data with the state cancer registry. https://www.cdc.gov/cancer/uscs/technical_notes/data_sources/index.htm
o Other data sources include physicians’ offices, radiation facilities, freestanding surgical centers, and pathology laboratories. Data from these facilities are frequently exchanged from their HIT/LIS systems to state cancer registries.
o At least 38 state cancer registries have received test and/or production reports that include these data elements from at least one provider (per internal technical and programmatic documentation)
o 71 Certified EHR Technology (CEHRT) products certified to 2014 Edition and 288 products certified to 2015 Edition for Cancer Registry Reporting, both of which require this data element, thereby demonstrating their ability to exchange these elements with external organizations.
o CDC Webinars on Meaningful Use and HL7 Clinical Document Architecture (CDA) https://www.naaccr.org/meaningful-use/
o Future exchange: Common Oncology Data Elements eXtensions (CodeX) HL7 FHIR Accelerator Cancer Registry Reporting Use Case to enable low-burden, mCODE-centered reporting of cancer data from cancer centers to registries that are aggregating data for different reasons. https://confluence.hl7.org/display/COD/CodeX+Use+Cases
https://chpl.healthit.gov/#/search; https://www.naaccr.org/meaningful-use/; https://www.cdc.gov/cancer/uscs/technical_notes/data_sources/index.htm
Potential Challenges
Restrictions on Standardization (e.g. proprietary code) Tumor Histologic Type: Not all values are present in either Coding System.
• ICD-0-3.2 does not list all of the histology plus behavior codes possible
• SNOMED CT does not include all of the histologies
http://www.iacr.com.fr/index.php?option=com_content&view=category&layout=blog&id=100&Itemid=577
Restrictions on Use (e.g. licensing, user fees) None
Privacy and Security Concerns None
Estimate of Overall Burden Low to moderate. Providers who diagnose or treat patients with cancer already document the proposed data elements in the EHR, but not always in structured format, especially for histologic type. Health IT system vendors can capture these elements in a structured format either through interoperable exchange with pathology laboratory systems or by implementing the ability to capture the structured elements directly in the system.

Of note, the cancer data elements proposed are currently transmitted from healthcare providers and facilities to state cancer registries, and ultimately to CDC (NPCR), NCI (SEER), American College of Surgeons (ACoS) and ACS (NCDB) registries using specialized registry software. We see this as a demonstration of low to moderate implementation feasibility.
Other Implementation Challenges Versions of tumor histologic type classification standards change over time. Terms and codes are added and deprecated. Terms are moved from one code to another. Behavior codes (benign, uncertain, in situ, and malignant) assigned to ICD-O codes change over time, affecting reportability of tumors. Recommended site codes for which a histology term or code is appropriate are similarly changed. Updates and revisions to the ICD-O codes are based on histologic terms in World Health Organization (WHO) Classification of Tumours (i.e., WHO Blue Books). There is lag between the publications of WHO terminology and when ICD-O codes are updated, leaving gaps and incongruities in available ICD-O codes. Therefore, clinicians and cancer registrars may encounter WHO Blue Book code(s) on reports that are not yet incorporated into the ICD-O. In addition, 1) publication of these codes and use of these codes in other healthcare IT systems, such as registry/surveillance software and laboratory information systems, often precedes the effective date of implementation and 2) ICD-O codes do not exist for every possible histology. A multi-national collaboration of cancer-surveillance-standard-setting and clinical partners led by NCI is engaged in an active collaboration to map WHO Blue Book and ICD-O codes across time to offer an open-source electronic resource to fill this gap by adjudication and consensus of formal workgroups. We believe it would be advantageous for registry and clinical standard setters, e.g., CAP, NAACCR, and others, to regularly review and update the referenced USCDI histology value set in the future to ensure harmonization and alignment with clinical and registry practice. These USCDI data set updates will be important to ensure minimal impact to clinical and registry workflows within CEHRT and cancer registry software. In addition, the USCDI submission Public Comment and Pilot Testing with vendor systems will be critical to understand both feasibility and any potential impact of CEHRT implementation of these data elements on clinical and registry workflow.

Data element names are not standardized between pathology laboratory and the cancer registry. For example, pathologists are often not able to determine what is “primary” in certain cancer cases when talking about the origin of a tumor when multiple subsites of a site such as colon are involved so their data element display name is “Tumor” site. Implementation guides should recognize these ambiguities and document how to correctly identify the correct data elements in a data repository when it is being evaluated for exchange. Receiving software should also have logic to properly process these data elements. While the exchange of these data elements between the hospital cancer registries and the state registries is mature, exchange of these data elements between other EHR and HIT systems and state cancer registries needs more significant support for the data elements and standards proposed here.

Comment

Submitted by nedragarrett_CDC on

Unified Comment from CDC

  • General Comment: Recommend moving this element to a new “Cancer Data” USCDI Class (not in the Observation class). 
     
  • Additional Use Case: This is a standard data item used by central cancer registries in all states. Data received through data exchange from medical facilities (e.g., laboratories, hospitals, physician EHRs, etc.) to central cancer registries for CDC and NCI’s national cancer surveillance systems, as required by law.  

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