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An initiative designed to improve sharing of patient data may provide “tremendous benefits” in cancer care and research, according to authors of a review article.

Dr. Alan P. Lyss

The goals of the initiative, called Minimal Common Oncology Data Elements (mCODE), were to identify the data elements in electronic health records that are “essential” for making treatment decisions and create “a standardized computable data format” that would improve the exchange of data across EHRs, according to the mCODE website.

Travis J. Osterman, DO, of Vanderbilt University Medical Center in Nashville, Tenn., and colleagues described the mCODE initiative in a review published in JCO Clinical Cancer Informatics.

At present, commercially available EHRs are poorly designed to support modern oncology workflow, requiring laborious data entry and lacking a common library of oncology-specific discrete data elements. As an example, most EHRs poorly support the needs of precision oncology and clinical genetics, since next-generation sequencing and genetic test results are almost universally reported in PDF files.

In addition, basic, operational oncology data (e.g., cancer staging, adverse event documentation, response to treatment, etc.) are captured in EHRs primarily as an unstructured narrative.

Computable, analytical data are found for only the small percentage of patients in clinical trials. Even then, some degree of manual data abstraction is regularly required.

Interoperability of EHRs between practices and health care institutions is often so poor that the transfer of basic cancer-related information as analyzable data is difficult or even impossible.
 

Making progress: The 21st Century Cures Act

The American Society of Clinical Oncology has a more than 15-year history of developing oncology data standards. Unfortunately, progress in implementing these standards has been glacially slow. Impediments have included:

  • A lack of conformance with clinical workflows.
  • Failure to test standards on specific-use cases during pilot testing.
  • A focus on data exchange, rather than the practical impediments to data entry.
  • Poor engagement with EHR vendors in distributing clinical information modules with an oncology-specific focus
  • Instability of data interoperability technologies.

The 21st Century Cures Act, which became law in December 2016, mandated improvement in the interoperability of health information through the development of data standards and application programming interfaces.

In early 2020, final rules for implementation required technology vendors to employ application programming interfaces using a single interoperability resource. In addition, payers were required to use the United States Core Data for Interoperability Standard for data exchange. These requirements were intended to provide patients with access to their own health care data “without special effort.”

As a fortunate byproduct, since EHR vendors are required to implement application program interfaces using the Health Level Seven International (HL7) Fast Healthcare Interoperability Resource (FHIR) Specification, the final rules could enable systems like mCODE to be more easily integrated with existing EHRs.
 

 

 

Lessons from CancerLinQ

ASCO created the health technology platform CancerLinQ in 2014, envisioning that it could become an oncology-focused learning health system – a system in which internal data and experience are systematically integrated with external evidence, allowing knowledge to be put into practice.

CancerLinQ extracts data from EHRs and other sources via direct software connections. CancerLinQ then aggregates, harmonizes, and normalizes the data in a cloud-based environment.

The data are available to participating practices for quality improvement in patient care and secondary research. In 2020, records of cancer patients in the CancerLinQ database surpassed 2 million.

CancerLinQ has been successful. However, because of the nature of the EHR ecosystem and the scope and variability of data capture by clinicians, supporting a true learning health system has proven to be a formidable task. Postprocessing manual review using trained human curators is laborious and unsustainable.

The CancerLinQ experience illustrated that basic cancer-pertinent data should be standardized in the EHR and collected prospectively.
 

The mCODE model

The mCODE initiative seeks to facilitate progress in care quality, clinical research, and health care policy by developing and maintaining a standard, computable, interoperable data format.

Guiding principles that were adopted early in mCODE’s development included:

  • A collaborative, noncommercial, use case–driven developmental model.
  • Iterative processes.
  • User-driven development, refinement, and maintenance.
  • Low ongoing maintenance requirements.

A foundational moment in mCODE’s development involved achieving consensus among stakeholders that the project would fail if EHR vendors required additional data entry by users.

After pilot work, a real-world endpoints project, working-group deliberation, public comment, and refinement, the final data standard included six primary domains: patient, disease, laboratory data/vital signs, genomics, treatment, and outcome.

Each domain is further divided into several concepts with specific associated data elements. The data elements are modeled into value sets that specify the possible values for the data element.

To test mCODE, eight organizations representing oncology EHR vendors, standards developers, and research organizations participated in a cancer interoperability track. The comments helped refine mCODE version 1.0, which was released in March 2020 and is accessible via the mCODE website.

Additions will likely be reviewed by a technical review group after external piloting of new use cases.
 

Innovation, not regulation

Every interaction between a patient and care provider yields information that could lead to improved safety and better outcomes. To be successful, the information must be collected in a computable format so it can be aggregated with data from other patients, analyzed without manual curation, and shared through interoperable systems. Those data should also be secure enough to protect the privacy of individual patients.

mCODE is a consensus data standard for oncology that provides an infrastructure to share patient data between oncology practices and health care systems while promising little to no additional data entry on the part of clinicians. Adoption by sites will be critical, however.

Publishing the standard through the HL7 FHIR technology demonstrated to EHR vendors and regulatory agencies the stability of HL7, an essential requirement for its incorporation into software.

EHR vendors and others are engaged in the CodeX HL7 FHIR Accelerator to design projects to expand and/or modify mCODE. Their creativity and innovativeness via the external advisory mCODE council and/or CodeX will be encouraged to help mCODE reach its full potential.

As part of CodeX, the Community of Practice, an open forum for end users, was established to provide regular updates about mCODE-related initiatives and use cases to solicit in-progress input, according to Robert S. Miller, MD, medical director of CancerLinQ and an author of the mCODE review.

For mCODE to be embraced by all stakeholders, there should be no additional regulations. By engaging stakeholders in an enterprise that supports innovation and collaboration – without additional regulation – mCODE could maximize the potential of EHRs that, until now, have assisted us only marginally in accomplishing those goals.

mCODE is a joint venture of ASCO/CancerLinQ, the Alliance for Clinical Trials in Oncology Foundation, the MITRE Corporation, the American Society for Radiation Oncology, and the Society of Surgical Oncology.

Dr. Osterman disclosed a grant from the National Cancer Institute and relationships with Infostratix, eHealth, AstraZeneca, Outcomes Insights, Biodesix, MD Outlook, GenomOncology, Cota Healthcare, GE Healthcare, and Microsoft. Dr. Miller and the third review author disclosed no conflicts of interest.

Dr. Lyss was a community-based medical oncologist and clinical researcher for more than 35 years before his recent retirement. His clinical and research interests were focused on breast and lung cancers, as well as expanding clinical trial access to medically underserved populations. He is based in St. Louis. He has no conflicts of interest.

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An initiative designed to improve sharing of patient data may provide “tremendous benefits” in cancer care and research, according to authors of a review article.

Dr. Alan P. Lyss

The goals of the initiative, called Minimal Common Oncology Data Elements (mCODE), were to identify the data elements in electronic health records that are “essential” for making treatment decisions and create “a standardized computable data format” that would improve the exchange of data across EHRs, according to the mCODE website.

Travis J. Osterman, DO, of Vanderbilt University Medical Center in Nashville, Tenn., and colleagues described the mCODE initiative in a review published in JCO Clinical Cancer Informatics.

At present, commercially available EHRs are poorly designed to support modern oncology workflow, requiring laborious data entry and lacking a common library of oncology-specific discrete data elements. As an example, most EHRs poorly support the needs of precision oncology and clinical genetics, since next-generation sequencing and genetic test results are almost universally reported in PDF files.

In addition, basic, operational oncology data (e.g., cancer staging, adverse event documentation, response to treatment, etc.) are captured in EHRs primarily as an unstructured narrative.

Computable, analytical data are found for only the small percentage of patients in clinical trials. Even then, some degree of manual data abstraction is regularly required.

Interoperability of EHRs between practices and health care institutions is often so poor that the transfer of basic cancer-related information as analyzable data is difficult or even impossible.
 

Making progress: The 21st Century Cures Act

The American Society of Clinical Oncology has a more than 15-year history of developing oncology data standards. Unfortunately, progress in implementing these standards has been glacially slow. Impediments have included:

  • A lack of conformance with clinical workflows.
  • Failure to test standards on specific-use cases during pilot testing.
  • A focus on data exchange, rather than the practical impediments to data entry.
  • Poor engagement with EHR vendors in distributing clinical information modules with an oncology-specific focus
  • Instability of data interoperability technologies.

The 21st Century Cures Act, which became law in December 2016, mandated improvement in the interoperability of health information through the development of data standards and application programming interfaces.

In early 2020, final rules for implementation required technology vendors to employ application programming interfaces using a single interoperability resource. In addition, payers were required to use the United States Core Data for Interoperability Standard for data exchange. These requirements were intended to provide patients with access to their own health care data “without special effort.”

As a fortunate byproduct, since EHR vendors are required to implement application program interfaces using the Health Level Seven International (HL7) Fast Healthcare Interoperability Resource (FHIR) Specification, the final rules could enable systems like mCODE to be more easily integrated with existing EHRs.
 

 

 

Lessons from CancerLinQ

ASCO created the health technology platform CancerLinQ in 2014, envisioning that it could become an oncology-focused learning health system – a system in which internal data and experience are systematically integrated with external evidence, allowing knowledge to be put into practice.

CancerLinQ extracts data from EHRs and other sources via direct software connections. CancerLinQ then aggregates, harmonizes, and normalizes the data in a cloud-based environment.

The data are available to participating practices for quality improvement in patient care and secondary research. In 2020, records of cancer patients in the CancerLinQ database surpassed 2 million.

CancerLinQ has been successful. However, because of the nature of the EHR ecosystem and the scope and variability of data capture by clinicians, supporting a true learning health system has proven to be a formidable task. Postprocessing manual review using trained human curators is laborious and unsustainable.

The CancerLinQ experience illustrated that basic cancer-pertinent data should be standardized in the EHR and collected prospectively.
 

The mCODE model

The mCODE initiative seeks to facilitate progress in care quality, clinical research, and health care policy by developing and maintaining a standard, computable, interoperable data format.

Guiding principles that were adopted early in mCODE’s development included:

  • A collaborative, noncommercial, use case–driven developmental model.
  • Iterative processes.
  • User-driven development, refinement, and maintenance.
  • Low ongoing maintenance requirements.

A foundational moment in mCODE’s development involved achieving consensus among stakeholders that the project would fail if EHR vendors required additional data entry by users.

After pilot work, a real-world endpoints project, working-group deliberation, public comment, and refinement, the final data standard included six primary domains: patient, disease, laboratory data/vital signs, genomics, treatment, and outcome.

Each domain is further divided into several concepts with specific associated data elements. The data elements are modeled into value sets that specify the possible values for the data element.

To test mCODE, eight organizations representing oncology EHR vendors, standards developers, and research organizations participated in a cancer interoperability track. The comments helped refine mCODE version 1.0, which was released in March 2020 and is accessible via the mCODE website.

Additions will likely be reviewed by a technical review group after external piloting of new use cases.
 

Innovation, not regulation

Every interaction between a patient and care provider yields information that could lead to improved safety and better outcomes. To be successful, the information must be collected in a computable format so it can be aggregated with data from other patients, analyzed without manual curation, and shared through interoperable systems. Those data should also be secure enough to protect the privacy of individual patients.

mCODE is a consensus data standard for oncology that provides an infrastructure to share patient data between oncology practices and health care systems while promising little to no additional data entry on the part of clinicians. Adoption by sites will be critical, however.

Publishing the standard through the HL7 FHIR technology demonstrated to EHR vendors and regulatory agencies the stability of HL7, an essential requirement for its incorporation into software.

EHR vendors and others are engaged in the CodeX HL7 FHIR Accelerator to design projects to expand and/or modify mCODE. Their creativity and innovativeness via the external advisory mCODE council and/or CodeX will be encouraged to help mCODE reach its full potential.

As part of CodeX, the Community of Practice, an open forum for end users, was established to provide regular updates about mCODE-related initiatives and use cases to solicit in-progress input, according to Robert S. Miller, MD, medical director of CancerLinQ and an author of the mCODE review.

For mCODE to be embraced by all stakeholders, there should be no additional regulations. By engaging stakeholders in an enterprise that supports innovation and collaboration – without additional regulation – mCODE could maximize the potential of EHRs that, until now, have assisted us only marginally in accomplishing those goals.

mCODE is a joint venture of ASCO/CancerLinQ, the Alliance for Clinical Trials in Oncology Foundation, the MITRE Corporation, the American Society for Radiation Oncology, and the Society of Surgical Oncology.

Dr. Osterman disclosed a grant from the National Cancer Institute and relationships with Infostratix, eHealth, AstraZeneca, Outcomes Insights, Biodesix, MD Outlook, GenomOncology, Cota Healthcare, GE Healthcare, and Microsoft. Dr. Miller and the third review author disclosed no conflicts of interest.

Dr. Lyss was a community-based medical oncologist and clinical researcher for more than 35 years before his recent retirement. His clinical and research interests were focused on breast and lung cancers, as well as expanding clinical trial access to medically underserved populations. He is based in St. Louis. He has no conflicts of interest.

An initiative designed to improve sharing of patient data may provide “tremendous benefits” in cancer care and research, according to authors of a review article.

Dr. Alan P. Lyss

The goals of the initiative, called Minimal Common Oncology Data Elements (mCODE), were to identify the data elements in electronic health records that are “essential” for making treatment decisions and create “a standardized computable data format” that would improve the exchange of data across EHRs, according to the mCODE website.

Travis J. Osterman, DO, of Vanderbilt University Medical Center in Nashville, Tenn., and colleagues described the mCODE initiative in a review published in JCO Clinical Cancer Informatics.

At present, commercially available EHRs are poorly designed to support modern oncology workflow, requiring laborious data entry and lacking a common library of oncology-specific discrete data elements. As an example, most EHRs poorly support the needs of precision oncology and clinical genetics, since next-generation sequencing and genetic test results are almost universally reported in PDF files.

In addition, basic, operational oncology data (e.g., cancer staging, adverse event documentation, response to treatment, etc.) are captured in EHRs primarily as an unstructured narrative.

Computable, analytical data are found for only the small percentage of patients in clinical trials. Even then, some degree of manual data abstraction is regularly required.

Interoperability of EHRs between practices and health care institutions is often so poor that the transfer of basic cancer-related information as analyzable data is difficult or even impossible.
 

Making progress: The 21st Century Cures Act

The American Society of Clinical Oncology has a more than 15-year history of developing oncology data standards. Unfortunately, progress in implementing these standards has been glacially slow. Impediments have included:

  • A lack of conformance with clinical workflows.
  • Failure to test standards on specific-use cases during pilot testing.
  • A focus on data exchange, rather than the practical impediments to data entry.
  • Poor engagement with EHR vendors in distributing clinical information modules with an oncology-specific focus
  • Instability of data interoperability technologies.

The 21st Century Cures Act, which became law in December 2016, mandated improvement in the interoperability of health information through the development of data standards and application programming interfaces.

In early 2020, final rules for implementation required technology vendors to employ application programming interfaces using a single interoperability resource. In addition, payers were required to use the United States Core Data for Interoperability Standard for data exchange. These requirements were intended to provide patients with access to their own health care data “without special effort.”

As a fortunate byproduct, since EHR vendors are required to implement application program interfaces using the Health Level Seven International (HL7) Fast Healthcare Interoperability Resource (FHIR) Specification, the final rules could enable systems like mCODE to be more easily integrated with existing EHRs.
 

 

 

Lessons from CancerLinQ

ASCO created the health technology platform CancerLinQ in 2014, envisioning that it could become an oncology-focused learning health system – a system in which internal data and experience are systematically integrated with external evidence, allowing knowledge to be put into practice.

CancerLinQ extracts data from EHRs and other sources via direct software connections. CancerLinQ then aggregates, harmonizes, and normalizes the data in a cloud-based environment.

The data are available to participating practices for quality improvement in patient care and secondary research. In 2020, records of cancer patients in the CancerLinQ database surpassed 2 million.

CancerLinQ has been successful. However, because of the nature of the EHR ecosystem and the scope and variability of data capture by clinicians, supporting a true learning health system has proven to be a formidable task. Postprocessing manual review using trained human curators is laborious and unsustainable.

The CancerLinQ experience illustrated that basic cancer-pertinent data should be standardized in the EHR and collected prospectively.
 

The mCODE model

The mCODE initiative seeks to facilitate progress in care quality, clinical research, and health care policy by developing and maintaining a standard, computable, interoperable data format.

Guiding principles that were adopted early in mCODE’s development included:

  • A collaborative, noncommercial, use case–driven developmental model.
  • Iterative processes.
  • User-driven development, refinement, and maintenance.
  • Low ongoing maintenance requirements.

A foundational moment in mCODE’s development involved achieving consensus among stakeholders that the project would fail if EHR vendors required additional data entry by users.

After pilot work, a real-world endpoints project, working-group deliberation, public comment, and refinement, the final data standard included six primary domains: patient, disease, laboratory data/vital signs, genomics, treatment, and outcome.

Each domain is further divided into several concepts with specific associated data elements. The data elements are modeled into value sets that specify the possible values for the data element.

To test mCODE, eight organizations representing oncology EHR vendors, standards developers, and research organizations participated in a cancer interoperability track. The comments helped refine mCODE version 1.0, which was released in March 2020 and is accessible via the mCODE website.

Additions will likely be reviewed by a technical review group after external piloting of new use cases.
 

Innovation, not regulation

Every interaction between a patient and care provider yields information that could lead to improved safety and better outcomes. To be successful, the information must be collected in a computable format so it can be aggregated with data from other patients, analyzed without manual curation, and shared through interoperable systems. Those data should also be secure enough to protect the privacy of individual patients.

mCODE is a consensus data standard for oncology that provides an infrastructure to share patient data between oncology practices and health care systems while promising little to no additional data entry on the part of clinicians. Adoption by sites will be critical, however.

Publishing the standard through the HL7 FHIR technology demonstrated to EHR vendors and regulatory agencies the stability of HL7, an essential requirement for its incorporation into software.

EHR vendors and others are engaged in the CodeX HL7 FHIR Accelerator to design projects to expand and/or modify mCODE. Their creativity and innovativeness via the external advisory mCODE council and/or CodeX will be encouraged to help mCODE reach its full potential.

As part of CodeX, the Community of Practice, an open forum for end users, was established to provide regular updates about mCODE-related initiatives and use cases to solicit in-progress input, according to Robert S. Miller, MD, medical director of CancerLinQ and an author of the mCODE review.

For mCODE to be embraced by all stakeholders, there should be no additional regulations. By engaging stakeholders in an enterprise that supports innovation and collaboration – without additional regulation – mCODE could maximize the potential of EHRs that, until now, have assisted us only marginally in accomplishing those goals.

mCODE is a joint venture of ASCO/CancerLinQ, the Alliance for Clinical Trials in Oncology Foundation, the MITRE Corporation, the American Society for Radiation Oncology, and the Society of Surgical Oncology.

Dr. Osterman disclosed a grant from the National Cancer Institute and relationships with Infostratix, eHealth, AstraZeneca, Outcomes Insights, Biodesix, MD Outlook, GenomOncology, Cota Healthcare, GE Healthcare, and Microsoft. Dr. Miller and the third review author disclosed no conflicts of interest.

Dr. Lyss was a community-based medical oncologist and clinical researcher for more than 35 years before his recent retirement. His clinical and research interests were focused on breast and lung cancers, as well as expanding clinical trial access to medically underserved populations. He is based in St. Louis. He has no conflicts of interest.

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