Condition, diagnosis, or reason for seeking medical attention.
Data Element
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Disease Trend
Description
Disease trend, also referred to as disease status, represents the clinician's overall judgment on the current trend of a condition, e.g., whether it is stable, worsening (progressing), or improving (responding). The judgment may be based a single type or multiple kinds of evidence, such as imaging data, physical examination, tumor measurements, laboratory data, etc. The condition trend can be reported multiple times during the course of a condition, each report representing the clinical judgement at that point in time. The element is important in assessing disease progression and determining the efficacy of treatments.
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Submitted By: Andre Quina
/ MITRE
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Data Element Information |
Use Case Description(s) |
Use Case Description |
Practitioner doing disease assessment and creating a plan of treatment (the A and P in SOAP) may leverage disease staging as a way to link to standards of care.
CMMI is also requiring the collection of certain specific “clinical data elements” (CDEs) from participants in the mandatory Radiation Oncology (RO) model scheduled to begin in January 2021, and has issued an informal RFI soliciting public comment on the draft CDEs. Staging is one of the proposed CDEs required for reporting in the RO model. See: https://innovation.cms.gov/media/document/ro-clin-data-elements-rfi-v2
Event for its collection and use: Staging is determined and recorded after diagnosis. Often staging is determined through a use of a variety of diagnostic tests. The results of those tests inform the disease stage. While disease staging is used to inform the treatment of many diseases such as Alzheimer’s and heart failure, it is most common in cancer treatment. In cancer treatment staging is used to describe the size of the tumor (in the case of solid tumors), location of a cancer, and if or where the cancer has spread. Staging is used to cluster clinically homogenous patients to inform treatment options, to establish cohorts of patients for research, and for cancer control purposes when comparting populations to assess outcomes or natural history (e.g., in a population-based cancer registry).
Frequency of use: While not all diseases or all cancers are staged, staging is a critical element for cancer care. For cancers that are staged, the frequency of use is near universal.
Broader collection and use: For cancers that are staged, staging information is foundational to understanding the extent and characteristics of the cancer. Staging can help to inform viable treatment options and predict the course a cancer will take and how likely treatments are to be successful. Staging information is relevant to nearly all Health IT systems supporting cancer patient care and public health. As a result, staging information is relevant to nearly all cancer related use cases for cancers that are staged and would be exchanged across all involved systems.
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Estimate the breadth of applicability of the use case(s) for this data element
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Staging can be considered a core element associated with the Problem domain as a way to communicate the extent and seriousness of the disease. In this context usage would extend to most practitioners using a certified EHR, which is the majority of physicians in the US.
Specifically for cancer roughly 1.8M people in the US will be newly diagnosed with cancer in 2020. There are approximately 13,000 oncologists practicing in the US. Staging is critical for all of those patients and oncologists for cancers that are staged.
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Use Case Description |
The trend of the disease can indicate the effectiveness of treatments. Disease trend provides an indication of patient outcome that is amenable for collection as part of routine care. Disease trend is being evaluated as part of the ICAREdataTM project focused on cancer. The overall goal of the ICAREdata project is to enable clinical oncology research by prospectively gathering high quality real-world data (RWD). The ICAREdataTM project is a collaboration between The MITRE Corporation and the Alliance for Clinical Trials in Oncology and is being conducted in association with randomized controlled trials (RCTs) and National Cancer Trial Network (NCTN) institutions. As a pilot use case for the mCODE (Minimal Common Oncology Data Elements) standard, the study is evaluating disease trend among other outcome elements of mCODE and to demonstrate a real-world data strategy for clinical trials. As part of the study, an open source infrastructure and automated standards-based interface for data capture and exchange are being developed and piloted.
Disease trend is a clinician’s qualitative judgment on the current trend of the cancer, e.g., whether it is stable, worsening (progressing), or improving (responding). The judgment may be based a single type or multiple kinds of evidence, such as imaging data, assessment of symptoms, tumor markers, laboratory data, etc. Through the ICAREdata study disease trend is being collected in the EHR for patients that are currently enrolled in a clinical trial that incorporates the ICAREdata protocol (currently 3 trials). The goal of the ICAREdata study is to demonstrate a correspondence between disease trend and traditional evaluations of tumor response used in cancer clinical trials (e.g., RECIST criteria). This would provide a validated measure of patient outcome in the EHR that would advance the use of real world data in support of post market surveillance, clinical trial design, observational studies, and clinical trial execution.
Event for its collection and use: Disease trend is collected at every patient encounter.
Frequency of use: Disease trend provides a critical patient outcome in structured form. Availability of structured patient outcome data is extremely limited, particularly for cancer patients. Disease trend represents the oncologist’s evaluation of the current response of the cancer to treatment. As such, disease trend is often the basis for many of the decisions around the current or future course of treatment.
Broader collection and use: With the current limited availability of structured patient outcomes it is extremely difficult to develop analytics to evaluate the safety and efficacy of approved therapies in real world populations. The broad availability and exchange of disease trend would accelerate the applicability of real world data across a broad variety of use cases.
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Estimate the breadth of applicability of the use case(s) for this data element
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While particularly applicable to cancer, disease trend is relevant to all conditions. As a core element associated with the Problem domain, usage of disease trend would extend to most practitioners using a certified EHR, which is the majority of physicians in the US.
See:
http://icaredata.org
https://confluence.hl7.org/display/COD/EHR+Endpoints+for+Cancer+Clinical+Trials
https://www.cdc.gov/cancer/dcpc/data/index.htm
https://www.asco.org/research-guidelines/reports-studies/state-cancer-care
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Healthcare Aims |
- Improving the health of populations
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Maturity of Use and Technical Specifications for Data Element |
Applicable Standard(s) |
HL7 FHIR Implementation Guide: minimal Common Oncology Data Elements (mCODE) Release 1 - US Realm | STU1
http://hl7.org/fhir/us/mcode/
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Additional Specifications |
HL7 FHIR Implementation Guide: minimal Common Oncology Data Elements (mCODE) Release 1 - US Realm | STU1
http://hl7.org/fhir/us/mcode/
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Current Use |
Extensively used in production environments |
Supporting Artifacts |
Staging information for cancer is collected in most EHR systems. For cancer the representation of staging is standardized. Staging is widely exchanged using APIs however many of those APIs are not broadly standardized. The standard exchange of staging information using FHIR based implementation guides is still limited but is progressing.
Disease trend is currently often only collected in unstructured notes. Through the ICAREdata study disease trend is being collected at an increasing number of health systems (currently 5 health systems) and has been implemented by Epic.
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Extent of exchange
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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 |
Staging information is frequently exchanged across a variety of use cases and settings.
Through the ICAREdata study disease trebd is being collected at an increasing number of health systems (currently 5 health systems). Disease trend and staging are being exchanged between those health systems and the Alliance for Clinical Trials in Oncology using FHIR APIs for analysis against clinical trial data.
https://confluence.hl7.org/display/COD/EHR+Endpoints+for+Cancer+Clinical+Trials, https://confluence.hl7.org/display/COD/EECT+Supporting+Materials
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Potential Challenges |
Restrictions on Standardization (e.g. proprietary code) |
AJCC codes frequently used for cancer staging are proprietary
There are no restrictions on disease trend
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Restrictions on Use (e.g. licensing, user fees) |
None |
Privacy and Security Concerns |
This data falls under general HIPAA regulations |
Estimate of Overall Burden |
How hard is it to access and provide the data?
Since staging and disease trend are routine evaluations for cancer the only additional burden is in the structured collection where that is not already part of standard workflows. The applicability of staging will vary by specialty.
Is it only available in an outside system, such as a lab reporting system?
No.
Does it need to be calculated by the patient or provider, or can it be automatically retrieved or calculated by the system in a production environment?
Both staging and disease trend are assessed by the clinician.
Does it require significant time on the part of patient or provider to access or record or does it require an interruption in normal workflow to capture?
Both staging and disease trend are routine evaluations for cancer. The applicability of staging will vary by specialty.
Does it require significant developer time to implement in EHR systems?
Epic is in the process of implementing mCODE data elements for the problem domain focused on disease trend. Given the minimal complexity for representing disease trend, implementation has been relatively low burden. Disease staging has variable complexity and use across different specialties leading to a higher implementation burden. However, most EHRs are already capable of recording staging for cancer.
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Submitted by suchen on
This data element has…
This data element has support from the HL7® FHIR® CodeX™ Accelerator community. CodeX supported FHIR data standards for cancer, genomics and cardiovascular health have a rapidly growing footprint of traction and adoption. The CodeX community is rapidly growing its membership, with invested Member leaders driving implementation-focused use case pilots forward.
The Disease Trend data element-related exchange is utilized in the CodeX EHR Endpoints for Cancer Clinical Trials Use Case by leveraging the minimal Common Oncology Data Elements (mCODE) Implementation Guide. Pertinent links for mCODE, and mCODE’s real world adoption and traction include:
This data element is important to the CodeX “ICAREdata” Use Case: EHR Endpoints for Cancer Clinical Trials: https://confluence.hl7.org/display/COD/EHR+Endpoints+for+Cancer+Clinical+Trials
This use case aims to capture high quality clinical treatment data in electronic health records (EHRs) to enable oncology research. There are 5 key partners, including government, research, and industry, involved in the use case. This prospective use case pilot is currently active at 7 health sites as part of 11 clinical trials.
This data element is also referenced to by the CMS’s Enhancing Oncology Model (EOM), which leverages mCODE for data submissions to CMS. The USCDI Disease Trend data element correlates to the “Current Clinical Status Trend” noted in EOM.