Narrative patient data relevant to the context identified by note types.

Data Element
Follow-Up
Description

Follow-up after interventions will assess the efficacy of different treatment modalities as well as potential post-treatment complications that can help inform clinical decision making.
Submitted By: Kevin Jung / University of California, San Francisco Breast Cancer Center
Data Element Information
Use Case Description(s)
Use Case Description For oncology, follow-up will include recurrence with branching logic (if yes, distant or local). Cancer recurrence rates are essential for understanding the performance and order of intervention, and is the bedrock of real world data. With it, we can transition to a learning health care environment.
Estimate the breadth of applicability of the use case(s) for this data element Level 2 – elements pertain to most or all patients, providers or requestors.
240 stakeholders
Link to use case project page https://www.fda.gov/science-research/advancing-regulatory-science/source-data-capture-electronic-health-records-ehrs-using-standardized-clinical-research-data
Use Case Description Follow up applies to any clinical intervention.
Estimate the breadth of applicability of the use case(s) for this data element Any healthcare provider within the United States.
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) ICD-10 and SNOMED CT

ICD-10 : https://www.cms.gov/Medicare/Coding/ICD10
SNOMED CT: https://www.snomed.org/
Additional Specifications FHIR R4 Implementation Guide
http://build.fhir.org/ig/HL7/genomics-reporting/StructureDefinition-followup-recommendation-mappings.html
Current Use This data element has been used at scale between multiple different production environments to support the majority of anticipated stakeholders
Supporting Artifacts Level 2 – at scale, or in more widespread production use (routinely collected already) on several different EHR/HIT systems.

1. Food and Drug Administration. Electronic Source Data in Clinical Investigations. fda.gov. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/electronic-source-data-clinical-investigations. Published September 2013. Accessed May 1, 2019.
2. 111th Congress of the United States of America. H.R.3590: Patient Protection and Affordable Care Act. congress.gov. https://www.congress.gov/bill/111th-congress/house-bill/3590. Published March 23, 2010. Accessed May 1, 2019.
3. Food and Drug Administration. Centers of Excellence in Regulatory Science and Innovation (CERSIs). fda.gov. https://www.fda.gov/science-research/advancing-regulatory-science/centers-excellence-regulatory-science-and-innovation-cersis. Published June 9, 2018. Accessed May 1, 2019.
4. CFR - Code of Federal Regulations Title 21 Part 11. fda.gov. https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfcfr/CFRSearch.cfm?CFRPart=11. Accessed May 1, 2019.
5. Food and Drug Administration. Computerized Systems Used in Clinical Investigations: Guidance for Industry. fda.gov. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/computerized-systems-used-clinical-investigations. Published May 2017. Accessed May 2019.
6. Food and Drug Administration. Use of Electronic Health Record Data in Clinical Investigations. fda.gov. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/use-electronic-health-record-data-clinical-investigations-guidance-industry. Published July 2018. Accessed May 1, 2019.
7. US Department of Health and Human Services, Asst. Secretary of Planning and Evaluation. Patient-Centered Outcomes Research Trust Fund. aspe.hhs.gov. https://aspe.hhs.gov/patient-centered-outcomes-research-trust-fund. Published November 23, 2015. Accessed May 1, 2019.
8. Wrenn JO, Stein DM, Bakken S, Stetson PD. Quantifying clinical narrative redundancy in an electronic health record. J Am Med Inform Assoc . 2010;17(1):49-53. doi:10.1197/jamia.M3390.
9. Siegler EL, Adelman R. Copy and Paste: A Remediable Hazard of Electronic Health Records. Am J Med. 2009;122(6):495-496. doi:10.1016/j.amjmed.2009.02.010.
10. Kalra D, Schmidt A, Potts H, Dupont D, Sundgren M, De Moor G. Case Report from the EHR4CR Project—A European Survey on Electronic Health Records Systems for Clinical Research. Health Connections. 2011;1(2):108-113.
11. Retrieve Form for Data Capture - IHE Wiki. wiki.ihe.net. https://wiki.ihe.net/index.php/Retrieve_Form_for_Data_Capture. Published July 20, 2017. Accessed May 13, 2019.
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.

1. Food and Drug Administration. Electronic Source Data in Clinical Investigations. fda.gov. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/electronic-source-data-clinical-investigations. Published September 2013. Accessed May 1, 2019.
2. 111th Congress of the United States of America. H.R.3590: Patient Protection and Affordable Care Act. congress.gov. https://www.congress.gov/bill/111th-congress/house-bill/3590. Published March 23, 2010. Accessed May 1, 2019.
3. Food and Drug Administration. Centers of Excellence in Regulatory Science and Innovation (CERSIs). fda.gov. https://www.fda.gov/science-research/advancing-regulatory-science/centers-excellence-regulatory-science-and-innovation-cersis. Published June 9, 2018. Accessed May 1, 2019.
4. CFR - Code of Federal Regulations Title 21 Part 11. fda.gov. https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfcfr/CFRSearch.cfm?CFRPart=11. Accessed May 1, 2019.
5. Food and Drug Administration. Computerized Systems Used in Clinical Investigations: Guidance for Industry. fda.gov. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/computerized-systems-used-clinical-investigations. Published May 2017. Accessed May 2019.
6. Food and Drug Administration. Use of Electronic Health Record Data in Clinical Investigations. fda.gov. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/use-electronic-health-record-data-clinical-investigations-guidance-industry. Published July 2018. Accessed May 1, 2019.
7. US Department of Health and Human Services, Asst. Secretary of Planning and Evaluation. Patient-Centered Outcomes Research Trust Fund. aspe.hhs.gov. https://aspe.hhs.gov/patient-centered-outcomes-research-trust-fund. Published November 23, 2015. Accessed May 1, 2019.
8. Wrenn JO, Stein DM, Bakken S, Stetson PD. Quantifying clinical narrative redundancy in an electronic health record. J Am Med Inform Assoc . 2010;17(1):49-53. doi:10.1197/jamia.M3390.
9. Siegler EL, Adelman R. Copy and Paste: A Remediable Hazard of Electronic Health Records. Am J Med. 2009;122(6):495-496. doi:10.1016/j.amjmed.2009.02.010.
10. Kalra D, Schmidt A, Potts H, Dupont D, Sundgren M, De Moor G. Case Report from the EHR4CR Project—A European Survey on Electronic Health Records Systems for Clinical Research. Health Connections. 2011;1(2):108-113.
11. Retrieve Form for Data Capture - IHE Wiki. wiki.ihe.net. https://wiki.ihe.net/index.php/Retrieve_Form_for_Data_Capture. Published July 20, 2017. Accessed May 13, 2019.
Potential Challenges
Restrictions on Standardization (e.g. proprietary code) None
Restrictions on Use (e.g. licensing, user fees) None
Privacy and Security Concerns A patient’s follow-up information is protected by HIPAA.
Estimate of Overall Burden None
ONC Evaluation Details
Each submitted Data Element has been evaluated based on the following criteria. The overall Level classification is a composite of the maturity based on these individual criteria. This information can be used to identify areas that require additional work to raise the overall classification level and consideration for inclusion in future versions of USCDI
Criterion #1
Maturity - Current Standards		 Level 0 - Data element is not represented by a terminology standard or SDO-balloted technical specification or implementation guide.
Criterion #2
Maturity - Current Use 		Level 0 - Data element is captured, stored, or accessed in limited settings such as a pilot or proof of concept demonstration.
Criterion #3
Maturity - Current Exchange		 Level 0 - Data element is electronically exchanged in limited environments, such as connectathons or pilots.
Criterion #4
Use Case(s) - Breadth of Applicability		 Level 0 - Use cases apply to a limited number of care settings or specialties, or data element represents a specialization of other, more general data elements.
Evaluation Comment This is a subset overlap of existing "Progress Note" and "Outpatient Note"

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