Description (*Please confirm or update this field for the new USCDI version*)
Type of work of a person. (e.g., infantry, business analyst, social worker)
Applicable Vocabulary Standard(s)
Applicable Standards (*Please confirm or update this field for the new USCDI version*)
Occupational Data for Health, version 20201030
Submitted By: Nedra Garrett
/ CDC
Data Element Information
Rationale for Separate Consideration
The concept of Job encompasses multiple unique, independent data elements and so should be its own Data Class.
Use Case Description(s)
Use Case Description
--Support public health electronic case reporting (eCR), analyses, and response by providing more timely and complete information for public health activities. Used to understand and quantify occupation (and industry)-related exposures and risks. Could reduce or eliminate the need for limited-use questions, such as ‘Are you a healthcare worker’ or ‘Are you a food handler’. Provides information for public health reporting, investigation, and response. approximately one-half of nationally-notifiable conditions would be supported by Job information.
Example 1: locate infectious disease outbreaks and intervene to prevent further illness. Job Industry would identify types of businesses associated with high rates of SARS-CoV-2 infection, e.g., meatpacking and poultry processing. Employer Name and Address would facilitate contact tracing. Job Occupation and Industry could support vaccination monitoring among essential workers.
Example 2: analyze work-related conditions such as silicosis and pesticide poisoning, to identify Industry sectors and Employers for whom interventions are needed to mitigate risk.
eCR program anticipates publication of new IGs (CDA/FHIR) that include ODH Job in Fall 2021 and will be working with EHR vendors to implement in 2022.
--Barry V, Dasgupta S, Weller DL, et al. Patterns in COVID-19 Vaccination Coverage, by Social Vulnerability and Urbanicity — United States, December 14, 2020–May 1, 2021. MMWR Morb Mortal Wkly Rep 2021;70:818–824. http://dx.doi.org/10.15585/mmwr.mm7022e1
--Bonwitt J, Deya RW, Currie DW, et al. COVID-19 Surveillance and Investigations in Workplaces — Seattle & King County, Washington, June 15–November 15, 2020. MMWR Morb Mortal Wkly Rep 2021;70:916–921. http://dx.doi.org/10.15585/mmwr.mm7025a3
Estimate the breadth of applicability of the use case(s) for this data element
Job data are important for public health infectious disease case reporting in all state, local, tribal, territorial jurisdictions and in data shared with CDC. For example, All US States and Washington, DC are funded through CDC’s Division of HIV Prevention, Division of TB Elimination, and Division of STD Prevention flagship Notice of Funding Actions to perform surveillance activities, including collection of these data for surveillance purposes.
Thirty states currently require health care providers to report selected occupational illnesses to a state agency.
1) Collect and use data that address “conditions in the places where people … work … that affect a wide range of health and quality-of life-risks and outcomes,", i.e., work as a social determinant of health (SDOH; https://www.cdc.gov/socialdeterminants/index.htm). Work and health are inextricably related, regardless of whether a condition is work-related: in the U.S., workers spend more than half their waking hours at work.
--Example: A person has a job as a customer service specialist (Job Occupation) at a newspaper publisher and printing business (Job Industry). She sees her primary care provider for respiratory issues. The care provider sees the job information, which prompts them to ask if she works near the newspaper printing operation. She reports that she moved to an office adjacent to the printing operation three months ago. The care provider provides an electronic referral to an occupational medicine specialist who can evaluate whether workplace exposures are causing the patient’s respiratory symptoms.
2) Inform diagnosis and management of illness and injury, management of health in the work environment. Also leverage history built over time: some work-related health conditions can manifest after a long latency.
3) Improve the quality of care by exchange of medical information (transitions of care, referrals, patient summaries, etc.) to provide a more complete and computable picture of factors that may affect the patient’s health. This will also reduce the need for data reentry.
--Example: Job supports collection of self-reported military service information, which can (1) prompt important conversations between a care provider and patient, and (2) can be used to facilitate referrals to the VA and support data-sharing. The HL7 Military Service History and Status FHIR profiles project, sponsored by the VA, is harmonizing with the ODH FHIR IG (and supports additional requirements; https://confluence.hl7.org/display/CGP/Military+Service+History+and+Status+FHIR+Profiles+Project+Page ).
4) Reduce burden by supporting patient-entry/review/update at or prior to registration for adults, e.g., via a patient portal, in-office kiosk or tablet, sharing from a personal health record (PHR). Also for some children per locality: e.g., an area where children may work on a family farm or in a family business.
5) Contribute, potentially, to patient matching algorithms.
6) Standardize Job Occupation, which may already be collected:
--Example: Obstetricians are required to ask a pregnant woman about her current job at the first visit.
--Example: Primary care medical homes (PCMH) are required to record [job] occupation to provide comprehensive care in the primary care setting.
Estimate the breadth of applicability of the use case(s) for this data element
In 2018, approximately 75% of adults age 18 and older had worked in the past 12 months and on average approximately 60% of adults in the U.S. currently are working. Only 5% of adults report that they have never worked. Since work and health are interrelated, most providers involved in direct patient care would potentially benefit from the capture, access, use, and exchange of Job information. Includes:
--209,000 primary care physicians
--many of the 120,000 certified physician assistants and 290,000 licensed nurse practitioners
--many of the 415,000 specialty physicians who are also primarily involved in direct patient care, e.g., those who care for injuries and are faced with return-to-work decisions, such as emergency medicine specialists, orthopedists, physiatrists; those who care for patients with chronic diseases caused by occupational exposures, such as pulmonologists, neurologists, nephrologists, and oncologists.
Collect and use data to reduce health disparities, e.g., patient care aides have lower healthcare access and utilization than clerical workers. 90% of patient care aides are women, and more than half are racial or ethnic minority workers.
--Example: Use linked demographic and standardized job information to tailor resources and information to a patient population. A Federally-Qualified Health Center collected Current Job Occupation as text during registration for one year (more than 27,000 patients). The text data were extracted and coded by public health (not needed with standardized vocabulary), then analyzed with demographic information. Many patients primarily spoke Portuguese and of those patients most of the women were maids or hotel housekeepers and many of the men were construction or maintenance painters. The Health Center updated their intranet site with educational materials, in Portuguese, for painters about lead exposure and for housekeepers about ergonomic hazards and exposure to cleaning agents. This was so popular that they developed additional materials for more of their working patients, including those who speak Spanish. The painters can also be identified for annual blood-lead-level screening. (https://apha.confex.com/apha/141am/webprogram/Paper288596.html ).
--Selden TM and Berdahl TA. COVID-19 and Racial/Ethnic Disparities in Health Risk, Employment, and Household Composition. Health Affairs. 2020. 39:9,1624-1632. https://doi.org/10.1377/hlthaff.2020.00897
Estimate the breadth of applicability of the use case(s) for this data element
In 2018, approximately 75% of adults age 18 and older had worked in the past 12 months and on average approximately 60% of adults in the U.S. currently are working. Only 5% of adults report that they have never worked. Since work and health are interrelated, most providers involved in direct patient care would potentially benefit from the capture, access, use, and exchange of Job information. Includes:
--209,000 primary care physicians
--many of the 120,000 certified physician assistants and 290,000 licensed nurse practitioners
--many of the 415,000 specialty physicians who are also primarily involved in direct patient care, e.g., those who care for injuries and are faced with return-to-work decisions, such as emergency medicine specialists, orthopedists, physiatrists; those who care for patients with chronic diseases caused by occupational exposures, such as pulmonologists, neurologists, nephrologists, and oncologists.
Facilitate access to clinical decision support, e.g., through use of CQL, and reuse of the data for examination of populations, especially those who are underserved.
--Example 2: Job Occupation and Job Industry use to identify patients who need certain vaccinations, screening for exposure to health hazards, and/or screening for early signs of work-related disease, such as chest radiographs for workers in industries with potential for silica exposure.
--Example 3: Job Occupation use (based on the ODH value set) to access lists of tasks, activities, and work contexts available via O*NET OnLine (https://www.onetonline.org/ ).
--Example 4: Job Occupation and/or Job Industry use to identify persons in high-risks types of work. In response to a recommendation from the National Transportation Safety Board (NTSB), two EHR vendors have devised clinical decision support tools for “the evaluation of nontraumatic loss of consciousness episodes or for a diagnosis of epilepsy that will notify providers of the patient’s [job] occupation, such as commercial driver; and remind them to address the occupational and driving Status of the patient” (https://data.ntsb.gov/carol-mainpublic/sr-details/H-18-021 ).
--Example 5: Work Classification and Supervisory Level or Pay Grade uses to support understanding of a patient’s work. Supervisory Level or Pay Grade distinguishes officer versus enlisted position for certain military occupations. Work Classification can be an indicator of access to benefits and financial stability (e.g., self-employed) or can prompt consideration of important voluntary work, such as volunteer firefighter.
Estimate the breadth of applicability of the use case(s) for this data element
In 2018, approximately 75% of adults age 18 and older had worked in the past 12 months and on average approximately 60% of adults in the U.S. currently are working. Only 5% of adults report that they have never worked. Since work and health are interrelated, most providers involved in direct patient care would potentially benefit from the capture, access, use, and exchange of Job information. Includes:
--209,000 primary care physicians
--many of the 120,000 certified physician assistants and 290,000 licensed nurse practitioners
--many of the 415,000 specialty physicians who are also primarily involved in direct patient care, e.g., those who care for injuries and are faced with return-to-work decisions, such as emergency medicine specialists, orthopedists, physiatrists; those who care for patients with chronic diseases caused by occupational exposures, such as pulmonologists, neurologists, nephrologists, and oncologists.
HL7 CDA® R2.1 IG: Consolidated CDA Templates for Clinical Notes; Occupational Data for Health, R1.1 – US Realm. http://www.hl7.org/implement/standards/product_brief.cfm?product_id=522 (Modular template for non-breaking insertion of Job (and/or other ODH sections) for any CDA IG social history section)
HL7 FHIR R4.0.1 Profile: Occupational Data for Health (ODH), R1, STU 1.1. http://hl7.org/fhir/us/odh/STU1.1 (Modular template for non-breaking insertion of Job (and/or other ODH profiles) for any FHIR IG social history section)
--HL7 FHIR R4 IG: Electronic Case Reporting (eCR) – US Realm, R1, STU 1. http://hl7.org/fhir/us/ecr/history.html (also R2, to be published late 2021 and implemented starting in 2022)
IHE Patient Care Coordination (PCC) Technical Framework (TF) Supplement: CDA Content Modules, Revision 2.7 – Trial Implementation. https://www.ihe.net/resources/technical_frameworks/#pcc (Modular template for non-breaking insertion of Job (and/or other ODH sections) for any CDA profile social history section)
Marovich S, Luensman GB, Wallace B, Storey E. Opportunities at the intersection of work and health: Developing the occupational data for health information model. J Am Med Inform Assoc. 2020 Jul 1;27(7):1072-1083. https://doi.org/10.1093/jamia/ocaa070
This data element has been used at scale between multiple different production environments to support the majority of anticipated stakeholders
Supporting Artifacts
Testing and demonstrations for HIMSS Interoperability Showcases 2016-2019 and the PHI Conference Interoperability Showcases in 2016 and 2018 used the IHE Healthy Weight (HW) profile. Involved 3 personal health records, 1 integration engine, 1 public health representative, 1 provider portal, and 1 EHR using a test environment. Deployed in interface engine production product.
Three 2020 NACCHO 360X Interoperability Demonstrations, using the IHE QEDm (FHIR) and CCD (CDA) formats. A PHR and public health representative used a test environment.
Testing and demonstration for HIMSS Interoperability Showcase 2021, 1 EHR implemented.
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
Testing and demonstration for HIMSS and NACCHO 360X Interoperability Showcases has involved 3 personal health records, 1 interface engine, 1 public health representative, 1 provider portal, and 2 EHRs.
Job will be included in the upcoming (fall 2021) public health case reporting (eCR) CDA R3 and FHIR R2 IGs, which CDC will be working with EHR vendors to implement in 2022.
Restrictions on Standardization (e.g. proprietary code)
The value sets for Occupation and Industry suggested in some interoperability standards are the CDC_Census2010 category value sets. However, the new ODH Occupation and Industry value sets assist with self-selection of coded entries that provide detail to support patient care. Crosswalks from ODH to CDC_Census2010 codes are available in the PHIN VADS Hot Topics section. A non-breaking “translation” in CDA or “slice” in FHIR can be used to transmit either or both ODH or CDC_Census2010 values; all relevant HL7 interoperability IGs and IHE interoperability content profiles are being updated accordingly. The translation is in the upcoming public health IGs.
Restrictions on Use (e.g. licensing, user fees)
none
Privacy and Security Concerns
Job is intended to be a part of the medical record and protected as such.
Estimate of Overall Burden
We estimate that it will take approximately 300 hours to implement Job as described in the HL7 EHRS Work and Health Functional Profile and “A Guide for Collection of Occupational Data for Health (ODH).”
Initially, data collection will likely occur primarily via patient self-entry. Based on usability testing of a data collection prototype, initial entry of all ODH (Job, Usual Work, Employment Status and Retirement Date, and Combat Zone Period) takes 5-30 minutes. As with other EHR data classes, such as medications and family history, the opportunity to review previously entered information will be key to reducing the collection burden. Leveraging interoperability standards will also help to minimize the collection burden by sharing the information across systems.
Other Implementation Challenges
The ODH value sets for Occupation and Industry are large, in order to provide recognizable terms. However, keyword text searches can be used to facilitate selection as described in the NIOSH “A Guide to Collection of Occupational Data for Health (ODH).”
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 2 - Data element is represented by a terminology standard or SDO-balloted technical specification or implementation guide.
Criterion #2 Maturity - Current Use
Level 2 - Data element is captured, stored, or accessed in multiple production EHRs or other HIT modules from more than one developer.
Criterion #3 Maturity - Current Exchange
Level 2 - Data element is electronically exchanged between more than two production EHRs or other HIT modules of different developers using available interoperability standards.
Criterion #4 Use Case(s) - Breadth of Applicability
Level 2 - Use cases apply to most care settings or specialties.
NACHC agrees with CDC's comment on harmonizing the term used in CDC NIOSH's ODH framework, to avoid ambiguity, and increase specificity in the type of data and standard to use for capturing occupation.
CSTE strongly supports the inclusion of current industry and occupation as critical data elements. Not every case can be investigated due to high volume of cases, inability to locate the person for an interview or other reasons. Determination of risk of illness, infection or other important exposures at work sites related to occupation and industry is critical to informing public health prevention measures and improving occupational health. An example of this occurred during the COVID-19 pandemic, when it was very difficult to get data on the occupation of persons who were infected or who had serious outcomes, including death, due to COVID-19. Only in retrospect, after performing special studies, did it become clear that health care workers, including home health aides, meatpackers and others had increased risk of infection due to exposures at their workplaces. Having real time information about occupational risk is critical to protecting people at work.
Work is a social determinant of health, and occupation and industry are key terms used together to describe a person’s work. The Occupational Data for Health (ODH) code system includes occupation and industry value sets derived from the federal standard classification systems and was included in the HTI-1 EHR certification rule for representing “occupation” and “occupation industry” (job occupation and job industry in interoperability standards). The current ODH code system includes incomplete and outdated occupation and industry value sets based on federal classification systems from 2012 and 2010, respectively. These classification systems do not necessarily maintain code continuity over time.
NIOSH is updating the ODH code system for occupation and industry, using up-to-date concepts with non-semantic codes cross-walked to the federal classification systems. The new, versionable code system will be complete by late 2024, and will support clinical care, population health and public health uses.
CDC suggests renaming the “Occupation” data element to “Job Occupation” and the “Occupation Industry” data element to “Job Industry.” The concept “Job” can encompass multiple independent data elements for a work position, including Job Occupation and Job Industry. Renaming these data elements would facilitate clear and consistent communication, aligning with data element names used in existing information resources and implementation guides cited in the USCDI submission. This would not represent a change in the definition or other content of these data elements.
NACHC fully supports the CDC-NIOSH ODH model, and believes occupational health is central to understanding patient risk and context in a patient-centered way.
We firmly support the use of the code systems and codes described by CDC-NIOSH and we can further state we are working with 3 clinical organizations using 3 different EHRs to implement these codes in production at this time.
We support all comments of CDC-NIOSH and CSTE.
Please see the attached document, summarizing NACHC's detailed comments on Occupation and Industry
CDC requests that the Job occupation and industry data elements (USCDI V3) be reclassified into a Job data class instead of Patient Demographics.
CDC requests the creation of Job and Usual Work data classes (USCDI V3 and Level 2) as submitted. The existing Work Information data class (Levels 1 and 2) includes data elements that are part of different “themes” (subjects) and are used differently. A Job (a work situation or position, including some volunteer positions) is a different subject than Usual Work (longest-held work). Most of the data elements for job or usual work are related to the respective theme (Job or Usual Work), not the person. This structure is borne out in the way the data elements are configured in interoperability standards and ensures that the data retain meaning and are not confused across themes. Job Occupation and Usual Occupation tie the respective themes to a person.
As data elements characterizing a Job, Usual Work or a person mature, having separate data classes will support data quality and reduce the possibility of the same information being collected in more than one way. For example, this proposed classification scheme could help clarify the variations in Employment Status. A person’s Employment Status (level 1, Work Information data class) is defined by ODH and supported by a value set that facilitates selection of a single entry about the person (mutually exclusive values). Employment, as defined by the Gravity Project (Comment level, SDOH data class), is based on the “type and conditions of employment,” i.e., Job. A person working multiple jobs, or who has retired and taken another job, cannot provide a single entry about themselves using the related value set under development. However, making the distinction between a person’s state of being employed vs conditions of employment within a Job would provide clarity in data collection and use.
CDC requests that the original name for the draft V3 element “Occupation” be used, i.e., “Job Occupation.” Naming the element “Occupation” can and does lead to substantial confusion because an occupation, or type of work, is defined by context. For example, it can refer to a person’s type of work at a job (a work situation or position, including some volunteer positions) or the type of work they’ve performed the longest amount of time, aka Usual Occupation. Other contexts include military occupation and employer-specific occupation (aka job title). Clear and distinct naming will help the data to be useful for both clinical care and public health. “Job Occupation” aligns with the many existing references to this data element, including interoperability standards, other ODH products, and discussions and presentations across a variety of audiences.
CDC encourages ONC to accept this data element in USCDI V3, given its value for clinical care and public health. Substantial work has been done to provide informatics products (ODH) to support its implementation: an information model and vocabulary, how-to guides, and interoperability templates for consistent use in data exchange transactions.
ADDITIONAL SPECIFICATIONS: REPLACE THE CURRENT LANGUAGE WITH THE TEXT BELOW (THE PROPOSED LANGUAGE UPDATES REFERENCES AND STANDARDS TO THEIR LATEST VERSIONS):
HL7 CDA® R2.1 IG: Consolidated CDA Templates for Clinical Notes; Occupational Data for Health, R2.1 – US Realm. http://www.hl7.org/implement/standards/product_brief.cfm?product_id=522 (Modular template for non-breaking insertion of Job (and/or other ODH sections) for any CDA IG social history section)
HL7 FHIR R4.0.1 Profile: Occupational Data for Health (ODH), R1, STU 1.1. http://hl7.org/fhir/us/odh/ (Modular template for non-breaking insertion of Job (and/or other ODH profiles) for any FHIR IG social history section)
Public health case reporting IGs including Job:
HL7 CDA R2 IG Public Health Case Report – the Electronic Initial Case Report (eICR), R2, STU R3 – US Realm. http://www.hl7.org/implement/standards/product_brief.cfm?product_id=436
HL7 FHIR R4 IG: Electronic Case Reporting (eCR) – US Realm, R2, STU 2. http://hl7.org/fhir/us/ecr/
IHE Patient Care Coordination (PCC) Technical Framework (TF) Supplement: CDA Content Modules, Revision 2.8 – Trial Implementation. https://www.ihe.net/resources/technical_frameworks/#pcc (Modular template for non-breaking insertion of Job (and/or other ODH sections) for any CDA profile social history section)
Wallace B, Luensman GB, Storey E, Brewer L. “A Guide to the Collection of Occupational Data for Health: Tips for Health IT System Developers” https://www.cdc.gov/niosh/docs/2022-101/
HL7 EHRS-FM R2: Functional Profile; Work and Health, R1 – US Realm. http://www.hl7.org/implement/standards/product_brief.cfm?product_id=498
Marovich S, Luensman GB, Wallace B, Storey E. Opportunities at the intersection of work and health: Developing the occupational data for health information model. J Am Med Inform Assoc. 2020 Jul 1;27(7):1072-1083. https://doi.org/10.1093/jamia/ocaa070
Additional IHE PCC TF Supplements including Job https://www.ihe.net/resources/technical_frameworks/#pcc :
IHE PCC TF Supplement to Volume 1, CDA Occupational Data Options, Revision 1.1 – Trial Implementation adds Job (and other ODH sections) to:
Cross-Enterprise Sharing of Medical Summaries (XDS-MS)
Exchange of Personal Health Record (XPHR)
Emergency Department Referral (EDR) profiles
IHE PCC TF Supplement: Query for Existing Data for Mobile (QEDm), Revision 2.2 – Trial Implementation
IHE PCC TF Supplement: International Patient Summary (IPS), Revision 1.1 – Trial Implementation
Federal Health Information Model (FHIM), Person Domain. https://fhim.org/
IHE Quality, Research and Public Health (QRPH) TF Supplement: Healthy Weight (HW), Revision 2.5 – Trial Implementation (includes Job) https://www.ihe.net/resources/technical_frameworks/#qrph
HL7 Version 2.9 Messaging Standard – An Application Protocol for Electronic Data Exchange in Healthcare Environments, Normative. (includes Job) http://www.hl7.org/implement/standards/product_brief.cfm?product_id=516. Job is pre-adopted in:
HL7 Version 2.6 IG: Early Hearing Detection and Intervention (EHDI) Results, R1, Normative. http://www.hl7.org/implement/standards/product_brief.cfm?product_id=344
CSTE is very supportive of including work information in USCDI. It is important for assessing the increase in risk for conditions that might be ascribable to industry and occupation. However, specific job title and place of work are distinct variables and should also be collected and included in USCDI v3, including the address and phone number of each place the patient currently works.
Submitted by RUy on
NACHC supports harmonizing the data element name with NIOSH ODH
NACHC agrees with CDC's comment on harmonizing the term used in CDC NIOSH's ODH framework, to avoid ambiguity, and increase specificity in the type of data and standard to use for capturing occupation.