Submitted By: Laurie P. Whitsel / American Heart Association/Physical Activity Alliance | |
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Data Element Information | |
Use Case Description(s) | |
Use Case Description | Providers typically capture and share information about physical activity in the same manner as information about other lifestyle factors such as smoking and substance use. Clinicians assess a patient’s level of physical activity against the Physical Activity Guidelines for Americans based on age and may drive interventions such as counselling or referral. Physical activity level can also be trended over time to help assess whether a patient’s levels are improving or declining. Clinical systems share these measures as part of the referral process and as part of patient record transfers. The Physical Activity Guidelines for Americans call for the capture of two measures – minutes/week of moderate to vigorous aerobic physical activity and days per week of muscle-strengthening activity. This proposal follows the literature-validated approach of splitting the first measure into two components of days/week and minutes/day, which patients have an easier time estimating and therefore produces a value more reflective of their actual aerobic activity level. Device data, such as step counts and heart rate information, can sometimes support Exercise Vital Sign measures where patients have access to devices. However, further research and validation are necessary to integrate those kinds of measurements into assessment, prescription, referral and patient follow-through. The page at the link below provides more detailed support for the importance of capturing and sharing physical activity information, including literature references. |
Estimate the breadth of applicability of the use case(s) for this data element | Per the US Physical Activity Guidelines, practitioners should capture and assess this element for all patients beginning at the age of 3 years. This equates to hundreds of millions of patients and about a million physicians, nurses, and other clinicians. |
Link to use case project page | https://build.fhir.org/ig/HL7/physical-activity/background.html#physical-activity-and-health |
Use Case Description | Public health, payers, clinicians, and others have a significant interest in assessing the level of aerobic and muscle-strengthening physical activity across patient populations, given the correlation between physical activity levels and patient health outcomes. Systems may report physical activity levels as patient health measures or as part of public health surveillance on an identified or de-identified basis. This type of reporting is not currently common standard of practice but is growing to inform the relationship between physical activity and patient outcomes and improve physical activity public health surveillance across the US population. When clinicians have identified a deficiency in a patient’s physical activity level, the clinician may refer the patient to the appropriate professional for interventions to help improve or sustain their physical activity levels. In such cases, clinical systems may communicate the physical activity measures to payers to support reimbursement for services and to service providers to provide an initial baseline for evaluation. Patients may also regularly capture the measures and share them with ordering providers, service providers, and-or payers to monitor progress. |
Estimate the breadth of applicability of the use case(s) for this data element | Approximately 75% of the U.S. population is inactive or otherwise do not meet the Physical Activity Guidelines. This includes about 75% of school-age children (83% of adolescents) who do not meet the recommended levels of physical activity. For adults 65 years and older, more than 86% do not meet the Guidelines. While not all would qualify for intervention, it is important to move toward standardizing exchange of this data element across health systems, payers, service providers and public health surveillance to optimize patient health outcomes. |
Link to use case project page | https://health.gov/healthypeople |
Healthcare Aims |
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Maturity of Use and Technical Specifications for Data Element | |
Applicable Standard(s) | The following LOINC codes correspond to components of the proposed measures: 89555-7 – Physical Activity – Days/Week 68516-4 – Physical Activity – Minutes/Day 82291-6 – Physical Activity – Muscle-Strengthening For the overall minutes/week measure, there is a standard LOINC code 89574-8 – Exercise Vital Sign that groups the Days/Week and Minutes/Day component, however it does not actually support capturing the calculated Minutes/Week component, even though the submitter of the code (Kaiser Permanente) makes regular use of the calculated value. HL7 will work with Kaiser and Regenstrief to either allow the existing ‘panel’ code to capture the calculated days/week measure or add an additional component that supports the calculation, making it easier to query for patients outside guideline without requiring client-side calculation. http://loinc.org/89555-7 http://loinc.org/68516-4 http://loinc.org/82291-6 http://loinc.org/89574-8 |
Additional Specifications | The Physical Activity FHIR implementation guide is going to ballot in the 2023-May cycle and HL7 should published it in Fall, 2023. HL7 hosts the draft continuous integration build version here: https://build.fhir.org/ig/HL7/physical-activity. |
Current Use | In limited use in production environments |
Supporting Artifacts |
The two components of the Exercise Vital Sign are part of the 2015 Certification Companion Guide on Social, psychological, and behavioral data (Paragraph (a)(15)(v)). A sizable portion of the U.S. EHR population has voluntarily certified to these criteria. Of the few healthcare systems that collect physical activity data, Kaiser Permanente is the largest system. Kaiser Permanente insures over 12 million people. Utilizing the Exercise Vital Sign, it is asked at every outpatient encounter with a healthcare provider. During 2020, there were over 31 million scheduled visits, which suggests this measure is quite extensively used each year. https://about.kaiserpermanente.org/who-we-are/annual-reports/2020-annual-report; https://bjsm.bmj.com/content/55/19/1099 |
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 |
There are about 150 EHR systems that have met the certification criteria for §170.315(a)(15) Social, Psychological, and Behavioral Data. This represents about 30% of the commercially available EHR systems voluntarily including this into their systems, suggesting a significant interest in the wider adoption of this standard. These criteria include two questions regarding physical activity like what we are proposing. If we consider the use of the Exercise Vital Sign we propose, in the Kaiser Permanente system, the Exercise Vital Sign is asked at every care visit in their network of over 700 medical offices and other healthcare facilities. That represents extensive use of exchanging data between the various healthcare facilities, as well as to patients. Other healthcare systems, such as Intermountain Health, use the Physical Activity Vital Sign (a similar questionnaire as the Exercise Vital Sign) within their EHR at their 225 medical offices. Furthermore, Prisma Health in Greenville, SC has twenty medical offices that participate in a physical activity assessment and referral program, Exercise is Medicine – Greenville. Staff screen participants for physical activity using the Physical Activity Vital Sign recorded into the EHR system. Their systems exchange the information with local YMCA organizations and patients. These are just examples of health systems where organization are integrating the data element into their standard of care. https://about.kaiserpermanente.org/who-we-are/annual-reports/2020-annual-report; https://intermountainhealthcare.org/annual-report-2020/healing#staying-fit; https://eimgreenville.org/ |
Potential Challenges | |
Restrictions on Standardization (e.g. proprietary code) | The base components of the measure are all freely available LOINC codes and we do not anticipate an issue in either updating an existing LOINC code or introducing a new one to capture the total minutes/week measure. There are other measures that are used in parts of healthcare to assess physical activity, including the Rapid Assessment of Physical Activity and Physical Activity Vital Sign which were reviewed in a 2018 AHA Scientific Statement . However, based on a literature scan as well as an HL7-convened expert group, it seems that the Exercise Vital Sign is the most appropriate and widely used measure and is an appropriate foundation to drive increased standardization. |
Restrictions on Use (e.g. licensing, user fees) | None |
Privacy and Security Concerns | This information could fall under the banner of personally identifiable healthcare information under HIPAA if captured in a healthcare setting, though it has a lower sensitivity level than most healthcare data. If captured and shared outside of a healthcare setting (e.g., on a personal device or shared between a patient and a personal trainer), there would be no HIPAA restrictions. |
Estimate of Overall Burden | Nearly all patients can estimate these values and the effort should require minimal time (~30 seconds) to report either by questionnaire or in conversation with a practitioner. Clinicians would typically gather this information as part of the same workflow as other lifestyle measures such as smoking and substance use. Where a patient engages in ongoing monitoring, it would typically only require reporting one measurement per month. At present, devices are providing supporting data such as heart rates, step counts, move minutes, exercise modality, etc. However, there is opportunity for the device data reporting to be more precisely congruent with Physical Activity Guidelines recommendations. EHR implementation would build on existing support for reading and writing Observation-based data and would fit into existing standards-based capture of lifestyle information. For those systems that already adhere to the optional certification criteria, it would only mean introducing the one new strength-based measure, which should fit into the same workflow, user-interface, and data exchange code. |
Other Implementation Challenges | Because the patients report and estimate the values, accuracy can vary. However, high accuracy is not necessary. Precision within 20-30% is sufficient for determining whether intervention is necessary or appropriate. Eventually, device data may be an important supplement or affirmation of self-reported data. This information is rarely culturally sensitive, though some patients may feel reluctant to share their information. |
Assessments of a health-related matter of interest, importance, or worry to a patient, patient’s family, or patient’s healthcare provider that could identify a need, problem, or condition.
Data Element |
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Physical Activity – Minutes/week
Description
For an average week in the last 30 days, how many minutes per week did the patient engage in moderate to vigorous exercise (like walking fast, running, jogging, dancing, swimming, biking, or other activities that cause a light or heavy sweat)? |
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