Having a standardized way of measuring patient physical activity - and sharing those measurements - is an essential step to improving physical activity levels, both at an individual and at a population level. Patients, care-givers, and Practitioners need standard measures to:

• Consistently evaluate whether a patient's activity levels are adequate for good health.
• Monitor trends to determine whether activity levels are improving (particularly in response to an intervention) or possibly declining (e.g. due to a health condition or other intervention).
• Allow coordination of care with a shared understanding of activity level between clinicians, patients and community-based service providers who can help patients assume a more physically active lifestyle and stay motivated.
• Form a basis for researchers interested in the correlation between physical activity level and health outcomes, as well as which interventions are most effective in boosting physical activity levels and associated outcomes.
• Allow de-identified information to flow into national or regional surveillance systems, such as public health. This information can then inform programming, evidence-based policy, and funding to address physical activity level challenges within certain communities or demographics.
• Support evidence-based remuneration of community-based physical activity professionals who support at risk patients in improving their activity levels.

This page describes standards for representing observations about a patient with respect to their level of physical activity as well as supporting observations that provide additional detail and evidence for those higher-level observations.

Base Measures

The foundational step in improving physical activity levels is having an agreed measure consistently used across EHRs to capture a patient's level of physical activity. There are a wide variety of different types of physical activity and numerous different ways of capturing what activities were performed, and varying granularities with which the data can be captured.

While fine-grained and detailed records (e.g. exactly which type of exercise was performed, which muscle groups were activated, how many repetitions were performed, how many intervals were done, etc.) are important for certain types of therapy and for research purposes, they are too complex and onerous for wide-spread use and are not easily evaluated to assess whether "this patient is sufficiently active to maintain good health". This is not to suggest that fine-grained measures should not be captured and shared, merely that they are currently outside the scope of interoperability intended to be fostered by this implementation guide.

This guide therefore mandates a slightly modified version of the very simple Exercise Vital Sign (LOINC 89574-8 ) as the primary measure of patient physical activity level for exchange and evaluation. The background page provides details on the evidence that supports this measure as accurate and appropriate for evaluating how well a patient meets guidelines for physical activity.

Exercise Vital Sign (EVS) is a measure used in healthcare to assess a patient's physical activity level. This measure is often taken during routine medical visits in the same manner as blood pressure, heart rate, or temperature. The EVS consists of two questions:

• For an average week in the last 30 days, how many days per week did you engage in moderate to vigorous exercise (like walking fast, running, jogging, dancing, swimming, biking, or other activities that cause a light or heavy sweat)?
• On those days that you engage in moderate to vigorous exercise, how many minutes, on average, do you exercise?

These two questions correspond to the LOINC codes 89555-7 and 68516-4. In this implementation guide, there are profiles to capture the answers to each of these questions - the days-per-week and min-per-day profiles. (Examples of Observations that comply with these two profiles can be found here and here.)

While these two questions are logically part of a single overall 89574-8 observation, this guide does not require the capture or sharing higher-level grouping observations that link the answers to the two key questions.

In addition, this guide captures two additional measures:

• The product of the two Exercise Vital Sign (EVS) measures, giving an average amount of moderate to vigorous physical activity in minutes/week (and captured using LOINC code 82290-8)
• An indication of the frequency of strength-based exercises a patient has performed, expressed as days/week (and captured using LOINC code 82291-6)

While the first of these is theoretically redundant with the two EVS measures, this calculated minutes/week measure is the one that is actually compared against national guidelines to determine whether a patient has adequate physical activity or not. As such, having it explicitly captured and stored allows for easier searching, trending and diagnosis. It is a derived measure.

The second measure allows evaluation of the patient against guidelines for muscle-strengthening activity.

NOTE: The physical activity captured by these measures is not limited to 'leisure' type activities such as jogging and swimming. Physical activity during work (e.g. heavy lifting, manual labor), as part of travel (e.g. commuting by bicycle), or at any other portion of the individual's day qualifies so long as it meets the "muscle-strengthening" or "moderate to vigorous/strenuous" physical activity categories.

This full set of measures corresponds with the recommendations for data sharing as represented in version 4 of the US Standards for Data Interchange (USCDI v4). Further information can be found in the USCDI Physical Activity data element.

Supporting Measures

While it is certainly possible for patients and their caregivers to estimate their average days/week and minutes/day of moderate to high-intensity exercise, relying exclusively on estimates is not necessarily ideal. Therefore, capturing additional information about physical activity can be helpful. This information may assist the patient in the creation of their estimates. It can also be used to provide clinicians and exercise professionals with more granular information to provide better insight into the patient's current exercise regime. Potential supplemental measures include:

• Step counts,
• Heart rate measurements,
• Daily activity logs,
• Others?

However, there are challenges with these measures. Continuous measures that capture heart rates on a per-minute or even a per-second basis can create an immense load of data that most clinical systems will not be able to (or at least wish to) manage. As a result, average measures are more useful. At the same time, an average heart rate over the course of a day is not terribly helpful either. 20 minutes of elevated heart-rate due to exercise simply blends in and becomes difficult to distinguish. In the same way, a total count of 20,000 steps per day indicates a certain level of activity. However, whether they constitute "moderate to vigorous" exercise is hard to determine. The same count of steps could represent an hour of jogging, or a day spent pacing while talking on the phone. Both are better than sitting, but only one would count as "moderate to vigorous" exercise.

For these reasons, this implementation guide places limits on the types of supporting measurements systems are expected to share. Systems are free to share raw measures and more fine-grained data if they choose, but there is no expectation within this implementation guide for systems to support sharing information beyond that described below - and even support for these supplemental data elements are optional.

An additional consideration is that capture of steps, heart rate, or even daily electronic activity logs requires that patients have access to electronic devices to capture such measurements. This will not be possible for all patients. Therefore, systems SHOULD NOT set any requirements for the inclusion of these finer-grained measures unless steps have been taken to eliminate patient accessibility barriers.

Criteria for Inclusion

In this first release of the implementation guide, an initial 'starting' set of supporting measures have been identified that were judged as meeting the right balance of considerations including:

• The measure is well-defined and understood, and ideally has a standardized code.
• Systems commonly capture the measure.
• The measure is useful in either supporting the determination of the primary measure or in providing appropriate care.
• The measure is one that can be shared without overloading systems or patients with volume.
• For manually captured measures, the measure is understandable for patients and realistic for them to track.

Not all these factors are true for all of the measures, but most must hold true for the measure to have made this first cut. Additional supporting measures are likely to be introduced in future versions of the IG. Suggestions via the change request mechanism are welcome.

Modeling Approach

The selected measures fall into two categories - activity-based measures and time-period-based measures. Rather than defining a separate profile for each measure, profiles are defined for each category, because the behavior is largely the same for each measure within the category. Only the Observation codes, allowed data type for response and unit of measure or response value set are different from measure to measure. Tables below list these varying parts. Eventually, computable ObservationDefinitions will be created for each measure once the FHIR tooling supports using these as part of the validation process.

Regardless of category, a common set of characteristics are associated with each measure:

• Measure Name - The informal name for the measure as it is used in this IG. This may differ somewhat from the formal name of the specified LOINC or other measurement code. It also reflects the restrictions on use (e.g. units, frequency of capture, etc.) that apply to its use within this IG.
• Code - This is the formal code that SHALL be used by systems compliant with this IG when sharing the measure. Implementers can also use other codes with equivalent meaning as extra repetitions, but the one specified in the table is required.
• Unit/codes - If specified, this will either be the UCUM unit of measure that SHALL be used if one is specified or the value set of codes that must be drawn from. For units, a fly-over provides the English meaning of the unit. For codes, a hyperlink will take the reader to the content for the value set and a fly-over will provide the canonical URL.
• Reporter - This indicates what type of user will generally be responsible for capturing this type of measure. This IG differentiates between two different types of users:
  • Patients (Pat.) encompasses both the individual whose physical activity is being managed/assisted as well as friends, relatives or others acting in their personal relationship capacity to assist the patient. (i.e. patient-captured measures include those recorded by parents, spouses, neighbors, etc.). This means the performer of the observation would be either Patient or RelatedPerson.
  • Providers (Prov.) are anyone working professionally delivering healthcare related services. This includes licensed healthcare professionals such as nurses, clinicians, and physiotherapists. However, it also covers individuals who might not be licensed such as personal trainers. This type of reporter would mean that the performer of the observation would be a Practitioner or PractitionerRole.
  The absence of a 'Y' in the column of a particular type of reporter does not mean this type of Observation cannot be performed by that type of individual, merely that it would be unusual or uncommon. It also means that systems focused on supporting data capture by that type of individual (Patient-engagement systems for patient-reported and Care Manager and Service Provider systems for provider-reported) would not typically support capturing observations not associated with their target user type. That said, all such systems SHOULD support receiving and storing all supporting information observations.
• Mechanism - The means by which the performer makes the Observation. There are two options:
  • Device (Dev.) observations will typically require some sort of hardware device to capture the value. This might be a small device such as a pedometer or watch, or a large device such as a bike or treadmill. The fact the measured value is reported by a device does not necessarily mean the data is electronically generated by the device. A patient or clinician might transcribe it. For example, an exercise bike might indicate the number of calories burned and that value is then recorded by a practitioner or patient. Device values such as maximums or averages might also not be directly calculated by the device that measures the raw parameter but might instead be calculated by intermediary devices such as a smart phone or personal computer. If the raw data comes from a device, the measurement is still considered device-based. Device-based observations SHOULD include information about the source device if the device does the reporting to allow tracking of when measurements come from the same or different devices (as a change in device might explain a change in measurement).
  • Manual (Man.) observations are directly made by the patient or by someone observing and interacting with the patient.
• Comparison Basis indicates if and how observations of this type will be evaluated by care providers
  • Progress indicates that there is no 'norm' or 'target' for the measure, but that the pattern of new measurements for a patient can be compared to prior measurements to see whether a patient is 'improving'. E.g. Taking more steps, burning more calories, etc.
  • Variation indicates that there is a 'norm' or 'target' for the measure, though it might vary by age, gender or other factors. A patient can be evaluated in terms of whether their measurement is under or over that norm and how far away from it they are. Progress can also be evaluated for such measures in terms of whether the patient is getting closer to the norm over time
  • N/A indicates that the measure is not suitable for comparison.
• Notes are additional comments about the utility or applicability of the measure.

Activity-based Measures

These are measures that apply to the period over which a patient engages in some relatively contiguous period of enhanced physical activity - a walk, a run, a swim, a period of weightlifting, etc. The time boundaries of the activity might be inferred (e.g. a device detects an increased step pace or heart rate) or could be manually determined by the reporter of the measure(s). Each 'activity' could result in all, a subset, or only one of these measures being captured. (In some cases, no measures might be captured, but in that case, the activity typically wouldn't be reported at all.)

Each of these measures is conveyed using the Activity Measure profile. In addition, these measures might be grouped together under a 'group' Observation that complies with the Activity Group profile. All observations collected beneath the group are considered to be associated with the same physical activity 'occurrence'.

Measure Name	Code	Unit	Reporter		Mechanism		Comparison	Notes
			Pat.	Prov.	Dev.	Man.
Activity performed (walk/run/bike/swim/...)	73985-4 - Exercise Activity	coded	Y			Y	N/A	Allows providers to understand types of muscle groups activated and engage in discussion about what's working and what isn't.
Activity duration	55411-3 - Exercise duration	min	Y	Y	Y	Y	N/A	If not specified, can be inferred by summing the two measures below (if present)
Minutes of moderate physical activity per activity	77592-4 - Moderate physical activity	min	Y			Y	Progress	Intensity level is subjective, but key to primary measure
Minutes of vigorous physical activity per activity	77593-2 - Vigorous physical activity	min	Y			Y	Progress	Intensity level is subjective, but key to primary measure
Peak activity heart rate	55425-3 - Mean Heart rate in Unspecified Time	/min	Y	Y	Y		Progress	Good proxy for intensity. More reliable than 'peak' rate.
Peak activity heart rate	55426-1 - Maximum Heart rate in Unspecified Time	/min	Y	Y	Y		Progress	Useful to monitor for change. Supplements ‘zone’ information in better understanding intensity. Particularly important in terms of supervised activities. Devices may produce spurious results for maximums, so some filtering may be necessary.
Calories per activity	55424-6 - Calories burned in Unspecified Time, Pedometer	kcal	Y	Y	Y		Progress	Measures are dependent on the device knowing height/weight, so without personalization may be less precise. Can vary from device to device. Useful to show progress and communicate with patients.
Experience of Activity	Experience - Experience of Activity	Feeling Scale	Y			Y	Progress	Level of positive or negative experience of an activity has a significant impact on a patient's long-term adherence to physical activity regimes. This code will be formally proposed to LOINC after testing and confirmation of utility.

Time-based Measures

These measures reflect values summed or averaged over a time period - typically a day, though some might cover longer periods. The period might be reflected in the definition of the code or in the units used for the measure. Measures that are calculated over a period longer than a day will have a start and end date specified in Observation.effectivePeriod indicating the period over which they are calculated.

Each of these observations also has an optional component that indicates the percentage of time over which the measure was calculated for which the device that captured the raw measurements was actually active. This can help evaluate the validity of the measure. For example, a daily step-count where the pedometer was only worn for an hour is likely not an accurate reflection of the patient's total steps for the day.

Each of these measures is conveyed using the Time-Based Measure profile.

Measure Name	Code	Unit	Reporter		Mechanism		Comparison	Notes
			Pat.	Prov.	Dev.	Man.
Daily Step Count	41950-7 - Number of steps in 24 Hours, Measured	/d	Y		Y		Progress	This measure is problematic for patients with lower mobility issues. However, it is widely used and well understood. Comparison across devices is poor, so primarily useful for general targets and comparison within the same device.
Peak daily heart rate	8873-2 - Maximum Heart rate in 24 Hours	/min	Y	Y	Y		Progress	Useful to monitor for change.
Average resting heart rate	40443-4 - Heart rate - resting	/min	Y	Y	Y		Variation	Useful for evaluation of recovery. Unusually high or low may be valuable for diagnostic purposes. Ideally calculated over a longer period (e.g. 1 week)
Calories per Day	41979-6 - Calories burned in 24 Hours, Calc	kcal/d	Y	Y	Y		Progress	This measure is dependent on the device knowing height and/or weight (depending on type of activity), so without personalization this measure may be less precise. As well, estimated calories can vary from device to device. However, comparing measures made with the same device is useful to show progress and set targets. This measure is often 'meaningful' to patients. However, it can't easily be used to determine exertion levels or duration and thus can't really be used to estimate the exercise vital sign.

The relationship between intermediate measures and base measures is not exact. I.e. the sum of all the "per activity" moderate and vigorous exercise minutes can't necessarily be added up and averaged to calculate the average days per week or minutes per day. Calories or steps and activity duration can't (yet?) be converted to minutes of moderate to vigorous exercise. Also, in determining their overall averages, a patient may include exercise that is not supported by a fine-grained measurement or might exclude device data they deem erroneous. (E.g. steps logged when the device was left sitting on the dryer.) The purpose of the supporting measurements is to assist the patient or caregiver in making their estimates as accurate as possible and to assist practitioners in understanding more about the nature and timing of the patient's exercise.

Device-based Measures

This guide does not define data standards for the raw point-in-time device-based data. HL7 has a Personal Healthcare Devices that provides a mechanism for implementers to expose raw device measurements as FHIR. In many cases, it may be simpler to leverage the Apple HealthKit, Android Fit or similar APIs to access the fine-grained measurements in order to determine the relevant averages.

Additional Measures

This guide does not define all types of observations that may be of interest to physical activity professionals. Certain lab tests, vital signs, details on functional limitations, etc. might also be helpful to be shared between care managers, patients and physical activity service providers. Expectations for the standardized exchange of most of these other types of observations is covered under US Core or some of the other 'relevant' implementation guides listed on the home page. Systems are free to support and share such additional information using the same exchange patterns defined in this IG. These observations (and in fact, any relevant records that support the 'category' element) may also be flagged with a category of "Physical Activity" if that is useful in managing access to information.