1a. Project Name

Mobile Health App Data Exchange

1b. Project ID

1551

1c. Is Your Project an Investigative Project (aka PSS-Lite)?

Yes

1d. Is your Project Artifact being Reaffirmed or proceeding to Normative directly after being either Informative or STU?

No

1e. Today's Date

1f. Name of standard being reaffirmed

1g. Project Artifact Information

1h. ISO/IEC Standard to Adopt

1i. Does the standard include excerpted text from one or more ISO, IEC or ISO/IEC standards, but is not an identical or modified adoption?

1j. Unit of Measure

2a. Primary/Sponsor WG

Modeling & Methodology

2d. Project Facilitator

Keith Boone

2e. Other Interested Parties (and roles)

US Office of the National Coordinator for Health IT (AllOfUs Health IT standards research sponsor)
US National Institutes of Health, All of Us Research Project
Open mHealth
Audacious Inquiry

2f. Modeling Facilitator

2g. Publishing Facilitator

2h. Vocabulary Facilitator

2i. Domain Expert Representative

2j. Business Requirements Analyst

2k. Conformance Facilitator

2l. Other Facilitators

2m. Implementers

3a. Project Scope

The initial scope of this project is to analyze variation in FHIR data exchanged from mobile health apps and devices for personal health information. Because mobile health apps and devices can convey a wide variety of data including hundreds of different kinds of measurements, this project will first look at a limited scope of data, including vital signs, physical activity, sleep and blood sugar.

These data elements are readily accessible in many mobile health apps and devices. Similar data is often used during treatment of disease affecting cardiovascular, cereberovascular, lower respiratory, and endocryne systems. These diseases are five of the top ten leading causes of death in the US (https://www.cdc.gov/nchs/fastats/leading-causes-of-death.htm) and four out of ten in the world (https://ourworldindata.org/causes-of-death). Thus, they are high priority items to address in this project.

The scope of this project is Universal even though current leadership of the project is US based. We have had participation in project efforts from individuals in the US, Europe and Asia, and who serve markets internationally. We welcome greater international participation in this project.

Attachments

3b. Project Need

There are multiple pathways to obtain personal health data from mobile apps and devices in FHIR. Some of these pathways are shown in the attached Powerpoint diagram and include:

* Proprietary API to FHIR Conversion (via cloud, mobile platform, or direct to device APIs).
* Proprietary to FHIR Conversion via an Intermediate Format (e.g., Open mHealth)
* Direct output in FHIR from a Device Gateway
* Exchange to EHR w/ Output in FHIR generated from an EHR

Each of these pathways can introduce variation due to the encoding of sematic codes describing the measurement, or variations in the way that units are expressed, or in the precision of data exchanged.

Because of the increasing use of personal health devices to augment care, this is of concern because it can introduce variation in personal health data that may be used for diagnosis, treatment and research.

The goal of this project is to determine the degree of semantic and precision variation in these pathways and determine what steps are needed to address this challenge to enable healthcare providers to use personal health device data for diagnosis, treatment and research.

3c. Security Risk

3d. External Drivers

3e. Objectives/Deliverables and Target Dates

1. Promote a FHIR Connectathon track (see https://confluence.hl7.org/display/FHIR/2019-09+Mobile+Health+Data+Exchange) to compare variations in pathways for getting FHIR Data. September and possibly January WGM.
2. Analyze variation and develop a plan to address sources of variation. Such a plan might include development of functional requirements or an implementation guide, but those details are not yet determined.
3. Implement action plan.

3f. Common Names / Keywords / Aliases:

3g. Lineage

3h. Project Dependencies

3i. HL7-Managed Project Document Repository URL:

https://confluence.hl7.org/pages/viewpageattachments.action?pageId=61505681

3j. Backwards Compatibility

No

3k. Additional Backwards Compatibility Information (if applicable)

3l. Using Current V3 Data Types?

3l. Reason for not using current V3 data types?

3m. External Vocabularies

3n. List of Vocabularies

3o. Earliest prior release and/or version to which the compatibility applies

4a. Products

4b. For FHIR IGs and FHIR Profiles, what product version(s) will the profiles apply to?

4c. FHIR Profiles Version

4d. Please define your New Product Definition

4d. Please define your New Product Family

5a. Project Intent

5a. White Paper Type

5a. Is the project adopting/endorsing an externally developed IG?

5a. Externally developed IG is to be (select one)

5a. Specify external organization

5a. Revising Current Standard Info

5b. Project Ballot Type

5c. Additional Ballot Info

5d. Joint Copyright

5e. I understand I must submit a Joint Copyright Letter of Agreement to the TSC in order for the PSS to receive TSC approval.

no

6a. External Project Collaboration

6b. Content Already Developed

6c. Content externally developed?

6d. List Developers of Externally Developed Content

6e. Is this a hosted (externally funded) project?

6f. Stakeholders

6f. Other Stakeholders

6g. Vendors

6g. Other Vendors

6h. Providers

6h. Other Providers

6i. Realm

Universal

7d. US Realm Approval Date

7a. Management Group(s) to Review PSS

FHIR

7b. Sponsoring WG Approval Date

Aug 02, 2019

7c. Co-Sponsor Approval Date

7c. Co-Sponsor 2 Approval Date

7c. Co-Sponsor 3 Approval Date

7c. Co-Sponsor 4 Approval Date

7c. Co-Sponsor 5 Approval Date

7c. Co-Sponsor 6 Approval Date

7c. Co-Sponsor 7 Approval Date

7c. Co-Sponsor 8 Approval Date

7c. Co-Sponsor 9 Approval Date

7c. Co-Sponsor 10 Approval Date

7e. CDA MG Approval Date

7f. FMG Approval Date

Aug 14, 2019

7g. V2 MG Approval Date

7h. Architecture Review Board Approval Date

7i. Steering Division Approval Date

Sep 16, 2019

7j. TSC Approval Date



Version

3

Modifier

Keith W. Boone

Modify Date

Nov 01, 2019 18:20

1a. Project Name

Mobile Health App Data Exchange

1b. Project ID

1551

1c. Is Your Project an Investigative Project (aka PSS-Lite)?

Yes

1d. Is your Project Artifact now proceeding to Normative directly or after being either Informative or STU?

No

2a. Primary/Sponsor WG

Modeling & Methodology

2d. Project Facilitator

Keith Boone

2e. Other Interested Parties (and roles)

US Office of the National Coordinator for Health IT (AllOfUs Health IT standards research sponsor)
US National Institutes of Health, All of Us Research Project
Open mHealth
Audacious Inquiry

3a. Project Scope

The initial scope of this project is to analyze variation in FHIR data exchanged from mobile health apps and devices for personal health information. Because mobile health apps and devices can convey a wide variety of data including hundreds of different kinds of measurements, this project will first look at a limited scope of data, including vital signs, physical activity, sleep and blood sugar.

These data elements are readily accessible in many mobile health apps and devices. Similar data is often used during treatment of disease affecting cardiovascular, cereberovascular, lower respiratory, and endocryne systems. These diseases are five of the top ten leading causes of death in the US (https://www.cdc.gov/nchs/fastats/leading-causes-of-death.htm) and four out of ten in the world (https://ourworldindata.org/causes-of-death). Thus, they are high priority items to address in this project.

The scope of this project is Universal even though current leadership of the project is US based. We have had participation in project efforts from individuals in the US, Europe and Asia, and who serve markets internationally. We welcome greater international participation in this project.

Attachments

3b. Project Need

There are multiple pathways to obtain personal health data from mobile apps and devices in FHIR. Some of these pathways are shown in the attached Powerpoint diagram and include:

* Proprietary API to FHIR Conversion (via cloud, mobile platform, or direct to device APIs).
* Proprietary to FHIR Conversion via an Intermediate Format (e.g., Open mHealth)
* Direct output in FHIR from a Device Gateway
* Exchange to EHR w/ Output in FHIR generated from an EHR

Each of these pathways can introduce variation due to the encoding of sematic codes describing the measurement, or variations in the way that units are expressed, or in the precision of data exchanged.

Because of the increasing use of personal health devices to augment care, this is of concern because it can introduce variation in personal health data that may be used for diagnosis, treatment and research.

The goal of this project is to determine the degree of semantic and precision variation in these pathways and determine what steps are needed to address this challenge to enable healthcare providers to use personal health device data for diagnosis, treatment and research.

3e. Objectives/Deliverables and Target Dates

1. Promote a FHIR Connectathon track (see https://confluence.hl7.org/display/FHIR/2019-09+Mobile+Health+Data+Exchange) to compare variations in pathways for getting FHIR Data. September and possibly January WGM.
2. Analyze variation and develop a plan to address sources of variation. Such a plan might include development of functional requirements or an implementation guide, but those details are not yet determined.
3. Implement action plan.

3i. HL7-Managed Project Document Repository URL:

https://confluence.hl7.org/pages/viewpageattachments.action?pageId=61505681

3j. Backwards Compatibility

No

6i. Realm

Universal

7a. Management Group(s) to Review PSS

FHIR

7b. Sponsoring WG Approval Date

Aug 02, 2019

7f. FMG Approval Date

Aug 14, 2019

7i. Steering Division Approval Date

Sep 16, 2019

Version

2

Modifier

Nathan Botts

Modify Date

Oct 02, 2019 16:23

1a. Project Name

Mobile Health App Data Exchange

1b. Project ID

1551

1c. Is Your Project an Investigative Project (aka PSS-Lite)?

Yes

1d. Is your Project Artifact now proceeding to Normative directly or after being either Informative or STU?

No

2a. Primary/Sponsor WG

Modeling & Methodology

2d. Project Facilitator

Keith Boone

2e. Other Interested Parties (and roles)

US Office of the National Coordinator for Health IT (AllOfUs Health IT standards research sponsor)
US National Institutes of Health, All of Us Research Project
Open mHealth
Audacious Inquiry

3a. Project Scope

The initial scope of this project is to analyze variation in FHIR data exchanged from mobile health apps and devices for personal health information. Because mobile health apps and devices can convey a wide variety of data including hundreds of different kinds of measurements, this project will first look at a limited scope of data, including vital signs, physical activity, sleep and blood sugar.

These data elements are readily accessible in many mobile health apps and devices. Similar data is often used during treatment of disease affecting cardiovascular, cereberovascular, lower respiratory, and endocryne systems. These diseases are five of the top ten leading causes of death in the US (https://www.cdc.gov/nchs/fastats/leading-causes-of-death.htm) and four out of ten in the world (https://ourworldindata.org/causes-of-death). Thus, they are high priority items to address in this project.

Attachments

3b. Project Need

There are multiple pathways to obtain personal health data from mobile apps and devices in FHIR. Some of these pathways are shown in the attached Powerpoint diagram and include:

* Proprietary API to FHIR Conversion (via cloud, mobile platform, or direct to device APIs).
* Proprietary to FHIR Conversion via an Intermediate Format (e.g., Open mHealth)
* Direct output in FHIR from a Device Gateway
* Exchange to EHR w/ Output in FHIR generated from an EHR

Each of these pathways can introduce variation due to the encoding of sematic codes describing the measurement, or variations in the way that units are expressed, or in the precision of data exchanged.

Because of the increasing use of personal health devices to augment care, this is of concern because it can introduce variation in personal health data that may be used for diagnosis, treatment and research.

The goal of this project is to determine the degree of semantic and precision variation in these pathways and determine what steps are needed to address this challenge to enable healthcare providers to use personal health device data for diagnosis, treatment and research.

3e. Objectives/Deliverables and Target Dates

1. Promote a FHIR Connectathon track (see https://confluence.hl7.org/display/FHIR/2019-09+Mobile+Health+Data+Exchange) to compare variations in pathways for getting FHIR Data. September and possibly January WGM.
2. Analyze variation and develop a plan to address sources of variation. Such a plan might include development of functional requirements or an implementation guide, but those details are not yet determined.
3. Implement action plan.

3i. HL7-Managed Project Document Repository URL:

https://confluence.hl7.org/pages/viewpageattachments.action?pageId=61505681

3j. Backwards Compatibility

No

6i. Realm

Universal

7a. Management Group(s) to Review PSS

FHIR

7b. Sponsoring WG Approval Date

Aug 02, 2019

7f. FMG Approval Date

Aug 14, 2019

7i. Steering Division Approval Date

Sep 16, 2019

Version

1

Modifier

Anne Wizauer

Modify Date

Sep 17, 2019 00:58

1a. Project Name

Mobile Health App Data Exchange

1b. Project ID

1551

1c. Is Your Project an Investigative Project (aka PSS-Lite)?

Yes

1d. Is your Project Artifact now proceeding to Normative directly or after being either Informative or STU?

No

2a. Primary/Sponsor WG

Modeling & Methodology

2d. Project Facilitator

Keith Boone

2e. Other Interested Parties (and roles)

US Office of the National Coordinator for Health IT (AllOfUs Health IT standards research sponsor)
US National Institutes of Health, All of Us Research Project
Open mHealth
Audacious Inquiry

3a. Project Scope

The initial scope of this project is to analyze variation in FHIR data exchanged from mobile health apps and devices for personal health information. Because mobile health apps and devices can convey a wide variety of data including hundreds of different kinds of measurements, this project will first look at a limited scope of data, including vital signs, physical activity, sleep and blood sugar.

These data elements are readily accessible in many mobile health apps and devices. Similar data is often used during treatment of disease affecting cardiovascular, cereberovascular, lower respiratory, and endocryne systems. These diseases are five of the top ten leading causes of death in the US (https://www.cdc.gov/nchs/fastats/leading-causes-of-death.htm) and four out of ten in the world (https://ourworldindata.org/causes-of-death). Thus, they are high priority items to address in this project.

Attachments

3b. Project Need

There are multiple pathways to obtain personal health data from mobile apps and devices in FHIR. Some of these pathways are shown in the attached Powerpoint diagram and include:

* Proprietary API to FHIR Conversion (via cloud, mobile platform, or direct to device APIs).
* Proprietary to FHIR Conversion via an Intermediate Format (e.g., Open mHealth)
* Direct output in FHIR from a Device Gateway
* Exchange to EHR w/ Output in FHIR generated from an EHR

Each of these pathways can introduce variation due to the encoding of sematic codes describing the measurement, or variations in the way that units are expressed, or in the precision of data exchanged.

Because of the increasing use of personal health devices to augment care, this is of concern because it can introduce variation in personal health data that may be used for diagnosis, treatment and research.

The goal of this project is to determine the degree of semantic and precision variation in these pathways and determine what steps are needed to address this challenge to enable healthcare providers to use personal health device data for diagnosis, treatment and research.

3e. Objectives/Deliverables and Target Dates

1. Promote a FHIR Connectathon track (see https://confluence.hl7.org/display/FHIR/2019-09+Mobile+Health+Data+Exchange) to compare variations in pathways for getting FHIR Data. September and possibly January WGM.
2. Analyze variation and develop a plan to address sources of variation. Such a plan might include development of functional requirements or an implementation guide, but those details are not yet determined.
3. Implement action plan.

3j. Backwards Compatibility

No

6i. Realm

Universal

7a. Management Group(s) to Review PSS

FHIR

7b. Sponsoring WG Approval Date

Aug 02, 2019

7f. FMG Approval Date

Aug 14, 2019

7i. Steering Division Approval Date

Sep 16, 2019

8 Comments

  1. Keith W. Boone Hi Keith! Initial review of this PSS revealed the following:

    1. I updated the sponsor to be Mobile Health. The PSS had Learning Health Systems listed. My apologies if that was the intention.
    2. Section 3.i: Please add a link to the HL7-managed project document repository
    3. This must be reviewed by the FHIR Management Group. I can add to their next call on 2019-08-14 at 4pm Eastern. It is preferred that a representative of the project attend the call to answer any questions. Please let me know who can attend and I will send a calendar invite.
    4. Following FMG approval, the PSS should be sent to the Infrastructure Steering Division for approval.
  2. Keith W. Boone Rob McClure Greetings! Before I can send this to TSC, it still needs a link to an HL7-managed project document repository in section 3.i. Once we've got that, I can send it for approval. Thank you!

    1. I've added a link to the repository in 3i now.

  3. Anne Wizauer Looks like this is ready for TSC.

    1. I just tried the link you posted, Ulrike and it worked for me. Maybe try again?

      1. thanks - it worked this time (smile)