HL7 Mobile/PHR Gap Analysis: Summary of Findings

1. HL7 Mobile/PHR Gap Analysis:Summary of Findings Mobile Health Workgroup March 2013

2. Context Mobile device use by consumers is widespread, in both developed and developing countries. For example, in the United States there are over 320 M mobile phones in use, more than one for everyone in the population*, and over half of new devices sold are smartphones. In consumer health, smartphones and tablets are presently being used to access personal health information, often in place of using personal computers. Some Personal Health Records systems (PHR-S) now available are designed solely for use on mobile devices. The HL7 standards for Personal Health Records (PHRs), as written, did not anticipate this change. As such, questions have been raised concerning the adequacy of these standards in providing vendor guidance and in certifying modern PHR systems. *mobithinking.com, December 2012 data

3. Problem Overview Background • The PHR/Mobile Gap Analysis Sub-group was established to determine the extent of changes needed in the PHR-S Functional Model to accommodate the use of mobile devices (i.e., smartphones, tablets) within the model. Scope • Review the recently balloted PHR-S functional model to determine how the introduction of mobile devices as actors within the model may result in changes to the model. • Make recommendations to the PHR-S functional model in terms of additional conformance criteria and/or creation of a mobile-specific profile for the PHR-S.

4. Key Finding One The functional aspects of HL7’s Personal Health Record System Functional Model (specifically, Function Names, Statements, Descriptions, and Conformance Criteria) DO NOT need to be modified in any way to accommodate the use of mobile devices and platforms in relation to PHR applications and data. For example: “The system SHALL capture the PHR Account Holder’s demographic information”applies equally to mobile and desktop-based technology.

5. Key Finding Two Certain PHR-S FM functionality can be tailored to mobile-based PHRs and mobile-based use cases based on • Mobile device properties • Context of mobile device use • Behaviors of individuals using mobile devices For example: Geo-location services can inform a consumer of nearby emergency room services. If a mobile device containing consumer information is lost, remote wipe functionality could also trigger backing up data to a pre-specified location.

6. Recommendation One Create one or more mobile-informed profiles for the PHR-S FM that account for use of mobile devices, including device use within specific contexts. For example: If a mobile device is used in a military theatre, the following PHR-S FM Conformance Criterion might be modified within a functional profile to read (added language in red): The system SHOULD provide the ability for the PHR Account Holder to control access to demographic information. Specifically, demographic information will not be displayed on a mobile device for military personnel who are in active combat zones; in non-combat zones, demographic information may be displayed on a mobile device.

7. Recommendation One Considerations Creation of functional profiles is a critical activity as products can only be certified against HL7 profiles, not functional models. Mobile-informed profiles can help industry deal with common issues in a standardized manner. In the absence of PHR-S mobile functional profiles, vendors using the PHR-S FM to create PHR systems should account for mobile devices as actors when determining product scope. Special care should be given to addressing security controls. For example: • Availability and control of location data. • Security in relation to device loss or compromise.

8. Recommendation Two As mobile devices can be actors in many health-related scenarios, expose these findings to other HL7 workgroups where mobile devices are significant system actors for consideration as to how models and methods might be affected. For example: • EHR uses of tablets and smartphones by clinicians. • Structured data entry where mobile devices are used for data collection. • Collection of family history information through structured forms on mobile devices to support Meaningful Use (MU) 2 standards. The appendices to this presentation include lists of mobile device characteristics, contexts of mobile device use, and user behaviors which may affect models and system functionality and are a starting point for examining current HL7 standards.

9. Appendix 1: Mobile Device Characteristics which May Affect Models and System Functionality • SMS messaging • Camera use • Geo Location functions • Near Field Communications capabilities • Device reliability • Role of continuous data collection and processing vs. at time of system sign-on (e.g., real-time alerts and notifications which can make escalated medical decisions, changes in expected behaviors based on longitudinal data, speed and immediacy of data used for clinical decision support) • Use of “basic” vs. “smart” mobile devices • Capabilities of mobile devices that lend to enhanced methods for detecting possible fraudulent system use • Capabilities of mobile devices that enable enhanced interactions with rules engines • PHI and PHII contained on devices • Unique device identifiers for available for audit and device identification

10. Appendix 2: Contexts of Uses of Mobile Devices which May Affect Models and System Functionality • Context of using services and transmitting data (mobile is changing the point of care—no longer just home/hospital—it is the place a person is at) • Social media impact and transfer of personally-identifiable data between patients, “friends”, family and providers (shares issues with PCs, however, access and use of social media platforms is often, if not predominately, mobile-centric) • Enterprise-provided devices vs. “Bring Your Own Device” (BYOD) • Audit considerations when devices are used for data collection and transmission • System non-functional requirements may need more flexibility based on context of use (e.g., temperature, humidity, battery life, bandwidth—both WiFi and G3/G4-- availability) • Context of use that may affect data reliability and integrity

11. Appendix 3: User Behaviors which May Affect Models and System Functionality • Mobile devices are prone to be lost more readily than PCs • consider how “data at rest” standards may need strengthening. • Consider need for data back up in relation to “remote wipe” scenarios • Consider “corner cases” in assumptions about user behaviors that may reduce mobile system security (e.g., typically a user has a mobile device under singular control, but with some regularity the device is shared with others)

12. Acknowledgements Key Sub-Group Contributors • Elaine Ayres eayres@nih.gov • Joe Ketcherside joeketch@me.com • Tim McKay tim.a.mckay@kp.org • John Ritter johnritter1@verizon.net HL7 Mobile Workgroup Co-Chairs • Gora Datta gora@cal2cal.com • Matthew Graham mgraham@mayo.edu • Nadine Manjaro nadine.manjaro@verizonwireless.com

13. HL7 Mobile/PHR Gap Analysis:Summary of Findings THANK YOU Tim McKay tim.a.mckay@kp.org