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2.4 Exemplary Use Cases

As noted in the Introduction, consumer mobile heath apps take many forms, and as such, conformance statements in section 3 of this standard must allow for variation based on multiple factors, including data sensitivity, the nature of conditions addressed by the app (e.g., wellness, chronic illness), and whether/how app data connect to other data sources.

In this section, three archetypal use cases are introduced. While most consumer mobile health apps will not precisely fit any of these models, the models are meant to demonstrate a continuum of issues which may be applied to any app. Use Case A covers the least sensitive example of a health app that collects user information, while Use Case B builds off of Case A with the inclusion of an external system through which personal data is synchronized with the device. Use Case C is the most sophisticated and generates the most requirements. Its description includes examples of the risk factors that should be considered by developers and users.

Section 3 (Conformance Criteria) includes discussion of considerations as to how subsets of conformance criteria can be addressed in different manners, referencing the use cases in this section as a way to provide directional, rather than pinpoint, guidance.

HL7 CMHAFF Standard Overview and Use Cases

2. Overview

Goals, Scope, Conformance Design Principles

CMHAFF Workgroup 0 9245 Article rating: No rating

The primary goals of cMHAFF are to provide a standard against which a mobile app’s foundational characteristics -- including but not limited to security, privacy, data access, data export, and transparency/disclosure of conditions -- can be assessed. The framework is based on the lifecycle of an app, as experienced by an individual consumer, from first deciding to download an app, to determining what happens with consumer data after the app has been deleted from a smartphone. It is important to note that the Framework does not speak directly to the specific health or clinical functionality of an app but can be extended to do so through the use of profiles (with constraints and/or extensions) developed on top of cMHAFF.

2.4.1 Use Case A

Simple, Standalone

CMHAFF Workgroup 0 8558 Article rating: No rating

A walking app collects data based on how far someone walks, using GPS technology. A consumer can view a history of walks taken and summary statistics related to distance walked and estimated calories burned. App developer is not a HIPAA-covered (see reference below) entity (CE) such as a healthcare provider, nor is the app sponsored by a CE (such as a hospital or physician).

2.4.2 Use Case B

Device-Connected Wellness App

HL7 CMHAFF 0 7455 Article rating: No rating

A weight management app helps consumers to systematically collect weight information, food consumption information and exercise information.  Weight can be entered manually, or a consumer can link a wireless scale to the app so that weight is automatically collected when using the scale.  Food consumption is entered manually, and the tool estimates calories consumed based on the consumer’s input. Exercise information may be entered manually or collected automatically through integration with a smart watch. A walking app collects data based on how far someone walks, using GPS technology. A consumer can view a history of walks taken and summary statistics related to distance walked and estimated calories burned. App developer is not a HIPAA-covered (see reference below) entity (CE) such as a healthcare provider, nor is the app sponsored by a CE (such as a hospital or physician).

2.4.3 Use Case C

EHR-Integrated Disease Management App

HL7 CMHAFF 0 7220 Article rating: No rating

A diabetes management app allows a consumer to collect blood sugar readings through a Bluetooth-enabled glucometer. A healthcare provider offers the app to enable the patient’s blood sugar to be captured through devices, rather than relying on manual entry by the patient, and to electronically transmit the readings to the patient’s physician, rather than using paper or FAX. Activity data are collected through an activity tracker, and a consumer can open the app to record meals and snacks to enable estimates of caloric consumption.

2.4.4 Risks, Key Differences, and Environmental Scan

Use Case Impact Factors

HL7 CMHAFF 0 7552 Article rating: No rating

For some apps, especially those like Use Case C, there are several potential threats and vulnerabilities which should be assessed and mitigated, where necessary, by mHealth developers (see 3.2.2 Product Risk Assessment and Mitigation). The primary goals of cMHAFF are to provide a standard against which a mobile app’s foundational characteristics -- including but not limited to security, privacy, data access, data export, and transparency/disclosure of conditions -- can be assessed. The framework is based on the lifecycle of an app, as experienced by an individual consumer, from first deciding to download an app, to determining what happens with consumer data after the app has been deleted from a smartphone. It is important to note that the Framework does not speak directly to the specific health or clinical functionality of an app but can be extended to do so through the use of profiles (with constraints and/or extensions) developed on top of cMHAFF.

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