The Functioning and Disability Reference Group (FDRG) of the World Health Organization’s Family of International Classifications (WHO-FIC) Network in 2013 discussed how a person-driven and person-owned mHealth solution could contribute to achieve health equity and universal health coverage through active participation of persons with health conditions, including persons with disabilities and chronic diseases.
It was clear to all that an authentic interdisciplinary health agenda goes beyond traditional bench to bedside and that an instrument was needed to capture a person’s individual perspectives, especially as it relates to human functioning as conceptualised in the International Classification of Functioning, Disability and Health (ICF) (World Health Organization 2001): a dynamic interaction between a person’s health condition and contextual factors.
It was agreed that ICF is providing the common language to record, share and interpret health information to facilitate person-centred service provision and to amalgamate data real-time to provide a population perspective. This common language is essential in assessing and collaborating to address the needs of individuals and communities, to develop effective policies and guidelines, and for ensuring that all people have access to the intended benefits.
The process to develop this ICF-based mHealth solution commenced with an international needs assessment survey. A total of 1191 responses were received from persons with disabilities, family members and service providers in 32 countries (Snyman, Kraus de Camargo & Gong 2014).
There was global consensus to proceed in developing the ICanFunction mHealth Solution (mICF). mICF will enable a person to direct, own and share functional and contextual information to facilitate a person-centred bio-psycho-social-spiritual approach to service provision and act as catalyst for shared decision-making, common goal setting and the continuity of care.
Respondents agreed that mICF should expand the multiple layers about what and where a person “is”, by what a person “does”. It should help shift the paradigm from a focus on disease towards a broader bio-psycho-social-spiritual perspective. It was also agreed that persons using the mICF should have the option to share and donate their anonymised data to enable Big Data analytics needed for precision healthcare to incorporate ICF-related information on functioning and contextual factors.
International consensus was also that mICF should not be just another mobile app that gathers information and does not provide any response. It should be a solution providing knowledge about a person’s own health; has the ability to interact and engage with information; provides access to technologies that suit individual needs; creates the feeling that using the application is beneficial; and users must feel in control and secure when using the technology (Kayser, Kushniruk, Osborne, Norgaard & Turner 2015).
The mICF will empower service users (e.g. health, social,education) or their proxies to become “agents” in their new role of “directing” the process of service provision and care. They will be enabled to describe their own abilities in strengths and limitations (functioning) regarding the interaction with the existing environmental barriers and facilitators by using mICF. They will own their data; be free to securely share their information and consult with service providers; experience improved communication with their service providers to facilitate shared decision-making; exchange information anonymously with other users of mICF worldwide and therefore be better informed about their treatment and rehabilitation options.
Administrators will have anonymised data available for Big Data analysis. These data will contribute to improve global public health surveillance, which is the foundation for decision-making in public health. It will empower decision-makers to lead and manage more effectively by providing timely, useful evidence. The Centers for Disease Control states in its CDC’s Vision for Public Health Surveillance in the 21st Century that “with the increasing availability of clinical, insurer, social, and environmental data sets, the immediate challenge is to organize the data into a format that is accessible and useful for epidemiologists, statisticians, and others who might be able to use these data for public health surveillance. Until these data are available in a useable format, interpretation by subject matter experts is impossible and the data will not be useful” (Centers for Disease Control and Prevention 2012:8). Figure 1 is a visualisation of how the mICF will function.
Figure 1. Visualisation of the mobile ICanFunction (mICF) information system
Components of mICF
The development of the mICF solution (see Figure 2) involves the development of a
- Graphical User Interface (GUI) and Application Programming Interface (API) tool to convert natural language terms to ICF language (FunctionMapper),
- Health Databank for Big Data analysis, and a
- Health Level Seven International (HL7) interoperability layer.
- These components are needed to enable (4) various frontend designs and applications used by service users to push and pull ICF-related data.
Figure 2: The various components of mICF