JMIR Publications

ABSTRACT

Background:

The Covid-19 pandemic forced the spread of digital health tools to address limited clinical resources for managing chronic health conditions. At the same time, it illuminated the population of older patients who could not access this care without an informal caregiver (IC) due to accessibility, technological literacy, or English proficiency concerns. For patients with heart failure (HF), this rapid transition to digital health further exacerbated the demand on ICs and pushed Canadians towards a dyadic care model in the management of chronic diseases, where patients and ICs work to manage care together. Our previous work identified an opportunity to improve this dyadic HF experience through a shared model of dyadic digital health. We call this alternative model of care “Medly-Caretown,” which empowers ICs to concurrently expand the patient’s ability for self-care while acknowledging IC eagerness to provide a greater level of support.

Objective:

The aim of this viewpoint paper is to present the systematic design and development of the Medly-Caretown dyadic management module. While HF is the outlined use-case, we report on disease-invariant features. Specifically, we outline our design methodology, and report on the output (six core features) of this methodology applied within the space of dyadic shared care for HF management. This work lays the foundation for future usability assessment of Medly-Caretown.

Methods:

This was a qualitative human-centred design study. To build the Medly-Caretown model, we 1) leveraged the Knowledge to Action (KTA) framework for its ability to translate knowledge into action, and 2) borrowed the Google Sprint from industry titans to quickly “solve big problems and test new ideas” which has been effective in the medical and digital health space. Specifically, we blended these two concepts into a new framework called the “KTA Sprint”.

Results:

Six core disease-invariant features were identified to support ICs in care dyads to provide more effective care and to capitalize on the synergistic benefits of dyadic care. These six features were designed to be customizable to suit the patient’s condition, were informed by stakeholder and task analysis, corroborated with literature, and vetted through user needs assessment interviews. These features include (1) Live Reports to enhance data sharing and facilitate appropriate IC support; (2) Care Cards to enhance guidance on the caregiving role; (3) Direct Messaging to dissolve the disconnect across the circle of care; (4) Medication Wallet to improve guidance on managing complex medication regimens; (5) Medical Events Timeline to improve and consolidate management and organization; and (6) Caregiver Resources to provide disease-specific education and support their self-care.

Conclusions:

These disease-invariant features were designed to address informal caregiver needs in supporting their care partner. We anticipate the implementation of these features will empower a shared model of care for chronic disease management through digital health, and will improve outcomes for care dyads.