One of the biggest challenges facing caregivers is planning for the slowly mounting responsibilities of being a caregiver. In his report, caregiver Bob Kelly wrote:
From our current vantage point, it is clear that a well thought out yet adaptable Caregiving Trajectory Plan from day one could have minimized the potential for misunderstandings and in particular mounting stress on my wife. A well planned Caregiving Trajectory Plan should be a roadmap for care capable of adaptation but designed to spread responsibilities, not stack them, as circumstances and needs change with the progression of this devastating disease.
In response to his request, we've designed Orbit Care, a simple app that allows caregivers and caregiver teams to create weekly plans. Here's how it works:
On Sunday evening, a caregiver will get a notification to build this week's plan:
Then, the app's user would take about 30 seconds on Sunday evenings to create their plan for the week, assigning team members (such as a sibling or a spouse) to specific to-do items auto-suggested based on the Caregiving Trajectories outlined in industry research like this.
Next, they can send notifications to other team members about their responsibilities, so that everyone is on the same page.
Finally, they will be offered additional assistance as needed, with relevant products and services provided.
All set! After the caregiver has gone about their week, they will get one more notification from Orbit Care, prompting them to reflect on their week:
The user will take another 30 seconds to complete the questions about the week's progress, first by marking items complete or not:
Then, they can reflect on anything else and record it:
Easy as that!
The products and services section can provide a real value to caregivers who might not otherwise know about these tools while also providing a potential means of revenue without costing the caregivers.
This product is a great starting point or MVP launch for other features. The app could gather critical data for caregiver preferences and machine learning could make the app even better over time.