Longitudinal learning stalls when engagement signals have no shared meaning.
Broad coverage can create false confidence, while narrow definitions can miss useful patterns.
Who you’d be doing this for
“We have plenty of activity data, but I can’t tell which patterns actually mean progress.”
Wanyama Kosgei · Population Health Manager
Needs clearer evidence about which patterns of participation are associated with sustained member progress.
What is at stake
Three recent analyses used different engagement definitions and reached incompatible conclusions. You need to choose what evidence is credible enough to learn from before standardizing it.
Why it isn’t already fixed
Every obvious fix costs something else. That’s the part you’d have to decide.
- broad signal coverage vs interpretable evidence
- fast exploration vs durable definitions
- inferred labels vs trustworthy learning
Why Sword Health
Pulse combines continuous cardiometabolic support with behavior-change interactions that need consistent longitudinal evidence.
Written with these in mind
Not your kind of problem? 46 more at Sword Health, or browse every organization.
This is the setup. The work is inside.
Running it puts you in the room: the full situation and its constraints, stakeholders who push back in their own words, and the decisions that are yours to make. What you produce becomes a Day One Plan — work you can show someone instead of describing.