Trust that connects
Reduce bias in member care
Improve maternal health outcomes
Let each patient feel heard
Improve quality domains
Can't track details because of heavy caseloads?
Your staff is doing the best they can with the limited resources available. They feel they can't give the right amount of attention to patients from being spread too thin. Give them back that power by capturing trends and summaries at a glance on each patient, and bubbling up the potential gaps in care before they happen.
Want to reduce staff turnover and burnout?
When staff feel like their work is not making an impact, and they are stretched then, they are in danger of burning out. Give your clinicians visibility into the effect of each session and each referral they make. Give them a sense of accomplishment, especially when difficult to gauge progress earlier on in treatment.
How it works
Start session
Login, start a session in the platform, then start your encounter, in-person or via your preferred telehealth platform. As long as audio is clear, we will be able to process it.
Post-encounter Processing
End the session, once the client leaves. Emotivo redacts identifying details, then uses AI to summarize into clinical notes and identify SDOH Z codes.
If no need for an AI Scribe, narrative notes can be analyzed for related SDOH Z codes.
Generate email or voice calls to CBOs
Once a client gives consent, automated communication kicks off to community- based orgs through channels already used, at a cadence that matches the type of need. This gathers referral status, and sends missing eligibility information if needed, so case managers don't run after referral gaps.
Review effectiveness and trends
Understand the latest capacity and speed of partner CBOs. Catch new trends in your population. Identify highest ROI interventions. Granular data is exportable to combine with your data. Integration ready for ONC certified EHRs. Integrations >>
2 Tarabichi Y, Higginbotham J, Riley N, Kaelber DC, Watts B. Reducing Disparities in No Show Rates Using Predictive Model-Driven Live Appointment Reminders for At-Risk Patients: a Randomized Controlled Quality Improvement Initiative. J Gen Intern Med. 2023 Oct;38(13):2921-2927. doi: 10.1007/s11606-023-08209-0. Epub 2023 May 1. PMID: 37126125; PMCID: PMC10150669.
3 Taylor L, Coyle C, Ndumele C, Rogan E, Canavan M, Curry L, and Bradley E. Leveraging the social determinants of health: what works?
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