We help Medicaid health plans and affiliated providers improve health outcomes for women, mothers, and children. Specifically, we leverage Artificial Intelligence (AI) and Machine Learning (ML), thoughtful data analytics, innovative digital tools, and SDOH to develop and implement solutions that identify at-risk individuals and provide technology-enabled outreach and patient engagement strategies. Empowering individuals and connecting them to their care dramatically increases their engagement and reduces health inequity, resulting in improved health and well-being.
Examples of our sustained, successful programs include lowering Emergency Department (ED) visits and hospitalizations for kids diagnosed with asthma and improving full-term birth rates. These programs utilize ML-driven predictive models, cost and quality dashboards, and messaging techniques to identify at-risk populations and engage them directly.
WAYS TO ENGAGE
Our Risk-Stratified Patient Engagement Offerings identify at-risk individuals (earlier in the process) and provide technology-enabled outreach and patient engagement strategies. Our risk prediction models work better when compared to other methods for identifying at-risk individuals because we factor in SDOH variables in addition to analyzing clinical and claims data.
Pediatric Asthma – A program utilizing a real-time predictive model that proactively― and dynamically― identifies very high-, high-, and medium-risk pediatric asthma patients for targeted, direct decision support interventions. Our program incorporates multiple touch points and messaging modes to improve medication compliance, reduce school absenteeism, and lower ED/hospital utilization.
Pre-term Birth Prevention – A program utilizing a real-time predictive model that identifies pregnant women who present at high risk for pre-term delivery. The physician, case manager, and patient are connected via various messaging modes (e.g., EHR alerts, texts, apps) that work to collect and share patient-specific information to reduce the probability of pre-term birth or post-delivery complications.
Our Dynamic Management Dashboards offer insights and tools that are necessary for effectively managing value-based care contracts. We have the requisite technology infrastructure to ingest diverse clinical and non-clinical datasets containing either structured or unstructured data. Data outputs are synthesized, simplified, and presented in user-friendly dashboards. Key dashboard features include:
- Geolocation to the county, zip code, or block level
- Multiple visualization
- Collaboration features
- Nimble, rapid refresh
PEDIATRIC ASTHMA PROGRAM
Goal: Decrease preventable asthma-related ED visits, hospitalizations, and costs through risk stratification and care re-design.
- The predictive model risk-stratified the children into different groups based on the likelihood that their asthma would exacerbate over the next 3 months and require an ED visit or hospitalization.
- Proactive outreach to physician practices and care managers.
- Risk-driven, text-messaging-based patient engagement.
4 Year Impact
PRE-TERM BIRTH PREVENTION PROGRAM
Goal: Decrease pre-term rates & costs through risk stratification and care re-design.
- The predictive model gathers data from diverse sources to drive early identification of at-risk pregnant women. This model then risk-stratified these women as they moved through their pregnancies on their chances of having an early delivery.
- Risk-driven, text-messaging-based patient engagement to drive prenatal visit attendance and offer prenatal education.
One Year Impact