https://store-images.s-microsoft.com/image/apps.34694.49c415f0-9291-47a6-9fb1-08f0f6fec7f6.e3aa1887-51c6-4ae3-a400-5071f90fe826.530a7d71-e8e9-4b06-9e2f-9c68c9e5c896

HealthEM.AI Cohort Builder Product by Tredence

Tredence Inc

(2 评分)

HealthEM.AI Cohort Builder Product by Tredence

Tredence Inc

(2 评分)

Improve time-to-value in healthcare with end-to-end management of your data lifecycle

Objective: Streamline and simplify medical and PMS data across all points of care to achieve strategic goals based on data insights and proven AI and ML models.

Tredence HealthEM.AI addresses the following challenges:
1. Reduce the unnecessary inpatient and emergency room utilization
2. Patients’ satisfaction with care services provided
3. Identify and retain patients on the care plan by providing appropriate care in the early months.

How do we address your challenges?
1. Use of developed AI/ML models using amalgamated claims, EMR, and SDOH (Social determinants of health) data to predict member future costs and outcomes
2. A unique retraining strategy to improve model accuracy beyond industry standards (2-4x higher).
3. An integrated library of modules with chronic models to support informed clinical decisions.
4. Azure Cloud-enabled PaaS components for faster and more scalable deployment.

Highlights:
1. Flexible delivery models and integration with EMR, HL7, and APIs for custom applications
2. AI/ML models with 2-4x higher accuracy for prescriptive insights
3. Affordable pricing models for small and medium health plans
https://store-images.s-microsoft.com/image/apps.39179.49c415f0-9291-47a6-9fb1-08f0f6fec7f6.4655261e-3b58-4d61-a608-8dc42a74ce96.4e38fdd9-caac-4530-b3b2-7eb184635ad3
/staticstorage/8165fe0/assets/videoOverlay_7299e00c2e43a32cf9fa.png
https://store-images.s-microsoft.com/image/apps.39179.49c415f0-9291-47a6-9fb1-08f0f6fec7f6.4655261e-3b58-4d61-a608-8dc42a74ce96.4e38fdd9-caac-4530-b3b2-7eb184635ad3
/staticstorage/8165fe0/assets/videoOverlay_7299e00c2e43a32cf9fa.png
https://store-images.s-microsoft.com/image/apps.39179.49c415f0-9291-47a6-9fb1-08f0f6fec7f6.4655261e-3b58-4d61-a608-8dc42a74ce96.4e38fdd9-caac-4530-b3b2-7eb184635ad3