Clinical Decision Support
Are You Ready for Predictive AI with Clinical Decision Support (CDS)?
Healthcare organizations feel pressured to implement AI-based CDS but worry about regulations, integration, and clinician buy-in. MeldRx combines suggestions and alerts from multiple AI and evidence-based CDS tools into a single dashboard that easily integrates with existing systems, such as EHRs. So, organizations can rapidly evaluate and adopt AI into their clinical workflows while ensuring trust and compliance.
Embedding Predictive AI into a Clinical Workflow
A patient visits their provider, initiating a clinical workflow.
The clinician accesses the patient’s chart, triggering the configured CDS system based on evidence-based and predictive AI protocols.
The system generates alerts, insights, or suggestions based on patient data.
The clinician reviews the alerts and suggestions to make care decisions and take action.
Actions (e.g. Tasks, Medications, Labs, etc.) generate new patient data.
Clinicians share feedback that helps improve protocols over time and reduce alert fatigue.
Clinicians may review more info such as clinical trials, research papers, and source attributes of the CDS protocols before making their decision or taking action.
FREE Resources for Embedding Predictive AI into a Clinical Workflow
Embedding Predictive AI in Clinical Decision Support
Discover how predictive AI augments traditional evidence-based practices. This white paper provides an in-depth look at regulatory insights, workflow integration, and best practices for embedding AI into clinical decision support.
Predictive AI for CDS A 7-Step Suitability Framework
Not every clinical challenge needs an AI solution. This framework offers a step-by-step guide to evaluating which problems are best solved with predictive AI, helping you determine where AI can make the most impact.
5-Step Self-Assessment Tool for Your Predictive AI CDS Solution
Kickstart your journey with our self-assessment questionnaire. Designed to help you think through implementing your first AI solution into your clinical workflows, it guides you in evaluating your requirements and identifying the next steps.
5 Ways We Simplify the Adoption of Predictive AI CDS into your Clinical Workflow
1
Unified Dashboard
A single, clinician-friendly interface consolidates scores, alerts, and recommended interventions from multiple AI and evidence-based CDS tools to streamline care decisions.
2
Continuous Feedback
A continuous feedback loop collects user feedback and performance data, enabling iterative improvements to CDS tools and reducing alert fatigue.
3
Open Ecosystem
A framework to combine third-party and in-house AI tools, enabling specialized models to be embedded in custom solutions alongside evidence-based protocols.
4
MeldRx Simulator
A unique feature that empowers clinicians to run "what-if" scenarios for individual patients or populations, to assess the impact or just evaluate interventions in a secure sandbox.
5
Flexible Deployment
A solution that can be deployed as a standalone system for population-level analytics or integrated into an EHR for real-time clinical alerts, using established standards like FHIR®.
Embedding Predictive AI into a Clinical Workflow
The organization configures the evidence-based or predictive AI CDS protocols in MeldRx.
A clinician logs in to their Health Information System (e.g. EHR).
The clinician opens a patient chart. The chart shows them a button to launch the alerts dashboard.
The clinician launches the dashboard, which displays alerts, insights, or suggestions based on configured protocols and the patient’s data from the EHR and/or the MeldRx workspace.
The clinician reviews the alerts and suggestions to make care decisions and take actions. Data generated from actions is synced back to the MeldRx workspace.
Data generated from actions may also be synced back to the EHR.
Clinicians share feedback that helps improve protocols over time and reduce alert fatigue.