Revenue cycle analytics

Purpose

1.1. Automate revenue cycle analytics for cardiology clinics to capture, analyze, and report on income streams, detecting revenue leaks, enhancing financial transparency, improving payer mix outcomes, and automating reconciliation with payors and billing systems.
1.2. Enables automated extraction and normalization of billing, charges, collections, denials, AR aging, and cash flow for revenue performance insights.

Trigger Conditions

2.1. Automate upon new EHR/EMR billing entries.
2.2. Automate by daily, weekly, or monthly revenue close.
2.3. Automate on payer file imports or claim status updates.
2.4. Automate on crossing pre-defined revenue or denial thresholds.
2.5. Automate based on scheduled business reporting timelines.

Platform Variants

3.1. Salesforce Health Cloud
• Feature/Setting: Automate report snapshots from Billing module; configure Analytics API for real-time dashboards.
3.2. Epic Systems
• Feature/Setting: Automate Clarity Reports export and integration via Bridges interface for revenue KPIs.
3.3. Cerner Millennium
• Feature/Setting: Configure RCM API for automated extraction of claim, posting, and payment data.
3.4. Microsoft Power BI
• Feature/Setting: Automate data pull using Power BI REST API for scheduled revenue dashboards.
3.5. Tableau
• Feature/Setting: Automate workbook refresh from SQL-based revenue data, using Tableau Data Extract API.
3.6. Qlik Sense
• Feature/Setting: Automating ETL with REST Connector to fetch and process revenue data for visualization.
3.7. Google BigQuery
• Feature/Setting: Automate scheduled queries for real-time revenue aggregation and reporting.
3.8. AWS QuickSight
• Feature/Setting: Automate ingestion from RCM databases using QuickSight Data Sources for revenue cycle analytics.
3.9. SAP BusinessObjects
• Feature/Setting: Automate financial report distribution with Scheduling Manager and universe revenue fields.
3.10. Oracle Analytics Cloud
• Feature/Setting: Automate financial analytics pipeline using Data Flows for cardiology-specific revenue variables.
3.11. Zoho Analytics
• Feature/Setting: API integration for automated periodic import of revenue, claim, and denial data.
3.12. Domo
• Feature/Setting: Automate connector setup for EHR/EMR and billing platforms to feed real-time revenue dashboards.
3.13. Sisense
• Feature/Setting: Automate Elasticube update from billing exports for near-live revenue cycle visualization.
3.14. Medisolv
• Feature/Setting: Automate financial metric tracking using Medisolv API for scheduled cardiology analytics.
3.15. Infor Cloverleaf
• Feature/Setting: Automate HL7 message routing of billing events to specialty analytics workflows.
3.16. IBM Cognos
• Feature/Setting: Automate scheduled batch reports from payment and denial database.
3.17. MuleSoft
• Feature/Setting: API-led automation for integrating disparate cardiology billing and claims systems.
3.18. InterSystems IRIS
• Feature/Setting: Automate FHIR-based ingestion of financial and claim objects for analytics.
3.19. Workday
• Feature/Setting: Automate Workday Financials report scheduling via RaaS (Report-as-a-Service) for AR and revenue analytics.
3.20. Google Sheets
• Feature/Setting: Automate data import from billing exports using automated triggers and Sheets API.
3.21. Alteryx
• Feature/Setting: Automating ETL workflows for extracting, cleaning, and blending revenue-related data sources.
3.22. Clarity Insights
• Feature/Setting: Automate analytics pipelines for extracting and correlating payment trends with claim lifecycle events.

Benefits

4.1. Enables entirely automated revenue performance analysis, accelerating monthly close and reconciliation.
4.2. Automates alerts on anomalies or revenue dips for proactive intervention.
4.3. Reduces manual analytics and report-building, freeing cardiology management staff.
4.4. Speeds up revenue cycle, automates identification of denial trends, and automates payer compliance.
4.5. Ensures automated, high-frequency revenue transparency supporting data-driven decisions for specialty practices.