UDP

The Clinovera Unified Data Platform (UDP) is a comprehensive, AI-powered data solution designed for healthcare organizations that need to unlock value from every type of data source — structured, unstructured, and imaging. By combining advanced AI with deep healthcare data expertise, UDP transforms fragmented, complex data into actionable intelligence for clinical, operational, and analytical teams across hospitals, skilled nursing facilities (SNFs), home-care networks, payers, and life sciences organizations.

UDP is delivered as a complete yet highly customizable solution that adapts to each organization's workflows and goals, enabling measurable outcomes in weeks rather than months. Unlike generic data platforms, UDP does not merely store data — it unifies, enriches, and activates it, ensuring every data point becomes usable intelligence without requiring large internal data science or engineering teams to get started.

Core Solution Pillars

• Automate and Streamline Operations: UDP automates 70–90% of claims processing, reducing claim rejections by up to 40%. Admission decisions for SNFs and home health can be made in minutes, and documentation time for home-care and post-acute providers is reduced by 50%.
• Simplify Integration and Interoperability: EHR connectivity can be achieved in 2–4 weeks using AI-driven mapping, eliminating the need for complex custom interface projects. UDP generates and enriches FHIR resources with standard terminologies including ICD, RxNorm, and LOINC. It also provides imaging intelligence by extracting insights from DICOM and radiology data.
• Drive Clinical Intelligence and Predictive Insight: UDP creates a unified patient record spanning EHRs, clinical notes, and imaging. AI-powered decision support improves decision speed by up to 40%, while predictive analytics reduces data preparation time by 70% and accelerates research initiatives.

Key Platform Capabilities

• Unified data aggregation from heterogeneous sources, including structured records, unstructured text, and imaging data.
• Multistep AI pipelines for automated data extraction and enrichment, incorporating OCR, NLP, terminology mapping, validation, and enrichment to clean and normalize inconsistent or low-quality data before it enters the unified patient model.
• Patient-centric record organization with AI-driven review and clinician review loops where required.
• Support for a broad range of healthcare data formats and standards: HL7 v2, FHIR, CCD/C-CDA, DICOM, flat files, and OMOP CDM.
• Domain-trained AI models fine-tuned for specific provider, payer, or research workflows, with configurable pipelines and organization-specific rules.
• Integration with major EHRs and clinical systems, as well as delivery into existing BI tools, FHIR or terminology services, Snowflake, Databricks, BigQuery, and other data repositories without disrupting current workflows.

Why Healthcare Teams Choose UDP

• Rapid time to value: Most clients achieve measurable outcomes — including automation gains, improved decision speed, and reduced documentation time — within 6–12 weeks of implementation.
• Minimal internal resource requirements: Clinovera provides pre-built pipelines, models, and services. The client team primarily provides data access, reviews validation samples, and confirms workflow requirements, minimizing internal engineering effort.
• Future-proof architecture: Built on open standards including FHIR, HL7, and OMOP CDM for long-term scalability and interoperability.
• Broad domain experience: Clinovera has extensive delivery experience across healthcare providers (hospitals, SNFs, home-care networks), payers (claims automation, adjudication, and analytics), and life sciences and research organizations (data enrichment and study enablement).

Real-World Applications

• Clinician-led, data-driven breast cancer care improvement programs.
• GenAI-optimized patient admissions workflows for SNFs.
• Disease registry development using OMOP CDM repositories.

UDP supports HIPAA-compliant deployments in private cloud or on-premises environments, with full data sovereignty and auditability. The platform is designed to connect to existing systems without disruption, making it suitable for organizations at any stage of their AI and interoperability journey — whether beginning with EHR integration, exploring AI automation, or scaling predictive analytics across the enterprise.