From retrospective reporting to proactive, insight driven execution

The Challenge: Insight Exists, Execution Lags

Healthcare quality and performance teams generate extensive reporting across Stars, HEDIS, Risk Adjustment, and value-based care programs. Despite increasingly sophisticated analytics environments, many organizations continue to operate reactively—waiting days or weeks for reports, navigating fragmented dashboards, and manually translating insights into action.

The challenge for healthcare analytics today is not generating more insights, but operationalizing them with speed, trust, and governance. Traditional analytics platforms are effective at producing reports but less effective at supporting operational decision-making. Analysts spend significant time writing and validating SQL and reconciling insights across claims, clinical, provider, and member datasets. Downstream users—quality, clinical, and operational teams—often rely on static exports which reduce productive hours that could be used for targeted actions. Gartner reports that digital workers save an average of ~3.6 hours per week using GenAI*, primarily by reducing manual analysis, context switching, and repetitive data tasks.

As quality and regulatory programs scale, healthcare organizations need more than reporting tools. They need an operational decision layer that delivers trusted, explainable insights and enables timely, defensible action across teams.

Perform+ ClinicalIQ brings these productivity gains to healthcare decision-making by combining a governed lakehouse, semantic layer, and explainable multi-agent reasoning—helping teams move from retrospective reporting to proactive, insight-driven execution at scale.

Introducing ClinicalIQ: Decision Intelligence on Databricks

Perform+ ClinicalIQ expands the Perform+ platform with a decision intelligence application built on Azure Databricks. It converts complex, multi-step reporting workflows into a conversational experience that supports faster, more confident decisions.

Instead of navigating multiple dashboards or submitting ad-hoc data requests, users can ask natural-language questions such as:

• Which contracts are within 0.25 Stars of the next rating threshold?
• Which members should be prioritized to close diabetes care gaps?
• Which providers represent the highest improvement opportunity within a specific geography?

ClinicalIQ returns contextual, explainable responses by combining member-level data, measure logic, provider attribution, geographic insights and more. All results are derived from governed datasets and certified metrics, ensuring consistency, trust, and audit readiness.

Operational Decision Support Built on a Governed Databricks Foundation

Perform+ ClinicalIQ leverages Databricks Genie to support different decision needs while remaining tightly aligned to Perform+’s governed data foundation. For routine operational questions, users receive fast, confident answers grounded in curated Stars, HEDIS, and Risk metrics—reducing reliance on manual SQL queries and dashboard navigation. For more complex decisions, the experience supports deeper analysis by clearly surfacing the data sources, measures, and logic used, enabling teams to review and defend outcomes when required.

This decision support is underpinned by a medallion lakehouse architecture on Databricks, governed through Unity Catalog, ensuring trust and consistency across all usage.

Key platform capabilities include:

• Gold‑layer Stars and HEDIS fact tables for standardized performance measurement
• A Genie semantic layer with certified metrics, business terminology, and trusted SQL
• Healthcare‑specific logic encoded through ontologies and contextual modeling
• Role‑based and attribute‑based access controls to support PHI‑safe usage

Together, these capabilities ensure that every insight delivered through ClinicalIQ is auditable, reproducible, and explainable, meeting the operational and regulatory expectations of healthcare organizations.

From Insight to Action at Enterprise Scale

ClinicalIQ is designed to support execution, not just analysis. Insights generated through the platform can be consumed directly by downstream workflows, including:

• Quality improvement initiatives
• Provider engagement programs
• Member outreach and care‑gap closure campaigns
• Independent reporting and analytics teams

By separating insight generation from execution channels, ClinicalIQ ensures that intelligence is operationalized across the organization—rather than remaining confined to a report, dashboard, or conversational interface.

As a result, healthcare organizations using ClinicalIQ move from static reporting to continuous decision support, from manual analysis to explainable AI‑assisted reasoning, and from delayed response to next‑best‑action execution—while maintaining governance, auditability, and compliance across Stars, HEDIS, Risk Adjustment, and value‑based care programs.

Source: *BusinessWire: Gartner Identifies Four Emerging Challenges to Delivering Value from AI Safely and at Scale