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Healthcare

Driving User Engagement and Decision-Making Through Customizable Analytics in Healthcare Technology

User interface displaying a personalized healthcare analytics dashboard tailored to clinical and administrative roles.

Focus Areas

Custom Analytics Development

User Engagement

Healthcare Technology

Custom analytics widgets being configured by users to monitor KPIs like patient outcomes, costs, and staffing levels

Business Problem

A healthcare technology platform serving providers, payers, and patients struggled with low user engagement and inconsistent utilization of analytics features. Though the platform offered a broad set of metrics, they were rigid, difficult to navigate, and misaligned with users’ roles and daily needs. This limited the ability of care teams, administrators, and executives to make timely, data-driven decisions. The company needed a solution to personalize insights, improve user experience, and unlock the full value of its data assets.

Key challenges:

  • Static Dashboards: Existing reporting features lacked flexibility and failed to reflect user-specific KPIs or workflows.

  • Low Adoption Rates: Clinicians and administrators found the analytics interface unintuitive and overly complex.

  • Siloed Data: Data from EHR systems, patient engagement tools, and billing systems were disconnected, reducing insight relevance.

  • Slow Decision Cycles: Without real-time, role-based analytics, decisions were delayed and often based on outdated reports.

The Approach

Curate partnered with the client to revamp the analytics experience by introducing a customizable, role-based analytics layer within the platform. The engagement focused on integrating diverse healthcare data sources, building modular dashboards, and enabling dynamic filtering and visualization options tailored to user needs—ultimately enhancing engagement, clinical efficiency, and strategic decision-making.

Key components of the solution:

  • Discovery and Requirements Gathering: Curate engaged product owners, data teams, and end users (clinicians, ops leaders, and execs) to gather insights and define success metrics. Priorities included:

    • Create customizable dashboards based on user roles and objectives

    • Integrate clinical, operational, and financial data sources

    • Ensure real-time access to metrics with drill-down capabilities

    • Enhance UI/UX to improve usability and interpretability

  • Analytics Solution Implementation:

    • Unified Data Warehouse: Integrated EHR, CRM, claims, and patient engagement data using ETL processes into a centralized lake-house architecture.

    • Modular Dashboard Templates: Developed flexible templates using Power BI and Looker that allowed users to customize KPIs, filters, and visualizations.

    • Role-Based Access Controls: Implemented fine-grained permissions to ensure appropriate data access and contextual visibility.

    • Embedded Analytics: Enabled in-app analytics experiences so users could interact with insights directly within their workflows.

    • Real-Time Refresh & Alerts: Configured automatic updates and alerting for key metrics such as appointment no-shows, care gaps, and patient risk scores.

  • Process Optimization and Engagement Enablement:

    • User Persona Mapping: Defined analytics needs across roles (e.g., providers, care managers, finance leaders) to inform dashboard design.

    • Interactive UX Design: Simplified interfaces with intuitive navigation, dynamic charts, and guided analytics walkthroughs.

    • Performance Tuning: Optimized queries and visualization rendering for speed and scalability.

    • Feedback & Iteration: Launched beta versions with pilot users and iterated based on real-time feedback.

  • Stakeholder Engagement & Change Management:

    • Cross-Functional Design Sprints: Brought together data engineers, designers, and users to co-create analytics modules.

    • Training & Documentation: Developed role-based onboarding guides, video tutorials, and in-platform tips.

    • Adoption Incentives: Tracked usage metrics and tied engagement to user performance goals.

    • Governance Committee: Established a data governance group to ensure relevance, integrity, and continuous improvement of analytics assets.

Business Outcomes

Boosted Platform Engagement Through Custom Insights


Users interacted more frequently and meaningfully with dashboards customized to their workflows, boosting log-in frequency and time-on-platform.

Improved Clinical and Operational Decision-Making


Real-time access to actionable data led to faster and more accurate decisions regarding staffing, patient care, and revenue optimization.

Stronger Cross-Team Collaboration


Standardized metrics and shared visualizations improved alignment across departments and reduced reporting silos.

Sample KPIs

Here’s a quick summary of the kinds of KPI’s and goals teams were working towards**:

Metric Before After Improvement
Monthly active analytics users 42% 81% 93% increase
Report customization requests High (manual, delayed) Low (self-service) 75% reduction in support load
Average dashboard load time 6.2 seconds 1.7 seconds 72% improvement
Time to decision on clinical alerts 12 hours 1 hour 91% faster decision-making
User satisfaction (analytics tools) 6.1 / 10 9.0 / 10 3-point improvement
**Disclaimer: The set of KPI’s are for illustration only and do not reference any specific client data or actual results – they have been modified and anonymized to protect confidentiality and avoid disclosing client data.

Customer Value

Personalized Engagement


Users received data aligned with their priorities, increasing satisfaction and usage.

Operational Efficiency


Executives and teams had a real-time view of performance metrics, enabling faster interventions.

Sample Skills of Resources

  • Data Engineers: Built ETL pipelines, optimized data models, and managed warehouse infrastructure.

  • BI Developers: Designed interactive, user-specific dashboards using Power BI, Looker, and embedded analytics tools.

  • UX/UI Designers: Simplified navigation and tailored the interface to healthcare workflows.

  • Product Managers: Defined requirements and prioritized features based on user interviews.

  • Change Management Specialists: Led adoption efforts through training and enablement initiatives.

Tools & Technologies

  • BI & Visualization: Power BI, Looker, Tableau

  • Data Warehouse: Snowflake, Azure Synapse, Google BigQuery

  • ETL & Orchestration: dbt, Apache Airflow, Fivetran

  • Analytics Embedding: Looker Embed API, Power BI Embedded

  • Collaboration & Support: Notion, Jira, Zoom, Slack

Healthcare professional interacting with an analytics tool that provides real-time, customizable insights for care delivery.

Conclusion

Through customizable analytics and real-time data access, Curate empowered the healthcare technology company to transform user engagement and accelerate decision-making. By aligning insights with the unique needs of each user group, the platform became a trusted, daily tool for driving better outcomes in patient care, operations, and strategy—laying the foundation for long-term growth and innovation.

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