Optimized revenue cycle management with Power BI dashboards

Our client, a U.S.-based Revenue Cycle Management (RCM) company, provides healthcare organizations with end-to-end solutions designed to streamline billing, claims processing, and financial tracking.

The company had built Power BI reports internally for data visualization, but poor navigation and slow performance prevented them from fully leveraging the platform’s capabilities.

To overcome these challenges, the client turned to EffectiveSoft, trusting our experience in healthcare projects. In collaboration with their in-house engineer, our team was asked to:

• Redesign dashboards to improve usability
• Structure reports by organizing the information into sections
• Improve performance to reduce long loading times
• Implement branding customization for each user
• Develop comprehensive documentation

We designed and developed Power BI dashboards that deliver an intuitive and personalized experience, restricted data access, and regulatory compliance. To achieve this, we implemented role-level security (RLS). We also integrated a custom logo display for visual identity. This allows each user to log in with their own credentials and access customized dashboards that display only relevant financial data for their organization.

To ensure smooth adoption and further support users, we provided detailed documentation covering dashboard functionality and data structure.

The client required custom, user-friendly dashboards with effective representation and comparison of key financial metrics. Initially, two possible approaches to time-based data evaluation were envisioned:

• Automatic comparison, where the system contrasts the current year’s data to the previous year’s data and the current month’s data to the previous month’s data (e.g., March 2025 vs. March 2024).
• User-defined period selection, where users select a custom time range, and the system automatically matches it to the same period in the previous year (e.g., if October 15, 2024–January 15, 2025, is selected, the system compares the data with October 15, 2023–January 15, 2024).

We developed multiple design concepts for each scenario. Ultimately, both approaches were implemented, enabling users to analyze data according to their preferences.

When developing the design, we also considered the client’s request for cube-based metric calculations. Therefore, we created custom visuals in Power BI to provide convenient and intuitive options for data representation. Taking this further, we designed the dashboard with an intuitive and well-organized structure.

We implemented an intuitive structure with smooth navigation between overall financial metrics and detailed reports.

The main page (Summary report) serves as the entry point, with a high-level overview of key performance indicators (KPIs) related to RCM. This includes charges, payments, accounts receivable (A/R), claim resolution metrics, and collection performance. From the Summary report page, users can navigate to more detailed subreports.

The client needed multiple ways to drill down into the same dataset. For example, in some cases, they wanted to view data in sequences like location → payer → provider, while in other cases, the preferred location → provider → payer.

However, reports were connected to an MDX cube model that made it challenging to configure such flexible logic. To solve this, we developed a custom hierarchy navigation.

Additionally, we implemented drill-through functionality that allows users to proceed from high-level summaries to more detailed subreports while maintaining the applied filters.

For more detailed reports, we included the following sections:

• Revenue overview: A high-level summary of key financial metrics, including revenue, payments, and adjustments. This section allows stakeholders to analyze and compare revenue trends over time.
• Claim denials: A comprehensive analysis of claim denial patterns, displaying the total number of rejected claims, top reasons for non-payment, and detailed breakdown by location.
• Billing productivity: An overview of encounter volumes, charge lags, and unbilled claims. This dashboard provides a detailed analysis of financial performance.
• Resolution rates: Insights into how efficiently claims are resolved without additional follow-up or rework.
• A/R aging: A thorough analysis of A/R aging, helping users monitor outstanding balances and aging performance.
• Collection performance: An overview of collection performance that enables stakeholders to evaluate how effectively charges are converted into payments and identify reimbursement trends.

The MDX cube model limitations, combined with the complex structure, affected the responsiveness of the reports. On certain pages, delays exceeded 10 minutes, making the system nearly unusable.

Our performance testing revealed that Power BI processed large volumes of data before applying filters rather than retrieving only the relevant dataset.

To overcome the filtering constraints, we used a customized Chiclet Slicer as a workaround. This ensured that only the selected period’s data was processed, reducing load times from minutes to a few seconds.

With improved structure, performance, and usability, the Power BI reporting system now delivers a fast, best-in-class, and efficient experience. The intuitive design and navigation make financial data easy to interpret, even for nontechnical users. According to our client’s feedback, the system’s high performance, clear structure, and personalization strengthened its effectiveness and attracted new users.