Best Practices for Designing Custom Healthcare Software with Built-in Power BI Dashboards

The healthcare sector produces everyday enormous volumes of data. Healthcare data is expanding from patient records to medical imaging to insurance claims. Healthcare companies also require real-time access to this data if they are to enhance operational, financial, and clinical results.

Power BI dashboards offer a practical means for healthcare companies to examine and learn from their data. Custom Power BI dashboards built right into healthcare IT systems allow companies to enable data-driven decision-making among all kinds of users, from managers to doctors.

However, developing custom healthcare software solutions with integrated Power BI capabilities requires careful planning and design. This article outlines best practices for healthcare IT teams embarking on these types of development projects.

Understand User Requirements and Data Sources

The first step is gathering user requirements and identifying data sources. Before writing a single line of code, product managers and developers need to understand:

What questions do users want the Power BI dashboards to answer? Interview end-users across various roles to understand their most important data analysis needs. Also, input from executives and stakeholders must be gathered.
How will we feed the dashboards with data? All possible data sources – EHRs, billing systems, clinical data repositories – document all plans for real-time data connections.
What does the data model have to support? Find out what the KPIs, metrics, dimensions, and granularity of data are required for making dashboards to satisfy the user’s require.

Time well spent is gathering end-user input thoroughly. It is the reason for the entire development roadmap, and it is the product that solves real problems for customers.

Build a Scalable Data Architecture

Healthcare data is often scattered across many disconnected systems. Building custom software with Power BI integration requires consolidating data into a scalable architecture that supports performance and governance. Working with an experienced Power BI consultant ensures these complex integrations follow best practices.

Implement data warehousing and ETL processes to integrate data from diverse sources. Using Azure services simplifies cloud or hybrid data warehousing.
Design reusable data models using star schema approaches. Well-designed models allow fast queries and easily adding of new data sources.
Establish data governance standards for security, privacy, data quality, metadata management, and user access controls.
Plan for data volume growth. Start with today’s needs but architect for 5-10X growth.

Investing in the underlying data architecture pays long-term dividends for faster dashboard development, plus overall data quality and governance.

Adopt Agile Development with Power BI

Waterfall software development with long release cycles doesn’t work well for data-driven products. Adopt Agile development approaches instead:

Take an iterative approach by delivering dashboard functionality in small increments. Get user feedback early and often.
Implement DevOps CI/CD pipelines to deploy updates quickly while maintaining quality. Automated testing and monitoring is essential.
Use source control (Git) to easily collaborate on Pthe ower BI dataset and report definitions.
Leverage certification testing before deploying to production environments.

An Agile approach gets valuable dashboard functionality in front of users faster, while DevOps automation ensures quality and stability.

Architect for Performance and Scalability

Performance issues are the downfall of many dashboards. Leverage the following architecture and design practices to ensure fast performance:

Implement row-level security to restrict data access for individual users. This optimizes query performance.
Design dashboards for interactivity using features like drill-downs, slicers, and filters. Build visualizations to answer one question at a time.
Set data refresh schedules to balance currency needs with system resource usage.
Use aggregate tables where appropriate to accelerate reporting. Store commonly accessed aggregations in Power BI rather than querying them real-time from transactional systems.
Test with production-sized data to confirm performance across user concurrency and data volumes. Identify and resolve bottlenecks.
Scale up Power BI capacities as usage grows by leveraging load balancing and auto-scaling capabilities.

Architecting for scale requires testing and infrastructure improvements over time. However, the investment prevents performance problems down the road.

Standardize Dashboard Development

Standardization helps streamline dashboard development while providing a consistent user experience:

Create a style guide documenting fonts, colors, layouts, iconography, etc., across dashboards.
Standardize dimensional modeling approaches with naming conventions for tables, columns, measures, and other metadata.
Develop a library of DAX calculations as a time-saver for new development.
Implement dashboard design templates with layouts for filters, legends, cards, multi-row displays, drill-downs, and other common patterns.

Standardization, templates, and libraries accelerate the development of new dashboards while reducing quality problems. Users also appreciate a consistent experience.

Design for Customization

While standardization has benefits, it also architects dashboards for configurability:

Expose parameters to modify dashboard behavior, allowing “self-service” changes without developer help.
Implement row-level security roles to filter dashboard data dynamically based on the user.
Use conditional formatting to alert users when KPI thresholds are breached. Allow end-users to configure rules and colors.
Provide a way to add comments to dashboards so users can collaborate on data insights.
Export data to Excel, .pdf, and other formats for ad hoc analysis.

Empowering users to customize dashboards to their needs without coding promotes adoption and “power user” evangelism.

Take a Mobile-First Approach

Healthcare is a mobile-first industry. Clinicians accessing dashboards on rounds need responsive design:

Use device-specific layouts to optimize screens for desktop browsers vs. smaller tablets and phones.
Simplify visuals for smaller displays while keeping KPIs visible.
Allow touch interactions like taps, swipes, scrolling, tooltips and popups.
Test on all target device types during development sprints.
Implement adaptive rendering so visualizations resize gracefully without horizontal scrolling.

Designing for mobile-first meets clinicians where they are already working. Optimization for different devices also benefits all users.

Implement Strong Security

Protecting patient data is a prerequisite for healthcare software.

Encrypt data both at rest and in transit over networks. Use signed certificates for SSL connections.
Mask direct identifiers (names, social security numbers) to avoid exposing PII unnecessarily.
Implement role-based access controls using Active Directory groups for simplified user provisioning.
Log user activity for auditing data access.
Use a VPN for external/remote user access. Require multi-factor authentication.
Conduct periodic penetration tests to validate security defenses and infrastructure configurations.

While no system is impenetrable, combining security best practices makes unauthorized data access extremely difficult.

Plan for Change Management

The most brilliant dashboards only deliver value if users actually adopt them. Get ahead of change management challenges:

Identify executive sponsors across IT, clinical, and operational areas to promote adoption.
Train users on dashboard capabilities with hands-on workshops and videos. Maintain online documentation and help.
Start small and iterate to build confidence with early user groups before expanding.
Encourage input and feedback to drive dashboard improvements in later releases.
Market success stories internally showing measurable improvements from dashboard usage.

Proactive change management and training help user groups across the organization benefit from the new analytics capabilities.

Conclusion

Building custom healthcare software with integrated Power BI dashboards enables data-driven insights for smarter decisions across the organization. Following these best practices for design, architecture, development, security, and change management helps ensure successful adoption and measurable improvements in patient care and financial performance. Keys to remember include: