Data trust: The foundation for informed decision-making

By Milliman MedInsight

7 March 2024

When it comes to getting the most out of your data, there is nothing more critical than the process by which you ensure that it is reliable.

Unfortunately, it is not easy to integrate many sources of healthcare data and ensure that it is not only accurate, but that it works together to deliver the insights you need.

While decades of actuarial and healthcare analytics experience may set Milliman MedInsight apart from other healthcare data analytics options, our process for ensuring data confidence is the foundation of everything we do for our clients.

The MedInsight data confidence model

The MedInsight Data Confidence Model is the product of our experience, but also the product of a mindset that takes nothing for granted. It is both a tool and an ongoing process for ensuring not just the quality of every single component and field, but also assessing to ensure that data makes sense in context.

That means claims data that holds up on its own and still holds up when clinical provider data and member data is layered in, so the cross section produces a valid, high-quality output. It includes searches for industry standard coding, compares results against Milliman benchmarks, and confirms that key business criteria and metrics are accurate and credible, including risk scores, episodes, and other evidence-based measures.

When we find errors, we go back to the source to ensure they have pulled the extract correctly and to learn if there are anomalies or practice patterns that may have impacted the data.

It is a structured and ongoing process incorporating formal steps, tools, peer review and more than 40 separate audits for identifying issues across file type to ensure that the data we collect for our clients is accurate, reliable, and understood across the enterprise.

Steps for building credibility, closing gaps

Embracing industry best practices, the DCM employs a tiered approach to evaluate data quality, utilizing the medallion architecture of bronze, silver, and gold. Here is how it works:

1. As the data files are submitted, the DCM’s automated file intake function provides immediate online feedback to the data suppliers regarding data file structure.

2. As files are received, automated file field and quality checks are run to identify possible data issues.

3. After the data has been accepted, additional data integrity tests are conducted. These tests, which include data submission comparisons over time, identify issues with the data that cannot be seen at an individual data file or field level.

4. By having access to data, it becomes possible to review various analytics, such as Benchmarks, Health Cost Groupers, Health Waste Calculator, and more. Additionally, the quality of the data can be assessed, including custom data quality artifacts designed for specific use cases.

A foundation of trust

Throughout the process, the system provides feedback to data suppliers, builders of decision support systems, and analytics end users so issues can be quickly identified and resolved.

The result is more than reliable data you can use to drive strategy and decision making; it is the trust and credibility you need to move your strategies forward.

Any analytics vendor can promise you reliable data, but what is their process to ensure you can trust your data and how fast can they deliver your data every month? The MedInsight Data Confidence Model is more than just solid analytic practices – it is a unique and transparent system of communication and participation that efficiently and effectively provides data reconciliation across multiple viewpoints. It is designed to ensure:

  • Delivery of your data in days vs. weeks
  • Timely communication back to data suppliers
  • Understanding of data limitations and gaps
  • Detailed auditing to identify hard-to-find issues, missing data and nonstandard coding
  • Identification of appropriate uses for data
  • Monthly file reconciliation and data quality validation against independent financial records
  • Accurate data that can be as granular as line of business by month

Partner with Milliman MedInsight for data you can use to do more

Leveraging trustworthy data, you can discover valuable insights and provide compelling recommendations that lead to improved patient outcomes, while simultaneously reducing risk and cost. This enables you to adapt and thrive with a competitive advantage in the ever-evolving healthcare industry.

Learn more about how Milliman MedInsight, leveraging the Data Confidence Model, will enable you to spend more time analyzing and less time cleaning your data.

Speak with a MedInsight team member today –or request a demo.

Contact us to learn more about healthcare data analytics