1998
1998
MedInsight History
Our journey of innovation and impact
For over 25 years, Milliman MedInsight’s participation in the world of healthcare analytics has centered on our cutting-edge tools and solutions that are revolutionizing the industry. Milliman MedInsight understands that success in healthcare requires collaboration across the entire ecosystem, from payers and providers to ACOs, purchasers, and consultants. With a strong foundation in actuarial science and extensive expertise in healthcare, Milliman MedInsight is dedicated to empowering payers and providers.
How Milliman MedInsight makes a difference in the market:
Milliman MedInsight Data Confidence Model
Ensure credible, high quality data, with speed to interpretation
Industry-leading Milliman MedInsight Benchmarks
Better evaluate what is driving cost, utilization, and trends within your population
Consultants
Milliman’s long history in actuarial science gives us a leg-up with unbiased research and expertise in risk assessment and healthcare management
Actionable savings
Identify, implement, and measure within a specific timeframe and immediate follow-up steps to act upon
Curated reporting
Tailored and specific reports to our clients needs across all healthcare markets
Data aggregation including EHR
Support better care coordination, health outcomes tracking, and decision-making with comprehensive integrated data
Relevant resources
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What to look for in ACO healthcare software: A buyer’s guide
Choosing accountable care organization (ACO) healthcare software is often handled as a procurement exercise, but the decision shapes how clearly your organization understands its financial position for years afterward. The quality of that decision is difficult to judge from a vendor demonstration, because most value-based care (VBC) software presents a similar front end: attributed lives, … What to look for in ACO healthcare software: A buyer’s guide
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HEDIS MY 2027: Key Changes healthcare organizations need to know
The National Committee for Quality Assurance (NCQA) has announced several upcoming changes to the Healthcare Effectiveness Data and Information Set (HEDIS®) that will influence how organizations measure, report, and improve quality of care.1 For Measurement Year (MY) 2027, these updates reflect emerging clinical priorities, advances in technology, and the healthcare industry’s continued shift toward digital … HEDIS MY 2027: Key Changes healthcare organizations need to know
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Case Study
Modernizing healthcare analytics to deliver faster cost and utilization insights
Cambia Health Solutions (Cambia) serves more than 2 million members through its regional health plans and is guided by a mission to make healthcare easier and lives better. To support that mission, the organization set out to strengthen its analytics foundation with a more scalable, reliable approach to delivering timely, trusted insights for actuarial and … Modernizing healthcare analytics to deliver faster cost and utilization insights
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What is risk adjustment software? A guide for healthcare organizations
Risk adjustment depends on accurate data, complete documentation, and consistent workflows. For healthcare organizations managing risk-based contracts, those requirements can become difficult to coordinate across teams, systems, and populations. Claims data may live in one place, clinical data in another, documentation review in a separate workflow, and reporting in static dashboards or spreadsheets. Risk adjustment … What is risk adjustment software? A guide for healthcare organizations
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Whitepaper
The importance of data selection in AI model training, testing, and deployment
Artificial intelligence is only as good as the data behind it. In healthcare, even small differences in inputs can lead to vastly different outcomes, making data quality and provenance critical to evaluating AI models. This whitepaper introduces the Milliman MedInsight Data Confidence Model, a structured approach built on 25 years of experience matching the right … The importance of data selection in AI model training, testing, and deployment
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Signs your organization needs better clinical and claims data integration
Almost no healthcare organization intentionally builds a fragmented data environment. Fragmentation develops through reasonable decisions: an acquired practice arrives with a second EHR instance, a risk-based contract introduces another payer file, a vendor relationship brings in laboratory or pharmacy feeds. Their combined effect is a set of systems describing the same patients and members differently. … Signs your organization needs better clinical and claims data integration
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How to choose the right risk adjustment vendor
Executive Summary Choosing a risk adjustment vendor should never be reduced to coding function alone. The right platform should improve documentation quality, integrate into clinical and operational workflows, provide transparent analytics, support prospective and retrospective programs, and maintain audit readiness. Organizations should prioritize configurable technology, explainable AI, strong governance, measurable outcomes, and an implementation approach … How to choose the right risk adjustment vendor
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Responsible AI in healthcare analytics: The MedInsight approach
Key Highlights Introduction› Analysis in the AI era› Principles of AI adoption at MedInsight› Conclusion› Download the white paper Introduction The recent explosion of artificial intelligence (AI) capability and deployment at scale has dramatically altered conversations and expectations for technology solutions. Healthcare and healthcare analytics are no exceptions to this. AI as a technological innovation … Responsible AI in healthcare analytics: The MedInsight approach
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Heart failure admissions: Cost implications of potentially avoidable inpatient care
Key Highlights Background› Methodology› Analysis› Conclusion› Download the article Heart failure (HF) represents one of the most pressing cardiovascular health challenges facing the United States (US). According to the CDC, heart failure occurs when the heart cannot pump enough blood and oxygen to meet the body’s needs. Although it is a serious condition, it does … Heart failure admissions: Cost implications of potentially avoidable inpatient care
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Examining trends and impacts of rising cesarean section delivery in nulliparous women
Key Highlights Introduction› Study population and delivery trends› Maternal age and payer mix› Costs and complications› Conclusion› Download the article Childbirth is the leading cause of hospital admissions in the United States, with cesarean deliveries being the most frequently performed surgical procedure.1 Cesarean deliveries are a crucial and life-saving intervention2 but they can also pose … Examining trends and impacts of rising cesarean section delivery in nulliparous women
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Why clinical data aggregation is essential for better healthcare analytics
Clinical data accumulates in many places at once, collecting in electronic health records, laboratory systems, pharmacy platforms, care management tools and claims files, each with its own format and update schedule. The consequences are familiar: two departments run comparable reports and arrive at different figures, and analysts spend their time reconciling records instead of interpreting … Why clinical data aggregation is essential for better healthcare analytics
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When screening becomes waste: Ovarian cancer testing in asymptomatic women
Key Highlights The “Silent Killer” and the Urge to Screen› The Current State of Ovarian Cancer Screening› Key Findings From the Analysis› Conclusion: Turning Insight Into Action› Key Takeaways for Healthcare Leaders› Download the article The “Silent Killer” and the Urge to Screen Ovarian cancer is the deadliest gynecologic cancer and the 10th leading cause … When screening becomes waste: Ovarian cancer testing in asymptomatic women
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