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Watch how Leah Binder, CEO at The Leapfrog Group uses HDMS's data analytics to help identify preventable health care errors.


Differentiating your health plan through proactive analytics

Webinar Details:

An estimated 80% of health care data is unstructured and the number of data sources is growing at a rapid pace. In an ever-changing health care industry, innovative use of information assets is essential for payers to differentiate themselves from the competition and demonstrate value to their plan sponsors.

Today's payers are continually looking for new ways to mitigate cost increases and improve the health of their members. To optimize plan performance, they need strategic insights to gain control over cost drivers, implement new operational models and pinpoint opportunities that can make the biggets impact on quality and outcomes.

In this webinar, HDMS and Meritain Health, a leading national TPA will discuss common challenges that payers face. Through a series of demonstrations, we will share best practices and show to to leverage the power of data to create high-value, actionable information that can be shared within the organization and with the plan sponsors.

During this webinar, payers will learn how Meritain Health, who serves over 2,300 clients nationally, uses proactive analytics to:

  • Understand and respond to the drivers of clinical risk over time
  • Monitor, manage and take action to move towards desired outcomes
  • Use information-driven insights to guide business transformation and clinicial innovation

Learn how this leading TPA is leveraging actionable analytic intelligence to provide their plan sponsors timely information to inform decisions.


Rob Corrigan, Senior Director, Advisory Services, HDMS

Shawn Shapiro, Informatics & Data Governance, Meritain Health

White Papers

Predictive Analytics in Healthcare: Actionable Insights that Deliver Results

For stakeholders across the health care system, much of the knowledge and insight needed to make better value-based care decisions remains locked away within vast amounts of raw data. Here’s how one third-party administrator (TPA) used proactive analytics to unlock this knowledge, reduce costs and improve outcomes for clients.

There is no shortage of data in health care. Industry stakeholders— employers, plan sponsors, payers, TPAs, health systems and provider organizations—are sitting on vast amounts of raw data, and more is generated and collected every day from a growing number of sources.

Industry estimates indicate only about 20 percent of this data is structured, meaning it is quantitative and objective, including vital signs and health markers like blood sugar and cholesterol levels. Up to 80 percent of health care data is unstructured, or qualitative and subjective, such as patient assessments of pain and level of discomfort gathered during patient encounters.1

Structured data can reside in digital silos and in differing formats that may present barriers to sharing and analysis. The sheer volume and nature of unstructured data presents even more of a challenge; qualitative data is frequently stored in system text fields, making it difficult to retrieve, interpret and analyze.

The result: despite the large amount of data available, health care organizations don’t always have the right data they need to make effective decisions— especially because system transformation toward value-based care and population health requires different datasets for optimal decision-making.

Proactive Analytics Unlocks Value

Proactive analytics is the key to unlocking the value hidden away in mountains of raw structured and unstructured data. The spectrum of analytical capabilities—from descriptive and diagnostic to predictive and prescriptive analytics—is about processing raw data into useable information and turning that information into knowledge and actionable insight. Proactive analytics is about taking action—knowing where and how to act, and measuring the results of those actions.

For health care organizations currently under or transitioning to value-based contracts, proactive analytics offers a tremendous opportunity to optimize performance and gain a competitive edge by addressing affordability and cost concerns, delivering better value to stakeholders throughout the system, and managing through market uncertainty

HDMS And Meritain Health: A Powerful Strategic Partnership

HDMS enables health care organizations to seize this opportunity through a powerful analytics platform that securely aggregates and integrates data from any source and performs value-added analytics and reporting that transforms raw data into meaningful information, robust knowledge and actionable insights.

HDMS partners with stakeholders across the health care system that want to move from a reactive reporting model (common in fee-for-service environments) to a proactive, analytically driven solutions model to deliver greater value and better results to their clients and members. Meritain Health is one such stakeholder.

Meritain Health, a leading national TPA, is known for providing its clients with flexible, actionable data solutions, extensive network strategies, and integrated best-in-class partner support. The following use cases illustrate how Meritain’s strong partnership with HDMS has enabled them to deliver best-in-class proactive analytical intelligence and decision support to clients.

Trend Analysis

Standard health plan reporting shows comparisons of current versus prior periods. This helps identify trends but leads to questions of why there are differences and what is causing the changes. One of the most important ways proactive analytics unlocks value in data is by enabling a deeper understanding of what, exactly, is driving trends. HDMS’ Components of Trend methodology enables clients to drill into and deconstruct data patterns across a variety of components in order to pinpoint why trends are occurring and what is causing them—without undue extrapolation or guesswork.

Use Case 1: Improving Cost Trends

Meritain’s client, a large education system with 30,000 member lives, wanted to understand cost drivers behind a year-over-year increase in plan expenditures in order to reduce risk and lower expenses. Using HDMS’ analytics platform, a Components of Trend assessment revealed the emergency department (ED) service category was significantly affecting overall plan expenses due to inappropriate utilization.

Based on this analysis, Meritain made plan modifications and developed strategies to steer members to more appropriate care, including increased contributions for preventive care and the addition of a telemedicine provider. The changes resulted in a 17.4 percent reduction in ED visits, a 20.1 percent increase in utilization of preventative care, and a 4.2 percent decrease in overall plan spending.

High-Cost Claimants

High-cost claimants (HCCs) concern most payers and plan sponsors because although they typically represent about 1 percent of members, they account for 33 percent of spending. Early identification and mitigation strategies can be helpful, but plans are challenged in identifying which members will become HCCs since prior HCC status only predicts future status in 25 percent of cases.2

HDMS’ platform helps plans identify members at risk of becoming HCCs in the next 12 months through use of predictive models based on chronic and comorbid conditions and compliance history. The platform can also predict a program’s effect on members’ health status, enabling clients to offer appropriate services before the member becomes a HCC.

Use Case 2: Reducing HCC Expenses While Improving Health

Meritain’s client, a construction company with 500 member lives, wanted to decrease plan expenses while maintaining the best level of care and improving health outcomes, consistent with the company’s firm belief in investing in their people to drive success. Meritain used the HDMS platform to identify people with a chronic or comorbid condition at risk of becoming HCCs and compare HCC activity with medical and disease management program participation.

The analysis enabled the company to identify at-risk employees, develop early intervention and engagement strategies, and validate the positive effect of medical/disease management programs, leading the employer to provide greater incentives for participation. These strategies led to a 35 percent increase in program participation, a 6.2 percent reduction in HCCs, and overall plan savings of 23.7 percent due to the decrease in HCCs.

Specialty Drug Costs

According to HDMS client data, specialty drugs cost 10 to 15 times more than traditional drugs and account for about one-third of plan pharmaceutical spending. These costs are projected to grow about 20 percent annually. Managing this spending involves more than focusing on the drugs themselves. Cost must be considered in the context of the member’s medical condition, medication compliance and treatment efficacy.

By linking medical, pharmacy and other data sources, HDMS’ platform captures this holistic view and enables plans to zero in on the practical effect of specialty drug spending and developing strategies for reducing that spending while ensuring quality member care.

Use Case 3: Decreasing Specialty Drug Costs

Meritain’s client, a large education system with 30,000 member lives, wanted to gain a deeper understanding of pharmaceutical utilization and determine opportunities to decrease specialty drug expenses while ensuring quality care for members and improving health outcomes.

Meritain used HDMS’ platform to integrate medical and prescription data for high-cost and high-risk patients, then drilled down to ensure participation in a medical-management program focused on adherence and closing care gaps. When possible, members were moved to a lower dosage and frequency. The results included a 12.2 percent reduction in year-over-year medical expenses for members filling specialty-drug prescriptions and a decrease in specialty drug costs of 19.5 percent.

Network Leakage

Strategies to keep members in network provide an effective way to help control plan spending and ensure quality care and better care coordination— particularly important in the era of value-based care. HDMS’ analytics platform features built-in research capabilities for exploring network leakage and identifying members and conditions associated with inappropriate or ineffective out-of-network care, especially in high-cost service areas. These insights inform proactive interventions on both the member and provider side (for example, a member’s assigned primary care physician) to keep care where it is most cost effective.

Use Case 4: Understanding and Stopping Network Leakage

A Meritain hospital system client with 9,000 member lives wanted to gain a deeper understanding of how care was delivered outside their network by analyzing referral patterns, member demographics and treated conditions, as well as address challenges related to domestic providers referring members to out-of-network care.

Using analytical data from the HDMS platform, Meritain was able to recommend interventions, including education and outreach to referring providers, that resulted in 38 percent fewer out-of-network referrals, 14.4 percent greater network use, and an overall reduction of 10.8 percent in the hospital’s medical plan spending.

About Meritain Health

National leader in third-party plan administration, business process outsourcing, self-funded plan designs, network management solutions and health management strategies

  • Over 30 years of experience
  • Over 1 million member lives across the U.S.
  • Independent subsidiary of Aetna
  • 70% increase in member population since 2011

Proactive Analytics Whitepaper



  1. Smithwick, J. (2015) Unlocking the value of unstructured patient data. Becker’s Health IT & CIO Review. Retrieved from unlocking-the-value-of-unstructured-patient-data.html
  2. Wilson, D., Troy, T., Jones, K. (2016) High Cost Claimants: Private versus Public Sector Approaches. American Health Policy Institute and Leavitt Partners.

Testimonial: Meritain Health

Watch how Shawn Shapiro, Director of Client Analytics at Meritain Health uses HDMS's data analytics to help drive decisions.


Specialty Pharmacy


Network Leakage & Utilization


Measuring Cost Trends For Impact

Case Study

Reducing Readmissions from Skilled Nursing Facilities in the Era of Value Based Care


In an effort to improve health care quality, safety, and outcomes, a large Midwestern health system representing 720,000 attributed members (including commercial, Medicare, and Medicaid populations) collaborated with Health Data & Management Solutions, Inc. (HDMS) to examine transition of care (TOC) data. This assessment examined discharges from skilled nursing facilities (SNF) that resulted in readmission to an acute care hospital within 30 days.

The Need

Hospitalizations associated with long-term care residents can be expensive and lead to negative outcomes for individuals in skilled nursing facilities, especially for the elderly and people with disabilities. Research has shown nearly a fourth of SNF stays result in a hospital readmission within 30 days of the initial admission, costing an average of $10,000 per hospitalization.¹

To provide residents with better care experiences and outcomes, the health system sought to assess all of its SNF stays taking place between the first acute and second acute stay. This measurement would provide the health system’s clinical leaders with a more complete picture of the number of admissions from or into a SNF. In addition, this patient-level data would provide the health system with actionable insights for advancing their quality initiatives and improving care, as well as identify preferred facilities based on their success in keeping patients from returning to the hospital.

The Analytic Challenge

The challenge the health system faced was linking several clinical events at the patient level and across time. To appropriately assess TOC data, the health system needed to identify all SNF stays, including transfers and multiple admissions. Using this information, they pinpointed the initial acute care hospitalization and determined if there was a subsequent readmission to an acute care facility within 30 days of the discharge date of the initial hospitalization. Further analysis required readmission rates—defined by the number of readmissions to acute care facilities divided by total SNF stays—to be broken out by patient type, facility, etc., to develop and drive quality improvement programs.

The Solution

Working closely with the health system, HDMS created new metrics to account for and identify all SNF transfers. These new metrics counted readmissions starting with the initial acute admission, SNF stay, and subsequent acute readmission within 30 days of initial discharge. HDMS’ flexibility in identifying all necessary SNF transfers data provided the health system with a comprehensive view of acute readmissions. The adjusted logic—including a SNF transfer in between admissions—resulted in more meaningful data to support the measurement and analysis of SNF quality and performance.

The Results

Upon implementation of the metrics, the health system was able to identify key insights that allowed for actions to reduce readmission rates. By expanding the analytic parameters for SNF readmission measure, the health system could more accurately assess readmissions, trends and SNF quality.

For example, the health plan uncovered overlooked readmissions that were not factored into the overall readmission rate. This data enabled the health plan to determine the true overall readmission rate, which was higher than previously understood. Armed with this new insight, the health system was able to better align resources and reduce its list of SNFs from approximately 100 facilities to a preferred set of 41 facilities with the best performance. This initiative increased the quality of care for the health system’s patients while reducing readmissions to acute care facilities and costs. The new SNF readmission measure has also been used in profiling quality across more than 400 physician groups within the health system’s network—resulting in similar positive changes being observed across the entire network.


Provider Case Study


¹Mor, V., Intrator, O., Feng, Z., et al.: The revolving door of rehospitalization from skilled nursing facilities. Health Af. (Millwood) 29(1):57-64, Jan.-Feb. 2010.


Webinar: Differentiating Your Health Plan Through Proactive Analytics