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Webinars

Top 10 ‘Must Haves’ for Payer Account Reporting

On-Demand Webinar Details:

Understand from an industry veteran the fundamental components needed in an analytics platform to deliver comprehensive account reporting to drive actionable improvements in cost and quality. The webinar will provide the audience with lessons learned and insights on what the Top 10 ‘must haves’ are for payer account reporting.

Webinars

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.

Speakers:

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 http://www.beckershospitalreview.com/healthcare-information-technology/ 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.
Case Studies

Population Health Management Analytics: Better Population Targeting with Healthcare Data

Client Profile: Lowe’s

  • Location: Mooresville, North Carolina
  • Industry: Retail
  • Number of employees: 265,000

Key Program Highlights

Through their collaboration with HDMS, Lowe’s is now able to:

  • Understand trends within a population
  • Create patient-oriented, pro-active health programs
  • Shift focus from treatment to wellness
  • Emphasize more cost-effective health choices
  • Communicate and incentivize healthy lifestyle choices
  • Collect data in a safe & secure way
  • Analyze biometric, medical and pharmacy data
  • Compare Lowe’s population to national health benchmarks

Lowe’s has been working with HDMS since 2006 and the relationship continues to grow and expand. Lowe’s relies heavily on its health data to understand trends within its population and also to identify any patterns that may indicate the need for proactive intervention to improve its population’s overall health. The strength of the relationship allows HDMS to work as an extension of the Lowe’s benefits organization.

The Situation

Starting in 2011, Lowe’s began to make its health programs and services more patient-focused and proactive. To gain visibility into its population, Lowe’s knew that it would have to rely even more heavily on its health data to successfully shift from a focus on treatment to prevention and wellness. Such a transition, if successful, would further the company’s commitment to patient-centered care while emphasizing more cost-effective health choices.

Lowe’s was looking to achieve the Triple Aim of health care – better health outcomes, lower costs, and a better patient experience – by focusing on the programs and services most likely to help maintain and improve the health of its employee population. Only by garnering clinical, risk, financial, and wellness data would Lowe’s be able to effectively communicate its new health and wellness strategy to its population.

The Need

Lowe’s needed to find ways to more effectively craft and target messages about its health and wellness programs to different segments of its population. By doing so, Lowe’s would be able to emphasize its programs that promoted better health while reducing overall health costs – all based on the support of strong data. Emphasizing health and wellness while reducing costs would help Lowe’s get closer to its goal of achieving the Triple Aim.

Not only did Lowe’s need to learn more about the health of its population, but it also needed to find ways to communicate and incentivize healthy lifestyles to its entire workforce. How to do this most effectively lay hidden in the company’s health data. HDMS helped unlock the answers.

The Solution

Using wellness data gathered from members logging onto the Lowe’s employee health portal, Lowe’s and HDMS were able to analyze the total employee population. This method allowed the needed data to be collected in a safe and secure way. A key benefit of using log-in data was the natural segmentation of the population into different groups by frequency of use. The data was then analyzed in multiple ways through the customized data analytics platform for Lowe’s.

The Lowe’s employee health portal log-in data was separated and mapped into six unique cohorts for further analysis among the total population:

  • All Non-users: employees whose IDs were not captured by the portal.
  • All Users: employees who had logged in regardless of frequency.
  • Situational Users: employees who logged in 1-3 times.
  • Novice Users: employees who logged in 4-11 times.
  • Active Users: employees who logged in 12-49 times.
  • Super Users: employees who logged in 50+ times.

HDMS analyzed biometric, medical, and pharmacy data. Lowe’s and HDMS then compared the population to national standards by  measuring a specific plan’s performance against recognized benchmarks and national standards.

The Results

By separating out and analyzing each of the cohorts – both individually and against the other groups – Lowe’s was able to discover much more than they originally anticipated about the health of its employee population. Specifically, the data revealed that there was a correlation between the frequency of employee logins and an increase in risk factors for chronic diseases. By using this data, Lowe’s was able to target messages to the high frequency users that would emphasize prevention, health and wellness to the segment of its population that most needed those messages reinforced.

When looking at the correlation between demographics and risk, the data revealed that the average age and risk of each cohort population was comparable until the log-in frequency increased, starting with Novice users. The data revealed that users who log-in more frequently tend to show a different pattern of health services utilization – including preventative health screenings such as for colon, breast and cervical cancer. Among Novice, Active and Super users there was also a noticeable difference in age as well as in both prospective and retrospective risk. HDMS also analyzed variances in BMI among the populations.

By discovering a possible correlation between certain health indicators and frequency of log-ins to the member portal allowed Lowe’s to create targeted messages about the weight loss programs it offers, prevention strategies, healthy diet and exercise advice, and information about heart disease, diabetes and other diseases customized to address those specific health characteristics.

The data revealed overall population health – and shed light on where and how the company could develop and share messages with certain cohorts of its population that will help improve overall health while controlling costs. Additionally, the data gave Lowe’s clear insight into both how to communicate with its population and what wellness messages would resonate with different cohorts within its population.

 

Lowe’s Case Study

White Papers

The Power of Prescriptive Analytics in Healthcare

Imagine two health plan sponsors that each employ ~10,000 mostly blue-collar workers. These plans decide to launch care management programs designed to reduce unnecessary emergency department (ED) visits and costs. The initiatives make sense, based on reams of data suggesting that a number of employees at both companies are receiving care in the ED that could be treated more appropriately — and less expensively — in an office or retail clinic setting, or possibly through a telemedicine visit.

Both programs include care managers and access to a triage service designed to divert patients from the ED to a primary care clinician. For those who end up in the ED despite these efforts, the member’s primary care clinician is notified of the patient’s status in the ED, increasing the likelihood of better care coordination. To reduce the chance of an ED revisit, the patient is sent home with educational materials about appropriate settings for health care.

One year after the programs were launched, ED visits and spending are down for both firms, but one realizes significantly larger savings. It turns out that when setting up the program, this employer had the foresight to act on an insight the other did not — the fact that a small number of its workers were habitual visitors to the ED. Armed with that knowledge, this employer rolled out a “right-sized” program that hit the bullseye. Meanwhile, the other company must scramble to play catch-up. In hindsight, the second company now sees that it could have succeeded with fewer care managers and a more streamlined telemedicine program focused mainly on habitual ED users.

Prescriptive analytics is the difference between having foresight and relying on hindsight. It is the difference between getting it right the first time, rather than doing so months or years — and potentially millions of dollars — later.

Prescriptive Analytics Tell You What to Do

The answer for employers like those profiled above is to invest in a platform that taps into the power of predictive and prescriptive analytics.

More often than not, reports that employers and payers rely on to make decisions are based on descriptive analytics — a summary of historical data that explains what happened. It’s great information, but provides only half the equation. Sometimes reports include predictive analytics, where information is extracted from existing data to explain what might happen in the future. This is the other half of the equation, which outlines multiple potential futures based on many possible actions. While predictive analytics is an improvement over descriptive analytics, using it alone can lead to confusion, given the many potential scenarios it produces.

What’s missing is a clear path to the best course of action. That is where prescriptive analytics comes in. It utilizes specialized software that pores over the many potential solutions and helps select the best one. The bottom line: Prescriptive analytics tell you what to do.

Payer Account Reporting “Must-Haves”

Payer account reporting is only as good as the data that comprises it. Insurers and employers whose prescriptive analyses are hitting the mark are likely using an analytics platform that offers the following:

  • Airtight security and data-integrity processes. Health care ranks near the bottom of major US industries in this regard. Legacy systems are particularly vulnerable in an era when attacks are more frequent and sophisticated. Best practices include:
    • Annual SOC II audits
    • Internal pen testing and static code scanning
    • Third-party pen testing and vulnerability scanning
    • Internal security auditing
    • Third-party daily review
    • Compliance with the National Institute of Standards and Technology’s security and     privacy controls
    • Role security
    • Secure passwords
  • Ability to link claims to biometric and other non-claims data. Allow plans and sponsors to go beyond diagnostic codes and adjudicated medical claims to identify illnesses earlier, in some cases before the recording of a diagnosis code on a claim. As an example, elevated BMI, cholesterol and blood pressure readings coupled with low current use of health services can unmask metabolic syndrome and potential high utilization in the future.
  • An online portal with key performance indicators and insights. 24/7 access to an easy-to-read dashboard of KPIs, along with an alert system that sends messages when a measure prompts a predetermined alert.
  • Proven methods to analyze trends. After spotting a troubling trend, use trusted tools from respected third parties to quickly get to the bottom of what’s causing it. For example, the Total Cost of Care model from HealthPartners of Minnesota can help determine whether cost, volume or intensity of service is the key driver. An analytics platform that offers a suite of such tools saves time and avoids aggravation.
  • Detailed insights into specialty pharmacy. This is the fastest growing component of medical spending, accounting for 36% of total drug spending in 2015. The keys are to:
    • have a common definition of specialty pharmacy and KPIs
    • design and refine cost containment strategies such as preauthorization programs, closed formularies and limited networks
  • Relevant benchmarks. Plan sponsors want to know how they compare to others. It’s important to have benchmarks that are up to date; large enough to be statistically credible and valid; and able to be broken out by region, plan design and industry type. They also need to be adjusted for age, gender and illness burden.
  • Network analysis. This is particularly important for employers who have moved to narrow or tiered networks. They will want to know why employees are going outside the network — specifically, what services are they seeking, from which providers and at what price? They’ll want to know whether to include a favored provider and at what price point. More importantly, they will want to know if providers in the network are the most efficient and/or high-quality in the area — or are there better choices?
  • Indicators of value-based care. As plans move from fee-for-service to prospective payment or value-based contracting, employers will want to know if their employees are actually receiving more high-value care and less low-value care. Just as important, are members receiving enough care? This is another instance where respected third-party tools come into play, making it easier for plan sponsors to monitor care and communicate findings with local providers.

Liberating the Power of Data with Storytelling

Finally, payer account reporting requires more than just a good analytics platform. Analytics can be little more than statistical noise unless they tell a story. Bridging the gap between data and a relevant story requires specialized skills from subject matter experts. They are the people who understand a plan sponsor’s goals and objectives, and they can tell the story to liberate the power of the data.

 

Prescriptive Analytics Whitepaper

Videos

Testimonial: Meritain Health

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

Videos

Network Leakage & Utilization

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Webinar: Differentiating Your Health Plan Through Proactive Analytics