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Webinars

Tiered Provider Networks: BCBS-SC Explores Learnings and Future Potential

In this webinar, the speakers explain how they used data analytics reporting to track and manage their tiered networks.  They focus on steerage, utilization and other specific metrics – and how it has changed over time.

Speakers: Mike Harris, Vice President, BlueCross BlueShield of South Carolina and Brent Raymond, Director Payer Account Services, HDMS

Case Studies

Maximizing the Potential of Healthcare Data for Better Population Targeting

Read how Lowe's works with HDMS to understand trends within its population and  identify patterns that may indicate the need for proactive
intervention to improve its population’s overall health.

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Case Studies

Measure the Impact of Preventative Cancer Screenings with Patient Outcome Analytics

A case study for employers and health plans

The Need

The Affordable Care Act (ACA) requires employers to fully cover preventive screenings for breast, cervical/uterine and colorectal cancers.

For one state agency, declining member utilization of these preventive screenings was a cause for concern. Why were utilization rates dropping? Moreover, what impact was the reduction having on the agency’s costs and its members’ health outcomes?

The Analytic Challenge

The state agency, which administers health benefits for 205,000 employees and dependents, set out to identify the cost and outcomes of the ACA-required preventive cancer screenings. What the agency really wanted to know was whether the screenings were resulting in earlier cancer detection, which in turn required less invasive and less costly treatment.

For quite some time, the agency simply assumed that the screenings were cost effective. The challenge was to accurately quantify their impact at a time when:

  • The American Cancer Society (ACS) released new, more targeted guidelines that lowered the number of people it recommended for the preventive screenings.1 (The ACS believed the change would result in higher prevention rates even with fewer people screened.)
  • Screening utilization was declining.
  • Only 6 to 8 percent of members who were screened were actually diagnosed with cancer or a related condition as a result.

The Solution

The state agency’s population health manager (PHM) uses HDMS’ analytics and reporting solution on a quarterly basis to analyze trends in cost and utilization of employee benefits. With HDMS’ data management expertise, the PHM trusted the credibility of the analysis. To further evaluate the cancer screenings, the PHM took advantage of the solution’s built-in evidence-based guidelines to create episode-based analysis groups (cohorts) from claims and enrollment data to measure whether members:

  • Were diagnosed with any cancer within the three years prior to being diagnosed with breast, cervical, uterine or colorectal cancer. (This helped to identify new cancer cases as opposed to recurring cancer cases.)
  • Received medical services for a cancer diagnosis within 60 days of a preventive cancer screening.

The Results

Analysis clearly showed the value of preventive cancer screenings for members and for the state agency:

  • The majority of new cases of breast, colorectal and cervical cancer among the agency’s members were initially diagnosed as a result of preventive screenings.
    • 80% of new cases of breast cancer were associated with preventive screenings¹
    • 11% of members who received screenings received additional treatments – not just for cancer
    • Cervical cancer screenings led many members to additional uterine or ovarian testing
  • Members diagnosed with breast, cervical, uterine or colorectal cancer through the preventive screenings experienced fewer medical complications, as shown through lower relative health risk scores.
    • Breast Cancer
      • 00 Average risk score of members diagnosed with breast cancer
      • 88-6.53 Average risk score of members diagnosed with breast cancer
    • Cervical Cancer
      • 00 Average risk score of members diagnosed with breast cancer
      • 31-4.22 Average risk score of members diagnosed with breast cancer
    • Those diagnosed through preventive screenings recorded lower total costs of cancer care on a risk-adjusted cost basis, as well as relative to expected cancer treatment costs.
      • 9% Decrease in the cost of treatment for breast cancer
      • 6% Decrease in the cost of treatment for colon cancer
    • Overall, paid claims for all three types of cancer screenings was 3.6 percent lower than in previous years.

Data-informed insight improves health

Today, the state agency reviews a preventive screening dashboard every quarter to monitor outcome metrics. Furthermore, working together with HDMS to perform proactive data analysis may open up new insights into opportunities to reduce costs and improve member health. It’s just one powerful illustration of how robust data analysis can help employers and health plans measure and enhance the effectiveness of preventive health benefits.

In the Know

The ACS’ updated preventive screening guidelines are now focused on smaller populations. However, they target age and gender groups that account for 82 to 92 percent of breast, cervical, uterine and colorectal cancer diagnoses. Screenings identify 68 percent of new breast cancer cases and more than 89 percent of other new cancer cases earlier. So, although the number of eligible members who received preventive cancer screenings declined, compliance with Healthcare Effectiveness Data and Information Set (HEDIS) guidelines, which measures individual clinical care influenced by health plan programs, generally improved. (The exception was compliance for breast cancer screenings.)

 

Cancer Screening Case Study

 

¹Grady, D., “American Cancer Society, in a Shift, Recommends Fewer Mammograms,” The New York Times, Oct. 20, 2015, https://hms.harvard.edu/news/american-cancer-society-shift-recommends-fewer-mammograms

HDMS proprietary data

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.
Useful Documents

Specialty Pharmacy Data Analytics

Analytic value

With specialty pharmacy analytics, organizations can:

  • Track specialty drug trends year-over-year to support forecast models and understand the financial impacts of specialty pharmacy needs within specific populations.
  • Identify the top 10 most commonly prescribed medications to determine benefit/formulary management strategies.
  • Target top prescribers of specialty drugs and potential outliers to inform provider education programs.
  • Assess appropriate off-label prescribing vs. potentially inappropriate prescribing patterns.

About the analytics

Recognizing the growing significance of specialty drugs, HDMS has developed a new analytics package designed to track cost and utilization of specialty drugs within a client’s population and thereby inform future actions.

  • Our specialty drug reporting package provides:
  • An overview of specialty drug utilization and costs
  • Three-year trends, including pharmacy vendor costs and forecasts of future costs
  • Identification of top specialty drugs used by your population and top prescribers of specialty drugs
  • Evaluation of specialty pharmacy drugs provided in a clinical setting by episode treatment group

These reports utilize HDMS’ standard Specialty Drug list. As there is no industry-wide standard definition of specialty drugs, HDMS’s specialty drug list is comprised of pharmaceutical products that address complex, chronic, or rare conditions with multiple comorbidities (e.g., cancer, rheumatoid arthritis, multiple sclerosis). The HDMS definition is updated monthly, incorporating up-to-date research and new National Drug Codes.

Implementation

Data needs: These reports are developed from existing pharmacy claims and require standard pharmacy data sources. In order to properly identify the prescribing provider, HDMS requires vendors to provide this information within the claims data submitted for our analytical usage.

Timeline: Please work with your account manager to promote these standard reports into your HDMS data analytics platform environment.

Business need

Specialty drugs represent a significant portion of pharmacy spending. In 2014, less than 1% of all prescriptions were written for specialty drugs, yet they accounted for approximately 32% of total drug expenditures and 11% of total health care spending.¹ It is projected specialty drugs will account for 50% of all pharmacy spending ($235 billion) by 2018.² HDMS specialty pharmacy analytics are designed to help you stay on top of these growing trend.

 

Specialty Pharmacy Analytics

 

­­­­­­­­­­­­­­¹Express Scripts. Insights: U.S. Rx Spending Increased 13.1% in 2014. http://lab.express scripts.com/insights/industry-updates/ us-rxspending-increased-13-percent-in-2014.

²Lotvin, Alan M; Shrank, William H; Singh, Surya C; Falit, Benjamin P; Brennan, Troyen A. Health Affairs 33.10 (Oct 2014): 1736-44.

Case Studies

Population Health Analytics Strategy Reveals Opportunities for Improvement

Background

South Country Health Alliance (SCHA) is a county-based health plan serving twelve rural Minnesota counties. Formed in 2001, SCHA offers seven programs to its more than 41,000 members, all of whom are Medicare and Medicaid participants. SCHA’s mission is to empower and engage its members to be as healthy as they can be, build connections with local agencies and providers who deliver quality services, and be an accountable partner to the counties they serve.

The Need

SCHA’s overall objectives were to improve key performance indicators for its population health and care management programs, and better control costs while improving quality and care coordination. SCHA leadership identified four primary obstacles to achieving these objectives:

  1. Inability to aggregate comprehensive data from multiple community partners, all of whom used different data types, formats, schedules and rules for utilization.
  2. Lack of an analytical tool that would enable greater utilization transparency and help address growing cost containment pressures.
  3. Poor overall population management due to health care disparities in rural communities across the twelve-county service area.
  4. Health care delivery was focused primarily on more expensive reactive treatment versus less costly preventative care.

The Analytic Challenge

In order to address these challenges, SCHA needed to answer key questions about its member population; for example: Where are costs being generated? What are the trends in medical and prescription drug utilization? Are there anomalies in care plans, products, age groups or service categories that require management action?

Access to the comprehensive, actionable data required to answer these types of questions was difficult to obtain for two reasons. First, numerous community partners across SCHA’s geographically dispersed service area used disparate systems and datasets, so data intake was a challenge. Second, data was delivered to SCHA in multiple formats using varying monthly schedules and inconsistent rules for utilization, making the data difficult to analyze, consume and interpret.

The Solution

Working closely with HDMS, SCHA’s first step was to build an enterprise data warehouse to facilitate data gathering from disparate source systems across the twelve-county service area. This enabled data intake to be standardized, allowed for more efficient data aggregation and storage, and provisioned the stored data for analysis and reporting.

The second step was to unlock the value of the warehoused data through an HDMS solution that enriched the data, enabled robust analysis through various lenses, and supported reporting of data in a consumable format to aid interpretation and decision making. The HDMS solution addressed SCHA’s functional needs, as well as ensured ease of-use to internal staff and their community partners.

The Results

  • Initial cost savings: SCHA and HDMS worked together to expedite implementation of the HDMS solution by approximately 15 percent or 37 days. As a result, project costs were reduced by approximately $300,000, allowing SCHA to redirect these resources to support its mission and operations.
  • Enhanced analytical insight: Using data gathered from various feeder systems and enriched through the HDMS solution, SCHA is now able to conduct in-depth analysis into key areas of its population: uncovering where gaps in care are most prevalent, tracking utilization and cost trends by program and service type, identifying service type anomalies, and more.

For example, the population can be segmented into county-by-county analytical cohorts — such as episode treatment groups (ETGs) — enabling SCHA to identify opportunities for greater efficiencies in cost or utilization. As a result, care management programs are more effective, costs are better controlled, disparities are reduced, and overall population health improved. 

  • Ease and consistency of reporting: Analytical reports are produced in easy-to-consume formats that vary based on the needs of the audience while preserving patient confidentiality. Community partners in each of the twelve counties are now evaluated using common metrics. Best practices of those with favorable performance characteristics are shared with partners in other counties to improve overall quality and population health.
  • Improved decision making: Because of the ease with which a variety of reports can be generated, SCHA senior leadership is able to review operations more frequently and with greater consistency. Performance metrics that are outside a specified tolerance zone or trending unfavorably are quickly identified and rapidly addressed through additional management assistance and attention.
  •  Long-term value: SCHA is now able to transition its health care resources from reactive treatment to more effective and cost-saving preventative care, promoting greater value and member health improvement, and enabling SCHA to better fulfill their mission.

 

View the Case Study

Case Studies

Custom Healthcare Payer Data Analytics Solution Improves Analysis of Health Management Data

Client Profile

  • Location: Southeast
  • Industry: Health Insurance
  • Number of covered lives: + 1,000,000

Key Program Highlights

Through their collaboration with HDMS, the insurer is now able to:

  • Unite market and product data in one platform
  • Standardize reporting processes
  • Produce reports relevant to diverse audiences
  • Enhance visibility into datasets
  • Complete an accurate analysis of program costs
  • Demonstrate value of health management programs
  • Save users valuable time and resources from manual reporting

As the number of programs designed to promote health and wellness continues to grow, so does the need to collect, normalize and analyze increasing volumes of health management data. This was certainly the case for a large Southeastern health insurance company, representing nearly one million participants.

Like other health care organizations, clinical reporting at the organization had become more complex and detailed over time. The lack of a cohesive and uniform platform paired with the growing need to integrate health management program data with other types of clinical and cost/use information increased demands on already limited resources. The use of multiple reporting tools across different business units also resulted in frequent data reconciliation issues, making accurate reporting a costly and time-consuming endeavor.

In addition, the insurer needed an effective method for evaluating the costs of the health management programs it offered to members. Together, the insurer and HDMS established a plan for leveraging current analytic solutions to gain additional insights, better meet the needs of its employer clients and address an increasing complex set of reporting needs.

The Situation

As a longstanding HDMS customer, the insurer successfully used HDMS’s flagship data analysis and reporting tool for more than 10 years. As part of the expanded collaboration, the insurer worked with HDMS to fully integrate the data from several ancillary services into the tool. The organization also expanded its collaboration with HDMS to include Population Health Management analytics which deliver presentation-ready management reports for its employer groups.

To build on these investments, enhance visibility into its datasets, better evaluate costs and demonstrate program value, the next step was to implement a more comprehensive – yet flexible – way to analyze and review health management program data. By placing data into one unified platform, the insurer sought to increase efficiencies, save valuable staff time and preserve resources that could be devoted to other mission-critical tasks.

The Need

At the outset of the project, the insurer identified a number of specific needs and requirements the new clinical health management reporting platform would need to meet, such as the ability to input new data from diverse sources and apply standardized codes and formats. The platform would also need to allow intuitive, easy access for users, including case managers, company leadership, health managers and account managers.

Recognizing the development of such a solution would require tight collaboration and flexibility between both organizations, HDMS worked closely with the insurer to meet these needs by:

  • Incorporating new data sources as they were identified
  • Establishing a uniform, underlying file architecture
  • Formulating diverse enrollment, engagement terminology and access codes between health management, case management and complex care
  • Reaching consensus on data methodology and reporting objectives

The Solution

The collaboration between HDMS and the insurer resulted in a highly flexible, customized and user-friendly system. Building on the existing data analytics platform, the new solution allowed data input from many more sources – including disease management, case management, lifestyle management and wellness program data – all of which were vital to assess the effectiveness and utilization of health management programs.

The new platform also unified codes, standardized processes and provided customized templates, tables and dimensions that took the needs of all health data end users into consideration.

Ultimately, more than 30 customized clinical eligibility dimensions – a collection of reference information used to determine whether a member may or may not be considered to have a condition or be allowed to enter a care management program – were added to the platform to facilitate greater data analysis and reporting. These included both participant and risk dimensions as well as customized data tables for a range of wellness-specific initiatives.

The Results

As a result of this collaboration, HDMS’ customized reporting solution has delivered a wealth of benefits for members and staff. One of the biggest advantages so far has been the ability to combine data, analysis and reporting in one platform. In conjunction with the predictive modeling tool, users can quickly and easily analyze enrollment, participation and cost data for a wide range of health management programs.

“The biggest value from the HDMS platform is the customization of the data base based on customer’s specific needs. The  platform allows us to send and pull data independently of other areas. Now we can add indicators to HCC reports to identify participants and see if they’re in disease management, case management or maternity management.” – Medical Director

Additional benefits include:

Reduced wait times for reports

“Without the need to aggregate multiple platforms, reports that once took staff all day to produce can now be generated in as little as an hour. Beyond dramatically accelerating report delivery times to clients and staff, these new efficiencies have freed up valuable resources that can now be devoted to other projects and initiatives.”

Higher Client Satisfaction

Whether clients want to better understand what’s happening related to admissions, out-of-network claims or emergency department (ED) visits, users are empowered to quickly and efficiently produce customized, high cost claimant reports, and conduct drill down analysis by claimant, facility type or service.

 “The new reports and deliverables have been very well-received by clients. In fact, with the level of customization and detail the reports now provide, we have secured a competitive edge in the local marketplace.”

 Improved Ease of Use

While previous HCC reporting processes required a great deal of manual intervention, the new platform dramatically streamlines workflow and eliminates the need for the many hands-on, cumbersome steps that caused a drain on productivity. Clinical teams find the participation-to-utilization linkage to be especially useful.

 “Health management data is now better organized and presented in a more intuitive format.”

 “Our clinical leaders and staff, including health coaches, appreciate the fact they don’t need to have a programming background to capture the information and reports they need.”

 Enhanced decision support

The combination of timelier reporting and episode data enable more accurate recommendations for program and benefits plan design going forward. For example, predictive modeling information, such as risk scores, also enables nurses to prioritize outreach efforts. Using this information, the organization was able to increase program enrollment by more than 650% in the span of two quarters.

Increased data visibility

The platform allows users to identify HCCs and see how risk levels shift and change over time based on a variety of factors like age or recent diagnoses. For opt-in programs like maternity management, having the ability to rapidly identify members that could benefit from these programs but are not yet enrolled can help drive more effective outreach and engagement.

 

HDMS Health Plan 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