How stakeholders can maximize the value of real-world data analytics

Organizations across the healthcare continuum are increasingly leveraging real-world data (RWD) and real-world evidence (RWE) to inform strategy and decision-making with the goal of reducing costs and improving patient outcomes.1 However, payers have lagged behind other actors, such as healthcare providers and pharmaceutical companies, in maximizing RWD’s potential.

Payers have a wealth of internal claims data that can be analyzed to better understand patient populations, design improved programs and establish new initiatives. Today, forward-thinking payers are beginning to take advantage of these resources, and many expect to expand their use of analytics in the years to come.

Find the right resources and tools

Most payers recognize the importance of analytics, but many internal analytics teams struggle with a lack of time and resources. In fact, 83% of payers believe analytics is an important part of their strategy, yet only 17% believe they have the right skills and technology to effectively leverage data.2

Common obstacles include staffing constraints, difficulty interpreting complex data, and slow turnaround times for analysis, which prevent all payers from maximizing the value of analysis. Because of these challenges, 84% of payers outsource some of their analytical work to external agencies.3 However, using an effective analytics platform can help payers overcome these hurdles, allowing them to conduct effective analytics in-house instead of outsourcing this work.

The first step towards maximizing the potential of analytics is collecting the right data. The most common source of data, used by 92% of paying agencies that perform analyses, is internal complaints data. Payers may also use external claims data, as well as other external sources, including electronic medical records and prescription data.

In terms of software, payers must have an end-to-end solution that allows them to create datasets, run analyses, and share their results on a single platform. Often, payers use separate solutions for analytics and reporting, which results in less comprehensive analytics and less robust insights. The best platforms will be scalable and easy to use even for staff without a technical background, allowing organizations to overcome the challenges of staffing and hiring in technical roles.

Use cases for payers

Progressive fee organizations have already started leveraging data analytics to improve processes and reduce costs. The analysis can enable payers to better understand the needs of their member populations and the barriers they face in accessing care, which can help them design better programs and evidence-based initiatives to meet those needs. Among payers currently using analytics, some of the most common use cases are program design and evaluation, service utilization benchmarking, and benefit design.

According to Panalgo’s 2022 Payer Benchmarking Report, 80% of payers who perform healthcare analytics use it to inform program design and evaluation. Payers can use analytical tools to statistically model the performance of different care programs, compare patient outcomes before and after the program, and create benchmarks for treated versus untreated patients. Payers can also use analytics to assess individual patients in terms of resource use, compliance, and outcomes, and decide whether certain members should be included in programs.

For example, when creating disease management programs, analytics can first help payers identify which patients to include based on certain criteria. Once patients are enrolled, payers can track the success of the program based on metrics such as the number of downstream procedures and hospital visits. This information can enable payers to make more informed decisions about how to allocate resources or expand programming, such as outreach to clinical staff and information sharing.

Payers can also use analytics to compare and identify service utilization trends, including the frequency and volume of costly procedures and spending on specific medications. This type of analysis allows them to discover which clinical areas are costing the health plan the most while also understanding patients’ out-of-pocket expenses in those areas.

Using this information, payers can design improved care programs that move patients away from expensive options to less expensive procedures or places of care, such as outpatient care instead of hospital care. By leveraging analytics for benchmarking service utilization, payers can not only reduce their own costs, but can also reduce the financial burden on patients.

More than half of payers currently using analytics also leverage this information for benefit design. When designing benefit programs for employers, payers can use analytics to address unmet medical needs by estimating the expected use of certain benefits and the average costs associated with them.

This information can help them decide which procedures and services to include in programs, whether to expand certain benefits, and how to set parameters, such as duration of benefits and number of visits. Many employers are increasingly interested in expanding benefits programs to retain top talent, and insights from analytics can enable them to do this intelligently and strategically.

The future of data analytics for payers

Some payers have already made significant investments in analytics, particularly with the adoption of healthcare data solutions, and many plan to increase their spending in this area. In 2021, the US healthcare payer analytics market was valued at $3.2 billion and is expected to expand at a high growth rate by 2030.4

By investing in data analytics now, payers can position themselves to compete with other payers by designing effective programs to meet changing patient needs. And, as staffing shortages continue to threaten healthcare, using the right tools will allow payers to upgrade their analytics teams and optimize their resources, while keeping analytics work going. internal.

Despite the use cases described earlier, payers still have plenty of room to expand their use of analytics. RWD holds unlimited potential to generate ideas that can lead to real change in healthcare. It is time for payers to seize this opportunity and act.

About the Author

Matthew Marshall is a Solutions Engineer at Panalgo.


  1. Real world proof. US Food and Drug Administration.
  2. Healthcare payers are keen on analytics, but feel unprepared. Health informatics analysis.
  3. Panalgo Payer Benchmarking Report 2022. Panalgo.
  4. Report Analyzing US Healthcare Payer Analytics Market Size, Share & Trends By Analytics Type (Descriptive Analytics), By Component (Software), By Delivery Model , by application and segment forecast, 2022-2030. Grand View Research.

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