Next-Level Analytics Part 1: Eight Insights to Expect From Your Patient Support Provider

By AmerisourceBergen |

Evaluating a patient support program provider? Have a conversation about these eight analytics considerations.
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As patient support programs continue to improve access to therapy, they have become essential for most modern medicines. Patient services can be a valued connector across the care journey, providing data and insights that help accelerate speed-to-therapy for everyone.

And indeed, market competition to provide patient services has intensified, which means choosing the right patient support partner for your program is all the more important. Moreover, it's a big responsibility.

So how can pharmaceutical manufacturers select a partner who will deliver on their promises and prioritize the patient's experience?

Reviewing the analytics philosophy is a good first step. Data can tell a profound story about physician uptake, pharmacy fulfillment and patient access. A support program provider with the right client analytics strategy will translate data into actionable operational, clinical and financial insights for manufacturer partners.

During the vetting process, look for a partner with demonstrated ability to pair empirical trends and patterns with underlying context to produce insights that uncover and address unexpected barriers, leading to faster access to therapy. Remember to take a closer look at these key areas to ensure quality data practices.

1. Reporting vs. analytics

Reporting and analytics each contribute to the data narrative, but they have very different purposes and are used in different ways.

Whereas analytics helps provide ongoing, high-level strategic direction and indications about performance, reporting provides raw data about specific criteria—such as counts of active patients, providers and sites. Reporting usually requires the end user to process and derive insights independently. Ultimately, analytics takes that a step further and tells the real "story behind the story."

Analytics enables insights from payer authorizations, specialty pharmacy activity or socioeconomic dynamics. These insights uncover new barriers to entry, as well as new opportunities to improve services. While a typical program health dashboard should include key performance indicators, the insights gleaned from them matter as much—or more— than the surface-level metrics.

It's important to understand not just that a patient support program partner is leveraging analytics, but that they have a sound strategy and knowledge of the types of analytics needed to measure success and take action. For example, predictive analytics uses data based on previous events to diagnose specific areas. It can help “predict" where there are efficiencies needed. Prescriptive analytics, on the other hand, can utilize the data analysis from predictive analytics to offer up actionable next steps. Having a clear understanding of the level of expertise the client analytics team can offer in specific areas can help you determine how well a partner can meet your patients' needs.

Do your data insights meet the standard?

Patient support providers should offer a baseline level of reporting that covers key program data, including:

  • Program Activity—Counts of Patients, Providers and Sites; Call Metrics; Compliance to Service Level Agreements; Service Utilization; Field Force Performance; Patient Drop-offs
  • Specialty Pharmacy Activity—Shipment Activity; Fulfillment Barriers
  • Payer Experience—Coverage; Prior Authorizations; Access Options; Average Deductible and Out-of-Pocket Costs
  • Provider Experience—Type of Site; Volume Changes; Patient Growth; Provider Turnaround; Enrollment Form Data

2. Field force activity

The activity of a program's field support is another great barometer for program effectiveness. As the on-the-ground team, field representatives can influence factors like how effectively provider offices capture patient information on enrollment forms. But simply deploying field teams without checking in on their progress is a huge miss. That's why patient support programs should include that team's activity within their overall analytics purview—especially in regard to training, relationship building and compliance oversight.

3. Benefits verification trends

Benefits verification is a multi-step process and impacts speed-to-therapy for patients. For a comprehensive look, the analytics should not only alert when delays are identified, but also what to do about it. For example, complexity in the enrollment process can lead to missing information that causes delays.

Monitoring benefits verification trends may identify new or intensified barriers. It might also highlight acceleration to therapy due to proactive program changes designed to improve the patient experience. Your vendor should have the experience to isolate key data points, research and provide insights gained and work with you to make program adjustments to optimize your program and patients' experience.

4. Initial enrollment barriers

Much of a program's analytic focus is on current patients, and for good reason. But what about all the people who didn't start on therapy as expected? Failure to start medication or fill a prescription can be due to affordability; it could be because a patient is underinsured, doesn't qualify for patient assistance, or encounters obstacles like social determinants at other junctures of the patient journey. Analyzing patient data can help uncover areas for improvement throughout the patient journey and ways to provide education, or even geographic opportunities to target.

5. Enrollment form completions

The enrollment form can mean the difference between faster therapy or a frustrating holdup. By looking at completion insights from both providers and patients, your partner can work with you to develop forms that collect the right information, the first time. This means understanding what has worked and what hasn't in terms of readability, word choice, spacing, font sizes and typography. It also means knowing which providers from which geographic areas may need additional support from field personnel to speed up form completion.

6. External market influences

The right partner should be able to combine program data and market expertise to make recommendations. Gleaning insights from analytics often requires assessment within a broader context to understand drivers, impacts and opportunities. These types of analytics aren't derived from the program itself, but from other reliable sources like industry experts or healthcare agencies. For example, data from the Census Bureau or Centers for Disease Control and Prevention (CDC) may tell an insightful story about socioeconomic factors and help inform customized solutions.

7. Clinical context

A well-rounded analytics program wraps empirical data—whether internal or external—into a clinical context. This is where data scientists with a background in nursing, patient support, or pharma can provide critical help. For example, adherence disparities among cancer patients may link back to outside medical circumstances that only a clinician would know. A comprehensive analytics suite pairs that specialized knowledge and subject matter expertise with quantitative fact.

8. Specialty pharmacy fulfillment

Conversion data gleaned from pharmacy fulfillment can elevate analytic insights to new heights—but it's imperative to have a partner who 1) has experience working with specialty pharmacies, and 2) has access to information across the patient journey to remove barriers to care, such as shipment delays and refill issues.

Reading between the numbers

Selecting the right partner to provide your program's patient support services can be challenging, and it takes time to vet each potential provider effectively. But it's important not to discount your own business needs during the process; you deserve to have a great partner with the structure, tools and talent to derive the best insights for your program.

And ultimately, these considerations are just a few elements to think about when talking with a potential patient support services partner about the health and quality of their data. Still, they're a good first step. After all, with the right insights available, you can take actions to accelerate and optimize speed-to-therapy for patients.

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