Winning at Scrabble: Improving patient engagement

Using data to create meaningful human experiences

By Amarinder Sidhu and Shahana Yeasmin

Scrabbling through data

Remember the last time you played Scrabble? It’s likely you spent much of the game contemplating a jumble of upturned tiles and wondering, “How do I acquire the right tiles and combine the individual letters to produce a high-value, triple word score?”

Biopharmaceutical companies face an analogous situation when contemplating the abundance of patient data that they collect from internal and external sources and wondering, “How do we acquire the right data sets and combine them to produce high-value insights to improve patient engagement and produce a meaningful, personalized human experience?

Biopharmas continually accumulate vast quantities of data across the patient engagement ecosystem. Third-party vendors, contracted hub service providers, payer claims, and specialty pharmacies create numerous rich and deep data sets. Unfortunately, companies can't do much with this raw, disparate data. They need to aggregate, analyze, and turn it into insights they can leverage to better understand patients’ individual and collective needs as they progress through the treatment cycle; how those needs impact the biopharma’s patient services operations; and what opportunities exist to close gaps in the patient journey and service operations.

Biopharma companies that employ unified, patient-centered data management and analytics to harness the power of data insights can drive better patient engagement, program efficiency, and effectiveness; improve treatment outcomes and operating performance; and deliver an elevated, meaningful human experience.

The challenge: Knowing the patient as a consumer

Disparate data is just one aspect of biopharma manufacturers’ complex challenge of knowing and understanding the patient as a consumer within the complex ecosystem biopharmas deliver their products. Other participants include wholesalers, pharmacy benefits managers (PBMs), group purchasing organizations (GPOs), government agencies, specialty pharmacies, health care providers (HCPs), and payers.

When an individual is diagnosed with an illness or condition, the information and support they receive from a biopharma’s patient services program—financial assistance, disease education, medicine use instructions, patient support group resources, and other offerings—are critical components of their treatment journey. By law, biopharmas cannot interfere in actual care decisions, so companies essentially have to provide support services to both HCPs and patients—and to know as much as possible about each, so they can intervene at the right times and places to reduce the administrative burden, facilitate the logistics delivery of therapies for complex disease journeys, or provide the right HCP or patient education.1

A patient services program that utilizes disparate data pulled from multiple, siloed sources will lack a comprehensive view of each patient’s (and their HCP’s) unique needs and, subsequently, how to best support them. This can lead to service gaps, suboptimal medication adherence, and biopharma revenue loss. To illustrate, more than 25% of all first-time prescriptions are left unfilled in a typical year, 30% of scripts for chronic conditions such as diabetes and high blood pressure are not filled,2 and 69% of commercially insured patients did not fill their new prescriptions when they had to pay more than $250 out of pocket.3

Biopharmas need to be strategic when acquiring, aggregating, and analyzing the multitude of patient data sets from pre- and post-prescription commercial and non-commercial engagements. And everything they do in this process has to be compliant with industry regulations. For example, patient data from R&D or pre-prescription commercial engagement has to be appropriately anonymized to provide better patient services during the therapy phase, and even then, only if the right consents exist on the use of the data.

The solution: Leveraging data effectively

How can biopharmas leverage patient data, with appropriate consent, to deliver right-sized service programs that provide a good patient engagement experience? Organizations should deploy a cloud-based, unified patient data management and analytics platform that is sized for their current situation, while making sure it has a foundation that can scale as they grow and add new services and therapies.4

Such a platform can offer much-needed visibility into individual patients’ therapeutic journey and help biopharmas identify opportunities for improvement in program performance across patient acquisition adherence, retention, conversion, and ecosystem engagement. Specifically, the platform’s analytical applications generate insights that biopharmas can use to:

  • Ensure patients have “the path of least resistance” to accessing the correct therapy/medication they need.
  • Identify patient cohorts struggling with adherence and provide efficient and targeted patient adherence intervention programs, improving health outcomes.
  • Proactively determine patients at a high risk of withdrawal and implement targeted retention campaigns.
  • Identify provider ecosystems or payer accounts that require a differentiated engagement strategy to optimize performance.
  • Develop or refine service programs and more effectively convert patients onto a therapy and get them to stay on it.

Investing for future value

If creating insights that enable biopharma manufacturers to identify and close service gaps and strengthen patient engagement is so beneficial, why aren’t more companies doing it? For some, the complexity of data acquisition and data management is a major hurdle: Their current IT systems simply lack the capabilities to aggregate and standardize data from different sources so it can be used in analytics.

Data control and ownership present another challenge: Many biopharmas use third parties to collect patient experience data, which the manufacturer typically receives via disparate data feeds. These are neither easily connected nor analyzed, hindering insights that present a comprehensive view of the patient from onboarding through specific support interactions. Outsourcing may have worked in the past, and it may still be an option for specialized service transactions (e.g., prior authorizations), but overall coordination of service delivery for a differentiated patient experience should be handled internally. Manufacturers need to own their patient service platform to gain a more longitudinal view of patient interactions and data.5

This approach requires a long-term view of technology investments. Some biopharma executives (especially those at smaller companies) struggle with justifying the necessary investment in patient insights software and services—which can appear daunting—particularly if the business case’s projected time horizon for realized value—improvements in patient conversion, retention, and compliance metrics—is later rather than sooner. Outcomes also may be unpredictable when modeling costs and benefits: Patients are consumers, and they have choices. Despite repeated, effective patient interactions, biopharmas can’t make patients take their medication if they don't want to.

Potentially compounding technology and cost challenges are patient services employees’ reluctance to adopt new tools, metrics, and processes, as well as increased pressure on biopharma-third party relationships that arise from increased visibility into vendors’ operational performance and effectiveness. Still, we know from experience that companies which have invested for future value have seen benefits accrue over time. In one pilot, a client using our CognitiveSpark™ for Patient Experience product set a commercial conversion agreement rate of 0.8% to 1% to justify its spending on the patient insights solution. In our most recent review, the client’s commercial conversion rate improved by upwards of 15%. In another example, our team found that 12% (16,000) of a patient population was eligible for a copay card, of which 2,400 had given protected health information (PHI) and presented an immediate opportunity for a 2% conversion increase. By playing with several variables on the patient experience dashboards, we identified this population segment in a few days, as opposed to months of analytical digging.

Looking through a wider lens, if clients start to integrate patient-reported data from wearables, devices, and other sources with patient insights, that data can be de-identified and used as a source in a real-world evidence (RWE) platform, in value-based contracting analysis and, potentially, in marketing programs (based on the type of patient consent). It also empowers organizations to build deeper relationships with patients, facilitate access, increase trust, and drive adherence. It’s also a leading way to address the growth of specialty products and personalized therapies, which require more integrated patient services.

Health care consumerism and value-based reimbursement are accelerating the push for industry stakeholders to improve patient engagement and provide a meaningful patient experience. As biopharma companies continue to introduce new therapies, they will need to show providers, payers, and patients that these therapies are having positive, real-world impacts; that they are actually treating and curing people. We anticipate that increased life sciences market competition will make collecting, aggregating, and analyzing patient data to relieve pain points in patient onboarding and treatment adherence even more important in the years to come.

Check out part three of the series to learn how a lean digital core can help therapy manufacturers deliver on rare disease launches for patients and caregivers.

Get in touch

Amarinder Sidhu
Managing Director
Deloitte Consulting LLP

Shahana Yeasmin
Deloitte Consulting LLP

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