David Laros is Vice President of Digital Strategy, Analytics and I﻿nsights at 

David Laros, Beghou Consulting

As launch timelines accelerate and competition increases, pharmaceutical companies must find ways to leverage the insights at their disposal to improve their engagement with healthcare providers (HCPs) and patients, while strengthening their brands. The patient hub provides a golden opportunity for this enhanced engagement, as long as pharma companies take advantage of the data contained within these hubs.

The rise of complex biologic therapies in the early 2000s brought the earliest patient support services, which essentially served as call centers focused on offering financial assistance. Today, hubs offer a variety of services, including onboarding a patient on therapy, adherence, support programs, supply chain coordination, and more. These hubs facilitate myriad digital interactions between patients and the pharma company. When they work well, hubs help patients start and stay on the therapies they need and ease workloads for HCPs and pharmacies. When they fall short of their potential, hubs decrease the original intention of supporting the patient across the journey.

While the hub has many features at the heart of these programs, what we will focus this article on is data. Essentially, pharma companies must do more with their hub data to improve the patient journey. Hubs have or possess the potential to have rich patient data that can be mined for insights on preferences and future behavior. By taking full advantage of hub data, companies can make their hubs more personalized and experiential. However, today, most companies are only scratching the surface and are not fully utilizing hub data. Turning granular data from hubs  into insights that drive action will help companies become more patient-centric in their commercial operations.

From a call center to a digital experience

The 1990s witnessed launches of numerous blockbuster drugs. The first hubs served as financial support for patients on complex and expensive biologic therapies. By the early 2000s, many pharma companies began realizing their blockbuster new offering faced competitors treating the same patients. Payers were growing stronger. And, in many cases, patients became a more important part of the equation. These factors helped create a second generation of patient hubs that included patient support features. These new hubs offered services such as processing and submitting complex claims for rare disease products and sending patient reminders—such as refill reminders—to improve adherence to prescribed therapies.

However, hubs were not taking full advantage of their data to achieve customized analytical capabilities, predictive models that could anticipate therapy adherence, and powerful patient-level individualization. These shortfalls limited the effectiveness of the patient hub.

More recently (2010-2020), as pharma organizations placed a greater focus on therapies for rare diseases, patients required more hands-on support compared to mass-market therapies. Thus, companies added more sophisticated services to support patients receiving rare disease therapies, such as coordinating treatments with HCPs and securing transportation to the treatment site (for example, for patients traveling to receive cell and gene therapies).

Moreover, this period is when digital transactions mushroomed. The digital revolution led to an explosion of data, as medical data were doubling every 73 days. Digital capabilities allowed larger (but not always insightful) amounts of information to be collected and analyzed. Such data involved product sales, purchase frequency, patient demographics, and more. Hubs were beginning to show their larger potential.

Today, while more progress is essential to improve patient centricity, a far more proactive patient hub has blossomed. The long COVID-19 pandemic brought with it an explosion in the number of digital prescription transactions. Many hubs now have a bevy of patient-centric features and benefits to those calling, emailing, texting, scanning, or engaging in chat. 

Telemedicine continues to grow, with patient hubs playing a key coordination role between prescriber and patient. For example, companies such as Hims and Ro provide a one-stop-shop for patients to digitally connect with HCPs, receive a prescription, and have the therapy shipped right to their doors.

Hubs are also playing a more central role in interactions with distribution and payer networks, helping facilitate prior authorizations, reimbursements, the delivery of documentation for rare and expensive drugs, and the production of data for pharma companies to ease the tracking and recording of sales. Hubs connect patients and HCPs with available resources. For example, nudging applicable patients to leverage phone apps for disease or medication management.

Turning the hub into impactful technology

Today’s patients are more tech-savvy, inquisitive, discerning, and more inclined to change their preferences or seek alternative therapies. A survey conducted by Accenture found that nearly three-quarters of respondents have used digital technologies to manage their health.

Further, patients seek highly individualized attention. According to a survey by software company Dynata, 75% of US consumers wish their healthcare experiences were more personalized.

 In response, pharma companies must leverage their hub data to uncover valuable insights that allow them to offer more engaging, personalized experiences.

Here are four keys to implementing enhanced patient hubs:

Build the underlying data infrastructure.

Hubs should be built with underlying data acquisition tools that are unified, free of patchwork designs. The challenge is huge. Proactive planning, instead of a patchwork approach, allows companies to strategize around data ingestion, governance, and use. Further, it helps companies design a hub centered on improving the patient organization. 

By proactively mapping out a hub system, companies can think more holistically about the potential use cases of their offering. Then, they can prioritize each use case to take a step-by-step approach to building out their hub program. This approach ensures organizations have a comprehensive hub and all of the features work together to improve the patient experience.

In many cases, a company’s hub is outsourced to a third party. Oftentimes, this can mean the company is a step removed from a patient’s hub experience—and the data that come with it. Pharma companies must have a thoughtful service-level agreement (SLA) in place and ensure they can collect the appropriate metrics to gather data and insights from their hubs. Additionally, they must closely oversee the hub provider to ensure they follow the roadmap and develop tools for impactful patient experiences.

Incorporate many channels to serve tech-savvy patients. 

Today’s patients and their caregivers—whether they are parents of newborns, teenagers, GenX, middle aged, baby boomers, seniors, or super seniors—expect maximum user-friendliness and ease of access. Segments within each generation will have specific communications preferences and expect the hub to accommodate those preferences. Companies must double-down on their omnichannel experience to ensure they are reaching patients at the right time, on the right channel.

By proactively mapping out the hub and developing impactful features that personalize the experience for each patient, pharma companies will improve the patient experience, ultimately leading to happier patients and better adherence. Hubs can also improve the HCP experience; by providing easy access to documents, and features to improve authorizations and other tedious paperwork, hubs can reduce the workloads of HCPs and other functions in the patient journey. Taking steps which help ensure hubs become more experiential and highly personalized is the ideal route to better serve patients.

1. Safavi, K., et al. Digital adoption: Reaction or Revolution? 

https://www.accenture.com/us-en/insights/health/digital-adoption-healthcare-reaction-or-revolution

2. 75% of US Consumers Wish Their Healthcare Experiences Were More Personalized, Redpoint Global Survey Reveals. 

https://www.businesswire.com/news/home/20200218005006/en/75-of-U.S.-Consumers-Wish-Their-Healthcare-Experiences-Were-More-Personalized-Redpoint-Global-Survey-Reveals

Rohit Gupta is VP of Analytics Strategy and Transformation,

David Laros is VP of Digital Strategy, Analytics, and Insights, both at Beghou Consulting.

Articles

Methods that pharma companies can use to make the hub more personalized and experiential. 

Transforming the Patient Hub into a Hub of Patient Centricity

Attaining optimal access to healthcare practitioners has long been a challenge for pharmaceutical commercial teams. In response, they have turned to more comprehensive, digital augmented promotion to put important product news and information in front of healthcare providers (HCPs). As HCPs embraced multichannel touchpoints, it created new opportunities for pharma companies, but also challenges. After all, they needed to ensure their content stood out amid an increasing barrage of communication aimed at HCPs.

For the most innovative and customer-centric pharma, what may have started as a disjointed effort pushing messages out across a variety of channels eventually turned into a coordinated omnichannel approach. These companies use the customer journey to provide seamless coordination of online and offline channels, while creating a personalized customer experience.

A challenge to keep in mind is the information overload faced by HCPs. Hence, pharma companies must deploy highly tailored digital promotions to complement traditional, in-person sales efforts. If a commercial team can address in a compelling way an HCP’s specific needs using the channels the HCP prefers, it can improve its ability to engage this HCP. Of course, executing this approach successfully is easier said than done.

Using promotional response modeling in our work with pharma companies, we have found that the number of times an HCP needs to hear a message before it resonates is increasing. But that doesn’t mean companies should simply send more promotional emails. Instead, to improve the chance that an HCP sees and retains important information throughout the customer journey, a commercial team must spread its promotions across channels in a way that’s customized for each HCP. How can commercial teams do this effectively? It can be accomplished by ensuring sales and marketing teams coordinate closely, and make decisions rooted in rigorous analysis of data.

One key to executing omnichannel marketing well is to use both data and local insights to determine the next-best action, personalized for each customer. For example, if an HCP clicks on a digital ad about adherence, the next-best action might be to send them an email with details on the company’s patient support program. Especially as companies increase the frequency of promotional efforts, knowing when and where to best reach an HCP is key to boosting engagement.

By combining data, analytics, and advanced analytics-driven suggestions that incorporate local knowledge, the sales force can leverage information that would never be known from fragmented and incomplete data, no matter how rigorous and sophisticated a company’s analytics. This omnichannel approach allows commercial teams to create and implement a holistic strategy that ensures each customer receives the most appropriate, situationally dependent experience across all channels—from in-person meetings to emails, to social media, and other online channels. Call it “AI plus analog.” This mix of new and old in omnichannel marketing allows the sales force to complement the efforts of the marketing and digital teams.

Advanced analytics and artificial intelligence (AI) are powerful tools that play a critical role in omnichannel strategy. Commercial teams should apply analytics, via machine learning and AI, to the barrage of data available to them—to uncover deep insights into HCP preferences and prescribing practices.

At the same time, analytics and AI alone are not enough to power an omnichannel approach. A sophisticated omnichannel strategy also considers the local insights of the sales force—the people who know the HCPs better than anyone else.

Most pharma companies have all the pieces of the omnichannel puzzle—sales reps with important customer insights; data and technology systems to uncover trends in HCP preferences; an understanding of the customer journey. Now, they must bring the pieces together into a coordinated approach.

David Laros is VP of Digital Strategy, Analytics, and Insights at Beghou Consulting.

Why deploying AI and analytics in tandem is a key targeting tool. 

Solving the Omnichannel Puzzle

Emerging next-generation patient support tools offer pharmaceutical companies the ability to deliver more tailored communications that effectively address patients’ concerns about their therapies. The end goal here is to improve adherence to prescribed therapies. There’s no need to rehash the adherence problem in the health care industry. It is a long-standing challenge, and all parties (from patients to providers to pharma companies) stand to benefit from even a slight uptick in adherence.

Patient support tools aren’t new, but the wide availability of anonymized patient-level data has enabled innovation in the space. Today, these platforms offer pharma companies the ability to take patient engagement efforts to new levels of sophistication and effectiveness by better customizing messages and delivering them at the most pivotal points in the treatment journey.

But, to unlock the full potential of these patient support tools, pharmaceutical companies must recognize the crucial role advanced analytics plays in facilitating enhanced patient engagement that yields improved adherence. These tools can deliver a meaningful return on investment for pharma companies if they marry adoption of these platforms with a sophisticated data analytics operation that includes three key components:

A multitude of data sources (from anonymized patient-level diagnosis, prescription, and medical claims data to payer data to HCP affiliation data) that companies can layer on top of each other and mine to uncover insights.

Machine learning models that help them analyze these layers of data, account for the various levers that impact adherence, and generate insights into adherence motivators for different patients (e.g., safety, efficacy, administration, cost, etc.).

Messages informed by analytics-derived insights that drive action from patients.

For pharmaceutical companies, the prescription is clear: adopt these next-gen platforms that offer more intelligent and real-time communications capabilities. But, to make the most of these platforms and ensure their communications with patients are timely, appropriate and impactful, they must construct a sturdy analytics backbone for these platforms.

A move toward more intelligent communication with patients

Pharma companies should acquire layers of data they can plug into machine learning models to uncover insights about treatment journeys and roadblocks to adherence for different categories of patients (e.g., patients in different geographies, with different comorbidities, with different payer cost structures, etc.). To acquire patient-level data, pharma companies must secure opt-ins from patients. To do so, it’s important to develop a strong patient recruitment methodology that makes clear for patients the connection between data-sharing and improved care.

A pharma company’s communications with patients must take into account the fact that each patient has a different set of concerns that affects his or her willingness to stay on therapy. For some, drug efficacy is a top concern. For others, side effects are the biggest issue. For still others, price and payer red-tape issues stand in the way of therapy starts or refills.Adherence impediments also will vary by therapy area. After all, the worries a patient may have about an oncology treatment will be vastly different from the concerns a patient has when prescribed a primary care drug.

Companies must aim to understand at a granular level the factors that impact adherence. From there, companies can develop more effective messaging campaigns and better assess the impact of different elements of those campaigns. The goal is to gain a 360-degree view of the patient treatment journey to enable communication that is helpful to the patient and encourages them to start and remain on important therapies, in line with a physician’s guidance. The better a pharma company understands the patients taking its drug, the more effectively it will be able to tailor messages to those patients to drive adherence. To take effective action, companies first need the comprehensive intelligence that comes from advanced analytics.

Creating a data analytics infrastructure for patient support

A pharma company’s data ecosystem should mirror the path of a drug from the health care professional to the pharmacy to the payer to the patient. A company can weave patient-level data in with position-level data, affiliation data, payer data, and campaign data from its patient support platform. Then, apply sophisticated analytics methods to gain a detailed understanding of the interplay between the many overlapping factors that influence adherence. The specific analytics methods a company uses will vary depending on what insights the company hopes to tease out of the data, but these methods can include supervised modeling, unsupervised modeling, correlation analysis, and much more.

From there, the company can start to home in on the proper timing, context and content for its patient messaging campaigns. Then, with this analytics infrastructure in place, it can more agilely adjust course as circumstances change.

The end result is more impactful content, a messaging cadence that aligns with key points in a patient’s treatment journey, and more proactive interventions to address patient concerns. For example, the introduction of a copay card at the right time can ease cost concerns. And clear and pointed messaging about the importance of taking a medicine exactly as its prescribed in order to realize promised benefits can help reinforce drug efficacy claims.

As pharma companies continue to work to become more patient centric in their commercial efforts, they must recognize the essential role a sophisticated data analytics operation plays in enabling next-generation patient support and engagement. By building a robust analytics infrastructure alongside adoption of advanced patient support platforms, pharma companies will start to communicate in more intelligent ways with patients and therefore develop more trusting relationships with patients, presenting themselves less as impersonal conglomerates and instead as key enablers of improved health.

To unlock the full potential of new patient support tools, pharma companies must recognize the crucial role advanced analytics plays in facilitating enhanced patient engagement that yields improved adherence. 