More than 50% of newly approved drugs today target specialty and rare diseases.
Specialty drugs represent less than 5% of prescriptions, yet account for 54% of pharmaceutical spending.
U.S. Food and Drug Administration (FDA)
Patient access is a mission-critical capability that enables patients to initiate and remain on therapy. The underlying challenge lies in fragmented patient access ecosystems that delay therapy initiation and impact outcomes.
Lenmeldy and other high-cost chronic therapies can have life-changing results, but any inefficiencies in patient access translate directly into revenue leakage, increased disease burden, and diminished value from these advanced treatments.
The focus must shift from access itself to how it is managed, orchestrated, and scaled across an increasingly complex healthcare ecosystem.
The Patient Access Paradox
Patient access programs were designed to simplify therapy initiation and improve adherence. However, in practice, they often operate within highly fragmented ecosystems.
These ecosystems typically include:
- Hub services that coordinate benefits verification, prior authorizations, and onboarding
- Digital platforms for enrollment, communication, and adherence tracking
- Specialty pharmacy networks that manage distribution and patient engagement
- Data and analytics layers that track outcomes and program effectiveness
While each component plays a role, the lack of integration across these layers creates operational inefficiencies and delays.
As a result, patient access programs struggle to deliver a seamless, patient-first experience.
The Hidden Cost of Fragmented Patient Access
Fragmentation is a measurable business risk that can delay therapy initiation, limit enrollment and increase revenue leakage.
A study by patient intake software maker Phreesia found that nearly 60% of patients are unaware of the support programs available to them. As a result, less than 5% of eligible patients enroll, limiting program effectiveness. Other impacts of ineffective patient access programs include:
| Operational Inefficiencies |
Disconnected systems across hubs, payers, and pharmacies lead to delays in benefits verification, prior authorization, and therapy initiation. |
| Revenue Leakage |
Delays and drop-offs in onboarding directly impact therapy adoption and revenue realization. |
| Compliance Exposure |
Complex regulations around patient assistance, data privacy (HIPAA/GDPR), and reimbursement create ongoing risk for pharma organizations. |
| Poor Patient Experience |
Lack of real-time visibility results in reactive engagement, leading to patient frustration and reduced adherence. |
Unless these gaps are addressed, patient access programs will continue to underperform, despite increasing investments.
Why Are Traditional Patient Access Hub Models Breaking Down?
Traditional patient access programs were built around hub models designed for a simpler healthcare landscape, but today’s environment demands far greater agility. High-cost therapies, evolving payer policies, and digitally empowered patients are exposing the limitations of traditional hub models, including:
- Legacy Platforms: Rigid systems that cannot adapt quickly to new therapies or payer rules
- Manual Workflows: Heavy reliance on human intervention for document processing and approvals
- Siloed Data: Lack of unified visibility across patient journeys
- Limited Analytics: Inability to proactively identify drop-offs or adherence risks
These limitations result in slow onboarding, high administrative costs, and inconsistent patient outcomes.
The Solution: Hybrid, AI-Enabled Access Models
To address these challenges, pharma organizations are moving toward hybrid hub models that combine internal capabilities with outsourced services, powered by digital platforms and AI.
This shift is defined by five important transformations:
| Unified Data Ecosystems |
Configurable Workflows |
Configurable Workflows |
Patient-First Engagement |
Compliance by Design |
| Integration of patient, provider, payer, and pharmacy data into a single interoperable platform. |
Modular, low-code systems that adapt to therapy-specific requirements and payer dynamics. |
Automation of document processing, decision support, and workflow orchestration to reduce cycle times. |
Omnichannel communication, simplified enrollment, and personalized outreach. |
Embedded governance frameworks ensure regulatory alignment and audit readiness. |
This evolution represents a fundamental shift, from process-centric hubs to intelligence-driven access ecosystems.
How Is AI Transforming Patient Access?
Artificial intelligence is emerging as the key enabler of this transformation, addressing both operational inefficiencies and experience gaps. Below are four key AI use cases that enable the shift from traditional hub models to new intelligent patient access programs.
| AI-Driven Patient Enrollment |
AI can extract data from multiple sources, including forms, portals, and faxes, and automatically populate systems. It can also pre-screen eligibility based on insurance, diagnosis, and financial criteria, significantly reducing onboarding time. |
| Automated Hub Operations |
Tasks such as benefits verification, prior authorization drafting, prescription processing, and financial assistance workflows can be automated, reducing manual effort and accelerating therapy initiation. |
| Intelligent Data Governance |
AI-powered redaction and de-identification enable organizations to analyze sensitive patient data while maintaining compliance with HIPAA and GDPR regulations. |
| Predictive Patient Engagement |
AI models can identify patients at risk of non-adherence or abandonment and recommend targeted interventions, enabling proactive care management. |
Together, these capabilities transform patient access from a reactive process into a proactive, intelligence-driven system.
From Access to Experience: The New Competitive Advantage
As therapies become more complex and patient expectations rise, access programs are evolving into experience platforms.
The focus is shifting toward faster therapy initiation, higher patient engagement and adherence, personalized, data-driven interactions, and real-time visibility across the patient journey.
In this environment, patient access is no longer just a support function; it becomes a strategic differentiator.
Organizations that can deliver seamless, intelligent access experiences will gain a significant competitive edge.
The Future of Patient Access
The next generation of patient access models will be defined by:
- End-to-End Digital Integration: Seamless connectivity for all stakeholders
- AI-Augmented Decision-Making: Real-time insights that guide interventions
- Direct-to-Patient Models: Greater emphasis on home-based care and engagement
- Outcome-Driven Programs: Focus on adherence, quality of care, and real-world evidence
As these trends converge, patient access will become a core driver of both clinical outcomes and commercial success.
Moving From Fragmentation to Intelligence
To meet the demands of high-cost, complex therapies, patient access programs must evolve from fragmented, manual processes to AI-enabled, patient-centric ecosystems.
Organizations that unify data, modernize workflows, and embed AI into their access strategies will accelerate therapy initiation, improve adherence, and deliver better patient outcomes.
With deep expertise in healthcare and life sciences, digital engineering, AI-led automation, and compliance-driven transformation, Coforge helps pharma organizations reimagine patient access, from fragmented hub operations to intelligent, scalable, patient-first models.
By combining domain expertise with advanced technology capabilities, Coforge enables enterprises to build next-generation patient access ecosystems that drive efficiency, compliance, and superior patient experiences at scale.
