Healthcare is awash in data, yet most of it remains untapped. Every day, providers and payers generate mountains of information, including clinical notes, diagnostic reports, patient conversations, and more. However, according to IDC, 90% of enterprise data is unstructured, and can take many static, disconnected forms such as documents, images, contracts, emails, and more.
This isn’t just a technical challenge; it’s a multi-billion dollar problem that puts patient outcomes at risk and burns out providers.
What Are the Hidden Costs of Unstructured Data?
Why does unstructured data drive billions in wasted spending? Because administrative complexity, rising documentation demands, and increasing regulatory pressure overwhelm healthcare providers.
These challenges manifest in several costly ways:
- Clinician documentation overload: Physicians spend nearly twice as much time on EHR and desk work as on patient care, plus 1–2 hours nightly on clerical tasks, according to the American Medical Association. This burden fuels burnout and hidden costs across the system.
- Prior authorization delays: Slow approvals create $13B in annual administrative costs and inefficiencies, straining reimbursement and delaying care.
- Compliance risk: Hospitals lose an estimated 3–5% of net patient revenue to denials, documentation errors, and audits, often millions annually for mid-sized systems.
- Disjointed tech: Providers rely on multiple point tools that lack real-time intelligence and workflow automation, creating inefficiencies and gaps in care coordination.
These issues extend beyond lost revenue, delayed patient care and straining clinicians. When unstructured data remains inaccessible, the consequences spread far beyond the provider level.
System-Wide Consequences of Unstructured Data
When unstructured data isn’t accessible or analyzed, inefficiencies cascade through every part of the healthcare system:
Providers spend more time managing documentation, diagnostics, and treatment plans than caring for patients. The burden leads to frustration, burnout, and reduced job satisfaction.
Healthcare IT teams struggle to reconcile disconnected data scattered across fragmented systems. Integrating disparate sources is time-consuming and often incomplete, resulting in gaps in patient records and care coordination.
Payers lose millions due to inefficiencies in risk adjustment and delayed reimbursements. Inaccurate or incomplete data makes it difficult to assess risk, process claims, and ensure timely payments.
Patients face delays, denied claims, and missed opportunities for timely care. When documentation is incomplete, patients may not receive the right treatment when they need it and may be left navigating complex appeals processes.
Valuable insights also go unnoticed. Inaccurate or incomplete documentation can result in revenue losses of up to 10% annually for healthcare organizations, according to JAMA. These gaps can cost facilities millions each year, while risk factors remain buried, limiting proactive care and early interventions.
Together, these dynamics contribute to financial instability, clinician burnout, and fragmented care coordination.
Moving Towards Data Management Solutions
Instead of chasing more data, the industry is beginning to ask how to make the data it already has actually useful. That means moving away from siloed systems and manual workarounds and toward integrated approaches that blend technology, smarter workflows, and stronger collaboration.
Promising innovations include:
- Ambient listening: Technology that captures and transcribes doctor-patient conversations in real time, reducing manual note-taking and documentation burden.
- Natural language processing (NLP): AI tools that analyze and extract medical concepts, clinical details, and actionable insights from free-text notes and unstructured data.
- AI-driven recommendation engines: Systems that streamline clinical and administrative workflows by suggesting documentation improvements, coding support, and automated prior authorization triggers.
- Secure delivery: A process that structures, encrypts, and routes healthcare data into EHRs, payer systems, and analytics platforms while maintaining HIPAA compliance.
These innovations are powerful on their own, but their real impact emerges when they come together in an integrated solution.
Looking Ahead: From Data to Decisions
As the industry prepares for HLTH 2025 this October, the conversation is shifting—from generating more data to unlocking the value of the data we already have. The future of healthcare lies not in creating more data, but in finally putting the data we already have to work.
By embracing interoperability, intelligent automation, and user-centered design, healthcare organizations can unlock meaningful insights, improve outcomes, and deliver better care for all.
That’s the vision behind HealthSense AI, our new solution built on the foundation of AWS HealthScribe. HealthSense AI uses ambient listening and natural language processing (NLP) to capture and interpret clinical conversations in real time—transforming unstructured data into structured, actionable insights.
The goal? To reduce documentation burden, improve coding accuracy, surface patient risks, and streamline prior authorization—all while maintaining HIPAA compliance and supporting better care coordination across the ecosystem.
We will be showcasing HealthSense AI and its broader healthcare innovation strategy at the upcoming HLTH Conference in Las Vegas, October 19–22.
Schedule a meeting to see a live demo of the platform and learn how we’re helping healthcare leaders move from data overload to data-driven action.
Join us at our HLTH reception to connect with peers and explore what’s next in healthcare innovation.
