According to the Paubox Report, 83% of healthcare IT teams report that legacy systems disrupt their day-to-day operations, creating effects that extend beyond the IT department. "I've seen firsthand how legacy email platforms can quietly—but critically—undermine operational stability and efficiency across healthcare organizations," says Matt Murren, CEO of True North ITG.
Legacy systems in healthcare aren't just old technology—they're operational anchors that drag down organizations. This challenge extends beyond healthcare, as demonstrated by industry research. As highlighted in RT Insights' article Modernizing for Growth: Overcoming the Hidden Costs of Legacy Systems, studies show that nearly two-thirds of companies spend more than $2 million annually on maintaining legacy systems. Furthermore, the publication notes that "the cost of maintaining outdated technology often outweighs the investment required to modernize."
The financial burden is even more when examining recent industry data. According to Forbes Technology Council's analysis in Is Your Legacy IT Infrastructure Draining Your Budget? Here's What You Need To Know, research reveals that "up to 80% of companies' IT budgets is spent keeping old IT systems afloat," while "40% of IT leaders regret their legacy technology purchases." This represents a drain on resources that could otherwise be invested in patient care improvements and innovative healthcare solutions.
These aging platforms, often built decades ago, were designed for a different era of healthcare delivery. Today's interconnected, data-driven healthcare environment demands agility, interoperability, and real-time access to information that these systems simply cannot provide. As noted in Healthcare data security and privacy in Data Warehouse architectures, "Any institution that continues to employ a legacy system in its operations is putting its patients in danger." The research further emphasizes that "The larger the hazard surface area rises the longer these susceptible technologies are in use."
According to the Paubox Report, the most common challenges healthcare organizations face with legacy systems show operational disruption:
The disruption manifests in countless ways throughout healthcare facilities. Staff spend time navigating interfaces, manually transferring data between incompatible systems, and working around technical limitations that shouldn't exist in modern healthcare. Every minute lost to system inefficiencies is a minute taken away from patient care.
One of the challenges legacy systems create is their inability to communicate effectively with modern healthcare applications. Electronic Health Records (EHR) systems, patient monitoring devices, laboratory information systems, and billing platforms often operate in isolation, creating dangerous data silos that fragment the patient care continuum.
This fragmentation problem resonates across industries. As Michael Berthold, CEO and co-founder of KNIME, explains in How Data Silos Impact AI and Agents, "Data silos are making it much harder for agents to get unified insights based on a holistic view of the data about an object of interest, such as a customer or an employee, or just a single user." In healthcare, this translates to clinicians struggling to access patient information across different systems—much like having to check the CRM for company information, then switch to a support system for technical issues, and finally review online forums for additional context.
Gordon Robinson, senior director of data management R&D at SAS, emphasizes the broader implications in the same article: "Inconsistent data across silos means different parts of an organization may track similar data independently, leading to discrepancies and the lack of a single source of truth." This challenge becomes troubling in healthcare environments where patient safety depends on having complete, accurate information readily available.
This integration challenge reflects a broader industry trend. As RT Insights explains in their analysis, "many older systems lack standardized APIs, requiring businesses to use specialized middleware to enable compatibility."
Healthcare IT teams find themselves constantly building workarounds, custom interfaces, and temporary solutions to bridge these gaps. These patches not only consume valuable resources but also introduce additional points of failure and security vulnerabilities. The result is a web of interconnected systems that becomes increasingly fragile and difficult to maintain. According to Healthcare data security and privacy in Data Warehouse architectures, "Integrating legacy systems with big data warehouses can be a threat to security as data import and export channels of these legacy systems might not support encryption and similar security features deployed in big data warehouses."
The root causes of these integration challenges are embedded in organizational structure and technology choices. As Josh Weinick, a sales engineer at Blink Ops, notes in How Data Silos Impact AI and Agents, "Most silos are caused by a mix of legacy infrastructure, organizational culture and inconsistent data standards. When teams cling to their own systems and definitions, or when older technology doesn't integrate well with modern AI platforms, it's easy for silos to form."
Read also: How legacy systems disrupt patient care
Legacy systems pose security risks. Many of these platforms were developed before cybersecurity became a primary concern, lacking modern encryption, access controls, and threat detection capabilities. Healthcare organizations, which store some of the most sensitive personal data, become attractive targets for cybercriminals seeking to exploit these vulnerabilities. The Paubox Report confirms this concern, with 47.6% of healthcare organizations identifying persistent security vulnerabilities as a major challenge with their legacy systems.
The security threat is not merely theoretical—it represents a clear and present danger to healthcare organizations. Forbes Technology Council's research reveals that "70% of data breaches occur in organizations that run their IT using legacy systems!" Even more alarming, they note that "with the average cost of a data breach at an all-time high of $4.88 million, many organizations risk suffering a breach they're unable to recover from." For healthcare organizations already operating on thin margins, a single major breach could prove financially devastating.
Axel Wirth, Chief Security Strategist of Medcrypt and consultant for the Healthcare Sector Coordinating Council, Cybersecurity Working Group, explains the elevated risks that legacy medical devices present: "Although any networked medical device could be compromised by an attacker, legacy devices elevate the risks resulting from two categories of weaknesses a) by exposing vulnerabilities that can no longer be patched (for example in an end-of-life commercial operating system), and b) through poor design decisions that were made in times of lower security awareness and regulatory requirements that, unfortunately, can not be mitigated due to the device's end of support. Either issue can introduce backdoors in devices, which can then give an attacker an opening to exploit the device itself or to use it as an entry point to the larger hospital network."
The challenge is compounded by the fact that many legacy systems cannot be easily updated or patched. Vendors may no longer provide support, or updates might require extensive system downtime that healthcare facilities cannot afford. This creates a situation where organizations must choose between operational continuity and security best practices.
Read also: Securing legacy systems within healthcare
Despite investments in healthcare technology, many organizations find themselves less productive than before due to legacy system constraints. Healthcare workers, who should be focused on patient care, instead spend considerable time managing technology that doesn't work as intended. The data from the Paubox Report illustrates this challenge clearly: 45% of organizations struggle with outdated and complex user interfaces, while 44.3% face system performance bottlenecks that slow down daily operations.
The efficiency impact extends across all industries, with particularly concerning implications for healthcare. Research cited by the Forbes Technology Council found that "organizations using outdated IT tools compared to AI-based solutions experience a 25% drop in efficiency, leading to increased operational costs, slower response times and heightened employee frustration." In healthcare settings, where every moment counts in patient care delivery, this efficiency loss can translate directly into compromised patient outcomes.
Nurses document the same information multiple times across different systems. Physicians wait for slow systems to load patient data. IT staff continuously fight issues rather than implementing strategic improvements. The 41% of organizations reporting limited mobile and remote work support highlights how legacy systems fail to meet the modern healthcare workforce's needs, especially in an era where flexibility and remote access have become essential.
This productivity drain has real financial implications. Healthcare organizations operating on thin margins cannot afford to have their most valuable resources—clinical staff—bogged down by technological inefficiencies. The 83% of IT teams reporting disruptions represent organizations losing productivity and, ultimately, profit. The problem extends to clinical decision-making as well. Research in Healthcare data security and privacy in Data Warehouse architectures notes that "Clinical decision support (CDS) in electronic health records (EHRs) has been found to improve patient safety. Despite this, CDS signals are routinely overruled, which is concerning in the critical care population because this group may be at more risk of injury."
Legacy systems don't just maintain the status quo—they actively inhibit innovation. Healthcare organizations want to implement artificial intelligence for diagnostic support, leverage IoT devices for remote patient monitoring, and utilize advanced analytics for population health management. However, legacy systems often lack the technical foundation necessary to support these cutting-edge capabilities.
The innovation barrier is widespread across industries, with particularly challenging implications for healthcare advancement. Forbes Technology Council research found that "almost 60% of CTOs surveyed by Forrester say their legacy tech stack is too costly and inadequate for modern applications." This technological inadequacy becomes especially problematic in healthcare, where the inability to adopt new innovations can directly impact patient care quality and outcomes.
The challenge of implementing AI initiatives becomes even more complex when data remains trapped in silos. According to a recent Gartner survey cited in How Data Silos Impact AI and Agents, 63% of organizations either do not have or are unsure if they have the right data management practices for AI. Even more concerning, Gartner predicts that through 2026, organizations will abandon 60% of AI projects unsupported by AI-ready data.
Gordon Robinson from SAS emphasizes the financial implications in the same article: "Poor data leads to underperforming models, which can cost organizations tens of millions of dollars or more." For healthcare organizations already operating on thin margins, these failed AI investments represent an opportunity cost.
This innovation barrier is not unique to healthcare. As RT Insights observes in their analysis, "companies relying on outdated technology struggle to adopt emerging innovations like cloud computing, automation, and AI, putting them at a competitive disadvantage." Additionally, they note that "as businesses grow, legacy systems become a bottleneck, requiring expensive modifications to accommodate expansion."
Michael Berthold from KNIME provides additional context on why established organizations face particular challenges: "If a company has been around for a while, it will have different tools and systems, and the act of unifying it all is doomed from the start. Even worse, if that company bought a couple of other companies in recent years that brought along their own tools and data solutions."
The inability to innovate puts healthcare organizations at a competitive disadvantage and prevents them from delivering the advanced care that patients increasingly expect. Organizations become trapped in a cycle where legacy systems prevent the adoption of new technologies that could improve both operational efficiency and patient outcomes. Interestingly, research highlighted in Healthcare data security and privacy in Data Warehouse architectures reveals a paradox: "Despite being a security risk, medication-related decision support performed better in the legacy system than in the commercial system, however, the study shows that both have a lot of room for improvement." This finding shows the challenging reality that while legacy systems pose significant risks, they sometimes outperform newer systems in specific clinical functions, making replacement decisions even more complex.
Because replacements are expensive, complex, and often require system downtime that hospitals can't afford.
Yes, compliance with data retention and privacy laws can make it difficult to decommission older systems quickly.
Vendor lock-in makes it costly and technically challenging to switch to modern platforms without losing critical functionality.
They cause frustration and burnout by forcing teams to constantly troubleshoot outdated technology.
Yes, cloud-based platforms offer scalable and more easily integrated alternatives to on-premise legacy infrastructure