When Healthcare Technology Fails, Is It Really a Staff Problem?

Healthcare organizations continually invest in technology intended to improve efficiency, strengthen documentation, support clinical decision-making, and enhance patient care. Electronic health records, automated workflows, clinical decision-support tools, and artificial intelligence are increasingly embedded in everyday operations. Yet the introduction of new technology does not always produce the improvements organizations anticipate. Staff may find themselves navigating additional screens, duplicating information, developing workarounds, or spending more time managing technology than completing the work it was intended to support.

When these problems arise, the response often focuses on the people using the systems. Additional training is provided, procedures are reinforced, and performance expectations are revisited. These measures may be appropriate in some circumstances. But they raise a broader question: Are the difficulties related to individual performance, or do they reflect problems with the technology, the workflow, or the way the organization has implemented the system?

This question is explored in the 2026 article “AI and the Human Factor in Healthcare,” published in Medicine, Health Care and Philosophy. The authors examine the relationship between artificial intelligence, healthcare professionals, and the human factors that influence how technology is used in healthcare. Their discussion provides a useful starting point for considering a broader operational question: when technology does not work as intended, how much of the problem lies with the people using it, and how much lies within the systems in which they work?

Understanding that distinction is an important part of healthcare leadership.

Looking Beyond Individual Performance

Human factors and ergonomics research examines how people interact with the various components of a work system including technology, tasks, processes, organizational structures, and the physical work environment. Rather than examining human performance in isolation, this discipline considers how these elements interact and influence one another.

This perspective has particular importance in healthcare, where even seemingly straightforward tasks often involve multiple systems, competing priorities, interruptions, and time-sensitive decisions.

A healthcare professional who repeatedly enters the same information into different fields, struggles to locate relevant patient information, or must move between multiple applications to complete a single task may not be experiencing a training problem. The difficulty may reflect a system that does not adequately support the way the work is performed.

The World Health Organization recognizes that patient safety is influenced by multiple, interconnected factors. Its discussion of patient safety identifies organizational processes, technology, staffing, communication, teamwork, and human behavior as contributors to patient harm. This broader understanding is important because it moves the discussion beyond the assumption that adverse outcomes can be explained by individual mistakes alone.

This does not mean that individual accountability is unimportant. Competency, appropriate training, adherence to procedures, and professional responsibility remain essential. Rather, individual performance and system design should be evaluated together. Addressing only one may leave important contributors to a problem unidentified.

When Technology Creates Additional Work

Electronic health records provide a useful example of the relationship between technology design and operational performance.
EHR systems are intended to make patient information more accessible, support continuity of care, and improve documentation. However, the way information is organized and presented can affect how efficiently professionals perform their work.

A 2025 scoping review published in the Journal of Evaluation in Clinical Practice, titled Usability Challenges in Electronic Health Records: Impact on Documentation Burden and Clinical Workflow, examined 28 studies selected from 2,387 identified records. The researchers identified recurring problems involving poorly designed interfaces, excessive navigation, fragmented information, task switching, and the need for workarounds.

These difficulties can have consequences beyond frustration with a software application. When information is scattered across multiple screens, professionals must devote additional attention to locating, reviewing, and reconciling it. Duplicated documentation and workarounds can introduce further opportunities for errors and increase the time required to complete tasks.

The significance is not that electronic records are inherently problematic. Their value depends, in part, on how well they support the clinical and administrative processes they are intended to facilitate.

A separate 2026 study published in npj digital medicine, When Better Data Meets Better Design: How EHR Data Usability and System Usability Shape Physicians' Cognitive Load, examined survey responses from 564 physicians across 32 specialties. The researchers found that system usability and data usability influence different aspects of cognitive load. Better system usability was associated with reduced unnecessary cognitive effort, while better data usability supported engagement with clinically meaningful information.

Providing more information does not necessarily make a system more useful. How information is organized, presented, and integrated into the work process matters.

The Human Factors Perspective on Artificial Intelligence

These considerations become increasingly relevant as healthcare organizations introduce artificial intelligence.

AI applications may assist with documentation, summarize clinical records, identify patterns, support risk assessment, and help coordinate information across teams. Their potential value is considerable, but their performance cannot be evaluated solely by examining the technology itself.

An AI tool may function as intended from a technical standpoint while creating difficulties in the environment where it is used. Its recommendations may arrive at the wrong point in a workflow, require additional manual data entry, or present information in a way that is difficult to interpret. Staff may also become overly reliant on automated recommendations or, conversely, spend considerable time checking and correcting their output.

In their 2022 article, Eight Human Factors and Ergonomics Principles for Healthcare Artificial Intelligence, Mark Sujan, Rachel Pool, and Paul Salmon argue for moving beyond a technology-centered approach toward a systems perspective. Their discussion emphasizes the importance of understanding how AI interacts with people, tasks, workflows, and organizational environments.

This is not an argument against AI adoption. It is a recognition that technical performance and operational effectiveness are not necessarily the same thing. A system can produce accurate outputs yet still be difficult to incorporate safely and efficiently into everyday work.
Similarly, the FUTURE-AI international consensus guideline for trustworthy and deployable artificial intelligence in healthcare, published in The BMJ, addresses the development and deployment of trustworthy AI in healthcare. Its recommendations include involving end users in defining requirements, establishing appropriate human oversight, evaluating usability in real-world clinical environments, and assessing clinical utility and safety.

These considerations suggest that evaluating AI should involve more than asking whether the technology works. Organizations also need to understand how it changes the work being performed.

What This Means for Hospice Organizations

Hospice organizations have their own operational considerations when evaluating technology. Care is delivered across multiple settings, often by interdisciplinary teams working independently and together. Information must move between nurses, physicians, social workers, chaplains, aides, administrative personnel, and other members of the care team. Coordination with patients, families, facilities, pharmacies, and other providers adds further complexity.

Technology is expected to help manage these demands, but implementation can introduce new challenges if the systems do not reflect how hospice work actually occurs.

Consider a documentation platform that requires clinicians to enter similar information in multiple locations. A scheduling system that does not adequately account for travel time, visit requirements, or changing patient needs. An automated assessment tool that does not accommodate the complexity of an individual patient's circumstances. Or an AI-generated clinical summary that saves time initially but requires extensive review and correction before it can be relied upon.

Each example raises questions about more than whether staff have received adequate training. Does the technology reflect the realities of hospice operations? Does it support communication across disciplines? Does it make relevant information easier to access? Does it reduce unnecessary work, or does it simply redistribute that work?

These are operational questions with potential implications for documentation quality, care coordination, staff workload, and organizational performance.

The research cited above is largely drawn from broader healthcare settings, rather than hospice-specific studies. As such, the findings should not be interpreted as evidence that hospice organizations experience these problems at any particular rate. However, the human-factors principles identified in these studies provide a useful framework for evaluating technology in hospice environments.

A More Comprehensive Approach to Technology Implementation

For organizational leaders, the practical challenge is to evaluate technology as part of the entire work system rather than as a standalone product and that process begins before implementation. Staff who will use a system should have an opportunity to explain how their work is performed, where information is needed, what creates delays, and which tasks are particularly difficult. The perspectives of clinicians, administrators, compliance professionals, and other affected users can reveal operational requirements that may not be apparent during a software demonstration.

Evaluation should also continue after implementation. A system that performs well during testing may behave differently when introduced into a busy organization with competing demands and varying levels of user experience. Leaders should examine whether documentation time has changed, whether duplicate work has increased, whether communication has improved, and whether staff have developed informal workarounds to accomplish tasks the system does not adequately support.

When problems emerge, the response should include an examination of the underlying process. Additional training may be necessary, but it should not automatically become the default solution. In some circumstances, workflow adjustments, interface changes, improved system integration, clearer procedures, or reconsideration of the technology itself may be more appropriate.

Accountability remains part of this process. Staff must understand their responsibilities, use systems appropriately, and exercise professional judgment. Organizations, in turn, must ensure that the tools and processes they provide are reasonably suited to the work expected of their employees.

Technology, People, and Organizational Responsibility

The relationship between people and technology in healthcare is not a simple question of choosing one over the other. Technology can improve access to information, reduce repetitive tasks, support consistency, and help organizations manage increasingly complex operations. At the same time, its benefits depend on the environment in which it is introduced and the way people interact with it.

An important contribution of human-factors research is its recognition that performance is shaped by the interaction between individuals and the systems in which they work. When something goes wrong, examining those interactions can provide a more complete understanding than focusing exclusively on the person closest to the problem.

For hospice leaders, this is particularly relevant as organizations continue to evaluate new technologies and incorporate AI into their operations. The objective should be to understand not only what a technology can do, but also what it requires of the people expected to use it.

Ultimately, successful technology implementation is not measured simply by whether a system has been installed, whether employees have completed training, or whether a process has become automated. It should also be evaluated by whether the technology supports the work, strengthens coordination, and contributes to the organization's ability to deliver appropriate, effective, and person-centered care.
The question, then, is not simply whether staff are adapting to technology. It is whether the technology, the workflow, and the organization are working together effectively.