Identifying Opportunities for Workflow Automation in Health Care: Lessons Learned from Other Industries

Abstract

Background Workflow automation, which involves identifying sequences of tasks that can be streamlined by using technology and modern computing, offers opportunities to address the United States health care system's challenges with quality, safety, and efficiency. Other industries have successfully implemented workflow automation to address these concerns, and lessons learned from those experiences may inform its application in health care. Objective Our aim was to identify and synthesize (1) current approaches in workflow automation across industries, (2) opportunities for applying workflow automation in health care, and (3) considerations for designing and implementing workflow automation that may be relevant to health care. Methods We conducted a targeted review of peer-reviewed and gray literature on automation approaches. We identified relevant databases and terms to conduct the searches across sources and reviewed abstracts to identify 123 relevant articles across 11 disciplines. Results Workflow automation is used across industries such as finance, manufacturing, and travel to increase efficiency, productivity, and quality. We found automation ranged from low to full automation, and this variation was associated with task and technology characteristics. The level of automation is linked to how well a task is defined, whether a task is repetitive, the degree of human intervention and decision-making required, and the sophistication of available technology. We found that identifying automation goals and assessing whether those goals were reached was critical, and ongoing monitoring and improvement would help to ensure successful automation. Conclusion Use of workflow automation in other industries can inform automating health care workflows by considering the critical role of people, process, and technology in design, testing, implementation, use, and ongoing monitoring of automated workflows. Insights gained from other industries will inform an interdisciplinary effort by the Office of the National Coordinator for Health Information Technology to outline priorities for advancing health care workflow automation.

User Experience (Ux) Design in Medical Products: Theoretical Foundations and Development Best Practices

“…Optimizing workflow efficiency in medical products is crucial for enhancing productivity, reducing errors, and improving overall patient care (Zayas-Cabán et al, 2021). In healthcare settings, where time is often of the essence and the stakes can be high, streamlining user tasks and workflows is essential for enabling healthcare providers to focus on what matters most: delivering high-quality care to patients.…”

“…In many healthcare settings, providers are required to navigate multiple systems, interfaces, and documentation requirements throughout the course of their day, leading to inefficiencies, frustrations, and cognitive overload. Designers must identify opportunities to streamline user tasks, eliminate unnecessary steps, and automate routine processes, enabling providers to focus their time and attention on patient care (Zayas-Cabán et al, 2021). For example, in the design of electronic health record (EHR) systems, designers may implement features such as customizable templates, smart documentation tools, and clinical decision support algorithms to streamline documentation workflows and reduce data entry burden.…”

“…For example, in the design of clinical decision support systems, designers may implement algorithms that analyze patient data in real-time to provide providers with personalized treatment recommendations and alerts, enabling them to make more informed decisions quickly and effectively. In conclusion, optimizing workflow efficiency in medical products is essential for enhancing productivity, reducing errors, and improving overall patient care (Zayas-Cabán et al, 2021). By simplifying and streamlining user tasks, designing intuitive interfaces, integrating interoperability and data exchange capabilities, and leveraging data analytics and machine learning, designers can create medical products that support, rather than hinder, clinical workflows, enabling providers to deliver high-quality care more efficiently and effectively.…”

Development of a Collaborative Robotic Platform for Autonomous Auscultation

“…In the medical sector, the introduction of robotics and autonomous technologies is contributing to face the increasing number of patients per health professional and maintaining the existing level of quality in health services. In this context, automation allows, among other possibilities, professionals to carry out easier and safer diagnostic activities, not necessarily implying the presence of, or direct contact between, a doctor and his patient [4][5][6][7].…”

Automated and Optimized Neurosurgery Scheduling System Improves Resident Satisfaction

“…For instance, industries such as airline and manufacturing have long used advanced scheduling systems to optimize workforce allocation, considering factors such as employee preferences, shift rotations, and regulatory constraints. 2,3 These systems use sophisticated algorithms and machine learning techniques to achieve efficient and equitable schedules, a concept that can be adapted to the medical residency context. For example, an airline crew scheduling software program considers crew preferences, legal rest requirements, and flight connections, similar to how medical residency schedules need to account for clinic duties, duty hour limits, and educational needs.…”