Automation in Health Care: The Need for an Ergonomics-Based Approach

Abstract

Healthcare quality and efficiency challenges degrade outcomes and burden multiple stakeholders. Workforce shortage, burnout, and complexity of workflows necessitate effective support for patients and providers. There is interest in employing automation, or the use of “computer[s] [to] carry out... functions that the human operator would normally perform,” in health care to improve delivery of services. However, unique aspects of health care require analysis of workflows across several domains and an understanding of the ways work system factors interact to shape those workflows. Ergonomics has identified key work system issues relevant to effective automation in other industries. Understanding these issues in health care can direct opportunities for the effective use of automation in health care. This article illustrates work system considerations using two example workflows; discusses how those considerations may inform solution design, implementation, and use; and provides future directions to advance the essential role of ergonomics in healthcare automation.

PRACTITIONER SUMMARY

This article highlights the essential role of ergonomics in the effective design, implementation, and use of automation in health care. By discussing unique considerations for automation in health care and through two illustrative examples, we demonstrate the importance of an ergonomics approach for developing automated healthcare solutions.

INTRODUCTION

Health care continues to experience variability in access, safety, health outcomes, and disparities burdening both patients and providers worldwide (Dzau et al. 2021; Schoen et al. 2007). Globally, healthcare spending is expected to increase to $15 trillion by 2050 (Global Burden of Disease Health Financing Collaborator Network 2019) yet estimates suggest that anywhere between 20% to 40% of what is spent on health care is considered wasteful (Chalkidou and Appleby 2017; Shrank, Rogstad, Parekh 2019). Meanwhile, many countries continue to experience high disease burden, uneven access to services, healthcare disparities, and high rates of avoidable deaths (Gunja, Gumas, and Williams II 2023; National Academies of Sciences, Engineering, and Medicine 2018). Concurrently, burnout increasingly impacts global health worker productivity and retention, which in the United States (U.S.) alone is estimated to cost $4 billion annually (National Academies of Sciences, Engineering, and Medicine 2019), at a time when the industry is facing workforce shortages (Crisp and Chen 2014; GBD 2019 Human Resources for Health Collaborators 2022; Karuna et al. 2022; Liu et al. 2017; National Academies of Sciences, Engineering, and Medicine 2019; Woo et al. 2020), trends which were exacerbated by the COVID-19 pandemic (Leo et al. 2021; Morgantini et al. 2020; Poon et al. 2022). In addition, patients and members of their social networks engaged in their care (Valdez and Brennan 2015) (referred to in this article collectively as “patients” hereafter) are increasingly expected to manage a complex set of health tasks (National Research Council 2011), which often require care coordination across multiple providers and health insurance models.

Continued challenges with healthcare quality, workforce burnout and expected shortages, plus increased complexity of workflows, create an imperative to effectively and efficiently allocate work ensuring delivery of high-value care. There is increasing interest within the healthcare sector to leverage automation (Pang et al. 2018), or the use of “computer[s] [to] carry out certain functions that the human operator would normally perform” (Parasuraman, Sheridan, and Wickens 2000), across workflows to improve efficiencies, reduce costs, improve safety, improve health outcomes, reduce healthcare disparities, and drive innovation. While automation advances have historically focused on production systems and use of robotics to increase productivity or efficiency (Sauter 2007; Smith and Carayon 1995; Staccioli, Virgillito, and Back 2021), automation aimed at reducing workload enabled by information technology and modern computing has created new opportunities to improve workflows. More specifically, Zayas-Cabán, Okubo, and Posnack (2022) recently outlined priorities for advancing automation of workflows across a range of healthcare delivery domains, as illustrated in Figure 1, and highlighted strategies to advance those priorities.

Figure 1.

Healthcare workflow domains.

Adapted with permission from Clinovations Government + Health. Priorities to accelerate workflow automation in health care. Washington (DC): ONC; 2022 Oct [cited 2023 Apr 22]. 31 p. Available from: https://www.healthit.gov/sites/default/files/page/2022-10/PrioritiestoAccelerateWorkflowAutomation-508-1022.pdf

¹Adapted from: The AHA Center for Health Innovation. What is population health management? [Internet]. Chicago (IL): AHA; 2023 [cited 2023 Apr 28]. Available from: https://www.aha.org/center/population-health-management

²Adapted from: Centers for Disease Control and Prevention. Introduction to public health surveillance [Internet]. Atlanta (GA): CDC [last updated 2018 Nov 15; cited 2023 Apr 28]. Available from: https://www.cdc.gov/training/publichealth101/surveillance.html and Vlahović-Palčevski V, Mentzer D. Postmarketing surveillance. Handb Exp Pharmacol. 2011;205:339–51. doi:10.1007/978-3-642-20195-0_17.

While automation in the form of robotics is more widely implemented in physical care delivery and health management workflows related to surgery, medication dispensing, or rehabilitation (Kolpashchikov, Gerget, and Meshcheryakov 2022; Kyrarini et al. 2021), many information-based healthcare workflows continue to be predominantly manual. Current uses of automation in more information-based healthcare workflows target operational tasks with goals such as reducing missed appointments (Snodgrass and Schoch 2019; Starnes et al. 2019), increasing patient throughput (Dayarathna et al. 2019; Gul and Guneri 2012), and streamlining both billing and payment collection (Colpas 2013). Some of these applications have shown that person (e.g., health beliefs, socioeconomic status) and external environment factors (e.g., weather) need to be considered in automation solutions (Starnes et al. 2019). The development of automation to support care delivery and health management workflows includes the use of algorithms for identifying disease and predictive analytics to alert providers about specific health conditions (Davenport and Kalakota 2019). These solutions improved mortality rates, length of stay, and readmission rates (Shimabukuro et al. 2017) or slightly outperformed current processes (Nait Aicha et al. 2018) but their development focused on clinical efficacy, system validation, or performance and not on usefulness or understanding how these solutions impact real-world workflows and work systems. Broadly, care delivery and health management workflows related to clinical decision-making or patient-provider interactions, and workflows related to population health management, reporting, or surveillance, have not seen similar levels of automation.

Health information technology (IT) companies as well as the broader IT sector have begun developing automated tools and applications to support information-based care delivery and health management workflows. These tools are increasingly being incorporated into healthcare delivery (Amarasingham et al. 2014; Liu et al. 2019; Topol 2019). For many of these tools and applications, it is unclear whether or to what extent their design and implementation have explicitly accounted for the needs of the people performing the work as well as the complexities of the work systems in which they are embedded (Karsh et al. 2010). To avoid negative impacts on health care seen with implementation of other technologies such as infusion pumps (Yu, Obuseh, and DeLaunteris 2021), bar-coded medication administration (Carayon et al. 2014; Mulac et al. 2021), electronic health record systems (Abbott and Weinger 2020; Carayon et al. 2014), and patient portals (Ali et al. 2018; Baldwin et al. 2017; Zayas-Cabán and White 2021), making effective advances in automation in health care like those made in other industries (Hancock 2019) requires careful attention to ergonomics from the outset. While there is increased use of IT and modern computing (Ugajin 2023), there is limited research regarding the impact on healthcare work systems from data-driven automation interventions. This article discusses the unique aspects of health care and the essential role of ergonomics in the effective design, implementation, and use of automation in health care. It also highlights the importance of work system factors in considering automation solutions through two example workflows and outlines potential next steps.

UNIQUE WORK SYSTEM ASPECTS OF HEALTH CARE

Health care has several unique characteristics, underscoring the importance of attending to work system elements in advancing the design, implementation, and use of any new technology. These elements, illustrated in Figure 2, include tasks, the person or people who perform them, tools and technologies used, organizational conditions, and the internal as well as external environment in which tasks are performed (Carayon et al. 2006; Carayon 2009; Carayon et al. 2020; Hendrick and Kleiner 2001; Holden et al. 2013; Smith and Carayon-Sainfort 1989). Healthcare workflows, or “the sequence of physical and mental tasks performed by various people within and between work environments” (Agency for Healthcare Research and Quality 2011), across the domains in Figure 1 consist of multiple tasks performed by paid health professionals or by patients conducted individually or in collaboration with others (Holden et al. 2013; Holden and Valdez 2021). These workflows may impact or be impacted by multiple actors (e.g., administrative staff, pharmacists, insurance specialists) even if they are not directly engaged in the specific workflow of interest. Workflow tasks may be conducted across different settings with unique physical characteristics, such as clinics, hospitals, private residences, pharmacies, rehabilitation facilities, and community spaces. The combination of tasks, actors, and settings may make their discovery for analysis and understanding challenging, particularly for workflows primarily performed by patients (Gorman, Wellbeloved-Stone, and Valdez 2018).

Figure 2.

Work system elements.

Adapted with permission from Holden RJ, Carayon P, Gurses AP, Hoonakker P, Hundt AS, Ozok AA, et al. SEIPS 2.0: a human factors framework for studying and improving the work of healthcare professionals and patients. Ergonomics. 2013;56(11):1669–86. doi: 10.1080/00140139.2013.838643.

How health care is organized is further influenced by factors beyond the organizations and settings where care is delivered or managed. Access to and cost of healthcare services may be influenced by how health care is financed and regulated, which varies across countries (Wallace 2013). In the U.S., for example, health care is one of the most heavily regulated sectors of the economy (Food and Drug Administration 2022; Michigan State University 2022; Ozalp et al. 2022), with regulations spanning many levels; and payment for services is determined by a complex array of private and public insurance.

Healthcare technology is generally developed by third-party companies focused on best-of-breed solutions to address a singular application. Technology solutions address a specific problem or process with varying degrees of consideration as to how they will be integrated into provider and patient work systems (Hignett et al. 2013). In addition, patients may use tools not purpose-built for health care to support their healthcare-related tasks such as electronic or paper calendars to manage multiple appointments including medical appointments (Zayas-Cabán and Valdez 2012), physical or electronic files to archive laboratory test results (Zayas-Cabán and Valdez 2012), or social media to communicate about health or access health information (Valdez et al. 2017). While newly proposed regulation in the U.S. aims to improve transparency in artificial intelligence, algorithms, and other types of automation for providers (Health Data, Technology, and Interoperability NPRM 2023), patient-facing applications may not be subject to the same transparency and disclosure requirements.

There are parallels between the use of and considerations for automation in other sectors of the economy that illustrate similar opportunities and considerations for automation in health care (Zayas-Cabán, Haque, and Kemper 2021). For example, autonomous or assisted-driving vehicles and airplanes are designed to prevent collisions. Similarly, automation of healthcare workflows must be designed to prevent harm to patients and providers. In aviation, scheduling and managing flights and crew rotations requires automation to be flexible and adaptive to uncertainty due to factors such as airplane capacity, connection times, and weather. Similarly, scheduling and managing healthcare appointments and procedures requires consideration of factors such as resources (e.g., available people, space, and equipment), patient readiness (e.g., data gathered on prior tests and completion of prior authorization), and human behavior shaped by both personal characteristics and a wide range of external factors (e.g., missed, delayed, or cancelled appointments and walk-ins). Production industries manage supply chain and delivery mechanics and disruption, and, similarly, healthcare organizations must also manage supply chain and logistics for clinical encounters, procedures, and treatment. In the service sector, hotels manage staffing to respond to customers, schedule room cleaning and availability, and introduced technology that allows customers to check in, request services, and/or modestly tailor their rooms. Similarly, healthcare facilities manage room turnover and availability based on appointments, admissions, discharges, and in-house transfers. In addition, they need to manage the staff that performs the turnover work to maintain both workforce and patient loyalty.

While these parallels exist, experts have identified unique complexities to health care that are important to consider when automating workflows (Zayas-Cabán, Haque, and Kemper 2021, Clinovations Government + Health 2022). First, patients, providers, and other actors collaborate to co-produce health care to improve health. Patients and providers engage in shared decision-making regarding treatment, which requires patient’s trust in their individual providers, healthcare organizations, and, implicitly, any technology used in the delivery of healthcare services or in self-management. In addition, there is unique variability in healthcare delivery across specialties, practices, and regions. Further, the data and standards used to describe and share health and health process information are complex. Health care also features a distributed and non-standardized infrastructure across organizations, including workforce and technologies. Moreover, different from other industries, health care is delivered locally; there is generally no international competition for healthcare services. Importantly, financial or economic benefits of improvements in the delivery of healthcare services may accrue to payors (e.g., health insurers or employers who pay for insurance policies) who stand to gain from improved efficiencies such as reducing unnecessary services. Lastly, because of the nature of health care, preserving patient privacy and ensuring the security of patient information is paramount.

THE ROLE OF ERGONOMICS IN AUTOMATION AND HEALTH CARE

Automation has been increasingly deployed across production, transportation, and service industries (Zayas-Cabán, Haque, and Kemper 2021). Specific applications span aviation, financial services, banking, and hospitality industries, and have been implemented to improve safety, reduce or eliminate redundant tasks, remove high-cost waste, and identify fraud and abuse. Increased availability of electronic data coupled with advances in data analytics, artificial intelligence, and other computational approaches and technologies have further facilitated the development of automation across different sectors of the economy (Zayas-Cabán, Haque, and Kemper 2021).

Many factors cited in the literature point to broader considerations for automating workflows and determining which workflows should be automated for both professionals and consumers (Dadashi et al. 2014; Navarro et al. 2018; Sauer and Rüttinger 2007). These factors include attributes of workflows that lend themselves to automation. For example, a high degree of automation has been associated with manual and frequently repeated workflow tasks with clear and well-defined roles and responsibilities performed in environments with highly advanced technology and analytics (Zayas-Cabán, Haque, Kemper 2021). Notably, ergonomics’ role in advancing effective automation is recognized. Hancock (2019) points to the importance of ensuring that the human element of a work system is well understood and factored into the design, instead of focusing solely on or primarily on the technology that may facilitate or drive automation. The importance of continuous evaluation and improvement of automation, including monitoring for unintended consequences, is also well established (Bainbridge 1983; Hancock 2019; Parasuraman 2000). Lessons from the use of automation in railways, aeronautics, and consumer products further illustrate that effective automation requires attention to the complexities of work systems and interactions amongst its different elements (Dadashi et al. 2014; Navarro et al. 2018; Sauer and Rüttinger 2007; Zayas-Cabán, Haque, Kemper 2021). Successful automation in other industries is associated with attention to and understanding of several work system factors including the people involved, tasks within the workflow, and available technology (Zayas-Cabán, Haque, and Kemper 2021). In addition to those factors, understanding the organization and internal and external environments is important in health care.

There have been calls for the application of ergonomics to health care for several decades (Bonjer 1976). There is increased recognition of the role of ergonomics approaches and the need to attend to work systems considerations in health care (Carayon et al. 2014). Ergonomics approaches and methods have been applied to improve healthcare quality, safety, and efficiency (Xie and Carayon 2015; Hignett et al. 2015; Carayon et al. 2018; Russ et al. 2015) and design of new care delivery models (Kopach-Konrad et al. 2007). Similarly, it is essential to integrate ergonomics into any automation efforts in health care to avoid documented challenges in the design, implementation, and use of other healthcare technology (Carayon et al. 2014; Karsh et al. 2010).

WORK SYSTEM CONSIDERATIONS

Experts have identified illustrative examples of healthcare workflows that may benefit from automation, included in Tables 1–3 (Clinovations Government + Health 2022). Tables 1–2 provide examples of care delivery and health management workflows performed primarily by patients (Table 1) or providers (Table 2), and Table 3 includes examples of population health workflows where automation designed using ergonomics-driven approaches could improve access to information.

Table 1.

Care delivery and health management workflows performed by patients to consider for automation.

Workflow	Rationale
Electronic health data sharing	• Enable patients to access their data and control data sharing with third-party applications and other providers without relying on healthcare providers and paper-based systems • Empower patients to be active participants in their care and verify provider data
Post-encounter care coordination	• Ensure care management and monitoring tasks are immediately underway after ambulatory and inpatient encounters to improve health outcomes • Connect patients with advocates and community and non-clinical resources for social needs
Care planning	• Facilitate information sharing, communication, data verification, and decision-making with care teams
Billing and payment	• Streamline, simplify, and bring transparency to costs from providers and payors
Customer service	• Reduce burden on providers and administrative staff for scheduling and other care delivery support tasks • Improve patient experience through tailored and relevant interactions • Provide digestible information in patient-friendly terms and venues • Ensure critical messages are received, understood, and acted upon

Adapted with permission from Clinovations Government + Health. Health IT workflow automation policy development: workshop summary report. Washington (DC): ONC; 2022 Oct [cited 2023 Apr 22]. 25 p. Available from: https://www.healthit.gov/sites/default/files/page/2022-10/WorkflowAutomationWorkshopSummaryReport_508-1022.pdf

Table 3.

Population health workflows to consider for automation.

Workflow	Rationale
“Define” the patient	• Enable care providers and delivery organizations to understand “data blind spots” and provide “life-focused” care • Facilitate widespread availability of sophisticated population health analytics tools and data
Collection and use of non-clinical data sets	• Provide innovative ways to advance understanding of social determinants of care • Increase availability of useful patient insights from third parties outside of health care
Communication, information gathering, and identify verification	• Reduce use of paper forms and tasks that require providing the same administrative or clinical information multiple times • Consistently collect and support use of information regarding patients’ communication needs and preferences, such as primary language or method of contact
Reporting registry and quality measurement data	• Reduce manual burden associated with report development, generation, and transmission • Decrease length of time to share public health and quality measurement data

Adapted with permission from Clinovations Government + Health. Health IT workflow automation policy development: workshop summary report. Washington (DC): ONC; 2022 Oct [cited 2023 Apr 22]. 25 p. Available from: https://www.healthit.gov/sites/default/files/page/2022-10/WorkflowAutomationWorkshopSummaryReport_508-1022.pdf

Table 2.

Care delivery and health management workflows performed by providers to consider for automation.

Workflow	Rationale
Remote care delivery and monitoring	• Extend telehealth and virtual health across the care spectrum • Transform care delivery across settings with monitors and alerts that notify patients and their providers of an appropriate visit based on wearables, sensors, and other technologies
Inpatient and outpatient decision making	• Reduce manual tasks by streamlining data collection, review, and translation into practice • Reduce burden on providers to locate relevant data within electronic health record (EHR) and other systems to support real-time care decisions
Encounter follow-up	• Eliminate reliance on workarounds that reside outside the EHR by improving follow-up schedules for clinical reminders
Inbox triaging	• Reduce inefficient roles and tasks for inbox monitoring by assigning messages to appropriate care team members and administrative staff and tracking responses
Scheduling	• Reduce information gathering burden and improve appointment efficiency to better understand and respond to condition severity and requests for medical records prior to scheduling appointments or procedures
Care team member collaboration and communication	• Reduce duplicative information gathering by streamlining check-in, registration, and rooming workflows
Patient sensing	• Increase efficiency and capacity for ongoing monitoring of patient status to facilitate care management and treatment
Control monitoring	• Reduce unnecessary variation that may lead to duplication of effort, patient safety events, inconsistent quality of services, or inefficient workflows

Adapted with permission from Clinovations Government + Health. Health IT workflow automation policy development: workshop summary report. Washington (DC): ONC; 2022 Oct [cited 2023 Apr 22]. 25 p. Available from: https://www.healthit.gov/sites/default/files/page/2022-10/Workflow Automation Workshop Summary Report_508-1022.pdf

To specifically illustrate the work system considerations in automating healthcare workflows, we present two different care delivery and health management workflow examples, one from the perspective of the patient and the other from the perspective of the treating provider. These examples already include some automation used to generate standing orders, scheduling, and notification, but could benefit from additional automation. Table 4 provides descriptions of work system elements, as identified in the Systems Engineering Initiative for Patient Safety (SEIPS) 2.0 model (Holden et al. 2013), for each of the two examples. This approach can be a first step in incorporating ergonomics approaches to understand work system design and functioning.

Table 4.

Work system factors in two example care delivery and health management workflows.

	Workflows
Work System Elements	Patient: Obtaining a COVID-19 vaccine	Provider: Reviewing laboratory results and conducting necessary follow-up
Person	Age, cognitive function, understanding of vaccine-related guidance and information, attitudes toward vaccinations, physical abilities, language, medical history	Knowledge of and experience with laboratory test, underlying diagnosis, and patient history and characteristics; skills and experience with technology used to order laboratory tests, receive and review results, and share and communicate results with patients
Tasks	Multiple tasks each with its own level of complexity including determining eligibility, determining vaccine availability, making an appointment, traveling to the appointment, receiving the vaccine, observing and reporting any side effects, obtaining documentation of vaccination status, and reporting vaccination status	Multiple tasks each with its own level of complexity including receiving notification results are ready, accessing laboratory report, reviewing laboratory report, conveying results to patients and/or sharing information with patients regarding results, follow-up as needed. Additional factors include complexity of patient history, diagnosis, and medication regimens.
Tools and Technology	Tools (e.g., cellular phones, computers, printers, pamphlets) with varying designs and levels of complexity needed to access information regarding vaccine eligibility and availability, schedule an appointment, attend the appointment, report side effects, and obtain and share vaccination status information	Ease of access and use as well as configuration of tools or technology employed to access, review, and share results; and conduct any follow-up
Organization	Means to travel to an appointment, vaccine affordability, and availability of social support	Patient volume load, whether other personnel assist and are available to assist when appropriate (e.g., other colleagues to monitor abnormal result alerts or for consultation, patient educator), policies with regards to results sharing, investment in relevant technology
Internal Environment	Different settings employed across tasks with unique set of physical attributes that may enable or make it difficult to complete them: pre-administration tasks may be conducted at a private residence or another community setting; vaccine may be received at multiple different locations including, government facilities, pharmacies, doctors’ offices, schools, or places of employment. Infrastructure and its characteristics (e.g., availability of Internet) may facilitate or hinder each task.	Workspace design and layout, workstation design and interface with relevant technology and information systems, whether conducted in an inpatient or outpatient environment
External Environment	Availability of the vaccine and desirable appointments at convenient locations; policies that may influence how vaccines are distributed, to whom, and at what cost; public communication and discourse regarding vaccination	Infrastructure at external laboratories, regulations with regards to laboratory results sharing, market-influenced availability of technology and features and personnel pay levels, societal expectations regarding laboratory results sharing

Obtaining a COVID-19 vaccine is an example of a care delivery and health management workflow that was common across the U.S. and in other countries during the pandemic. Automation was used in this workflow to provide consolidated information on vaccine availability, encourage appointment scheduling and send reminders (Suarez 2021; Gwynne, Ratwani, and Dixit 2023), generate vaccine orders at scheduled appointment times (Suarez 2021), and generate notifications to schedule second dose appointments (Suarez 2021). As individuals began seeking vaccines, they were faced with a disconnected and labor-intensive search process. Private individuals leveraged open and available data and modern computing technologies to automate the process of searching for vaccines (Basu 2021; Maxouris 2021). In addition, large healthcare provider organizations leveraged existing information systems to automatically check for patient portal accounts and send text messages to patients to schedule vaccine appointments (Suarez 2021; Gwynne, Ratwani, and Dixit 2023). However, older patients encountered technical issues when responding to text message-based vaccine appointment scheduling prompts, which impacted their ability to successfully make an appointment (Gwynne, Ratwani, and Dixit 2023). Further automated and consistent tools could have facilitated an understanding of vaccine eligibility based on personal characteristics and local availability. Automation might facilitate making information available in multiple languages, using clear and plain language, and for use across platforms and systems. There was a need for the development of tools that quickly integrated vaccine availability information in real-time and presented it to users in an easy-to-navigate way that would facilitate search based on preferred parameters such as location, transportation, hours, and vaccine type. More seamless integration and navigation between different systems to facilitate appointment scheduling, reminders, and follow-up was also needed. Further, automation could have enabled more effective recording of vaccine administration information, integration of vaccine records with appropriate medical records, and provision of vaccine records to patients in multiple modalities for their records and further sharing as needed.

A robust understanding of work system factors associated with this workflow would help inform the design and implementation of any related automation solutions. First, while this example workflow focuses on the role of the patient, obtaining a COVID-19 vaccine is influenced by a combination of several care delivery and health management, reporting, and surveillance workflows led by other actors including providers and public health experts. At a high level, the workflow and related tasks summarized in Table 4 may seem straightforward. However, they involve a complex set of steps. The ability to complete workflow tasks was influenced by person factors, including the understanding of information and guidance regarding vaccination influenced by how information was conveyed to the public (e.g., is the information in a language that patients could understand, at the appropriate reading level, clear, and simple). As a result, this influenced patients’ knowledge of where to seek relevant information or knowledge regarding eligibility and availability. Completing each task required interaction with different technologies and information systems, relying on varying data sources and infrastructure, influencing the ability to effectively access relevant information, determine vaccine availability, and schedule appointments. As many information-based processes have shifted to electronic forms, individuals without access to high-speed Internet, lack of clarity on functionality on different websites and scheduling systems across multiple platforms, and general lack of facility with searching on the Internet for resources, faced barriers in completing relevant tasks.

Availability of family, friends, and other community support also influenced not only vaccination appointment scheduling but the ability to travel to appointments. External environmental factors influenced where and how vaccines were made available, and how eligibility and availability information was communicated to the public. Local communities implemented vaccine distribution differently, leveraging existing infrastructure to interface and communicate with provider, regional, and national organizations, and their information systems. Local implementation and infrastructure impacted patients’ ability to navigate across sources of information and several different information systems. This resulted in complexity in scheduling appointments at a convenient and accessible time and location as members of the public had difficulty finding reliable, comprehensive information regarding vaccine availability at specific locations.

Laboratory results review and follow-up is another example of a care delivery and health management workflow that is common across many inpatient and outpatient healthcare settings. Automation is currently used to send notifications to providers regarding abnormal laboratory results (Slovis et al. 2017) and to communicate test results to patients (Pillemer et al. 2016; Steitz et al. 2019). Automated alerts to providers have not always resulted in quicker response and clinical action, and there have been calls to better understand their effects on clinical workflow (Slovis et al. 2017). Automated sharing of test results with patients has been shown to provide desired access to clinical information (Pillemer et al. 2016; Steitz et al. 2023), but technologies and approaches used to provide access to results may require complex tasks that burden patients and result in disparate access to laboratory results information (Steitz et al. 2019). This workflow may also benefit from additional automation solutions, depending on how currently used tools are designed and implemented. Functionality that supports comparison of laboratory results over time would enable more efficient provider review. Automated integration of features that support results follow-up including consultation, access to relevant information resources, ordering repeat or additional testing, adjusting medications, scheduling follow-up appointments, conducting referrals, or reporting relevant results to a public health agency for surveillance, may also benefit providers. Automation may further facilitate more effective communication of results to patients by enabling the integration of tailored educational materials to accompany laboratory results, sharing of results with individuals in their social network as identified by patients, tailoring results reporting based on health and numerical literacy levels, or tailoring any related action steps so they are culturally relevant.

Design and implementation of any automation solutions, however, would benefit from the robust understanding of work system factors associated with this workflow. First, while the example, as described, focuses on the role of the provider, this workflow is influenced by other operational and care delivery and health management and, in some cases, reporting and surveillance workflows led by other actors including patients, administrative personnel, and laboratory staff. Laboratory results review and follow-up by a provider requires information access and gathering, review, analysis, and communication, and may involve a series of follow-up activities. Busy providers may need to respond to any alerts regarding results during or outside the course of other clinical activities or have alert reviews assigned to other individuals within their organization. Ease of access and use of laboratory reports, as well as tools that help facilitate review and comparison to past results, communicate with the laboratory or consult knowledge resources, support clinical decision-making regarding laboratory results, facilitate conveying results to patients while adding relevant notes and useful health information resources to support patient education and conduct any follow-up, influence providers’ ability to perform these tasks efficiently and effectively.

Providers may perform workflow tasks at an office, while moving through a clinic, hospital, or at home – each location featuring varying characteristics that may influence the ability to efficiently complete these tasks. The availability and design of relevant tools may be influenced both by organizational decisions regarding what systems to invest in as well as the broader market availability of well-designed technologies. In addition, organizational implementation decisions and choices regarding existing tools and technologies impact available functionality and ease of use. For example, while standardized interfaces exist between healthcare provider organizations and laboratories, they must be configured to support automated linking of results received to the ordering provider and individual patients to facilitate ease of access and review. More broadly, organizational and external policies may further influence timing and modality sharing results with patients.

IMPLICATIONS FOR AUTOMATION

As illustrated by the above examples, several work system factors can impact and guide efforts to automate healthcare workflows as summarized below and illustrated in Figure 3.

Figure 3.

Healthcare work system factors that impact and guide automation.

• Multiple actors

  Interactions between actors (e.g., patients, providers, administrative staff) within and across workflows require any automation solution to consider these multiple roles, individual needs, values, and preferences, and how all actors may be impacted. Ergonomics methods have been used to understand teamwork within the context of surgery (Hignett et al. 2013), which could be expanded to other healthcare specialties and individuals involved.

• Workflow variability

  Variability in how workflows may be performed across settings or regions creates challenges to standardizing across individual, organizational, or market levels. Understanding which workflow aspects are consistent across settings or locations may yield insights into what tasks may be automated. The extent to which a workflow is consistently conducted across settings and regions may further impact the demand for automation solutions across organizations and markets.

• External factors

  Socioeconomic and other external factors outside of the control of healthcare organizations or patients, such as access to transportation, may need to be reflected in automation solutions to support appointment scheduling or required travel to an appointment. Automation solutions may need to account for the way such factors shape patient needs.

• Infrastructure

  The technical development of automation solutions may need to account for extant terminologies used to code health data and information as well as updates needed as standards evolve. Workforce and technology availability may impact the kinds of automation solutions that can be implemented in a standardized way across regions. Differences in personnel, staffing levels, and patient volume across settings may inform where automation may be of most benefit across organizations.

• Safety, Privacy, and Security

  To mitigate potential risks to patient safety, consideration of work system factors in healthcare workflows may aid automation developers in understanding the degree to which humans are involved in decision-making for any given workflow and how that may impact the level of automation. Careful attention must also be given to ensuring the privacy of patient data and maintaining the security of patient information.

Understanding workflows across healthcare settings and domains will require mixed methods approaches to conduct robust assessments of all work system elements and their interaction (Holden and Valdez 2021; National Research Council 2011). Use of mixed methods is important to both characterize and understand context regarding work system elements and workflows. A variety of methods have been utilized in other ergonomics applications that can be employed across automation design, implementation, and to evaluate use. Frequently used qualitative methods include observations, interviews, and focus groups; commonly used quantitative methods include task analysis techniques, questionnaires, user testing, and analysis of clinical or performance data (Hignett et al. 2013; Xie and Carayon 2015).

In general, automation solutions in health care should support information gathering, aggregation, transmission, analysis, synthesis, and/or display activities to reduce the cognitive load of those involved. The broader goal should not focus on replacing those involved in a particular workflow (Topol 2019), but instead on making them available for high-value work by removing the performance of rote tasks that may be susceptible to error or reducing tasks that do not have requisite financial reimbursement for the time spent. Automation in health care may help not only drive efficiency and quality but also support personalization of healthcare interactions that are better aligned with the needs of individuals involved.

CONCLUSION

Variable quality, high and continually increasing costs, and increased burden on patients and providers, have spurred interest in automating healthcare workflows. Automation may offer opportunities to reduce manual and redundant tasks, enable more effective and efficient care delivery, and potentially support the personalization of healthcare services. However, due to unique factors regarding the way health care is delivered and managed and the complexity of healthcare workflows, consideration of ergonomics is essential to the effective design, implementation, and use of workflow automation solutions. As illustrated via two example workflows, attending to and understanding work system factors and their interactions is particularly important in health care.

The field of ergonomics is in the beginning stages of determining how best to automate healthcare workflows in ways that meet the needs of multiple user communities and support complex work systems. While it is expected that an ergonomics approach would enable doing so effectively, concrete operationalizations of ergonomics-based approaches to automating healthcare are still nascent. To that end, we provide a list of suggested directions for future work to move forward in creating ergonomics-informed automation of healthcare workflows. As summarized in Table 5, the ergonomics community should pursue new research, engagement, resource and tool development, and training opportunities to effectively advance the use of ergonomics in the design, implementation, and use of automation in health care. The field of ergonomics has a unique opportunity to further examine healthcare workflows and work systems and inform the development of sector-specific approaches to automation.

Table 5.

Next steps to advance ergonomics-based healthcare workflow automation.

Opportunity	Focus
Research	• Advance understanding of the complexity of health work across workflow domains, actors, and settings and how to incorporate into design (Hignett et al. 2013) • Identify what is needed to implement a work system-based approach to automation design and evaluate the effectiveness of such approaches (Hignett et al. 2013; Xie and Carayon 2015; Zayas-Cabán and White 2020) • Develop ergonomics methods and resulting automation solutions in ways that account for differences in the work system at scale
Engagement	• Advocate and engage in policy and standards development activities to ensure inclusion of ergonomics-related requirements in any relevant policy initiatives and adopted standards and best practices (Gettinger and Zayas-Cabán 2021; Ratwani et al. 2015; Savage, Fairbanks, and Ratwani 2017) • Develop educational campaigns for multiple stakeholders and groups that represent them, including healthcare providers, patients, policymakers, and developers regarding the importance of ergonomics-driven design of healthcare automation
Resource and tool development	• Develop principles, tools, and other resources for technology development firms to facilitate improved integration of ergonomics into design, implementation, and studies of use of healthcare automation solutions
Training	• Work to ensure ergonomics training is integrated into relevant health (e.g., across clinical roles and specialties, health management and administration, health policy, public health, health informatics) and automation-related curricula (e.g., computer science, information sciences or information technology) • Expand existing or develop additional ergonomics training and certificate programs for current health and automation professionals • Offer ergonomics trainees robust training in healthcare delivery and services, including focus on both patient and provider perspectives

DATA AVAILABILITY STATEMENT

No new data were generated or analyzed in support of this work.