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New Insights on Safety and Health IT

A. Zach Hettinger, MD, MS; Raj Ratwani, PhD; Rollin J. (Terry) Fairbanks, MD, MS | August 1, 2015 
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Perspective

Despite the widespread adoption of electronic health records (EHRs) over the last 10 years, the usability of these systems continues to be a serious challenge.(1) Although most physicians would not want to return to paper-based systems, physicians are frustrated with current health information technology (IT) and there are many examples of errors that have led to patient harm.(2,3) Anecdotally, health care workers often describe near misses and hazardous conditions related to the usability of EHRs. In contrast, many consumer electronic product designs include elegant human interfaces that mitigate error, and the airline industry designs safe interfaces that reduce the incidence of pilot errors.

The usability of any device or system can be broken down into two major categories: basic interface design (human factors [HF] 1.0) and cognitive support of the user (HF 2.0). The basic interface design should follow well-established principles that ensure information is clear and readable, such as font size and color, while also providing adequate contrast between text and the background. Focused on the cognitive support of the user, HF 2.0 entails much greater detail and a deep understanding of the workflow and cognitive needs of the user.(4,5) Designers focusing on HF 2.0 principles seek to understand how users accomplish their work in the context of their actual work environment (e.g., observations, task analysis, and other ethnographic techniques) and engage in iterative user testing of the interface throughout the development process.(4-6)

Integrating formative usability testing into the development process is critical to successful HF 2.0 efforts. For example, a well-designed HF 1.0 electronic order screen may have clearly labeled medications in a readable font and size, with an intuitive search function that minimizes the potential for user error by separating and graphically distinguishing similar sounding medications. An HF 2.0 display would allow the user to view a patient's current vital signs, medications, and medical problems on the same order writing screen, enabling the user to help direct therapy or catch an error before an order is signed. Just relying on focus groups or subject matter experts may result in a functional order writing system, but a strong user-centered design process would go much further, capturing the information needs, anticipating potential errors, and effectively designing out those errors from the system.

Most elements of HF 1.0 were identified many years ago, in classic human factors literature and through application in other domains.(7) This detail makes it surprising that health care IT systems so often violate HF 1.0 principles, leaving clinicians to struggle with the legibility or interpretation of data presented within the EHR. We believe that software and device developers are increasingly following these design principles, and beginning to perform adequate interface testing. This, coupled with the retirement of many legacy systems, will lead to the resolution of many of these remaining HF 1.0 issues.

We are more concerned about the lack of progress in addressing HF 2.0 challenges. Nearly all EHR vendors, both large and small, struggle with the challenge of designing for numerous permutations of workflows, clinical specialties, and physical environments in which their EHRs are deployed.(8) Yet these systems must be designed with the cognitive needs of the frontline users in mind for each specialty and each user role (physician, nurse, tech, clerk, etc.). For example, an HF 1.0 patient discharge tool may have the necessary textbox fields that allow the provider to enter all of the important discharge instructions. But an interface incorporating HF 2.0 design principles would ensure easy access and display of relevant nursing notes, changes in patient status and vital signs, automatically highlight abnormal test results, and suggest follow-up information based on those results. In current systems, abnormal findings and change in a patient's status are easily missed during the discharge process, despite the fact that the information is contained somewhere in the EHR, just not presented in a meaningful way to the user.

This process of supporting the cognitive needs of the user in health care is further complicated by the complexities of the implementation process and the design decisions required of the implementing provider.(9) No matter how well designed a system is "out of the box," the implementation team will still have very significant design decisions that will dramatically impact the usability and safety of the system. These design decisions should not be solely left to team members sitting in a conference room looking at screenshots and mockups of systems and workflows. To do this well, EHR vendors, health care systems, and frontline health care workers need to partner so that all can deeply appreciate the intersection between the technology and the users and design the system accordingly. These efforts must leave adequate time for testing the systems during the development process, and should not be rushed after the system is built and ready to be implemented.

Anecdotally, we have seen EHR vendors give their clients a wide range of advice regarding implementation. Some offer best practice recommendations, drawn from the literature or prior implementations. Others take a hands-off approach, leaving the purchasing hospital or clinic to customize the system themselves, perhaps hoping to limit their own liability by doing so. At this time, it is not clear which one of these approaches is most likely to lead to a safe, efficient EHR.

From our experience in studying EHRs and their implementations, we believe that health care systems and vendors would be well served by a library of lessons learned and use cases that they can draw upon to design and install their systems. Too often, health care systems undertaking a new EHR installation find themselves reinventing the wheel and repeating the same mistakes and missteps that another institution made previously. This is neither sustainable, nor desirable when it comes to implementing safe and efficient health IT systems.

This is not to say that all implementations should look alike—systems vary too much for there to be a cookie-cutter approach, and we need to preserve room for innovation by vendors and customization by institutions. But a more standardized approach to implementation would remove the guesswork and would likely save tremendous amounts of money and time. There are already some strong collaborations between vendors and associations like the Healthcare Information and Management Systems Society (HIMSS) Electronic Health Record Association, and this is a hopeful trend. But more needs to be done to support vendors' design innovation and for health care organization to focus on taking care of patients, instead of spending time on interface problems that were answered decades ago.(10)

A. Zach Hettinger, MD, MS Medical Director National Center for Human Factors in Healthcare, MedStar Institute for Innovation Department of Emergency Medicine, Georgetown University School of Medicine Washington, DC

Raj Ratwani, PhD Scientific Director National Center for Human Factors in Healthcare, MedStar Institute for Innovation Department of Emergency Medicine, Georgetown University School of Medicine Washington, DC

Rollin J. (Terry) Fairbanks, MD, MS Director National Center for Human Factors in Healthcare, MedStar Institute for Innovation Department of Emergency Medicine, Georgetown University School of Medicine Washington, DC

References

1. Hsiao CJ, Hing E. Use and characteristics of electronic health record systems among office-based physician practices: United States, 2001?2013. NCHS Data Brief. 2014;(143):1-8. [go to PubMed]

2. Friedberg MW, Chen PG, Van Busum KR, et al. Factors Affecting Physician Professional Satisfaction and Their implications for Patient Care, Health Systems, and Health Policy. Santa Monica, CA: RAND Corporation; 2013. [Available at]

3. Magrabi F, Ong MS, Runciman W, Coiera E. An analysis of computer-related patient safety incidents to inform the development of a classification. J Am Med Inform Assoc. 2010;17:663-670. [go to PubMed]

4. Guarrera TK, McGeorge N, Stephens R, et al. Better pairing of providers and tools: development of an emergency department information system using cognitive engineering approaches. In: Proceedings of the International Symposium on Human Factors and Ergonomics Society in Health Care. 2013;2:63. [Available at]

5. Bisantz AM, Mazaeva N. Work domain analysis using the abstraction hierarchy: two contrasting cases. In: Bisantz AM, Burns CM, eds. Applications of Cognitive Work Analysis. Boca Raton, FL: CRC Press; 2008. ISBN: 9780805861518.

6. Fairbanks RJ, Bisantz AM, Sunm M. Emergency department communication links and patterns. Ann Emerg Med. 2007;50:396-406. [go to PubMed]

7. Nielsen J. Finding usability problems through heuristic evaluation. In: CHI '92 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. New York, NY: ACM Press; 1992:372-380. [Available at]

8. Ratwani RM, Fairbanks RJ, Hettinger AZ, Benda N. Electronic health record usability: analysis of the user centered design processes of eleven electronic health Record vendors. J Am Med Inform Assoc. 2015;22:1179-1182. [go to PubMed]

9. Karsh BT. Beyond usability: designing effective technology implementation systems to promote patient safety. Qual Saf Health Care. 2004;13:388-394. [go to PubMed]

10. Ratwani R, Hettinger AZ, Fairbanks RJ; National Center for Human Factors in Healthcare. Anticipating Unintended Consequences of Health Information Technology and Health Information Exchange: The Role of Health IT Developers in Improving Patient Safety in High Reliability Organizations. Washington, DC: Office of the National Coordinator for Health Information Technology, Department of Health and Human Services; January 2014.

This project was funded under contract number 75Q80119C00004 from the Agency for Healthcare Research and Quality (AHRQ), U.S. Department of Health and Human Services. The authors are solely responsible for this report’s contents, findings, and conclusions, which do not necessarily represent the views of AHRQ. Readers should not interpret any statement in this report as an official position of AHRQ or of the U.S. Department of Health and Human Services. None of the authors has any affiliation or financial involvement that conflicts with the material presented in this report. View AHRQ Disclaimers
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