Abstract
Background
Diagnostic Errors are a major source of patient harm, most of which are caused by cognitive errors and biases. Despite research showing the relationship between software systems and cognitive processes, the impact of the Electronic Health Record (EHR) on Diagnostic Error remains unknown.
Methods
We conducted a scoping review of the scientific literature to (1) survey the association between aspects of the EHR and diagnostic error and (2) through a human-systems integration lens, identify the types of EHR issues and their impact on the stages of the diagnostic process.
Results
We analyzed 11 research articles for the relationship between EHR use and Diagnostic Error. These articles highlight specific technical, usability, and workflow issues with the EHR that pose risks for diagnostic error at every stage of the diagnostic process.
Discussion
While technical problems such as EHR interoperability and data integrity pose critical issues for the diagnostic process, usability and workflow issues such as poor display design and inability to track test results also hamper clinicians’ ability to track, process, and act in the diagnostic process. Current research methods have limited coverage over clinical settings, are not standardized, and rarely include measures of patient harm.
Conclusion
The available evidence shows that EHRs pose risks for diagnostic error throughout the diagnostic process, with most issues involving their incompatibility with providers’ cognitive processing. A structured and systematic model of collecting and reporting on these errors is needed to understand how the EHR shapes the diagnostic process and improve diagnostic accuracy.
Keywords: Electronic Health Records, Diagnostic Error, Information Processing, Human-Systems Integration, Patient Safety
INTRODUCTION
Diagnostic errors are attributed to more patient harm than any other type of error and are associated with up to 80,000 deaths per year in the United States1,2. Diagnostic errors also account for the largest number of medical malpractice claims and the most severe patient harm3. There are numerous causes of diagnostic error, with cognitive error and cognitive biases being the most frequent4. Consequently, understanding providers’ cognition in the diagnostic process is imperative for addressing diagnostic error. Providers’ cognitive processes are shaped by the tools and technologies they use to gather and process information5; with electronic health records (EHRs) now widely adopted in the United States to store, view, and act on patient information, understanding the intersection between the provider’s cognitive processes and the EHR is necessary to address cognitive errors and biases in the diagnostic process6.
While the association between EHRs and patient harm is recognized (especially with medication-related errors) the role of the EHR in diagnostic errors is not as clear7,8. The diagnostic process is generally understood to involve three stages of cognitive processing: gathering relevant information, developing a set of working or final diagnoses, and implementing a plan based on the diagnoses9. The EHR’s functionality, usability, and integration with other aspects of the clinical environment can serve to either support or disrupt any of these three stages of cognitive processing underlying the diagnostic process10. For example, a providers’ inability to use the EHR to find abnormal clinical data can make them blind to information that could shape the entire diagnostic process. A human-systems integration approach, one that considers how people interact with technology as part of the larger work system, can help identify specific EHR use issues that need to be addressed to reduce the likelihood of diagnostic error11.
Despite the central role of the EHR in information gathering and processing, few studies have attempted to systematically assess its contribution to cognitive errors in the diagnostic process. To address this gap, we performed a scoping review of the literature to, (1) survey studies describing the association between aspects of the EHR and diagnostic error, and (2) through a human-systems integration lens, identify the types of EHR issues and their impact on specific diagnostic process stages. Knowing the scope of the literature, the specific EHR issues, and the specific diagnostic stages impacted will help direct the research agenda and can inform training, design, development, implementation and use of EHRs.
METHODS
Search Strategy
Our scoping review was focused on surveying the relationship between EHRs and Diagnostic Error in peer-reviewed literature. Our final search criteria expanded each of these concepts to include a broad set of related terms to ensure a comprehensive search of associations between the EHR and various aspects of the diagnostic process including laboratory testing, imaging, and communication12. We limited studies to those written in English and published between January 2008 (approximate timing of development of the Health Information Technology for Economic and Clinical Health (HITECH) Act) and March 2021. The search was conducted across the following databases: Medline, EMBASE, Cochrane Central Register of Controlled Trials (CENTRAL), PsycINFO, Cumulative Index to Nursing and Allied Health Literature, and Web of Science. The process and results of the scoping review are show in Figure 1 as a PRISMA flow diagram13.
Figure 1.
PRISMA diagram showing the results of our scoping review for EHR use and Diagnostic Error.
Review Process
The screening and review process followed methods found in similar scoping reviews designed to include the maximum number of potentially relevant studies12,14. First, three researchers (RD, CB, SS) screened 2136 abstracts returned from the literature search to identify research articles relevant to both Diagnostic Error and EHR use. Relevance to Diagnostic Error was construed broadly as the identification of an actual diagnostic error (missed, delayed, or wrong diagnosis) or the disruption of a process known to impact diagnostic accuracy (ex. lab result entered in wrong chart). Relevance to EHR use was similarly construed broadly as reports of attitudes, behaviors, or data relating to the interaction between clinicians and the EHR or EHR-integrated information systems. To ensure reliability of the screening process three researchers initially met to jointly review 50 abstracts and gain group consensus on inclusion criteria (see footnote). For example, studies focusing on only Diagnostic Error or EHR use measures were excluded, as were editorial and opinion articles. Following this, the remaining abstracts were divided by the three reviewers for independent review, with periodic meetings of the review team to discuss relevance of unclear or ambiguous abstracts. At this stage of the process, as is typical in scoping reviews12, the review team was very permissive with relevance of articles to ensure the largest scope of studies could be reviewed in the full text. 70 articles deemed relevant to both Diagnostic Error and EHR-use were then assessed for eligibility in the final review. At this stage, the three researchers divided and independently reviewed these articles based on the presence of explicit reference (direct or indirect) to the relationship between EHR use and Diagnostic Error. Each included study had to demonstrate either research findings or discussion of data relating to EHR use and Diagnostic Error, to be included in the final analysis. The three researchers reviewed each other’s subsets and met to resolve any unclear or ambiguous determinations.
Analysis and Synthesis Process
Three researchers collaboratively reviewed the articles selected for final analysis to extract basic study characteristics (see Table 1). These data were stored in a spreadsheet which was the basis of the descriptive analyses and following qualitative synthesis of the included articles.
Table 1. Study Characteristics extracted from each research article included for final review.
| Study Characteristic | Definition |
|---|---|
| Clinical Setting | One or more clinical domains in which the study was conducted, including ambulatory/outpatient care, emergency department (ED), inpatient, and clinical lab. |
| Study Type | The general research approach of the study, including retrospective analysis, observation, or literature review. A study could have one study type. |
| Data Source | The data sources used in the study, including EHR data, root cause analysis (RCA) database, clinical interview, clinical observations and/or surveys. A study could use one or more data sources. |
| Research Method | One or more specific research methods used in the study, including:
|
The three researchers then extracted specific aspects of EHR use related to diagnostic error, termed study-specific EHR issues, from each article. These EHR-issues were contextually specific to each study; for example, in a paper investigating the root causes of patient misidentification errors, “misinformation from manual entry on laboratory forms” was a human-EHR interaction associated with 14 errors and was therefore extracted as specific EHR issue. These specific EHR issues were then synthesized (where appropriate) into more general issues associated with EHR use across different clinical contexts; these are termed general-topic EHR issues (see Figure 2).
Figure 2.
Process of extracting and consolidating general-topic EHR issues.
Each general-topic EHR issues was then categorized by the three researchers to identify the type of EHR problem, including:
Technical: issues related to the hardware and software functions of the EHR
Usability: issues related to the design and practical use of the EHR's functions
Workflow: issues related to work processes shaped by the EHR’s design or implementation
Each general issue was also associated with one or more stages of the diagnostic process, including:
Information Gathering: process of collecting information such as patient history, results from a patient physical, and results from laboratory testing and imaging
Medical Decision-Making: process of establishing a diagnosis and subsequent care plan,
Plan Implementation and Communication: the process of documenting the care plan and communicating the care plan with relevant providers and outside parties.
This categorization resulted in a final model of EHR use related issues extracted from our scoping review and what parts of the diagnostic process they affected (see Figure 3). The three researchers reviewed the final model with the entire research team for a final group consensus.
Figure 3.
General-topic EHR issues in the Diagnostic Process
RESULTS
Summary of Reviewed Papers
The final search returned 2,118 unique abstracts. After reviewing abstracts 70 articles were determined to have some possible relevance to both EHR use and Diagnostic Error. A full-text review of these articles determined that 11 explicitly documented a relationship between EHR use and Diagnostic Error15-25. The summary of study characteristics for these 11 papers can be found in Table 2. Most articles (n = 9, 81.8%) focused on diagnostic errors in Ambulatory or Primary Care settings. Retrospective analyses were the most common form of study type (n = 9, 81.8%), with data sources including EHR Data (n = 4, 36.3%) and Root Cause Analysis (RCA) databases (n = 4, 36.3%). The most common research methods were Meta-RCAs (n = 4, 36.3%) and Primary RCAs (n = 3, 27.2%).
Table 2. Summary of Study Characteristics for 11 Research Articles selected for Full Text Review.
1 Includes RCA databases maintained by a healthcare system and a malpractice insurance company.
| Study Characteristic | Category | Number of Papers |
|---|---|---|
| Clinical Setting (each paper can have multiple) | Ambulatory/Primary Care | 9 |
| Inpatient | 3 | |
| ED | 2 | |
| Clinical Lab | 1 | |
| Study Type | Retrospective Analysis | 9 |
| Observation | 1 | |
| Literature Review | 1 | |
| Data Source (each paper can have multiple) | EHR Data | 4 |
| RCA Database1 | 4 | |
| Clinical Interviews | 3 | |
| Clinical Observation | 1 | |
| Survey | 1 | |
| Methods | Meta-RCA | 4 |
| Chart Review/RCA | 3 | |
| EHR Data Analysis | 1 | |
| Ethnography | 1 | |
| Secondary Survey Analysis | 1 | |
| Literature Review | 1 |
Includes RCA databases maintained by a healthcare system and a malpractice insurance company.
Synthesis of Study-Specific and General-topic EHR issues
We analyzed the 11 articles and extracted 30 unique study-specific EHR issues impacting the diagnostic process (see Supplementary Table 1, Appendix). The specificity of these study-specific issues varied significantly, ranging from broad issues such as “data entry”17 to more discrete issues such as “pick list”18. Articles ranged from having a minimum of one EHR issues25 to 7 EHR issues18. These 30 study-specific issues were then synthesized into 12 general-topic EHR issues (see Supplementary Table 2, Appendix), with each general topic based on 1 (Delay in Diagnostic Follow-Up) to 5 study-specific EHR issues (Wrong, Missing, or Misplaced Data). Finally, these 12 general-topic EHR issues were categorized by type of EHR problem, spanning Technical (4 issues), Usability (4 issues), and Workflow (4 issues). These issues were finally aligned with the stages of the Diagnostic Process (see Figure 3). The following sections describe in detail each stage of the diagnostic process and the general-topic EHR issues identified as affecting that stage.
General-topic EHR issues in Diagnostic Information Gathering
Seven articles (63.6% of papers) reported technical failures at this stage of diagnostic processing that undermine clinicians’ ability to develop a full understanding of patients’ clinical data. Three papers reported on wrong, missing, or misplaced data implicated in diagnostic error. Similarly, three papers reported the lack of interoperability between clinical information systems and data loss due to poor conversion as being an issue in diagnostic information gathering. The failure of EHR alert systems to fire under expected circumstances also disrupted clinicians’ typical patterns of information gathering as reported in two studies. Four articles (36.3% of papers) reported usability failures interfering with clinicians’ information gathering, most commonly including issues around the detection of abnormal lab results, managing EHR inbox notifications, and navigating a fragmented EHR interface to gather diagnostic data. Finally, two studies (18.1% of papers) highlighted workflow issues, primarily related to clinical documentation in the EHR such as progress notes and problem lists. While not an explicit malfunctioning of the EHR, the design and documentation requirements in the EHR can result in poorly maintained problem lists and encourage copy-forward notes that hide important details and overwhelm clinicians’ information gathering processes.
General-topic EHR issues in Diagnostic Decision-Making
Two articles (18.1% of papers) described how usability issues such as the fragmented display of data in the EHR make it difficult for providers to interpret the information in the EHR, even if they are aware of it. In addition to fragmented data displays, one paper highlighted how the poor usability of EHR messaging inboxes and notifications make it difficult for clinicians to track communication among the care team, potentially interfering with collaborative decision-making. Three articles (27.2% of papers) highlighted workflow issues showing that the EHR’s impact on information available to providers and modalities of clinical communication could hinder providers’ ability to make sound medical decisions. For example, two papers found the lack of face-to-face communication among clinicians created obstacles to sustained thinking and discussion of diagnostic decision-making, and two papers highlighted how clinical documentation in the EHR could prevent clinicians from appreciating critical information such as a deteriorating clinical situation.
General-topic EHR issues in Diagnostic Communication and Plan Implementation
Four articles (36.6% of papers) reported technical issues impacting effective diagnostic communication and plan implementation. Two papers highlighted how interoperability issues can thwart this stage of the diagnostic process if orders are not appropriately transferred across information systems. Additionally, two papers reported that the inability of the EHR to consistently track the status of referrals and test results is a significant limitation forcing providers to actively monitor and “pull” relevant information out of a variety of information systems. Three papers (27.2% of papers) reported usability issues posing barriers to accurate plan implementation. Two of these three papers specifically noted that complicated data entry forms can lead to incorrect orders or even wrong patient errors. The EHR inbox was also identified as a significant risk area that can impact provider’s ability to identify and efficiently manage clinically relevant communications. Finally, four papers (36.3% of papers) reported workflow issues including impaired clinical communication with colleagues and patients, unsafe workarounds for documentation, and delayed or unresolved diagnostic follow-through.
DISCUSSION
Our review of the literature shows that research on the impact of the EHR on diagnostic error is scarce, despite extensive research showing the relationship between software systems and cognitive processes. Within these limitations, we found a broad set of EHR use issues related to diagnostic error and gaps for future research which point to the importance of a human-system integration approach to improving diagnostic safety.
The studies included in our review shed important light on significant risks for diagnostic error related to EHR use with specific technical, usability, and workflow issues that impact providers at every stage of the diagnostic process. While well-known problems with EHR interoperability and data integrity pose critical issues for the diagnostic process, the majority of general-topic EHR issues involve usability and workflow issues related to providers’ cognitive processing. These problems include display issues that can result in clinicians missing vital information when making diagnoses and workflow issues that hamper clinicians’ ability to execute and track the results of their treatment plans. Further, the cumulative effect of these issues on cognition is poorly understood. This finding is not only significant in substantiating the impact that EHR design and implementation has on providers’ cognitive processing, but also highlights the opportunity for these risks to be studied and mitigated. The variety of issues documented in this review show that the EHR, while a valuable information resource, can pose many risks to the diagnostic process, and that many of these risks have to do with providers’ perception and processing of information.
Few papers we reviewed systematically assessed the impact of EHRs on the outcomes of the diagnostic process in a way that can be used to understand and improve their functioning. Unlike diagnostic procedures or tests, which can be evaluated through clinical trials for diagnostic measures such as sensitivity and specificity, the effect of EHRs on the diagnostic process exists only in real-world practice and is more difficult to determine. Researchers have used a variety of methods including root cause analyses, surveys, and EHR data analysis, but these methods can be very labor intensive, are not standardized, rarely include measures of patient harm, and cannot be assembled into a common data source. To better measure and identify specific contributing factors of the EHR to diagnostic error, a structured and systematic model of collecting and reporting on these data is needed. Further, all the papers we reviewed focused on physician use of the EHR, which neglects the broader scope of EHR users involved in the diagnostic process such as nurses, pharmacists, and other allied health professionals.
The limitations of the literature certainly bias our review and resulting framework, but also point to important areas for future research. Our search criteria limited the papers we reviewed to those set in the United States, published in English, and published near formulation of the HITECH Act. This limitation is appropriate for surveying EHR use in the United States but as a result we do not account for additional factors that could influence EHR issues in other nations. Most of the papers selected for review focused on EHR related problems in the ambulatory setting and were limited to certain specialties; as such, our study does not describe problems across other care environments and the spectrum of specialties. Further, the lack of detail about EHR vendors and implementation in these studies make it difficult to differentiate factors that are more generally associated with EHR use or specific to certain technology platforms. Finally, as mentioned above, the lack of a standardized paradigm for investigating EHR contributions to diagnostic error make it likely that there are other types of issues not addressed in our framework. This is also magnified by the advent of telehealth and digital health technologies which introduce new risk factors; as such, our framework should not be considered comprehensive.
The notion of the EHR as a “cause” of diagnostic error is complex, not only due to the complexity of an EHR system’s interactions with the diagnostic process but also due to the ambiguous expectations of the healthcare professionals who rely on EHR systems for their work. While debate about the specific problems and responsibilities of the EHR is important, it is also imperative to focus on a multi-level approach to improving diagnostic accuracy. Critical functions like the diagnostic process must be resilient, which means that a variety of methods should be used to mitigate risk, including improved functionality, design, and training.
CONCLUSION
Our review demonstrates that not enough attention is being directed toward the association between the EHR's integration in the clinical environment, clinicians’ cognitive processes, and diagnostic errors. Available evidence highlights e-iatrogenic risks for error throughout the diagnostic process, with many of these risks having to do with providers’ ability to perceive and process information using the EHR. Understanding how the EHR shapes the cognitive processes is fundamental to addressing the diagnostic error problem and a new paradigm for collecting data on these errors is needed to fill this gap. We hope this review encourages all stakeholders including those funding research, researchers conducting studies, EHR vendors and other industry partners, as well as policy makers to work together and place greater focus on this topic.
Supplementary Material
ACKNOWLEDGEMENTS
This study was funded by the Agency for Healthcare Research and Quality (AHRQ) Grant ID R18HS027119. We would like to thank Andrew Hamilton for his support in developing the query used to search the literature databases. We would also like to thank Sarah Florig, Sky Corby, and Seth Krevat for their commentary and support throughout the project.
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