E-Iatrogenesis: Human-Machine Interface E-Iatrogenesis: Chapters

E-iatrogenesis: Human-Machine Interface

e-Iatrogenesis: Chapters 1 and 2

Rationale, Issues, and Hypothesis

Rationale for Topic Selection

With the publication of the Institute of Medicine's (IOM) 2000 landmark report, to Err is Human, the public, their representatives, and the medical profession woke up to the fact that seeking medical care increases the risk of injury and death. At the time, best estimates suggested that between 44,000 and 98,000 Americans died each year from medical errors. These care-related mistakes are believed to cost the U.S. healthcare system about $2 billion each year. The prevalence of medication errors can vary greatly depending on the setting. For example, the medication error rate for hospitals was found to vary from about 0.3% overall to over 10% in a pediatric ICU setting. In addition, one estimate suggested that less than 10% of medication errors are ever reported.

One of the solutions discussed in the IOM report is the implementation of electronic safeguards in the form of computerized medical records, barcoding, and electronic medication administration records (IOM, 2000). The conversion of patient medical information into a digital format was projected to not only reduce the cost of healthcare, but increase the opportunities for automated surveillance strategies that protect the health of patients.

To promote the adoption of electronic health record (EHR) by individual providers and hospitals, the Centers for Medicare and Medicaid Services (CMS) has been given a mandate by Congress via the HITECH Act of 2009 to provide funds to help defray the costs of implementation (CMS, 2013). Eligible providers under Medicare can receive up to $44,000, while providers under the state-run Medicaid programs can receive up to $63,750. Participation is not required, nor is EHR implementation, but by 2015 providers who have not implemented an EHR system will have their Medicare and Medicaid payments adjusted downward by 1% for the first year. Over the subsequent years, this penalty will eventually reach a maximum of 5% of Medicare and Medicaid payments.

This carrot and stick approach would be toothless if the number of patients covered by Medicare and Medicaid were small. However, spending on Medicare, Medicaid, and the Children's Health Insurance Program (CHIP) in 2010 approached a trillion dollars and represented close to one third of America's health care spending (Klees, Wolfe, and Curtis, 2012). EHR implementation on a national scale is therefore official government policy at the federal level, but one with teeth capable of chewing away at providers' profit margins if they fail to implement an EHR system and utilize it in a meaningful way.

The above policy is based on the assumption that EHR implementation will provide cost savings and improve patient safety (IOM, 2011). At the time, however, the empirical evidence to support these claims was absent. In the aftermath of the publication of several research articles revealing that implementation can increase the harm to patients, the IOM formed a committee to study this issue (IOM, 2011). The committee members concluded that the patient safety benefits of EHR implementation have yet to be substantiated empirically in a consistent manner. Of the different EHR software modules that exist, the most promising for reducing medical errors was found to be computerized physician order entry (CPOE) and clinical decision support (CDS).

The IOM Committee on Patient Safety and Health Information Technology noted that adapting EHR tools to meet clinician's needs is probably the best approach for ensuring patient safety (IOM, 2011). However, alterations in clinical workflow due to EHR implementation can impede efforts to effectively communicate patient information, increase workloads, cause alert fatigue and information overload, and precipitate EHR system avoidance behaviors, including the use of shortcuts. These problems can erode attempts to improve patient safety.

The need to better understand the information needs of clinicians has not gone unnoticed by researchers. From a theoretical perspective, there exists a clinical communications space within which clinicians share information (reviewed by Collins, Bakken, Vawdrey, Coiera, and Currie, 2011). To the extent that clinicians can communicate easily, whether verbally, by phone, or email, a shared understanding exists that allow the concepts exchanged to be understood by the parties involved. This shared knowledge and skills is called the 'common ground.'

Common ground, however, is not always sufficient for high quality care. Effective care teams are typically composed of individuals with unique knowledge and skills, but for these members to contribute in a meaningful way common ground must still be established. Therefore, common ground allows care team members to both communicate effectively and to make unique contributions to patient care. The overall effect is to expand the knowledge and skills of the care team and increase the quality of care. This phenomenon is called 'distributed cognition' and it is responsible for increasing the quality of care beyond the capabilities of a single clinician.

An EHR system could be framed as a contributing member of a clinical care team because it is capable of contributing unique knowledge and capabilities; however, the ability to make contributions would also be limited by the extent of common ground established between the EHR system and clinicians. A priori, the magnitude of EHR/clinician common ground would be a function of both clinician training and system usability. Based on the perspective of the IOM Committee on Patient Safety and Health Information Technology, system usability is a function of implementation strategies, system adaptability by end users, point of care use, and usability feedback loops (IOM, 2011). However, these are not the only factors believed to influence whether an EHR system can protect or improve patient safety. The IOM Committee acknowledged that much more research needs to be done to understand how best to design, implement, and maintain EHR systems in a manner that predictably reduces the prevalence of medical errors.

Justification for Choice of Topic

The above discussion reveals what could be an impending crisis in patient safety as more and more providers implement EHR systems in their clinics and hospitals without understanding the risks. As I began to read through the IOM report on Health it, the lack of empirical evidence supporting the safety of EHR implementation was surprising, if not unsettling. Years ago the experts proclaimed that converting paper medical records into a digital format would provide many benefits, including lower costs and increased patient safety. Yet, the same experts are now cautioning clinicians about the risk to patient safety that such systems pose and the need for more research to better understand this issue. From my perspective, this seemed like an important and contemporary issue that is not going to be resolved any time soon. For this reason, I thought it was important to try and understand what is and is not known about the human-machine interface issues that arise in clinical settings.

This topic is relevant across disciplines, but even more so in the technology-driven critical care setting. The imposition of a poorly designed and implemented EHR system can no longer be viewed as a benign artifact of modern medicine, but as a potential threat to patient health and provider profitability that must be dealt with decisively and without delay. As I progress in my career, there could be a moment when I'm given responsibility for such a system. By digging into the literature on this topic I will be better prepared for such an event and in a position to offer suggestions on what needs to be done to make the system more efficient and less error prone. In addition, there is no conceivable expiration date on this topic as more and more providers' transition from paper to electronic medical information systems, while continuing to encounter problems.

The Human-Machine Interface Issues

If it were true that converting from paper to electronic medical records improved patient safety and provided cost savings then there would be little controversy, but according to a number of publications, including a comprehensive IOM (2011) report on this topic, there is little empirical evidence to base these assertions upon. Instead, there is a growing body of empirical evidence suggesting that the cost benefits are elusive for many and that patient safety may be at risk. A significant chasm therefore exists between past recommendations, current official government policy, and the clinical evidence being generated.

EHR systems have been predicted to provide many benefits. These include increased patient safety, reduced operational costs associated with a paperless clinic, sharing of patient information among different providers, remote access to patient information in real-time, and searchable databases that can be used by researchers (IOM, 2011). While these projected benefits are enticing, the most critical is patient safety. EHR systems are believed capable of reducing medical errors because handwriting becomes legible as it is converted into digital text and medication orders can be transmitted instantly and legibly to pharmacists who then fill stat orders without delay. In addition, EHR systems have been designed to provide clinical decision support to help alert clinicians to risks associated with a treatment approach or medication mix.

These projected benefits are rarely realized, however, and instead clinicians find that they become chained to terminals, communicate with their peers less, and spend less time with the patient (Han et al., 2005). In addition, the workload on clinicians is often increased past the point of reasonable because it is too intrusive and time consuming to document patient encounters during clinic time (Grabenbauer, Skinner, and Windle, 2011). The amount of information that can accumulate in a patient's record from multiple sources can be daunting and lead to information overload. CDS alerts can be so common that clinicians begin to ignore them. The negative impact that EHR systems can have on clinician communications is also troubling, because in-person observations by nurses can provide invaluable insights into the treatment needs of a patients that cannot be communicated effectively electronically. Systems have been observed to be slow during peak use periods and in some cases crash (Fernandopulle and Neil, 2010). Vendor support during such crises may be slow or absent, which can lead to seeing and treating patients 'blind.'

Many of the EHR-associated complaints are concerned with the human-machine interface or system usability. In contrast to experiencing greater legibility, complaints about the character size being too small and having to use non-intuitive navigation steps are not uncommon (Tschannen, Talsma, Reinemeyer, Belt, and Schoville, 2011). The absence of standards of care adapted for EHR systems is also a problem, as nurses feel adrift in the absence of traditional cues formally used to signal a new order from a doctor. Charting now takes place at the end of a shift or the day, as nurses wait for doctors to make the necessary entries. The resulting impact on clinic workflow can sometimes be dramatic and put patients at risk for harm.

One of the more important aspects of EHR implementation is system usability from the perspective of clinicians. Usability is determined by the ease with which clinicians can navigate through patient information, how many steps it takes, and the cognitive load this task imposes (Ahmed, a., Chandras S., Herasevich V., Gajic, O., and Pickering, 2011). Usability in turn has been shown to be inversely associated with medical errors. Stated another way, intuitive quick navigation to needed information reduces the cognitive load of clinicians and thus the error rate. The human-machine interface can therefore be a significant source of medical errors.

Increasing the usability of a system requires a behavioral approach that examines in detail the steps that a user employs during the retrieval or entry of information. Both physical and mental actions are relevant, since the latter is proportional to the cognitive load induced by the task (Ahmed, a., Chandras S., Herasevich V., Gajic, O., and Pickering, 2011). Such studies have revealed that usability is a function of interface design and customizable features. In other words, an EHR system that can be user modified to meet the needs of clinicians in a specific clinical setting, while performing a specific task, will impose the least cognitive load on users of the system.

As EHR vendors try to meet the various needs of clinicians, commercial systems have become more complex. This trend seems to be in direct conflict with the above discussion about the relationship between usability, cognitive load, and error rates. Clinicians who have transitioned from older, locally-designed, bare bones systems to recent commercial EHR systems lament the simplicity of the older systems (Abramson et al., 2012). These vendors seem to be trying to provide all the 'bells and whistles' that any clinician would ever need without realizing that such efforts could be increasing the risk of harm to patients.

What seems to be needed is more research into how the clinician interfaces with the machine in specific clinical settings in order to better understand how EHR systems should be designed. This will require detailed analysis of clinicians as they enter or retrieve information. This data could then be used to optimize EHR interfaces to reduce the cognitive load on clinicians. If EHR systems are going to make a positive contribution to patient safety and healthcare costs, then the design and implementation of such systems needs to be based on empirical evidence. Currently, such evidence is weak and inconsistent.