Safety issues related to the electronic medical record (EMR): synthesis of the literature from the last decade, 2000-2009.
Medical informatics (Usage)
Health care industry (Technology application)
|Publication:||Name: Journal of Healthcare Management Publisher: American College of Healthcare Executives Audience: Trade Format: Magazine/Journal Subject: Business; Health care industry Copyright: COPYRIGHT 2011 American College of Healthcare Executives ISSN: 1096-9012|
|Issue:||Date: Jan-Feb, 2011 Source Volume: 56 Source Issue: 1|
|Topic:||Event Code: 200 Management dynamics Computer Subject: Health care industry; Company business management; Technology application|
|Organization:||Organization: American Medical Informatics Association|
|Geographic:||Geographic Scope: United States Geographic Code: 1USA United States|
Healthcare is a complex industry burdened by numerous and complicated clinical and administrative transactions that require many behavioral changes by patients, clinicians, and provider organizations. While healthcare information technology (HIT) is intended to relieve some of the burden by reducing errors, several aspects of systems such as the electronic medical record (EMR) may actually increase the incidence of certain types of errors or produce new safety risks that result in harm. Healthcare leaders must appreciate the complexity surrounding EMRs and understand the safety issues in order to mandate sound EMR design, development, implementation, and use. This article seeks to inform executives, clinicians, and technology professionals what has been learned through published research on the safety of HIT systems during the last decade, focusing on computerized physician order entry (CPOE), clinical decision support systems (CDSS), and bar-coded medication administration (BCMA).
While hospital electronic medical records (EMR) are intended to reduce medical errors, several aspects of the EMR may actually increase the incidence of certain types of errors or produce new safety risks that result in harm (Ammenwerth and Shaw 2004; Bates et al. 2001; Horsky, Zhang, and Patel 2005; Koppel et al. 2005). Threats to patient safety can be introduced during any phase of the EMR lifecycle, such as planning, design, development, testing, implementation, operations, and maintenance. Within each of these processes, technology, people, and the work environment can individually or collectively generate errors (Ash, Berg, and Coiera 2004).
The EMR is a very complicated technology, consisting of millions of lines of code typically authored by multiple programmers (Ash, Berg, and Coiera 2004). More important than its technical reliability is that many functions may be designed by people who do not know or fully appreciate the complex interaction of the human--computer interface and the consequences of designs that may, in hindsight, have impaired patient safety. As far back as 1995, the Food and Drug Administration acknowledged that insufficient design and testing of software-driven products could result in errors, increased healthcare costs, and patient harm (Burlington 1996).
End users can serve as sources to identify safety issues during multiple processes. While end users are sometimes consulted in design or design-enhancement processes, many end users lack knowledge of standardized dictionaries, design principles, human-computer interaction, and the impact of poor design on work and patient safety. During operation of the EMR, multiple end users can introduce errors into the EMR through multiple points of data entry (Hogan and Wagner 1997).
The EMR and the end user come together in a work environment that is also very complex (Ash, Berg, and Coiera 2004). Healthcare work environments are characterized by excessive noise, high workloads, complex tasks that require rapid user responses to information, multitasking, and serious consequences when errors occur (Salvemini 1998). Tasks carried out by healthcare professionals in these environments are often context-dependent, nonlinear, interrupted, and dependent on clear and timely communication (Horsky, Zhang, and Patel 2005). The convergence of the complexities of the EMR and the need for changes in associated work flow create a large sociotechnical system where new behaviors emerge, some leading to unintended consequences that cause harm (Ash, Berg, and Coiera 2004).
Healthcare leaders must appreciate the complexity surrounding EMRs and understand the safety issues in order to mandate sound EMR design, development, implementation, and use. This article seeks to highlight what has been learned through research on the safety of these systems from 2000 to 2009. Three aspects of the EMR were selected for examination. These include computerized physician order entry (CPOE), clinical decision support systems (CDSS), and bar-coded medication administration (BCMA). The intended purpose is to prevent errors through effective design, development, and implementation and, as a result, reduce safety risks. However, all new systems generate unintended adverse consequences to patient safety that may relate to design or implementation problems. What follows is what has been learned related to beneficial effectiveness and unintended consequences associated with three major functions of the EMR.
In 2000, the Institute of Medicine's (IOM) Committee on Quality of Health Care in America released a seminal report titled To Err is Human: Building a Safer Health System that estimated that more than a million injuries and nearly 100,000 deaths each year in the United States are attributable to medical errors. In this report, the authors differentiated between active and latent errors. Active errors occur on the front line where the effects of these errors are felt almost immediately. Latent errors result from system failures and tend to be removed from the direct control of frontline people (Reason 1990). Latent errors include things such as poor design, incorrect installation, faulty maintenance, bad management decisions, and poorly structured organizations that create an environment that may fail to prevent or even may promote a human failure that may result in patient risk of injury. The IOM report asserted that latent errors, such as those hidden in complex health information technology applications, pose the greatest threat to safety in a complex system because they are difficult for end users to see and can lead to multiple types of active errors.
A second IOM report, Crossing the Quality Chasm, identified challenges associated with use of information technology in healthcare to improve quality of care (Committee on Quality of Health Care in America 2001). The authors called healthcare the most complex sector of the economy because of numerous and complicated transactions that require many behavioral changes by patients, clinicians, and provider organizations. Underinvestment in clinical information systems by provider organizations is compounded by difficulties in demonstrating the benefit of clinical information systems. Healthcare providers are also challenged in securely maintaining patient health information and creating an infrastructure that enables exchange of data and information across diverse settings.
Another landmark article described anecdotal evidence that while electronic medical records and associated clinical information systems can reduce errors, they can also cause errors (Bates et al. 2001). Examples provided included the wrong selection from two medications similarly spelled appearing in close proximity on the computer screen and physicians writing orders in the wrong electronic record. The authors recommended that adverse consequences resulting from the use of information technology be continuously monitored, measured, and evaluated.
By 2007 sufficient evidence in the literature prompted Weiner and colleagues to coin the term "e-iatrogenesis" to denote patient harm resulting at least in part from health information technology. The authors referred to e-iatrogenesis as the most critical unintended consequence of health information technologies and said they coined the term to draw attention this critical issue. An e-iatrogenic event may involve errors of commission or omission and can be associated with any aspect of a health information system such as the EMR, CPOE, or CDSS. E-iatrogenic errors fall into technical, human--machine interface, or organizational domains and may represent an electronic version of a "traditional" error, such as a medication error, or new errors never seen before, such as a CDSS recommendation for a wrong diagnosis.
Also in 2007, Palmieri, Peterson, and Ford coined the term "technological iatrogenesis" to describe errors caused by the addition of technological innovations into complex healthcare systems. The authors acknowledged the contribution of health information technology to make healthcare delivery safer and the new varieties of iatrogenic errors stemming from this technology. They also advocated for the use of risk management solutions such as failure mode effect and root cause analyses. Additionally, the authors encouraged healthcare leaders to avoid quick fixes to issues surrounding technology, such as a focus on human error, and move to a broader system perspective.
By 2008 The Joint Commission released a sentinel event alert titled "Safely Implementing Health Information and Converging Technologies" focusing on technology-related adverse events and encouraging healthcare providers to be alert to the associated safety risks and preventable adverse events. The Joint Commission cited Weiner and colleagues (2007) stating that unintended adverse events typically arise from two areas, human--machine inter faces and organization or system design. Recommendations in the sentinel event alert were to design technology to be safe and to use technology safely.
A comprehensive review of the literature was conducted using CINAHL, PubMed, and MEDLINE databases to identify relevant research published between and including the years of 2000 and 2009. Other databases were added when the original searches yielded fewer than 20 articles. These additional databases included Academic Search Premier, Academic OneFile, Business Source Complete, JSTOR, and Google Scholar. Manual searches of reference lists in published articles on safety issues in the EMR were also conducted.
Search terms included "safety," "errors," "electronic medical record," "electronic health record," "clinical decision support," "computerized physician order entry," and "bar-coded/barcode/ barcoding medication administration." Additional terms were identified during the search and included terms such as "unintended consequences," "e-iatrogenesis," "work flow," "work processes," "workarounds," and "computerized provider order entry."
Inclusion criteria were predetermined to be (1) English language publications; (2) research studies identifying errors related to EMR, including CPOE, CDSS, and BCMA; and (3) the hospital setting. Titles and abstracts identified in the database and reference list search meeting these inclusion criteria were initially screened to exclude those clearly not meeting the inclusion criteria. Publications focused solely on the surveillance or prevention of errors or in settings outside of the hospital were excluded. Similarly, studies published only as abstracts with insufficient information were also excluded.
A spreadsheet was created that contained key elements to be extracted from the publications. Extracted data included author(s), title, journal, publication year, sample, design/methods, findings, conclusions, types of errors, and causes of errors. Data from the published studies meeting the inclusion criteria were then abstracted and entered into the spreadsheet.
Summary of Search Findings
A total of 24 studies matching the inclusion criteria were identified through a comprehensive search of databases and references lists as previously described. These studies are outlined in an exhibit on www.ache.org/pubs/jhmsub.cfm.
Analysis of Literature Review Findings
As can be seen in the online exhibit, studies were found in 13 different journals. Thirty-three percent of the research was presented through the journal or conference proceedings of the American Medical Informatics Association (AMIA). Five studies (21 percent) were published in the Journal of the American Medical Informatics Association and three (12 percent) in the AMIA Annual Symposium Proceedings. Few studies were published in clinical journals alerting clinicians to the possibilities of system-induced errors. No publications on EMR-related errors were found in healthcare management journals thereby educating management about the potential issues. Lastly, few articles on safety issues related to the EMR were found in safety or quality journals in the last decade.
Exhibit 1 illustrates a temporal trend of articles related to EMR safety issues in CPOE, CDSS, and BCMA during the last decade. While the adoption of EMRs by hospitals is increasing steadily, the published research involving the safety of the EMR seems to have peaked in 2005, and only three papers per year have been published for the last four years (see Exhibit 2).
The design of the 24 studies is also worth noting. There was one randomized controlled trial, one interventional study, one quantitative and qualitative study, two qualitative studies, and three case studies. The remaining 16 studies used descriptive or comparison designs.
Exhibit 2 illustrates differences related to the focus of published research on errors related to CPOE, CDSS, and BCMA during the last decade. The dominance of articles related to CPOE is notable in 71 percent of the publications, followed by clinical decision support systems (17 percent) and bar-coded medication administration (12 percent).
By extracting information from the online exhibit, patterns related to the three areas of focus can be identified (Exhibit 3). These patterns are grouped as process, people, technology, organization, and environment related.
Exhibit 4 presents a picture of EMR-related safety issues reported in the research literature from 2000 to 2009, one that should be compelling to healthcare leaders, clinicians, and technology professionals. Thirty-five safety issues were reported in the literature on BCMA, 16 on CDSS, and 83 on CPOE.
The larger number reported for CPOE is a result of the significantly larger number of studies evaluating CPOE as demonstrated earlier in Exhibit 3. These findings indicate that the promise of the EMR to reduce errors in healthcare must be tempered by the need to identify, evaluate, and improve safety issues resulting from the EMR.
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CPOE has been touted as reducing errors in patient care, in large part by eliminating illegible orders and transcription errors. However, CPOE can actually increase the number of adverse events (Berger and Kichak 2004). Research studies in the last decade demonstrated safety issues with CPOE ranging from communication to medication errors to mortality and other unintended consequences (Dykstra 2003; King et al. 2003; Han et al. 2005; Campbell et al. 2006).
Researchers also found that CPOE can increase the coordination load among clinicians resulting in new opportunities for new sources of error (Cheng et al. 2003). For example, nurses may be unaware of new patient orders when physicians enter new orders remotely using CPOE. Prior to CPOE, nurses would see physicians making rounds, talk with them, and thus know when to expect orders. Using a descriptive design, Cheng and colleagues (2003) observed clinicians in an intensive care unit following implementation of CPOE. They concluded that the increased coordination load and the resulting new sources of errors were related to the assumption by designers that physician ordering is a linear process.
Ash and colleagues (2007) studied the extent and importance of unintended consequences related to CPOE in 176 hospitals drawn from 448 acute care hospitals listed in the HIMSS Analytics Database, plus 113 US Veterans Affairs Hospitals. Using telephone interviews, the researchers found that unintended consequences of CPOE considered most important by subjects included new work or more work, work flow, system demands, communication, emotions, and dependence on the technology. They found no correlation between the types of unintended consequences and number of years using CPOE.
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CDSS is intended to support the real-time clinical decisions of healthcare professionals in providing optimal patient care. CDSS is thought to be the key differentiator between paper-based and electronic documentation by providing necessary data and/or algorithm-based alerts or reminders to clinicians during their daily work. Tsai, Fridsma, and Gatti (2003) discovered that CDSS can be reduced in its usefulness when incorrect information is provided. Some healthcare professionals may trust the computer more than is warranted, resulting in errors in decisions.
Similarly, the effectiveness of CDSS is reduced when clinicians are subjected to alerts or other information perceived to lack benefit. Van der Sijs and colleagues (2009) studied the alert overrides for time-dependent drug-drug interactions (TDDI). The researchers found that incorrect overrides of TDDI alerts were an important cause of medication administration errors. Overrides were found to be a result of alert fatigue along with low alert specificity and unclear alert information content.
Garg et al. (2005) published a systematic review of randomized and nonrandomized controlled trials to assess the effects of CDSS and to identify study characteristics predicting benefits. The review included 100 studies over six years (1998 through 2004). The researchers concluded that while CDSS has been reported to improve practitioner performance, the effects on patient outcomes are understudied, and findings from the few published studies are inconsistent.
BCMA is intended to ensure safe medication administration. As Koppel and colleagues (2008) point out, BCMA can create workarounds that result in errors. The authors found 15 types of workarounds surrounding omission of process steps, steps performed out of sequence, and unauthorized BCMA process steps.
BCMA is also dependent on the correct performance of other processes. McDonald (2006) describes a case where a patient was mistakenly given the wrong bar-coded identification wristband. A subsequent laboratory test demonstrated severe hyperglycemia and the wrong patient was almost administered what could have been a fatal dose of insulin. Verification of patient identity based solely on an armband is insufficient; it does not guarantee that the armband and the person are the same.
Patterson, Cook, and Render (2002) used a qualitative research design to describe the experience of nurses during implementation of BCMA. Using ethnographic observation the researchers found five negative side effects associated with BCMA implementation:
1. Nurses experienced "automation surprise" by automated removal of medications.
2. Breakdowns occurred in the coordination of care between nurses and physicians.
3. Nurses dropped activities during busy periods to gain efficiencies and reduce workload.
4. Monitored activities such as medication administration were prioritized.
5. There was a decreased ability to deviate from routine linear sequences.
The authors concluded that these side effects of BCMA could create new paths for adverse drug events and require preemptive evaluation and intervention.
Research on safety issues related to the EMR, specifically CPOE, CDSS, and BCMA, has only begun to uncover the unique unintended opportunities for error and harm that derive from clinical information systems deployment. The complexity of these systems, individually and collectively, is notable, as is the effect they have on current practice, work flow, and work environment. While these systems can undoubtedly improve patient care, safety issues left unidentified or unaddressed can undermine their benefits to patient safety. Studies on the benefits of these systems in relation to the potential harm must be considered.
Healthcare leaders must have knowledge of errors resulting from EMRs and access to discussion relative to the accountability for such errors. In 2009, Koppel and Kreda wrote about EMR vendors being liability-free when their products are involved in adverse events. The "hold harmless" contractual and legal device puts liability for technology-induced errors squarely on provider organizations and healthcare professionals referred to as "learned intermediaries." Under this legal doctrine, physicians, nurses, pharmacists, and other clinicians are held accountable for identifying and correcting any errors generated by software defaults.
The pressure on hospitals to implement EMR has never been greater. A large part of the driving force relates to demonstrated and presumed improvements to patient safety. The findings of this review reveal that the literature demonstrates unintended consequences of EMR deployment that must be considered. Several aspects of the EMR can increase the incidence of certain types of errors or produce new safety risks that result in harm. The existence of only 24 published articles during the past decade suggests that greater focus upon the nature and mechanisms of e-iatrogenesis would be beneficial in the near term. The role of healthcare leaders in the safety of EMR cannot be understated. Leaders must be aware that thorough EMR deployment is not a panacea. Effective planning, design, and development are essential to prevent the time, cost, and safety consequences of poorly created and implemented EMRs. Additionally, leaders on the provider side should be involved in the maturation of products; their leadership is essential to realize the potential of these technologies.
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David A. Snyder, MD, FACHE, chief quality officer and chief medical informatics officer, Medical College of Georgia Health System, Augusta, Georgia
Dr. Harrington and her colleagues have given us a succinct summary of ways that patient injuries still occur despite, or even because of, the use of electronic medical records and their support systems. Certainly, some of the potential sources of injury in electronic systems are purely technical. These are important, and we can't dismiss them. That said, our technical colleagues are adept at fixing them once we as providers and facilitators of care have clearly articulated our concerns.
The more insidious risks of electronic medical records, however, may be found in the nature of the work itself, and in the human factors surrounding the people who do that work. Those of us who have to deal daily with the resource and time constraints involved in patient care are masters of the workaround. We have to be. Workarounds that improve patient value, safety, and efficiency are useful and commendable. Those that circumvent safety features built into electronic and other systems solely in the interest of saving time are not. Many of the system safety issues identified by Harrington and colleagues arise from this latter category. They are not intrinsic to the technology itself; rather they reflect misuse of otherwise invaluable tools. What can we do, then, to use these marvelous tools to their best advantage?
First of all, what goes into an EMR is largely our responsibility as end users, but many of us have so far not actively participated in the development of these systems. Witness the dearth of clinical engagement in the materials Dr. Harrington and her colleagues have presented to us. Moving forward, all of us as healthcare leaders and workers must be intimately involved in, and committed to, the ongoing design and evolution of the workflows and content of the clinical information systems we use. Expecting technology this complex to work perfectly for all of us straight out of the box and to accommodate our every individual whim is not reasonable; so, busy as we are, we have to make the time to do this.
Next, we must recognize that, despite its prodigious capability to store and organize data and to remember and rapidly apply previously defined rules to that data, a programmed computer is not intelligent. The computer is just a tool to assist us in the optimal application of our own intelligence to the care of our patients. We should never defer to a computer or compete with a computer. We should, rather, use a computer as one of the many valuable tools at our disposal; and, when a patient suffers harm, we should first look to ourselves, not to "the box."
Finally, we must evolve our care culture. The tradition of American medicine is one of heroic, autonomous caregivers seeking errorless perfection in the performance of work that routinely involves uncertainty. To attack and eliminate the errors in care that still occur despite our most devoted efforts to this end, we must reexamine our approach. I think that care delivery must move toward a more realistic and achievable concept of team care, in which caregivers of many disciplines collaborate in good faith within systems that have been intentionally designed to keep the occasional errors and unforeseen threats which are inescapable features of our work from reaching and harming our patients. In such a culture, we will refine our tools--the EMR included--to our patients' best advantage. We will also make circumventing the safety features of these tools simply unimaginable.
Linda Harrington, PhD, vice president for advancing nursing practice, Baylor Health Care System, Dallas, Texas; Donald Kennerly MD, PhD, vice president of patient safety and chief patient safety officer, Baylor Health Care System; and Constance Johnson, PhD, assistant professor, Duhe University, Durham, North Carolina
EXHIBIT 3 Types of EMR-Related Safety Issues BCMA People related Incorrect dose dispensed Knowledge gaps of BCMA Stocking errors False sense of security in BCMA Storage errors Knowledge gaps of BCMA safety organization related issues insufficient staffing Process related Changes in clinical communication Technology related patterns Weakening human vigilance BCMA system unavailable Failure to scan bar code Patient without bar code wristband Wrong bar code wristband on Inability to scan bar code patient Multiple screens required to Scanning steps omitted complete Scanning steps performed out of transaction sequence Connectivity failures Unauthorized scanning steps Battery not charged or fails Patient situation interferes with BCMA equipment failure scanning Information not readily available Insufficient monitoring of Computer cart or scanner is too patient large, heavy, or bulky Mislabeling of medication with Bar code scanning procedure slower wrong bar code or more difficult than other Medication not administered as methods documented Overriding of error warning Environment related Clinician exceeds preset medication administration time Ambient noise interference Drug not in formulary Distractions Different drug formulation Incorrect medication dispensed CDSS People related Technology related False expectations of clinical Lack of patient-specific clinical decision support decision support Perceived accuracy Drug-drug interactions Clinical knowledge deficit Rearranging clinician priorities Clinical judgment gaps Inaccurate clinical decision Knowledge gaps of CDSS safety support issues Inaccurate program logic Transfer of responsibility to Missing data resulting in CDSS inaccurate recommendation Data overload Lack of maximum daily dose alert Alert fatigue Overdependence on technology CPOE People related Process related Inexperience Change management Clinical knowledge deficit More data to manage Critical thinking gaps Changes in clinical communication Erroneous alert overriding patterns Increased cognitive load Increased coordination load among Typing errors clinicians Negative emotions Execution of orders prior to Overdependence on technology submission of CPOE Execution of orders prior to Delay/failure in discontinuing verification medications because of Need for clinician to be at difficulty in seeing entire list workstation to receive phone of current medications orders Failure to cancel Requirement for additional procedure-related medications if verification tasks procedure postponed or cancelled Changes in work flow Impermissible antibiotic diluents Urgency of medical care Inability to select individualized More work dose ranges New work Failure to suggest prophylactic Less time with patient due to therapy more time with computer Failure to suggest medication Paper persistence monitoring Failure to flag drug-drug interactions Failure to flag drug-allergy contraindications Failure to flag drug-disease contraindications Failure to alert nurses with new or stat orders Failure to differentiate look-alike drug names Organization related False allergy information Post hoc timing of allergy Changes in the power structure information Cultural changes Conflicting orders Interruptions Duplicate orders Insufficient clinical staffing Cancellation of all medications Insufficient IT staffing for surgery Heavy workloads Challenges with variable dosage Failure to educate on what the regimens CPOE can and cannot do Failure to differentiate look-alike patient names Keypad entry error Improper data placement Wrong selection of order set Environment related Wrong selection from a pick list Dense pick lists Distractions Selection of incorrect dosing frequency Selection of inappropriate dosage Technology related for required route Multiple required passwords Insufficient interface design Misidentification of patient Loss of data during system crashes because of poor CPOE display Delays in medications during Fragmented displays downtime Difficulty discerning patient's Low alert specificity medications because of multiple Unclear alert information screen displays Incorrect guidance for medication Free text orders dosing Linear nature of CPOE for Inconvenience of logging in nonlinear physician ordering Timed logout disruption Discrepancy between verbal order Difficulty identifying who is and electronic form in CPOE logged in Default stop orders Increased time required to input Default drug times causing first orders and second doses to be Unable to input orders prior to administered too closely patient admission together Slowed system during peak use Difficulty ordering non-formulary Loss of connectivity medications Ongoing system changes Requirement to cancel current Poor coordination in deploying medication prior to modifying test, train, and production current medication versions Loss of information during care transitions Timely updating of order sets
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