introduction to medication errors essay

Medication Administration and Patient Safety Essay

Introduction, medication errors, medication labeling policy.

Medication administration is highly important for the patients’ safety. It was estimated that medication errors are the most common type of mistakes in the healthcare system (Nanji, Vernest, Sims, & Levine, 2015). One of the reasons for such errors occurring in the wrong procedure of medication labeling (Mishra, 2014). To improve this situation, national standards for medication labeling were developed and introduced into the practice (The Joint Comission, 2015). Thus, drug labeling is the policy of medications, solutions, and container labeling which might lead to reducing the rate of medication errors in the nurse’s practice.

The quality and safety of medical care, among other issues, highly depends on the accuracy of healthcare workers. Medication errors are commonly spread type of human-factor medical mistakes. According to “About medication errors” (2017), this type of error could be defined as “any preventable event that may cause or lead to inappropriate medication use or patient harm while the medication is in the control of the health care professional, patient, or consumer” (para. 2). Frequently, nurses are considered to be responsible for these errors because medication preparation is a part of their duties (Smeulers, Onderwater, Zwieten, & Vermeulen, 2014).

The most frequent medication errors are mistakes with drug name, concentration, and time of its injection. A nurse should be especially attentive and careful in a case if medication preparation (drug dissolving with the appropriate solvent to the appropriate concentration), according to a physician prescription, is required (Smeulers et al., 2014). One of the possible reasons for errors during drags preparation and injection is wrong medication labeling or label absence (Mishra, 2014). Thus, medication labeling policy is a possible solution to improve the situation and to reduce the rate of errors.

National patient safety goals were established by the Joint Commission (2015). The third goal was dedicated to medication safety, in particular, to the medication labeling procedure. According to the standards, all medications, prepared solutions, and their containers (syringes, basins, and others) should be labeled immediately after transferring from the original package and/or preparation. The label should include the medication name, concentration, and expiration date and time. All the unlabeled medications should be discarded (The Joint Commission, 2015). This policy directly affected the nurse’s work because medication preparation and administration are parts of nurses’ duties.

It could be stated that this policy might reduce the frequency of medication errors. The clear standard procedure of labeling might be helpful in the nurses’ services quality improvement. However, another important issue should be considered. According to the standards, the procedure of labeling should be performed immediately. This procedure requires time and might decelerate a nurse’s work, which can be crucial in the case of an emergency. Therefore, it is essential to develop and introduce into practice the fast and efficient protocol of medication labeling (Nanji et al., 2015).

It could be concluded that medication errors are the most common in the healthcare system. Occasionally, these errors could lead to serious consequences for the patient’s health. The wrong procedure of drug labeling could be named as one of the reasons for these mistakes. Nurses are often considered to be responsible for medication errors because drug preparation is their direct duty. Therefore, to improve the quality and safety of nurses’ service, the standard procedure of drug labeling was developed. Medication labeling policy might be helpful to reduce the rate of errors. However, further improvement of the procedure efficiency should be provided.

About medication errors (2017). Web.

Mishra, S. (2014). Diversity in prescription and medication errors. International Journal of Research in Pharmacy and Science , 4 (4), 39-45.

Nanji, K. C., Vernest, K. A., Sims, N. M., & Levine, W. D. (2015). Bar code-assisted medication labeling: A novel system to improve efficiency and patient safety. International Journal of Anesthesiology & Pain Medicine, 1 (1), 1-6.

Smeulers, M., Onderwater, A. T., Zwieten, M. C., & Vermeulen, H. (2014). Nurses’ experiences and perspectives on medication safety practices: an explorative qualitative study. Journal of nursing management , 22 (3), 276-285.

The Joint Commission. (2015). National patient safety goals effective . Web.

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Preventing Medication Errors (2007)

Chapter: 1 introduction, 1 introduction.

The Institute of Medicine (IOM) report To Err Is Human: Building a Safer Health System (IOM, 2000) identified medication errors as the most common type of error in health care and attributed several thousand deaths to medication-related events. The report had an immediate impact. In response, Congress apportioned $50 million in fiscal year 2001 for a major federal initiative to improve patient safety research and directed the Agency for Healthcare Research and Quality (AHRQ) to establish a Center for Quality Improvement and Patient Safety. The American people also took notice: 51 percent of respondents to a national survey conducted in late 1999 reported closely following the media coverage on the report (Kaiser Family Foundation, 1999). 1 The report’s impact has continued. Five years after its release, two members of the committee that produced the report (Leape and Berwick, 2005) reflected that it had led to:

Broader acceptance within the health care community that preventable medical errors are a serious problem.

A number of important stakeholders (for example, the federal government, the Veterans Health Administration, and the Joint Commission on Accreditation of Healthcare Organizations [JCAHO]) taking up the challenge to improve patient safety.

Accelerated implementation of safe health care practices. For example, JCAHO in 2003 required hospitals to implement a number of evidenced-based safe-care practices, and the Institute for Healthcare Im-

provement undertook its 100,000 Lives Campaign, aimed at fostering the use of safe practices.

Likewise, an article in Health Affairs reviewing the impact of To Err Is Human (Wachter, 2004) noted that the report had led to improved patient safety processes through stronger regulation (for example, expanded patient safety regulation by JCAHO). The article also pointed to the accelerated implementation of clinical information systems that can help reduce medication errors. In addition, progress had been made on workforce issues, particularly in hospitals through the emergence of hospitalists— physicians who coordinate the care of hospitalized patients. Overall, however, the review suggested that much more needed to be done. Examples cited were the limited impact of error reporting systems and scant progress in improving accountability.

The key messages of To Err Is Human were that there are serious problems with the quality of health care delivery; that these problems stem primarily from poor health care delivery systems, not incompetent individuals; and that solving these problems will require fundamental changes in the way care is delivered. A subsequent IOM report, Crossing the Quality Chasm: A New Health System for the 21st Century (IOM, 2001), took up the challenge of suggesting how the health care delivery system should be redesigned. It identified six aims for quality improvement: health care should be safe, effective, patient-centered, timely, efficient, and equitable (IOM, 2001).

The Quality Chasm report and the later IOM report, Patient Safety: Achieving a New Standard for Care (IOM, 2004), also emphasized the need for an information infrastructure to support the delivery of quality health care. The latter report called specifically for a national health information infrastructure to provide real-time access to complete patient information and decision-support tools for clinicians and their patients, to capture patient safety information as a by-product of care, and to make it possible to use this information to design even safer delivery systems (IOM, 2004).

To Err Is Human focused on injuries arising as a direct consequence of treatment, that is, errors of commission, such as prescribing a medication that has harmful interactions with another medication the patient is taking. Patient Safety focused not only on those errors, but also errors of omission, such as failing to prescribe a medication from which the patient would likely have benefited. Box 1-1 portrays in stark terms an example of the failure of the care delivery system to catch and mitigate a medication error and the tragic outcome that resulted.

MEDICATION ERRORS: THE MAGNITUDE OF THE CHALLENGE

Regardless of whether one considers errors of commission or omission, error rates for various steps in the medication-use process, adverse drug

event rates in various care settings, or estimates of the economic impact of drug-related morbidity and mortality, it is clear that medication safety represents a serious cause of concern for both health care providers and patients. Data from a variety of settings demonstrate that medication errors are common, although the frequency reported depends on the identification technique used and the definition of error employed.

A 1999 study in 36 hospitals and skilled nursing facilities found a 10 percent medication administration error rate (excluding wrong-time errors) (Barker et al., 2002). In observational studies of hospital outpatient pharmacies, prescription dispensing error rates of 0.2 to 10 percent have been found (Flynn et al., 2003). And in a national observational study of the accuracy of prescription dispensing in community pharmacies, the error rate was 1.7 percent—equivalent to about 50 million errors during the filling of 3 billion prescriptions each year in the United States (Flynn et al., 2003).

The mortality projections documented in To Err Is Human were derived from adverse event data collected in a New York State study (Brennan et al., 1991; Leape et al., 1991) and a Colorado/Utah study (Thomas et al., 2000). In these two studies, medication-related adverse events were found to be the most common type of adverse event—representing 19 percent of all such events. In a variety of studies, moreover, researchers have found even higher rates of inpatient adverse drug events than were observed in the New York State and Colorado/Utah studies (Classen et al., 1991; Bates et al., 1995b) using less restrictive definitions of adverse drug events and more rigorous detection methods. More recently, major studies have shown that many adverse drug events occur in the period after discharge from the hospital (Forster et al., 2003), in nursing homes (Gurwitz et al., 2000, 2005), and in ambulatory care settings (Gandhi et al., 2003; Gurwitz et al., 2003).

In a major recent study, moreover, researchers found high levels of errors of omission in the U.S. health care system across a wide range of measures. The chance of receiving high-quality care was only about 55 percent (McGlynn et al., 2003).

Nearly 10 years ago, researchers estimated that the annual cost of drug-related illness and death in the ambulatory care setting in the United States was approximately $76.6 billion (Johnson and Bootman, 1997). Using the same approach, this cost was estimated to be $177.4 billion in 2000 (Ernst and Grizzle, 2001).

MEASURES TO IMPROVE MEDICATION SAFETY

Efforts to improve medication safety are made at all levels of the health care system: by helping the patient avoid medication errors; by organizing

health care units so that care is delivered safely; by creating health care organizations (collections of health care delivery units) that foster safe care, for example, through training for health care workers; and by encouraging health care organizations to deliver safe care by such means as regulatory and fiscal measures. Many of these efforts are long-standing and predate To Err Is Human . Key examples of such efforts are described below.

Helping the Patient Avoid Medication Errors

Since the early 1980s, the People’s Medical Society has developed guidelines to help consumers avoid medication errors in hospitals and at community and mail-order pharmacies (Personal communication, Charles Inlander, March 25, 2005). Medication errors can also take place in the home, and in June 2004, the National Consumers League, jointly with the Food and Drug Administration (FDA), launched Take with Care, a public education campaign addressing the need to be careful when taking over-the-counter (OTC) pain relievers (National Consumers League, 2004).

Organizing Health Care Units to Deliver Care Safely

For more than a decade, many organizations have provided guidance on safe medication practices for health care delivery units. Since 1994 the Institute for Safe Medication Practices has provided guidance on eliminating medication errors through newsletters, journal articles, and communications with health care professionals and regulatory authorities. In 1996 the National Coordinating Council for Medication Error Reduction and Prevention began publishing a series of recommendations on strategies for reducing medication errors (NCCMERP, 2005). Professional organizations have also offered guidance on medication safety. For example, the American Society of Health-System Pharmacists has provided guidance on safe pharmacy practices in hospitals and integrated health systems. Recently, the American Academy of Pediatrics published guidelines on the prevention of medication errors in the pediatric inpatient setting (Stucky et al., 2003).

Following the publication of To Err Is Human , AHRQ funded studies to evaluate best practices. The agency commissioned the Evidence-Based Practice Center of the University of California, San Francisco–Stanford University to evaluate the evidence supporting a long list of proposed safe practices, including many related to medication (Shojania et al., 2001).

In 2003, the National Quality Forum (NQF) identified 30 practices that should be adopted in applicable care settings, including implementing a computerized prescriber order entry system (safe practice 12) (NQF, 2003). In addition, JCAHO has been active in fostering patient safety for many years. In 1995 it implemented a Sentinel Event Policy that encourages

the voluntary reporting of serious adverse events and requires the performance of root-cause analyses for such events. Beginning in 1998, JCAHO disseminated patient safety solutions via Sentinel Event Alerts, based on analyses of reported sentinel events. Since 2003, JCAHO has set annual National Patient Safety Goals (JCAHO, 2006). Many of these goals relate to medications; an example is goal 13: Encourage the active involvement of patients and their families in the patients’ care as a patient safety strategy.

In parallel with the development of guidance on the delivery of safe care, emerging technologies have been developed to improve safety. These include electronic prescribing that automates the medication ordering process; clinical decision-support systems (usually combined with electronic prescribing systems), which may include suggestions or default values for drug doses and checks for drug allergies, drug laboratory values, and drug– drug interactions; automated dispensing systems that dispense medications electronically in a controlled fashion and track medication use; bar coding for positive identification of patients, prescriptions, and medications; and computerized adverse drug event monitors that search patient databases for data that may indicate the occurrence of such an event.

Creating Health Care Organizations That Foster Safe Care

The full benefits of technologies for preventing medication errors will not be achieved unless a culture of safety is created within health care organizations that are adequately staffed with professionals whose knowledge, skills, and ethics make them capable of overseeing the medication management of patients who are vulnerable and unable to manage their medications knowledgeably themselves (IOM, 2004). Indeed, the first safe practice in the NQF report Safe Practices for Better Healthcare is the creation of a culture of safety (NQF, 2003). The IOM’s (2004) Patient Safety report outlined the elements of a culture of safety: a shared understanding that health care is a high-risk undertaking, recruitment and training with patient safety in mind, an organizational commitment to detecting and analyzing patient injuries and near misses, open communication regarding patient injury results, and the establishment of a just culture seeking to balance the need to learn from mistakes and the need to take disciplinary action (IOM, 2004).

Two of NQF’s safe practices relate to the need for adequate resources. Safe practice 3 calls for use of an explicit protocol to ensure an adequate level of nursing based on the institution’s usual patient mix and the experience and training of its nursing staff. Safe practice 5 calls for pharmacists to participate actively in the medication-use process, including, at a minimum, being available for consultation with prescribers on medication ordering, interpretation and review of medication orders, preparation of medica-

tions, dispensing of medications, and administration and monitoring of medications.

Establishing an Environment That Enables Health Care Organizations to Deliver Safe Care

Many important systems, including accreditation, information technology, education, and knowledge generation, foster safe medication use. Important developments have occurred in each of these areas since the release of To Err Is Human . The medication-related National Patient Safety Goals and associated requirements established by JCAHO are an example in the area of accreditation. With regard to information technology, several IOM reports have stressed the need for an information infrastructure to support the delivery of quality health care. A key element of this infrastructure is the development and implementation of national health care data standards. In May 2004, Secretary of Health and Human Services Thompson announced 15 health care data standards for use across the federal health care sector, building on an initial set of 5 standards adopted in March 2003 (DHHS, 2004). In 2003 the Accreditation Council on Graduate Medical Education promulgated new residency training work-hour limitations (ACGME, 2003), drawing on published research on the relationship between fatigue and errors. And in response to To Err Is Human , Congress apportioned $50 million to support patient safety research; in early 2005, AHRQ published the results of this research (AHRQ, 2005).

STUDY CONTEXT 2

Attempts to improve medication safety must be considered against the background of a number of important contextual issues. First, it is essential to recognize the ubiquitous nature of the use of prescription and OTC drugs and of complementary and alternative medications in the United States. In the 2004 Slone Survey (Slone, 2005), 82 percent of adults reported taking at least one medication (prescription or OTC drug, vitamin/mineral, or herbal supplement) during the week preceding the interview, and 30 percent reported taking at least five medications. The three most commonly used drugs were all OTC—acetaminophen (used by 20 percent of the adult population in the week prior to the interview), aspirin, and ibuprofen. In 2003, 3.4 billion prescriptions were purchased in the United States; on average there were 11.8 prescriptions per person (Kaiser Family Foundation, 2004). Fifty-

five percent of the adults interviewed in the 2004 Slone Survey reported taking at least one prescription drug in the week prior to the interview, and 11 percent reported taking five or more such drugs (Slone, 2005). In the same survey, 42 percent of the adults surveyed reported taking vitamins and 19 percent herbal or other natural supplements.

Another key contextual issue is ongoing cost containment efforts. In recent years, these efforts have failed to limit increases in health care costs to the general inflation rate or less. National health spending in 2003 was $1.679 trillion, an increase of 7.7 percent over the previous year (Smith et al., 2005). This growth rate is not much below that for the previous year; in 2002 national health spending increased 9.3 percent over that in 2001 (Levit et al., 2004). U.S. prescription drug sales have been rising more rapidly yet. IMS Health Inc., a leading provider of information and consulting services to the pharmaceutical and health care industries, reported that prescription drug sales in the United States grew 8.3 percent to $235 billion in 2004, compared with $217 billion the previous year (IMS, 2005). This increase followed an 11.5 percent growth in 2003 over 2002 and an 11.8 percent growth in 2002 over 2001 (IMS, 2003, 2004). One critical implication of these figures relevant to this study is that efforts to control health care costs at the federal and state levels and within health care organizations mean that any new investments, including investments in medication safety, will need to be thoroughly justified.

Efforts to contain health care costs have had limited success because of a number of important cost drivers (IFoM, 2003). Innovative new pharmaceuticals are displacing older agents, which are usually cheaper because they are off patent. An aging population is leading to higher consumption of health care in general and pharmaceuticals in particular. A more demanding patient population is less accepting of restrictions on health care use for cost containment reasons. And a broader definition of treatable disease is increasing the demand for health care. Implementation of the Medicare prescription drug benefit is also likely to increase the demand for pharmaceuticals. The Administration’s Financial Year Budget projected that the net federal cost of the Medicare prescription drug benefit would be $37.4 billion in 2006, rising to $109.2 billion in 2015 (Kaiser Family Foundation, 2005).

The FDA is a key player in ensuring the safety of medications, both prescription and nonprescription. The FDA approves a drug for sale in the United States after determining that its clinical benefits outweigh its potential risks. After a drug has been approved, the FDA continues to assess its benefits and risks, primarily on the basis of reports made to the agency on the effects of its use. In 2004, withdrawal of the drug rofecoxib (Vioxx) by Merck & Co. Inc. for safety reasons increased public concern about the procedures used for assessing drug safety. In response to this concern, the

FDA requested that the IOM convene an ad hoc committee of experts (the IOM Committee on Assessment of the U.S. Drug Safety System) to conduct an independent assessment of the current system for evaluating and ensuring drug safety postmarketing.

Implementation of the Medication Modernization Act of 2003 (P.L. 108-173) will make the Centers for Medicare and Medicaid Services (CMS) the largest purchaser of prescription drugs in the United States and a major player in the way prescription medications are used. The next few years will be a pivotal period as CMS decides how it will administer the prescription drug benefit. There will be opportunities for introducing into the drug benefit rules safety guidelines for both prescribing and dispensing, and to use pay-for-performance incentives to enhance adoption of whatever guidelines are proposed. Further, there will be opportunities for medication safety research arising from the data CMS will collect as part of the drug benefit (CMS, 2005).

CMS will also become an important driver of electronic prescribing standards, whose development and implementation are called for by the Medication Modernization Act. The Medicare Prescription Drug Benefit final rule (42 Code of Federal Regulations Parts 400, 403, 411, 417 and 423) requires that Part D sponsors (e.g., participating Prescription Drug Plans and Medicare Advantage Organizations) support and comply with such standards once they are in effect. The final rule does not require providers to write prescriptions electronically; if prescribers send prescription information electronically, however, they will have to use the standards.

STUDY CHARGE AND APPROACH

In this context, at the urging of the Senate Finance Committee, the United States Congress, through the Medicare Modernization Act of 2003 (Section 107(c)), mandated that CMS sponsor a study by the IOM to address the problem of medication errors. The IOM convened the Committee on Identifying and Preventing Medication Errors to conduct this study, with the following charge:

To develop a fuller understanding of drug safety and quality issues through the conduct of an evidence-based review of the literature, case studies and analysis. This review will consider the nature and causes of medication errors; their impact on patients; and the differences in causation, impact and prevention across multiple dimensions of health care delivery including patient populations, care settings, clinicians, and institutional cultures.

If possible, to develop estimates of the incidence, severity and costs of medication errors that can be useful in prioritizing resources for na-

tional quality improvement efforts and influencing national health care policy.

To evaluate alternative approaches to reducing medication errors in terms of their efficacy, cost-effectiveness, appropriateness in different settings and circumstances, feasiblity, institutional barriers to implementation, associated risk, and quality of evidence supporting the approach.

To provide guidance to consumers, providers, payers, and other key stakeholders on high-priority strategies to achieve both short-term and long-term drug safety goals, to elucidate the goals and expected results of such initiatives and support the business case for them, and to identify critical success factors and key levers for achieving success.

To assess opportunities and key impediments to broad nationwide implementation of medication error reductions, and to provide guidance to policy-makers and government agencies in promoting a national agenda for medication error reduction.

To develop an applied research agenda to evaluate the health and cost impacts of alternative interventions, and to assess collaborative public and private strategies for implementing the research agenda through AHRQ and other government agencies.

The committee comprised 17 members representing a range of expertise related to the scope of the study, as described below (see Appendix A for biographical sketches of the committee members). The committee addressed its charge by reviewing the salient research literature, government reports and data, empirical evidence, and additional materials provided by government officials and others. In addition, a workshop was held to augment the committee’s knowledge and expertise through more focused discussion of specific issues of concern, and to obtain input from a wide range of researchers, providers of health care services, and interested members of the public. The committee also commissioned several background papers to avail itself of expert, detailed, and independent analyses of some of the key issues beyond the time and resources of its members.

SCOPE OF THE STUDY

CMS determined that this study should focus on issues related to the safe, effective, appropriate, and efficient use of medications . As mentioned above, a parallel IOM committee, the Drug Safety Committee, was tasked with assessing the postmarketing surveillance system for medications . There is some overlap between the present study and the work of that committee. The two committees and their staffs have worked together closely to define common areas in the two studies and develop consistent sets of recommendations.

Definitions

Drugs and dietary supplements.

This study addressed the quality of the five steps in the medication-use process: selecting and procuring by the pharmacy, selecting and prescribing for the patient, preparing and dispensing, administering, and monitoring effects on the patient. The study examined medication use in a wide range of care settings—hospital, long-term, and community. The term medication encompasses three broad categories of products—prescription and nonprescription drugs and dietary supplements—all regulated by the FDA (see Chapter 2 ).

According to the FDA (2004), a drug is defined as a substance that is recognized by an official pharmacopeia or formulary; intended for use in the diagnosis, cure, mitigation, treatment, or prevention of disease; intended to affect the structure or any function of the body (excluding food); and intended for use as a component of a medicine, but not a device or a component, part, or accessory of a device.

Biologic products (including vaccines, blood, and blood products) are a subset of drug products. Biologics are distinguished from other drugs by their manufacturing process—biological as opposed to chemical. Some biologics, principally vaccines (excluding their long-term effects), are within the scope of this study; blood and blood products and tissues for transplantation are excluded.

Drugs include both those that require a prescription and those that do not. Nonprescription drugs are usually termed over-the-counter (OTC). The characteristics of OTC drugs are such that the potential for misuse and abuse is low, consumers are able to use them successfully for self-diagnosable conditions, they can be adequately labeled for ease and accuracy of use, and oversight by health practitioners is not needed to ensure safe and effective use (FDA, 2005).

Dietary supplements , often called complementary and alternative medications , are another group of products often used for medicinal or general health purposes. The Dietary Supplement Health and Education Act of 1994 (P.L. 103-147) defined a dietary supplement as a product (other than tobacco) intended to supplement the diet that bears or contains one or more of the following dietary ingredients: a vitamin; a mineral; an herb or other botanical; an amino acid; a dietary substance for use by man to supplement the diet by increasing the dietary intake; or a concentrate, metabolite, constituent, extract, or combination of any ingredient cited above. While the primary emphasis of the study was on prescription and OTC drugs, attention was given to dietary supplements as well, and the discussion of drugs often applies also to the latter products.

Medication Error, Adverse Drug Event, and Adverse Drug Reaction

The terms medication error , adverse drug event , and adverse drug reaction denote related concepts (see Figure 1-1 ) and are often used incorrectly. To Err Is Human (IOM, 2000, p. 28) defined error and adverse event as follows:

An error is defined as the failure of a planned action to be completed as intended (i.e., error of execution), or the use of a wrong plan to achieve an aim (i.e., error of planning).

An adverse event is an injury caused by medical management rather than the underlying condition of the patient.

The Committee on Data Standards for Patient Safety was concerned that the phrase medical management did not embrace acts of omission . The committee gave considerable thought to expanding on these two definitions and produced the following (IOM, 2004, p. 30, 32):

An error is defined as the failure of a planned action to be completed as intended (i.e., error of execution), or the use of a wrong plan to achieve an aim (i.e., error of planning). An error may be an act of commission or an act of omission.

An adverse event results in unintended harm to the patient by an act of commission or omission rather than by the underlying disease or condition of the patient.

FIGURE 1-1 Relationship among medication errors, adverse drug events, and potential adverse drug events.

SOURCE: Gandhi et al., 2000.

The Committee on Data Standards for Patient Safety wanted to make clear that the potentially avoidable results of an underlying disease or condition—for example, a recurrent myocardial infarction in a patient without a contraindication who was not given a beta-blocker (an error of omission)—should be considered an adverse event (IOM, 2004). The Committee on Identifying and Preventing Medication Errors discussed the adverse event definition given in the Patient Safety report and decided to adopt this definition. Further attempts to operationalize the definition of adverse event may well lead eventually to additional modifications of the definition.

Consistent with the above definitions:

A medication error is defined as any error occurring in the medication use process (Bates et al., 1995a).

An adverse drug event is defined as any injury due to medication (Bates et al., 1995b).

An injury includes physical harm (for example, rash), mental harm (for example, confusion), or loss of function (for example, inability to drive a car).

Medication errors and adverse drug events have multiple sources. They may be related to professional practice; health care products, procedures, and systems, including prescribing; order communication; product labeling, packaging, and nomenclature; compounding; dispensing; distribution; administration; education of the patient or health care professional; and monitoring of use.

Implicit in the definition of medication errors is that they are preventable. However, most medication errors do not cause harm. Some do cause harm and are either potential adverse drug events or preventable adverse drug events (see Figure 1-1 ), depending on whether an injury occurred (Gandhi et al., 2000). Potential adverse drug events are events in which an error occurred but did not cause injury (for example, the error was detected before the patient was affected, or the patient received a wrong dose but experienced no harm) (Gandhi et al., 2000).

Adverse drug events can be preventable (for example, a wrong dose leads to injury) or nonpreventable (for example, an allergic reaction occurs in a patient not known to be allergic) (see Figure 1-1 ). Nonpreventable adverse drug events are also often termed adverse drug reactions 3 (Gandhi et al., 2000).

The World Health Organization has defined an adverse drug reaction as a response to a drug that is noxious and unintended and occurs at doses normally used in man for prophylaxis, diagnosis, or therapy of disease or modification of physiological function (WHO, 1975). This definition excludes injuries due to drugs that are caused by errors, which are of obvious interest. As a result, drug safety researchers coined the term adverse drug event to include both adverse drug reactions (which are nonpreventable), and preventable adverse drug events (Bates et al., 1995b). From the safety perspective, preventable adverse drug events are most important because they are known to be preventable today; adverse drug reactions are also important, however, since it may become possible to prevent them in the future by using new approaches, such as pharmacogenomic profiling.

Audiences for the Report

The committee sought to assess the roles of and make recommendations for all of the major stakeholders involved in the safe use of medications:

First and foremost, the consumer 4 or patient who uses a medication, as well as family members, friends, and neighbors who may be involved in assisting the patient.

Individual health care providers—physicians, nurses, and pharmacists.

The organizations responsible for delivering care, for example, hospitals, nursing homes, ambulatory clinics, pharmacies, and pharmacy benefit managers.

Those responsible for salient policy (Congress and state legislators), payment (CMS and commercial insurers), regulation (for example, the FDA and state regulatory bodies), accreditation (for example, JCAHO), and professional education (for example, schools of nursing).

Manufacturers of medications and the systems used in medication delivery (for example, intravenous pumps and health information technology systems) and providers of value-added services (for example, tools that indicate harmful drug–drug interactions).

In carrying out the study, the committee took the view that the goal of all these stakeholders with regard to medication use should be to optimize the relationship between the patient and the health care provider(s) so as to meet the six aims set forth in the Quality Chasm report (care should be safe, effective, timely, patient-centered, equitable, and efficient) (IOM, 2001). In

general, the health care system should enable the flow of all information needed to choose medications that optimize health to the extent possible in accordance with the preferences of the patient. In addition, all health care stakeholders should attempt to produce information on and inform patients and providers about the balance between effectiveness and safety, rather than addressing either in isolation. Effectiveness (tangible benefits— those that can be felt by the patient—in the actual setting in which the medication is used) rather than efficacy (benefit based on ideal circumstances of use) is the appropriate measure for the purpose of informing patients and providers. Further, all stakeholders should strive to produce a system in which the transactions that ensue following a decision about using a medication at a particular dose and time are free of errors.

REPORT OVERVIEW

Part I of this report addresses the causes, incidence, and costs of medication errors. By way of background, it begins with a case study illustrating how medication errors can arise through a combination of organizational and individual failures. Chapter 2 provides an overview of the system for drug development, regulation, distribution, and use, identifying the many points at which errors can occur. Chapter 3 summarizes the peer-reviewed literature on the incidence and costs of medication errors.

Part II of the report outlines the steps needed to establish a patient-centered, integrated medication-use system. It provides action agendas for achieving both short- and long-term improvements in medication safety for patients/consumers to support provider–consumer partnerships ( Chapter 4 ), for health care organizations ( Chapter 5 ), and for the industry that provides medications and medication-related products and services ( Chapter 6 ). In Chapter 7 , the committee outlines an applied research agenda designed to foster safe medication use. Finally, Chapter 8 proposes action agendas for those who set the environment in which care is delivered (for example, legislators, payers, and regulators). Appendix B provides a glossary and acronym list for the report, while Appendices C and D present detailed discussion of medication incidence rates and prevention strategies, respectively.

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Flynn EA, Barker KN, Carnahan BJ. 2003. National observational study of prescription dispensing accuracy and safety in 50 pharmacies. Journal of the American Pharmacists Association 43(2):191–200.

Forster AJ, Murff HJ, Peterson JF, Gandhi TK, Bates DW. 2003. The incidence and severity of adverse events affecting patients after discharge from the hospital. Annals of Internal Medicine 138(3):161–167.

Gandhi TK, Seger DL, Bates DW. 2000. Identifying drug safety issues: From research to practice. International Journal for Quality in Health Care 12(1):69–76.

Gandhi TK, Weingart SN, Borus J, Seger AC, Peterson J, Burdick E, Seger DL, Shu K, Federico F, Leape LL, Bates DW. 2003. Adverse drug events in ambulatory care. New England Journal of Medicine 348(16):1556–1564.

Gandhi TK, Bartel SB, Shulman LN, Verrier D, Burdick E, Cleary A, Rothschild JM, Leape LL, Bates DW. 2005. Medication safety in the ambulatory chemotherapy setting. Cancer 104(11):2477–2483.

Gurwitz JH, Field TS, Avorn J, McCormick D, Jain S, Eckler M, Benser M, Edmondson AC, Bates DW. 2000. Incidence and preventability of adverse drug events in nursing homes. American Journal of Medicine 109(2):87–94.

Gurwitz JH, Field TS, Harrold LR, Rothschild J, Debellis K, Seger AC, Cadoret C, Fish LS, Garber L, Kelleher M, Bates DW. 2003. Incidence and preventability of adverse drug events among older persons in the ambulatory setting. Journal of the American Medical Association 289(9):1107–1116.

Gurwitz JH, Field TS, Judge J, Rochon P, Harrold LR, Cadoret C, Lee M, White K, LaPrino J, Mainard JF, DeFlorio M, Gavendo L, Auger J, Bates DW. 2005. The incidence of adverse drug events in two large academic long-term care facilities. American Journal of Medicine 118(3):251–258.

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In 1996 the Institute of Medicine launched the Quality Chasm Series, a series of reports focused on assessing and improving the nation's quality of health care. Preventing Medication Errors is the newest volume in the series. Responding to the key messages in earlier volumes of the series— To Err Is Human (2000), Crossing the Quality Chasm (2001), and Patient Safety (2004) —this book sets forth an agenda for improving the safety of medication use. It begins by providing an overview of the system for drug development, regulation, distribution, and use. Preventing Medication Errors also examines the peer-reviewed literature on the incidence and the cost of medication errors and the effectiveness of error prevention strategies. Presenting data that will foster the reduction of medication errors, the book provides action agendas detailing the measures needed to improve the safety of medication use in both the short- and long-term. Patients, primary health care providers, health care organizations, purchasers of group health care, legislators, and those affiliated with providing medications and medication- related products and services will benefit from this guide to reducing medication errors.

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Article Contents

Introduction, some basic definitions, frequency and outcomes of medication errors, types of medication error and prevention, latent factors, detecting and reporting errors, prescribing faults and prescription errors, prescribing faults, prescription errors, the hedgehog principle and balanced prescribing, achieving balanced prescribing, conclusion: a prescription for better prescribing.

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Medication errors: what they are, how they happen, and how to avoid them

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J.K. Aronson, Medication errors: what they are, how they happen, and how to avoid them, QJM: An International Journal of Medicine , Volume 102, Issue 8, August 2009, Pages 513–521, https://doi.org/10.1093/qjmed/hcp052

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A medication error is a failure in the treatment process that leads to, or has the potential to lead to, harm to the patient. Medication errors can occur in deciding which medicine and dosage regimen to use (prescribing faults—irrational, inappropriate, and ineffective prescribing, underprescribing, overprescribing); writing the prescription (prescription errors); manufacturing the formulation (wrong strength, contaminants or adulterants, wrong or misleading packaging); dispensing the formulation (wrong drug, wrong formulation, wrong label); administering or taking the medicine (wrong dose, wrong route, wrong frequency, wrong duration); monitoring therapy (failing to alter therapy when required, erroneous alteration). They can be classified, using a psychological classification of errors, as knowledge-, rule-, action- and memory-based errors. Although medication errors can occasionally be serious, they are not commonly so and are often trivial. However, it is important to detect them, since system failures that result in minor errors can later lead to serious errors. Reporting of errors should be encouraged by creating a blame-free, non-punitive environment. Errors in prescribing include irrational, inappropriate, and ineffective prescribing, underprescribing and overprescribing (collectively called prescribing faults) and errors in writing the prescription (including illegibility). Avoiding medication errors is important in balanced prescribing, which is the use of a medicine that is appropriate to the patient's condition and, within the limits created by the uncertainty that attends therapeutic decisions, in a dosage regimen that optimizes the balance of benefit to harm. In balanced prescribing the mechanism of action of the drug should be married to the pathophysiology of the disease.

In 2000, an expert group on learning from adverse events in the NHS, chaired by the Chief Medical Officer, reported that since 1985 there had been at least 13 episodes in which people (usually children) had been killed or paralysed because of wrong administration of drugs by spinal injection; 12 involved vinca alkaloids; 10 were fatal. 1 Serious medication errors are uncommon, but it is salutary that it took so long to recognize that remedial action was needed in this case. 2 Even so, this error continues to be made. 3

A medication

A medication (a medicinal product) is ‘a product that contains a compound with proven biological effects, plus excipients or excipients only; it may also contain contaminants; the active compound is usually a drug or prodrug, but may be a cellular element’. 4

A codicil to this definition stipulates that a medicinal product is one that is intended to be taken by or administered to a person or animal for one or more of the following reasons: as a placebo; to prevent a disease; to make a diagnosis; to test for the possibility of an adverse effect; to modify a physiological, biochemical or anatomical function or abnormality; to replace a missing factor; to ameliorate a symptom; to treat a disease; to induce anaesthesia. Medication (the process) is the act of giving a medication (the object) to a patient for any of these purposes.

This definition reminds us of the distinction between the drug itself (the active component) and the whole product, which also contains supposedly inactive excipients. The definition of a medication encompasses not only chemical compounds—drugs, prodrugs (which may themselves have no pharmacological activity), stereoisomers that may have only adverse effects, or compounds that are used for diagnostic purposes (such as contrast media); it also includes cellular elements, such as inactivated or attenuated viruses for immunization, blood products (such as platelets), viruses for gene therapy, and embryonic stem cells; ‘contaminants’ includes chemical and biological contaminants and adulterants, the former being accidentally present the latter deliberately added.

Although the definition covers a wide range of compounds, it does not include medications when they are used to probe systems for non-diagnostic purposes, such as the use of phenylephrine to study baroreceptor reflexes in a physiological or pharmacological experiment.

An error is ‘something incorrectly done through ignorance or inadvertence; a mistake, e.g. in calculation, judgement, speech, writing, action, etc.’ 5 or ‘a failure to complete a planned action as intended, or the use of an incorrect plan of action to achieve a given aim’. 6 Other definitions have been published. 7

A medication error

With these definitions in mind, a medication error can be defined as ‘a failure in the treatment process that leads to, or has the potential to lead to, harm to the patient’. 8 , 9 The ‘treatment process’ involves all medications, as defined above.

Medication errors can occur in:

choosing a medicine—irrational, inappropriate, and ineffective prescribing, underprescribing and overprescribing;

writing the prescription—prescription errors, including illegibility;

manufacturing the formulation to be used—wrong strength, contaminants or adulterants, wrong or misleading packaging;

dispensing the formulation—wrong drug, wrong formulation, wrong label;

administering or taking the drug—wrong dose, wrong route, wrong frequency, wrong duration;

monitoring therapy—failing to alter therapy when required, erroneous alteration.

The term ‘failure’ in the definition implies that certain standards should be set, against which failure can be judged. All those who deal with medicines should establish or be familiar with such standards. They should institute or observe measures to ensure that failure to meet the standards does not occur or is unlikely. Everybody involved in the treatment process is responsible for their part of the process.

Adverse events and adverse drug reactions

An adverse event is ‘any abnormal sign, symptom or laboratory test, or any syndromic combination of such abnormalities, any untoward or unplanned occurrence (e.g. an accident or unplanned pregnancy), or any unexpected deterioration in a concurrent illness’. 4 If an adverse event occurs while an individual is taking a drug it could be an adverse drug reaction (ADR). The term ‘adverse drug event’ is sometimes used to describe this, but it is a bad term and should be avoided. 4 If an adverse event is not attributable to a drug it remains an adverse event; if it may be attributable to a drug it becomes a suspected ADR.

An ADR is ‘an appreciably harmful or unpleasant reaction, resulting from an intervention related to the use of a medicinal product’ 4 .

Some medication errors result in ADRs but many do not; occasionally a medication error can result in an adverse event that is not an ADR (for example, when a cannula penetrates a blood vessel and a haematoma results). The overlap between adverse events, ADRs, and medication errors is illustrated in the Venn diagram in Figure 1 . 8

A Venn diagram showing the relation among adverse events, ADRs and medication errors; the sizes of the boxes do not reflect the relative frequencies of the events illustrated (Reproduced from reference 8, with permission from Wolters Kluwer Health/Adis ©; Adis Data Information BV (2006); all rights reserved).

The precise frequencies of medication errors are not known. The method of detection can affect the estimated frequency. 10 Probably most errors go unnoticed (the error iceberg 11 ); of those that are detected a minority actually result in ADRs, or at least serious ones. For example, in a UK hospital study of 36 200 medication orders, a prescribing error was identified in 1.5% and most (54%) were associated with the choice of dose; errors were potentially serious in 0.4%. 12 In a survey of 40 000 medication errors in 173 hospital trusts in England and Wales in the 12 months to July 2006, collected by the National Patient Safety Agency, ∼15% caused slight harm and 5% moderate or severe harm. 13 In a US study, 1.7% of prescriptions dispensed from community pharmacies contained errors. 14 Since ∼3 billion prescriptions are dispensed each year in the USA, ∼50 million would contain errors. Of those, only ∼0.1% were thought to be clinically important, giving an annual incidence of such errors of about 50 000. Wrong label information and instructions were the most common types of errors.

However, it is important to detect medication errors, whether important or not, since doing so may reveal a failure in the treatment process that could on another occasion lead to harm. There is also evidence that the death rate from medication errors is increasing. From 1983 to 1993 the numbers of deaths from medication errors and adverse reactions to medicines used in US hospitals increased from 2876 to 7391 15 and from 1990 to 2000 the annual number of deaths from medication errors in the UK increased from about 20 to just under 200. 16 These increases are not surprising—in recent years hospitals have seen increased throughput of patients, new drugs have emerged that are increasingly difficult to use safely and effectively, medical care has become more complex and specialized, and the population has aged, factors that tend to increase the risk of medication errors. 17

When errors are detected, they can cause much dissatisfaction. According to a 2000 report citing UK medical defence organizations, 1 25% of all litigation claims in general medical practice were due to medication errors and involved the following errors:

prescribing and dispensing errors (including a wrong, contraindicated or unlicensed drug, a wrong dosage, or wrong administration);

repeat prescribing without proper checks;

failure to monitor progress; and

failure to warn about adverse effects (which might, however, not be regarded as a medication error).

The best way to understand how medication errors happen and how to avoid them is to consider their classification, which can be contextual, modal, or psychological. Contextual classification deals with the specific time, place, medicines and people involved. Modal classification examines the ways in which errors occur (for example, by omission, repetition or substitution). Psychological classification is to be preferred, as it explains events rather than merely describing them. Its disadvantage is that it concentrates on human rather than systems sources of errors. The following psychological classification is based on the work of Reason on errors in general. 18

There are four broad types of medication errors (labelled 1–4 in Figure 2 ). 8

A classification of types of medication errors based on psychological principles. For examples of prescription errors in each category see the text and Table 1 (Reproduced from reference 8, with permission from Wolters Kluwer Health/Adis ©; Adis Data Information BV (2006); all rights reserved).

Rule-based errors (using a bad rule or misapplying a good rule)—for example, injecting diclofenac into the lateral thigh rather than the buttock. Proper rules and education help to avoid these types of error, as do computerized prescribing systems.

Action-based errors (called slips)—for example, picking up a bottle containing diazepam from the pharmacy shelf when intending to take one containing diltiazem. In the Australian study mentioned above most errors were due to slips in attention that occurred during routine prescribing, dispensing or drug administration. These can be minimized by creating conditions in which they are unlikely (for example, by avoiding distractions, by cross-checking, by labelling medicines clearly and by using identifiers, such as bar-codes); 22 so-called ‘Tall Man’ lettering (mixing upper- and lower-case letters in the same word) has been proposed as a way to avoid misreading of labels, 23 but this method has not been tested in real conditions. A subset of action-based errors is the technical error—for example, putting the wrong amount of potassium chloride into an infusion bottle. This type of error can be prevented by the use of checklists, fail-safe systems and computerized reminders.

Memory-based errors (called lapses)—for example, giving penicillin, knowing the patient to be allergic, but forgetting. These are hard to avoid; they can be intercepted by computerized prescribing systems and by cross-checking.

For some examples of prescription errors see Table 1 . Examples of other types of medication errors under the same headings are given in reference 8.

Examples of prescribing faults and prescription errors

a This stresses the importance of prescribing by generic name whenever possible, since more errors are made by confusing brand names than generic names; however, in this case ‘Priadel’ had to be prescribed—modified-release formulations of lithium must be prescribed by brand name because of differences in bioavailability from brand to brand.

Mistakes (knowledge- and rule-based errors), slips (action-based errors) and lapses (memory-based errors) have been called ‘active failures’. 18 However, there are several properties of systems (so-called ‘latent factors’) that make prescribers susceptible to error. For example, working overtime with inadequate resources, poor support, and low job security all contributed to an increased risk of medication errors by nurses. 24 Among doctors depression and exhaustion are important. 25 , 26 Errors are more likely to occur when tasks are carried out after hours by busy, distracted staff, often in relation to unfamiliar patients. 19 There is a particular risk of errors when doctors first arrive in hospital, because of shortcomings in their knowledge, 16 and presumably also because they are unfamiliar with local prescription charts and other systems. Improved education and improved working conditions, including better induction processes, should reduce the risk of errors that are due to these factors; a national prescription form would help.

One difficulty in detecting errors is that those who make them fear disciplinary procedures and do not want to report them. 27 The establishment of a blame-free, non-punitive environment can obviate this. 28 The reporting of errors, including near-misses, should be encouraged, using error reports to identify areas of likeliest occurrence and simplifying and standardizing the steps in the treatment process. However, some systems for voluntarily reporting medical errors are of limited usefulness, because reports often lack details and there is incomplete reporting and underreporting. 29 A medication error reporting system should be readily accessible, with clear information on how to report a medication error, and reporting should be followed by feedback; detection may be improved by using a combination of methods. 30

Errors in prescribing can be divided into irrational prescribing, inappropriate prescribing, ineffective prescribing, underprescribing and overprescribing, and errors in writing the prescription. The inadequacy of the term ‘error’ to describe all of these is obvious. Failing to prescribe an anticoagulant for a patient in whom it is indicated (underprescribing) or prescribing one when it is not indicated (overprescribing) are different types of error from errors that are made when writing a prescription. I therefore prefer to use the terms ‘prescribing faults’ and ‘prescription errors’. 9 The term ‘prescribing errors’ ambiguously encompasses both types.

Irrational and inappropriate prescribing

‘Rational’ is defined in the Oxford English Dictionary as ‘based on, derived from, reason or reasoning’ and ‘appropriate’ as ‘specially fitted or suitable, proper’. 5 One would expect rational prescribing to be appropriate, but that is not always the case. A rational approach can result in inappropriate prescribing, if it is based on missing or incorrect information. If, for example, one does not know that another prescriber has already prescribed paracetamol unsuccessfully for a headache, a prescription for paracetamol might be rational but inappropriate. Consider an example from my own practice. 31

• A woman with Liddle's syndrome presented with severe symptomatic hypokalaemia. Her doctor reasoned as follows:

– she has potassium depletion;

– spironolactone is a potassium-sparing drug;

– spironolactone will cause her to retain potassium;

– her serum potassium concentration will normalize.

• She took a full dose of spironolactone for several days, based on this logical reasoning, but still had severe hypokalaemia. Her doctor should have reasoned as follows:

–she has potassium depletion due to Liddle's syndrome, a channelopathy that affects epithelial sodium channels;

–there is a choice of potassium-sparing drugs;

–spironolactone acts via aldosterone receptors, amiloride and triamterene via sodium channels;

–in Liddle's syndrome an action via sodium channels is required.

• When she was given amiloride instead of spironolactone her serum potassium concentration rapidly rose to within the reference range.

This stresses the importance of understanding the relation between the pathophysiology of the problem and the mechanism of action of the drug (see below).

Ineffective prescribing

Ineffective prescribing is prescribing a drug that is not effective for the indication in general or for the specific patient; it is distinct from underprescribing (see below). In a study of 212 patients, 6% of 1621 medications were rated as ineffective. 32 Of 196 US out-patients aged 65 and older who were taking five or more medications, 112 (57%) were taking a medication that was ineffective, not indicated, or duplicative. 33 And in a Scottish study, 49% of general practices prescribed homoeopathic remedies, 5% of practices accounting for 50% of the remedies prescribed. 34

One would expect ineffective prescribing to be minimized by the use of guidelines, but there is conflicting evidence; prescribing guidelines may be ineffective unless accompanied by education or financial incentives. 35

Underprescribing

Underprescribing is failure to prescribe a drug that is indicated and appropriate, or the use of too low a dose of an appropriate drug. The true extent of underprescribing is not known, but there is evidence of significant underprescribing of some effective treatments, such as angiotensin converting-enzyme inhibitors for patients with heart failure 36 and statins for hyperlipidaemia. 37

The sources of underprescribing include fear of adverse effects or interactions, failure to recognize the appropriateness of therapy, and doubts or ignorance about likely efficacy. Cost may play a part. 38 There is a tendency to avoid treatment in older people, 39 , 40 and this can lead to unwanted effects, 28 including the so-called risk-treatment mismatch, in which those who are at greatest risk are less aggressively treated, an effect that may be partly associated with age. 41 However, other factors may contribute to this type of mismatch, such as distraction by co-morbidities, miscalculation of the true benefit to harm balance and a reluctance to undertake or exacerbate polypharmacy. 42

In a study of the relation of underprescribing to polypharmacy in 150 elderly patients, the probability of underprescribing increased significantly with the prescribed number of drugs. 43 This resulted in failure to use β-adrenoceptor antagonists after myocardial infarction, ACE inhibitors for heart failure, anticoagulants in atrial fibrillation and bisphosphonates in osteoporosis.

Overprescribing

Overprescribing is prescribing a drug in too high a dosage (too much, too often or for too long). In some cases treatment is not necessary at all. For example, among hospital patients who were given a proton pump inhibitor treatment was indicated in only half. 44 Polypharmacy, defined as the use of five or more drugs, occurs in >10% of people aged over 65 years in the UK. 45 And although not all polypharmacy is inappropriate, 46 some undoubtedly leads to ADRs and drug-drug interactions.

Overuse of antibiotics is well known and much discussed. A systematic review of 55 trials showed that no single strategy or combination of strategies was better than any other and none was highly effective, although the authors singled out active education of clinicians as a strategy to pursue. 47

In a Spanish study, those who overprescribed were more likely to be in rural practices, further from specialist centres, caring for children, lacking postgraduate education and in part-time or short-term work. 48 In some countries, doctors’ income may have an effect. 49

All the factors that lead to medication errors in general contribute towards prescription errors. They include lack of knowledge, using the wrong drug name, dosage form, or abbreviation, and incorrect dosage calculations. 50 In a US study of about 900 medication errors in children, ∼30% were prescription errors, 25% were dispensing errors and 40% were administration errors. 51 In one study the most common form of prescription error was writing the wrong dose. 12 In six Oxford hospitals the most common errors on prescription charts were writing the patient's name incorrectly and writing the wrong dose, which together accounted for ∼50% of all errors. 16 In a hospital study of 192 prescription charts, only 7% were correctly filled; 79% had errors that posed minor potential health risks and 14% had errors that could have led to serious harm. 52

Table 1 lists some examples of prescribing faults and prescription errors under the headings of the four types of error. The remedies are as outlined above.

The major barrier to rational, appropriate and effective prescribing is failure to apply what I call the hedgehog principle. The Greek poet Archilochus (seventh century BC) wrote that ‘The fox knows many things, the hedgehog one big thing’. What he meant is not clear, since the text is fragmentary, but Isaiah Berlin suggested that it could be interpreted as distinguishing between ‘those who relate everything to a single central vision [hedgehogs] … and those who pursue many ends [foxes]’. 53 As a prescriber I am a hedgehog, and the one big idea to which I subscribe is the need to marry the mechanism of action of the drug to the pathophysiology of the disease. Using amiloride to treat hypokalaemia in Liddle's syndrome (as described above) is a perfect example of this principle. If in addition one pays attention to the balance of benefit and harm, one achieves ‘balanced prescribing’, defined as the use of a medicine that is appropriate to the patient's condition and, within the limits created by the uncertainty that attends therapeutic decisions, in a dosage regimen that optimizes the balance of benefit to harm. 54 Note that this definition includes the two components of the hedgehog principle: the disease and the medicine.

Indication : is there an indication for the drug? Effectiveness : is the medication effective for the condition? Diseases : are there important co-morbidities that could affect the response to the drug? Other similar drugs : is the patient already taking another drug with the same action? Interactions are there clinically important drug–drug interactions with other drugs that the patient is taking? Dosage : what is the correct dosage regimen (dose, frequency, route, formulation)? Orders : what are the correct directions for giving the drug and are they practical? Period : what is the appropriate duration of therapy? Economics : is the drug cost-effective?

The mnemonic for this list is ‘i.e. do I dope?’. Each item relates to an important process in prescribing, and in the absence of evidence that following this schedule improves prescribing, it makes sense to use it.

We all make errors from time to time. There are many sources of medication errors and different ways of avoiding them. However, we must start by being aware that error is possible and take steps to minimize the risks. The essential components of this are monitoring for and identifying errors, reporting them in a blame-free environment, analysis of their root causes, 57 changing procedures according to the lessons learnt and further monitoring.

How can we improve prescribing and reduce medication errors? Five prescriptions might help 35 , 58 :

℞ Education, to be taken as often as possible (a repeat prescription—learning should be lifelong).

℞ Special study modules for graduates and undergraduates, to be taken as required.

℞ Proper assessment: in the final undergraduate examination, to be taken once or twice; in postgraduate appraisal, to be taken occasionally; this could be linked to a licence to prescribe.

℞ A national prescription form for hospitals, to be applied uniformly and used as a training tool.

℞ Guidelines and computerized prescribing systems, to be taken if indicated (their roles and proper implementation are not yet clear).

Conflict of interest : None declared.

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Medication Error

• First Online: 17 October 2023

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• Abdul Mondul 3 , 4 &
• Mei Kong 5 , 6 , 7  

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Medication error is one of the leading patient safety concerns in healthcare, causing morbidity and mortality. It can occur at all stages of the medication process. Medication errors are frequent, often harmful, but with good systems and processes are largely preventable. There are five essential strategies to improve medication safety and avert errors. These include: (1) Appropriate usage of information technology (electronic health records (EHR), computerized physician order entry (CPOE), point-of-care clinical decision support (CDS), and bedside bar-coded medication administration (BCMA). (2) Addressing health literacy and engaging patients and families. (3) Standardize protocols, dosing, order sets with alerts, assessment parameters, and early recognition of potential adverse events for high-alert medications. (4) Thorough medication reconciliation at points in transition of care where new medications are ordered or existing orders are rewritten. (5) Foster pharmacy collaboration and better communication and interaction among members of the healthcare team and the patient. Every discipline is responsible to stop the line at any interval of the medication process when an error or potential error is identified. The goal is to prevent the error from reaching the patient. An organizational culture of safety is critical, where communication is embraced and staff are empowered to report concerns so changes can be made to prevent errors and improve safety.

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Mondul, A., Kong, M. (2023). Medication Error. In: Agrawal, A., Bhatt, J. (eds) Patient Safety. Springer, Cham. https://doi.org/10.1007/978-3-031-35933-0_11

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Describing and Quantifying Wrong-Patient Medication Errors Through a Study of Incident Reports

Megumi takahashi.

1 Department of Quality and Patient Safety, Tokyo Medical University, Tokyo, Japan

Hiroshi Okudera

2 Department of Crisis Medicine and Clinical Safety, University of Toyama, Toyama, Japan

Masahiro Wakasugi

Mie sakamoto, hiromi shimizu.

3 Department of Medical Management Office, Toyama University Hospital, Toyama, Japan

Tokie Wakabayashi

Tsuneaki yamanouchi, hisashi nagashima.

Our aim was to inform a new definition of wrong-patient errors, obtained through an analysis of incident reports related to medication errors.

We investigated wrong-patient medication errors in incident reports voluntarily reported by medical staff using a web-based incident reporting system from 2015 to 2016 at a university hospital in Japan. Incident report content was separately evaluated by four evaluators using investigational methods for clinical incidents from the Clinical Risk Unit and the Association of Litigation and Risk Management. They investigated whether it was the patient or drug that was incorrectly chosen during wrong-patient errors in drug administration in incident reports and assessed contributory factors which affected the error occurrence. The evaluators integrated the results and interpreted them together.

Out of a total 4337 IRs, only 30 cases (2%) contained wrong-patient errors in medication administration. The cases where the intended drugs were administered to incorrect patients occurred less frequently than cases where the wrong drugs were administered to the intended patients through the investigation of wrong targets. After a discussion, the evaluators concluded that the patient - drug/CPOE screen mismatch, caused by choosing the wrong patient, drug, or CPOE screen (mix-ups), occurred in the wrong-patient medication errors. These errors were caused by three conditions: (1) where two patients/drugs were listed next to one another, (2) where two patients’ last names/drugs’ names were the same, and (3) where the patient/drug/CPOE screen in front of the staff involved was believed to be the correct one. Additionally, these errors also involved insufficient confirmation, which led to failure to detect and correct the mismatch occurrences.

Based on our study, we propose a new definition of wrong-patient medication errors: they consisted of choosing a wrong target and insufficient confirmation. We will investigate other types of wrong-patient errors to apply this definition.

Introduction

Medication errors are defined as errors in the process of ordering or delivering a medication and can occur at any stage in the drug ordering, dispensing, and administration process. 1 These errors often lead to serious patient injuries, which are categorized as adverse drug events (ADEs). 1 , 2 The representative study on medication errors reported that 6.5% of adult inpatients suffered ADEs 2 and another study reported ADEs occurred in 27.4% of adult outpatients. 3 Most of the medication errors and ADEs occurred at the ordering and administration stages. 1–4 Before-after studies, which evaluated the effect of a computerized physician order entry (CPOE) system or barcode verification within an electronic medication-administration system (eMAR), showed the reduction of ADEs at the ordering and administration stages. 5 , 6

Among medication errors, there are several error types, such as “wrong dose”, “wrong frequency”, and “wrong drug” errors. 2 , 5–8 In addition, wrong-patient errors in medication administration are often reported. Wrong-patient errors can occur in various areas of healthcare, such as drug administration, phlebotomy, blood transfusions, and surgical interventions. 9 Regarding medication administration, wrong-patient error may also cause ADEs. 9 , 10 For instance, administration of sedative drugs to the wrong patient can lead to a disturbance in consciousness, or an insulin injection given to the wrong patient can lead to hypoglycemia or a life-threatening condition. 9–11 Although in the usual wrong-patient errors, patients themselves are incorrectly chosen, several other patterns or errors in medication administration also exist, such as the intended patient receiving the wrong drug or the intended drug going to the incorrect patient. To date, few studies have investigated whether it was the patient or drug that was incorrectly chosen during wrong-patient errors in drug administration, 11–14 but no clear definition of wrong-patient errors in drug administration has been proposed. Therefore, our aim was to further investigate and define wrong-patient errors in medication administration by examining incident reports (IRs), which were voluntarily reported by medical staff, through a web-based incident reporting system.

Materials and Methods

Hospital setting.

The participating hospital was a tertiary care hospital, which has 612 beds and provides highly advanced medical care, technology, and training, with the help of 372 physicians, 569 nurses, 34 pharmacists, 120 medical technology staff and 68 administrative staff. 15

Study Design

This study was planned as a retrospective observational study and approved by the Toyama University Hospital’s Clinical Research and Ethical Committee (2015–89) on November 25, 2015. It was conducted in accordance with the guidelines outlined in the Declaration of Helsinki. The subjects of this study were IRs, not patients; therefore, patient information was not obtained, and the need for informed consent from patients was waived by the committee. Data were fully anonymized and were considered not to include identifying information for involved patients and medical staff.

Incident Reporting System

A web-based incident reporting system (HOPE incident reporting system, Fujitsu Limited, Japan) was introduced at the participating hospital, which is linked to the electronic health record (EHR) system. Health care professionals involved in or witnessing patient safety incidents submit IRs through this system. This system can be accessed from all computer terminals in the hospital EHR system, allowing for anonymous incident reporting. Reporters enter the incident information in the recommended format. 15 , 16 The required information consists of the medical category in which the incident occurred, severity of incident, type of staff involved, type of error, and incident details, which were established by the national adverse event reporting system of the Japan Council for Quality Health Care 17 and widely accepted throughout Japan. The medical category in which the incident occurred consists of “medication”, “blood transfusion”, “therapeutics and procedures”, “medical devices and equipment”, “lines and tubes”, “clinical laboratory tests”, “medical care (eg, falls, slips, meals, etc.)”, and “other” ( Table 1 ). 17 The “medication” category further requires that the stage of drug administration (eg, prescribing, dispensing, formulation management, medication preparation, and administration) be listed when reporting the error. 17 The incident severity also needs to be entered, based on the national incident severity classification, which is defined by the National University Hospital Council of Japan ( Table 2 ). 18 For example, incident level 0 means that an error occurred, but was corrected before implementation, while the most severe, incident level 5, means there was a patient death caused by provided medical care. Cases that are incident level 3b or higher are regarded as ADEs. IRs which were submitted by reporters are stored in a database and are available by using keyword retrieval.

Medical Treatment Type for Incident Reports

Incident Levels Representing the Degree of Impact on Patients

Flow of Drug Administration

A CPOE system and clinical decision support system (CDSS) were available at the participating hospital. At ordering, the CDSS not only provides computerized advice regarding drug dose, but also checks for drug allergy. 19 , 20 Prescriptions are completed by physicians on computer terminals (prescription stage), and the transcriptions are generated in the CPOE system. Medication, which is dispensed (dispensing stage) and prepared by a pharmacist (formulation management and medication preparation stage), is dispatched from the pharmacy department and distributed by the ward nurses to the designated patient location. Intravenous (IV) drugs are placed in boxes and oral drugs are placed in small plastic cases with a note attached including the patient’s name (medication preparation stage). The nurses manually carry the IV drugs or oral drugs to the rooms where the patients are located and administer the medication. At the drug administration stage, the nurses have to identify the patients by asking them to provide their names and checking the ID number on the patients’ wristbands before oral medication administration. For IV drug administration only, the nurses can use the barcodes on the wristband to scan and check the patient’s identity. This is because our CPOE and eMAR systems can issue the labels which the barcodes for patient identification are printed on only for ordering IV drugs, not oral medication.

Data Collection

We collected IRs related to medication errors from the hospital incident reporting system, between April 1, 2015 and March 31, 2016. We used simple statistics for each type of medication error, incident level, type of staff involved, and the stage of drug administration where the error occurred. Among them, the IRs for wrong-patient errors in medication errors were extracted. Then the types of drugs (oral drugs, IV drugs), which were handled in the wrong-patient errors in medication errors and “the wrong targets” (patients, drugs), that is incorrectly chosen targets during these errors, were investigated. In addition, the incident level items, the type of staff involved, and the stage of drug administration were examined. Then, four evaluators consisting of a physician, two nurses, and a pharmacist, belonging to the hospital’s department of patient safety management, analyzed the content of the IRs separately, and identified the contributing factors for wrong-patient errors in medication administration. The methods of analysis for wrong-patient errors in medication errors in the IRs were adapted from the investigation methods for clinical incidents provided by the Clinical Risk Unit and the Association of Litigation and Risk Management. 21 Finally, the four evaluators integrated their evaluations and discussed their interpretations.

Medication Errors in Incident Reports

A total of 4337 incidents were reported between April 2015 and March 2016. Among them, medication-related incidents were the most prevalent (1525 cases, 35.3%) ( Table 1 ). Of the medication-related incidents, the largest number of incidents occurred at the medication administration stage (977 cases, 64.1%), followed by the preparation stage (200 cases, 13.1%), prescription stage (188 cases, 12.3%), dispensing stage (95 cases, 6.2%), and formulation management stage (65 cases, 4.3%; Table 3 ). The most frequent errors were due to “omission” (361 cases, 23.7%) and “wrong dose”, including “overdose” and “underdose” (242 cases, 15.9%), throughout all stages of drug administration ( Table 3 ). At the prescription stage, responses of “others” was most prevalent (73 cases, 38.8%), followed by “wrong dose” (52 cases, 27.7%) and “omission” errors (36 cases, 23.7%). On the other hand, at the medication administration stage, the most frequent errors were “omission” (281 cases, 28.7%), “wrong dose” (155 cases, 15.9%), “wrong administration timing” (106 cases, 10.8%), and “others” (233 cases, 23.8%).

Error Types and Stages of Medication Errors in the Incident Reports

Wrong-Patient Errors in Medication Administration

Wrong-patient errors were included in only 30 cases (2.0%) in the IRs related to medication administration ( Table 3 ). These mostly occurred at the medication administration stage (23 cases, 76.7%). In contrast, six cases (20%) occurred at the medication preparation stage and 1 case (3.3%) occurred at the prescription stage ( Table 3 ). For the type of staff involved, nurses were involved in 27 cases (90%), a physician was involved in one case (3.3%), and a pharmacist was involved in two cases (6.7%; Table 4 ). For incident level, there were no cases of incident level 3a or higher, which were considered ADEs. There were 12 incident level 2 cases (40%) where errors were implemented and slightly affected patients’ health without treatment and 14 incident level 1 cases (46.7%) where errors were implemented without harm. There were four incident level 0 cases (13.3%) where errors were corrected before implementation ( Table 4 ). As for drug type, there were 21 cases of oral drug errors (70%) and 9 cases of IV drug errors (30%; Table 4 ).

Wrong Targets and Event Information in Incident Reports with Wrong-Patient Errors

Abbreviation : IV, intravenous.

Wrong Targets in Wrong-Patient Errors of Medication Administration

For incorrectly chosen targets during wrong-patient errors in medication administration, there were only six cases (20%) where the wrong patient was chosen, and all of these cases occurred at the administration stage. Most of them (23 cases, 76.7%) were caused by picking up the wrong patient’s drugs. Furthermore, in one case (3.3%), the ward physician ordered the antibiotic drug through the CPOE screen of the wrong patient, which was due to using the same screen from another patient’s examination order before prescribing ( Table 4 ). The evaluators found that cases where the intended drugs were administered to incorrect patients occurred less frequently than cases where the wrong drugs were administered to the intended patients. After a discussion, the evaluators concluded that the drug-patient mismatch or the CPOE screen-patient mismatch, caused by choosing the wrong patient, drug, or CPOE screen (mix-ups), occurred in the wrong-patient errors in medication administration through the investigation of wrong targets. ( Table 4 )

Contributory Factors for Wrong-Patient Medicaiton Errors

The first evaluator, who was a physician, focused on the environment where mix-ups occurred. The evaluator found that contributory factors for the mix-up occurrence included conditions where two patients/drugs were listed next to one another, where two patients’ last names/drugs’ names were the same, and where staff involved firmly believed that the patient/drug/CPOE screen in front of him/her was the correct one ( Table 5 ). The second and third evaluators, who were nurses, focused on the confirmation action. They found that most of the incidents were caused by insufficient confirmation, which is a violation of the hospital patient identification rule. It was mostly caused by the impatience of medical staff. Furthermore, they found that 20–30% of the cases were categorized by recognition failures where the patient/drug/CPOE screen in front of the staff involved was believed to be correct. They concluded that in these cases, medical staff did not confirm it in the fixed procedure because it was believed to be correct ( Table 5 ). The fourth evaluator, who was a pharmacist, found the same contributory factors for the drug-patient mismatch as the first evaluator. This evaluator further noted that two cases (6.7%) where pharmacists were involved in the medication preparation were caused by insufficient patient identification, making it a case of confirmation rule violation ( Table 5 ).

Contributory Factors for the Error Occurrences

Abbreviations : Rev, reviewer; IV, intravenous; CPOE, computerized physician order entry.

After discussing the findings, the evaluators concluded that wrong-patient errors in medication administration consisted of two types of errors: choosing wrong targets and insufficient confirmation. Choosing wrong targets led to mismatches between the patient and the drug or the CPOE screen, and insufficient confirmation was the violation of confirmation rules set by the hospital, which failed to detect and correct the mismatch occurrences. Furthermore, in medication administration, choosing wrong targets, which led to the occurrence of mismatches between the patient and the drug or the CPOE screen, was caused by three types of conditions: (1) where two patients/drugs existed next to one another, (2) where two patients’ last names/drug names were the same, and (3) where the patient/drug/CPOE screen in front of the staff involved was believed to be correct without confirmation ( Table 5 ). The contributory factor for insufficient confirmation, which was the violation of the hospital confirmation rule in wrong-patient errors in medication administration, was the provider’s psychological state, resulting in the involved staff being impatient, or having recognition failure, where the patient/drug/CPOE screen in front of the staff involved was believed to be correct.

In this study, medication-related incidents were the most prevalent in IRs reported during 2015–2016. Among medication-related incidents, the largest number of incidents occurred at the medication administration stage (64.1%) with IRs occurring at the prescribing stage accounting for only 12.3% of the total incidents. The most frequent errors were “omission” (23.7%) and “wrong dose” (15.9%). In previous reports of medication errors, medication errors and ADEs mostly occurred at the prescribing and administration stages, and the most frequent error type was “wrong dose.” 1 , 2 , 4 However, it was also reported that CPOE systems, where physicians wrote orders directly on the computer, reduced legibility problems and transcriptional errors, and that the CDSS, which provided computerized advice regarding drug dose and checked for drug allergy, reduced dose errors and ADEs. 1 , 5 , 19 , 20 In the participating hospital, the CPOE system and CDSS were available, so the few errors at the prescribing stage and those due to “wrong dose” should have been prevented by these systems. On the other hand, in our study, errors at the medication administration stage were most frequent. In previous studies, the use of barcode scanning, which connected to the eMAR, improved the accuracy of patient identify verification and medication administration and reduced the occurrence rate of medication errors at the administration stage. 6 , 22 In the participating hospital, verification using barcode scanning was used only in the implementation of IV drugs because of our CPOE and eMAR systems. This might have affected the large number of IRs related to medication administration occurring at the administration stage.

Wrong-patient errors were included in only 30 cases (2.0%) of IRs involving medication errors in this study. However, this small sample was still able to provide us with useful information for enhancing the definition of wrong-patient errors. From our results, wrong-patient errors in drug administration were involved in two primary types of actions: (1) choosing an incorrect target (patient, drug, or CPOE screen) which led to a mismatch between a patient and a drug or CPOE screen and (2) a failure to correct these mismatches caused by insufficient patient confirmation, in violation of the hospital confirmation rule. Furthermore, we discussed and expected that common wrong-patient errors also consisted of incorrectly choosing a target (patient or medical care) which led to the mismatch between patients and their medical care, and insufficient confirmation by medical staff. We concluded it was necessary to investigate other type of wrong-patient errors and consider whether this definition fitted those errors.

The Emergency Care Research Institute (ECRI) published a special report on “patient identification error”, which presented a literature review on studies related to wrong-patient incidents. 23 In this report, “wrong-patient errors” were defined as “patient identification errors” and the cause of these errors was identified as poor adherence to the patient identification protocol. We considered that wrong-patient errors consisted not only of patient misidentification, but of mismatches between patients and their medical care, and poor identification by medical staff was not the cause of them, but the error itself which consisted of them.

Reason divided human errors into mainly two types of actions: unintended and intended. 23

The errors caused by unintended actions were called “slips” or “lapses”, which resulted from some failures in the execution and/or storage stage of an action sequence. Those caused by intended actions were called “mistakes”, defined as deficiencies or failures in the judgment and/or inferential processes involved in the selection of an objective, or in the specification of the means to achieve it. 23 We considered that choosing wrong targets which led to the occurrences of mismatch belonged to “slips”, while insufficient confirmation which failed to correct the errors belonged to “mistakes.”

Slips were reported to occur in simple tasks caused by the impairment of automatic procedural routines, which was affected by extrinsic factors. 23 We identified three types of conditions as the contributory factors for the occurrence of the drug-patient/CPOE screen-patient mismatch: (1) where two patients/drugs existed next to one another, (2) where two patients’ last names/drugs’ names were the same, and (3) where the patient/drug/CPOE screen in front of the staff involved was believed to be correct. Although the condition where the patient names were similar has been reported as a contributory factor of the wrong-patient errors, 8 the other conditions have not been mentioned in previous studies on wrong-patient errors. In these cases, the staff involved firmly believed that the patient/drug/CPOE screen that was picked up by him/her or in front of him/her was the correct one. It was supposed that the targets (patients/drugs/CPOE screen) next to the correct ones or in front of the staff involved, caught his/her attention and were believed to be correct ones. We thought that it is necessary to investigate the contributory factors for other types of wrong-patient errors in the future.

On the other hand, mistakes were reported to occur in rather complicated tasks caused by failures of higher-order cognitive processes, which were affected by intrinsic/extrinsic factors. 23 We identified that the contributory factors for insufficient confirmation in wrong-patient errors in drug administration were conditions where the staff involved was rushing, or strongly believed that the patient/drug/CPOE screen was the correct one. In previous studies, a contributory factor for insufficient patient confirmation was the cumbersome and unclear identification protocol process. 11–14 In our study, we revealed that staff involved in the error believed that the patient/drug/CPOE screen was correct, which introduces another contributory factor for insufficient patient confirmation. One explanation for this action may be the concept of “cognitive bias”. 24–26 Based on this concept, humans tend to find ways to justify their own actions as correct. We concluded that, in wrong-patient errors in medication administration, because the targets which were chosen by involved medical staff were believed to be correct, the procedures for confirmation were supposed to be unnecessary and omitted by him/her. We thought that it is also necessary to investigate the contributory factors for insufficient confirmation in other wrong-patient errors.

Limitations and Future Direction

Although we examined IRs to inform the definition of wrong-patient errors in medication administration in the current study, the number of IRs involving wrong-patient errors in medication administration was small. It would be beneficial to evaluate a larger number of cases in the future. Furthermore, we plan to consider whether the revised definition and newly defined contributory factors from the current study will apply to other wrong-patient errors in future studies.

Through our study, we proposed a new definition of wrong-patient medication errors: that they consisted of choosing a wrong target which led to mismatch between patients and drugs/CPOE screen, and insufficient confirmation which failed to detect and correct them. We identified three contributory factors for the occurrence of a mismatch between the drug/CPOE screen and the patient, which included situations where two patients/drugs were listed next to one another, where two patients’ last names/drugs’ names were the same, or where the patient/drug/CPOE screen in front of the staff involved was assumed to be correct. We will investigate IRs related to other types of wrong-patient errors and consider if this definition fits those errors, and investigate the contributory factors for them.

Funding Statement

This research was only supported by research fund of our department which was distributed by Tokyo Medical University, without any external fund.

The authors declare that there are no conflicts of interest regarding the publication of this paper.

Medication Errors in Healthcare

Introduction.

Medication errors are one of the common sources of poor health outcomes in healthcare systems. A recent study by John Hopkins hospital indicates that medication error is the third leading cause of patient death in the United States (US) and has surpassed diabetes and stroke (Carrie, 2022). Similarly, at least one in every seven patients receiving care is vulnerable to medication errors in a hospital in the US (Carrie, 2022). Medication errors may result from mistakes in dispensing, prescribing, and giving medication. Even though most medication errors are preventable, a lack of adequate knowledge, training and experience amongst healthcare professionals often results in increased medication errors. According to Rodziewicz et al. (2018), by analyzing medication errors, medical professionals and healthcare systems can protect patients and improve the quality of care received by patients. Therefore, this paper seeks to comprehensively analyze medication errors in healthcare, including the causal factors, possible solutions, and the ethical implication of implementing a possible solution to the problem.

Elements of the Problem

Medication errors threaten patient safety outcomes and may lead to dissatisfaction with patient safety and quality of care. The National Coordinating Council for Medication Error and Prevention (NCCMERP) defines a medication error as a preventable event that may lead to patient harm or inappropriate medication use, Aseeri et al. (2020) argue. However, a medication error is controlled by a healthcare provider and the patient. It is important to note that most medication errors are preventable if appropriate measures and taken into consideration. These errors may be connected to healthcare services, products, professional practices and procedures, including; administration, prescribing, communication, dispensing, product labelling and use. The primary element of medication errors in healthcare systems includes prescribing errors, dispensing, preparation stage, drug administration errors, and lack of care coordination and communication among the healthcare provider (Kozel, 2020).

Prescription errors are the leading cause of medication errors in the healthcare system. Prescription errors may arise due to a lack of critical information about the drug being prescribed to a patient and may result in fatalities, as Rodziewicz et al. (2022) argued. In the preparation stage, medication errors may result from dose miscalculation, wrongful administration of drugs, improper labelling, wrongful medication selection, and incorrect preparation. On the other hand, drug administration errors may arise from acts of care provider or patient, which may include dose omission, improper preparation, poor timing of drug administration, and improper drug administration rate. According to Hammoudi et al. (2018), dispensing errors are another common cause of medication errors. These errors may arise due to a healthcare provider or medical personnel commission. These errors include inappropriate drug prescription, wrong dosage, and incorrect entry into computer systems when dispensing drugs. Overall, dispensing errors may result in incorrect admission of drugs and incorrect dosage (Rodziewicz et al., 2022). Lack of care coordination and poor communication among healthcare providers is also other causes of medication errors. Instances such as miscommunication on the type of s drug, name quantity to be consumed, prescription, side effects and frequency of consumption are common causes of medication errors due to lack of care coordination and communication in the healthcare system.

Analysis of the Problem

Medication errors may result in adverse health outcomes and compromise the safety and quality of healthcare services. Medication errors may lead to more extended hospital stays, increased hospital readmission rate and a lack of trust between healthcare providers and patients; as Hammoudi et al. (2018) argued, these errors often lead to legal action against healthcare organizations and healthcare providers. This way, professional training and education are paramount in mitigating such errors. According to Hammoudi et al. (2018), healthcare providers, particularly nurses, account for nearly a significant proportion of medication errors. This number shows that even the most qualified healthcare practitioners are susceptible to a medication errors, hence the need for professional training and education for medical staff. Healthcare professionals must understand the possible causes of medication errors in a healthcare setting and the risk of adverse health outcomes. In addition, healthcare professionals should practice proper medication prescription and medication to reduce the likelihood of these errors. Healthcare professionals are equally involved in the preparation of drugs, administration and prescription of drugs; thus, they can develop solutions to address the problem (Rodziewicz et al., 2022). Addressing this problem is key to the safety and quality of healthcare services received by patients.

Studies indicate that the aged population and patient who requires special medical attention are the most vulnerable to medication errors. For instance, elderly patients are more susceptible to medication errors because of a lack of compliance and knowledge. Medication errors often result in psychological and emotional problems; these patients are constantly stressed, depressed and anxious. Handling the adverse impact on them is a financial burden that often leads to prolonged hospital stays or even readmission. Furthermore, patients are also likely to develop other complications out of medication errors problem (Rodziewicz et al., 2022). Moreover, healthcare professionals are reluctant to create a work culture anchored on shared responsibility and collaboration; this has escalated the problem and led to job dissatisfaction among healthcare providers.

Response to the Health Problem

Healthcare professionals do not commit medication errors intentionally during the medication process. Healthcare professionals are highly trained individuals with top-notch skills and knowledge required for the professional execution of their duties, especially in the prescription and administration of drugs. Perhaps, this is because healthcare professionals should be answerable when a medication error occurs; they are usually blamed for such errors, even though they may not have possibly been involved in the error problem (Rodziewicz et al., 2022). In most cases, they are subject to punishment from professional organizations. In addition, the accused healthcare professionals also tend to lose respect from their counterparts; this may have an adverse impact on their career compared to other forms of punishment that they may be subjected to the problem, Rodziewicz et al. (2018) argued. However, punishment is not a viable option when it comes to reducing medication errors, even though it promotes professional ethics and standards in the practice of the medical profession. This way, it is crucial to spot weaknesses within the healthcare system that could result in a medication error.

Care coordination and communication are crucial to finding a long-term solution to the medication problems in healthcare systems. According to Rodziewicz et al. (2022), an effective communication system among the healthcare providers such as pharmacists, nurses and physicians will reduce prescription and prescription errors. Pharmacist-nurse lead prescriptions can only be achieved through effective communication between nurses and pharmacists (Kozel, 2020). Such initiatives can help reduce medication errors during the prescription and administration of drugs. This also ensures that changes and errors during prescriptions are communicated promptly before drugs are administered to a patient.

Similarly, drugs should be labelled and packed accordingly to avoid any confusion. In addition, computerized models and simulated prescriptions should be integrated into the healthcare system to reduce medication errors related to the labelling and packaging of drugs (Kozel, 2020). Labelling also helps healthcare professionals and patients select the right drug for their medication. Drug prescriptions should also be made based on patient information to promote the correct usage of drugs. Modern technology such as barcode systems and EMR should be incorporated into healthcare institutions to help verify drugs before use (Dunn & Hazzard, 2019). Healthcare providers should be educated on medication guides, drug safety, and drug safety communication to avoid incidences of improper administration of drugs to patients. Automated dispensing systems should be incorporated into healthcare institutions as an efficient means of dispensing medication to minimize medication errors (Dunn & Hazzard, 2019). Communication and modern technologies should be enhanced in healthcare institutions to solve the problem of medication errors.

Ethical Implications

The ethical implication has a direct impact on the proposed strategies. The ethics principles and guidelines in healthcare require health professionals to protect the integrity of patient information through the highest standards of professional practice. Literature review indicates that healthcare providers have a role to play in protecting patient information so as not to compromise the well-being of the patients. Similarly, the principle of non-maleficence demands that healthcare providers should not compromise the patient’s well-being and demonstrate honesty, fairness and respect for others during their professional practice, as Rodziewicz et al. (2018) argued. These virtues reduce the incidences of medication errors, and may help healthcare providers to investigate the route course of a medication problem for patients, hence patient safety and quality care. By being accountable for any medication errors caused to patients’ healthcare professionals should strive for high ethical standards in their practice.

Implementation

To successfully adopt the above-proposed solution to the problem, healthcare institutions should incorporate evidence-based practices and best-solution approaches to implement different solutions as proposed (Kozel, 2020). EBP will help implement automated dispensing systems, error reporting systems, automated prescribing systems, and labelling and packaging of drugs to minimize medication errors. Implementation of this system also requires the professional expertise of other staff within the healthcare institutions, such as technicians and IT professionals. Nevertheless, resources such as computers, servers, and network systems will also be required to implement proposed solutions. Best solution approaches that can be implemented also include correct documentation and medication.

Medication errors are prevalent in healthcare systems and may adversely impact the patient’s health outcomes. Healthcare providers or patients themselves may cause these errors. The errors may arise due to improper drug, prescription drug dispensing errors, improper administration of drugs and lack of communication. Collectively these error occurrences of these errors may result in medication errors in healthcare institutions. For this reason, the discussion proposed specific solutions to help minimize the adverse impact of medication error on patient health outcomes. The proposed solution will help improve patient safety and quality of care and mitigate and reduce future incidences of medication errors.

Rodziewicz, T. L., Houseman, B., & Hipskind, J. E. (2018). Medical error prevention.

Rodziewicz, T. L., Houseman, B., & Hipskind, J. E. (2022). Medical error reduction and prevention. In  StatPearls [Internet] . StatPearls Publishing.

Aseeri, M., Banasser, G., Baduhduh, O., Baksh, S., & Ghalibi, N. (2020). Evaluating medication error incident reports at a tertiary care hospital:  Pharmacy ,  8 (2), 69.

Hammoudi, B. M., Ismaile, S., & Abu Yahya, O. (2018). Factors associated with medication administration errors and why nurses fail to report them.  Scandinavian journal of caring sciences ,  32 (3), 1038–1046.

Dunn, P., & Hazzard, E. (2019). Technology approaches digital health literacy.  International journal of cardiology ,  pp. 293 , 294–296.

Kozel, V. (2020). Reducing medication errors by adding a pharmacist and standardized communication to interdisciplinary team rounding: A quality improvement project.

Carrie, A. (2022, June 28). The eight most common root causes of medical errors. Always Culture. Retrieved September 28, 2022, from https://alwaysculture.com/hcahps/communication-medications/8-most-common-causes-of-medical-errors/

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• Published: 24 April 2024

The effect of electronic medical records on medication errors, workload, and medical information availability among qualified nurses in Israel– a cross sectional study

• Raneen Naamneh 1 &
• Moran Bodas   ORCID: orcid.org/0000-0002-6182-6362 1  

BMC Nursing volume  23 , Article number:  270 ( 2024 ) Cite this article

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Metrics details

Errors in medication administration by qualified nursing staff in hospitals are a significant risk factor for patient safety. In recent decades, electronic medical records (EMR) systems have been implemented in hospitals, and it has been claimed that they contribute to reducing such errors. However, systematic research on the subject in Israel is scarce. This study examines the position of the qualified nursing staff regarding the impact of electronic medical records systems on factors related to patient safety, including errors in medication administration, workload, and availability of medical information.

This cross-sectional study examines three main variables: Medication errors, workload, and medical information availability, comparing two periods– before and after EMR implementation based on self-reports. A final sample of 591 Israeli nurses was recruited using online private social media groups to complete an online structured questionnaire. The questionnaires included items assessing workload (using the Expanding Nursing Stress Scale), medical information availability (the Carrington-Gephart Unintended Consequences of Electronic Health Record Questionnaire), and medical errors (the Medical Error Checklists). Items were assessed twice, once for the period before the introduction of electronic records and once after. In addition, participants answered open-ended questions that were qualitatively analyzed.

Nurses perceive the EMR as reducing the extent of errors in drug administration (mean difference = -0.92 ± 0.90SD, p  < 0.001), as well as the workload (mean difference = -0.83 ± 1.03SD, p  < 0.001) by ∼  30% on average, each. Concurrently, the systems are perceived to require a longer documentation time at the expense of patients’ treatment time, and they may impair the availability of medical information by about 10% on average.

The results point to nurses’ perceived importance of EMR systems in reducing medication errors and relieving the workload. Despite the overall positive attitudes toward EMR systems, nurses also report that they reduce information availability compared to the previous pen-and-paper approach. A need arises to improve the systems in terms of planning and adaptation to the field and provide appropriate technical and educational support to nurses using them.

Peer Review reports

Introduction

Clinical/medical error is defined as a preventable adverse effect of medical care, whether it is harmful to the patient or not [ 1 ]. One of the most common types of medical error is medication error [ 2 ]. These errors seriously threaten individual safety and public health in general and are a challenge for the professionals involved. Such errors are responsible for 7000–9000 deaths per year in the United States of America alone, and the cost of medication errors is estimated at over 40 billion dollars per year, which causes a significant burden on the health system and society [ 3 ]. Many people suffer physical and psychological pain due to medication administration errors [ 2 , 3 ].

In Israel, qualified nurses administer prescription medications to patients staying in hospitals. Many measures are taken to ensure the safety of the process of medication administration in hospitals. According to the medication administration procedure in Israel, published in 2016 by the Ministry of Health [ 4 ], every instruction on medication administration should include the date, time, full name of the medication, medication form, dosage, frequency of administration, route of administration, duration of administration, and special instructions if applicable. In addition, administering medication requires the nursing staff to implement a series of actions before administering the treatment itself: address the patient’s sensitivities, compare the details of the instruction with the details of the patient and the medication, pay attention to the patient’s new medication and document the administration of the medication in the patient’s record, specifying the date and time of administration [ 4 ].

Unfortunately, despite all the efforts and steps taken by healthcare providers, clinical errors, including medication errors, do happen. Error rates in medication administration are still high, with consequences of significant disability for the victims [ 2 , 5 ]. Moreover, as a result of these errors, medical staff may experience harm to their self-confidence and work less efficiently, which may lead to more mistakes and further impair patient safety [ 2 , 3 ].

One way proposed in recent decades to prevent or reduce medication errors is the implementation of Electronic Medical Records (EMR) systems in medical centers [ 6 ]. EMR systems include a wide variety of technologies designed to assist medical processes and medical decision-making. EMR is a type of information technology through which doctors and nurses in hospitals can organize large amounts of information about the patient and optimize the use of information in their clinical work [ 6 ].

In general, findings in the literature indicate significant advantages of using EMR in improving the quality of patient care. Among the benefits found are improving patient safety, reducing the frequency of errors, saving time, preventing complications, improving communication between caregivers, and improving connectivity to other systems in the hospital, such as the pharmacy, laboratories, imaging centers, and others [ 7 , 8 , 9 ]. Many studies have found that computerized medical information systems may reduce errors in drug treatment through correct identification of the patient, increasing the availability of relevant medical information to prevent errors, such as drug interactions, as well as increasing access to current information about the patient’s history of the drug treatment and drug sensitivity [ 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 ].

However, the findings surrounding the effect of EMR on medical error reduction are still inconclusive with some studies reporting mixed results. For example, in a study conducted at the American University of Beirut Medical Center looking into 2,883 prescriptions, of which 1,475 (51.2%) were from the period before the implementation of electronic prescriptions (paper prescriptions) and 1,408 (48.8%) from the period after the implementation of electronic prescriptions, it was found that electronic prescriptions were associated with a significant reduction in errors in medication dosage and frequency of medication administration. However, they were associated with an increase in duplication errors [ 19 ]. Other studies report similar findings [ 25 , 26 ]. After looking into a decade of data between 2099 and 2018, Classen et al. concluded that (p. 1) “despite broad adoption and optimization of Electronic Health Record (EHR) systems in hospitals, wide variation in the safety performance of operational EHR systems remains across a large sample of hospitals and EHR vendors, and serious safety vulnerabilities persist in these operational EHRs.” [ 27 ].

Due to the complexity of the management of drug treatment by the nursing staff and the multitude of practices and procedures related to it, studies were carried out examining the subject of the satisfaction of nursing staff with the electronic prescription system. The findings were, again, mixed and inconclusive. Some studies reported an increase in staff satisfaction following gthe introduction of EMRs [ 28 , 29 ], while others reported dissatisfaction stemming from increased workload and burnout [ 30 , 31 ] and difficulty in retrieving and accessing information [ 32 ]. Consequently, some studies report that EMR systems may slow down and consume valuable time away from treating patients [ 33 ].

As evident from the literature, findings are inconclusive, and there is still a need to examine the effectiveness of EMR systems in reducing medication errors, as well as their contribution to patients’ safety and staff functionality. This current study aimed to assess nurses’ perception of EMR systems’ contribution to mitigating medical error, workload, and information availability. The working hypotheses were that nurses perceive the introduction of EMR systems as beneficial to reducing medical errors and workload and increasing information availability, compared with the previous pen & paper system.

STROBE statement

This study adheres to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines.

Study design

This cross-sectional study was performed between February and May 2022. It focused on a large group of qualified nurses in Israel and compared two periods: before and after implementing EMR systems in hospitals. The participants were asked to answer an online survey evaluating the research variables one time by recollecting the period when analog information collection infrastructures were used (pen-and-paper and printed sheets) and another time by addressing the situation during the current period when computerized medical information systems are being used. Differences between the two periods were analyzed for statistical significance. Of note is that most hospitals in Israel transitioned into electronic medical records by the late 2000s, with the last hospital transitioning in the late 2010s. The introduction of the EMR systems expanded the amount of data collected by the medical staff. For example, tracking of previous hospitalizations and reasons for non-administration of certain drugs are currently being collected in the EMR systems but were not recorded or less recorded in the older pen-and-paper system.

Population & sampling

The target population for this study was registered nurses in Israel. According to the Israeli Ministry of Health, there are 70,052 registered nurses as of 2020, of which approximately 60,000 have been working before the introduction of EMR Systems [ 34 ]. The inclusion criteria for this study were being a registered nurse, an adult (over age 18), Hebrew speaking, and having a recollection of the period in which pen-and-paper records were used. Exclusion criteria were not being a registered nurse, minor, non-Hebrew speaking, and having not worked as a registered nurse during the pen-and-paper period or having no recollection of it.

In the current study, we used non-probability sampling to recruit a relatively large number of participants quickly and affordably. We used social media to recruit the participants, as studies have demonstrated the usefulness of obtaining data through social networks [ 35 ]. In addition, the snowball method was used to distribute the questionnaire between colleagues. For the needs of the current research, which requires quick access to a unique (professional) population in a wide geographic distribution, the “snowball” approach was deemed the most practical. In addition, data collection also focused on Hillel-Yafe Medical Center, which experienced a cyber attack in October 2021, causing the entire hospital to resort back to pen-and-paper data management. This created an opportunity to collect data from a more recent occurrence of pen-and-paper utilization in a medical establishment. Emphasis was placed on creating a heterogeneous sample that would represent most of the population by distributing the questionnaire to different groups and cultures, Jews and Arabs.

The minimum sample size was calculated using the WinPepi calculator [ 36 ]. According to Aziz et al. [ 16 ], the incidence of medication errors reported by EMR system users is 0.5%, compared with 2.5% reported by those using analog (pen and paper) systems. Assuming 95% confidence and 99% power, the minimum sample size required is 100. The final sample in this study included nearly six times more participants ( N  = 591). According to WinPepi’s power calculator for paired samples, given the mean difference reported in this study, the current study has a power of 100%.

This study utilized a tool comprising both closed and open-ended questions. The former will be described in the following sub-sections. The latter, representing the qualitative part of this study, was used to understand better nurses’ stances toward EMR systems. This section was constructed of three free text questions: (1) What is your opinion regarding using EMR in your department? (2) In what way does the use of EMR benefit you, if at all? (3) In what way does the use of EMR bother you, if at all? The answers to these questions were analyzed using qualitative methods, according to Shkedi [ 37 ]. This approach to qualitative analysis provides a guide to open-text categorization and theme extraction that closely fits with Israeli (Hebrew-speaking audiences.

Participants were first asked to state whether they had the opportunity to experience administering medication while working with pen & paper prescriptions and documents. The lack of such experience was a criterion for exclusion from the study.

Socio-demographics were assessed using a questionnaire that included the following variables: gender (nominal; male, female, other), age (continuous; calculated using the year of birth), type of nursing staff (nominal; qualified nurse, department manager, deputy manager), seniority (continuous; in years), number of computer systems used in the department (continuous), and type of education (nominal; bachelor’s or master’s degree or higher).

Workload was assessed using a shortened version of the Expanding Nursing Stress Scale (ENSS) by French et al. [ 38 ]. The original questionnaire examines various stressors in nurses’ work and consists of 57 items. One factor in the questionnaire deals with workload. It consists of nine items, and its reliability was α = 0.86. Two of the questionnaire items were not relevant to the topic of the current study and were removed. Therefore, the final shortened version includes seven items on a Likert scale ranging from 1 (“disagree at all” / “very low”) to 6 (“agree to a large extent” / “very high”). An example of an item from the questionnaire: “I don’t have enough time to do what I am required to do.” The workload index was created by averaging the score of all seven items. A higher score means a higher workload. The questionnaire was translated into Hebrew and was validated through a pilot study among a small number of subjects ( N  = 32). Reliability as internal consistency (Cronbach’s alpha) in the pilot phase was 0.955 for the before questionnaire and 0.838 for the after questionnaire. In the final sample, the workload index’s Cronbach’s alpha value was 0.91 (before the implementation of EMR) and 0.86 (after).

Information availability was assessed using a shortened version of the Carrington-Gephart Unintended Consequences of Electronic Health Record Questionnaire (CG-UCE-Q) by Gephart et al. [ 39 ]. The internal reliability of the original questionnaire was α = 0.94 with a content validity index of 0.96. The original questionnaire consists of 36 questions and covers a variety of topics related to the change in the work process due to the implementation of computerized systems in hospitals. One of the issues covered is the availability of the patient’s medical information. For the present study, we selected five items relevant to measuring the availability of information. The rest of the items in the questionnaire were not relevant to the subject of the current study. Items range on a Likert scale from 1 (“do not agree at all”) to 5 (“strongly agree”). Example item: “When you have to make a decision about your patient, is there too little documented information about the patient for you to understand the clinical picture?“. The medical information availability index was calculated as the average of items’ scores after reversing the scores of items #1, 4, and 5. A higher score means greater availability of information. The questionnaire was translated into Hebrew and was validated among a small number of subjects ( N  = 32) from the study population. Reliability as internal consistency (Cronbach’s alpha) in the pilot phase was 0.924 for the before EMR questionnaire and 0.779 for the after questionnaire. In the final sample, the index’s Cronbach’s alpha value was 0.690 before EMR and 0.930 after.

Medication errors were assessed using a shortened version of the Medical Error Checklists questionnaire developed by Tsiga et al. [ 40 ]. The internal reliability of the original questionnaire was α = 0.96. The original tool is constructed of three parts, with each part containing 25 questions. The items represent a variety of medical errors, for example, wrong diagnosis, errors in medication prescriptions, communication failure, etc. Only eight items were found to be relevant for the current study, measuring medication administration errors, and those comprised the final tool used in this study. Items range on a Likert scale from 1 (“do not agree at all”) to 5 (“strongly agree”). Example item: “The prescription of the medication is illegible and unclear.” The medication errors index was calculated as the average of all eight items. A higher score means more errors in administering medication. The questionnaire was translated into Hebrew and was validated among a small number of subjects ( N  = 32). Reliability as internal consistency (Cronbach’s alpha) in the pilot phase was 0.954 for the before EMR questionnaire and 0.903 for the after questionnaire. In the final sample, the index’s Cronbach’s alpha value was 0.820 before the implementation of EMR systems and 0.700 after.

Statistical analysis

The statistical analysis of the results was performed using SPSS Version 28. The analysis included both descriptive and analytic statistics to explore the research hypotheses. This study has no missing data handling due to all items on the questionnaire being mandatory to answer. The statistical tests were chosen according to the variable distributions. Given the large sample size, parametric tests were used even for non-normally distributed measurements. Correlation between continuous variables was assessed using the Pearson correlation test. Associations between categorical and continuous variables were examined using Student’s paired-samples t-test. Multivariate regression analysis was conducted using the linear regression model for all three main dependent variables (medication errors, workload, and medical information availability). Analyses were performed in Enter mode following the negation of multi-collinearity. Only variables found to be associated with the dependent variables in the univariate analysis were introduced into the regression analyses. A p -value of 0.05 or lower was deemed statistically significant in all statistical analyses.

Sample description

In total, 622 nurses entered the questionnaire link, of which 31 (5%) indicated that they did not use pen-and-paper medical records and were subsequently excluded from the rest of the study. The final sample included 591 registered nurses working in government hospitals in Israel, of which 148 men (25%) and 443 women (75%). The average age was 33.92 years (SD 9.24 years), with a median age of 30.5. Most participants were employees at the ‘Sorasky’ Medical Center in Tel Aviv and “Hillel Yaffe” Hospital in Hadera (105 and 327, respectively). See Table  1 for additional socio-demographic breakdown.

Quantitative analysis

The findings show a significant difference in all assessed indices when comparing before the implementation of EMR systems and after, as follows. The perception of the number of medication errors after EMR systems implementation (M = 2.2, SD = 0.72) was reduced compared to before (M = 3.12, SD = 0.73) (t = 24.85, p  < 0.001). The workload after implementation of EMR systems (M = 2.77, SD = 0.92) was perceived as lower compared to before (M = 3.6, SD = 1.07) (t = 15.53, p  < 0.001). In total, this represents a  ∼  30% decrease in both medication errors and workload perception following the introduction of EMR systems. However, in contrast to our hypothesis, medical information availability after the implementation of EMR systems (M = 2.45, SD = 1.35) was lower compared to before (M = 2.6, SD = 0.74) (t = 2.44, p. 0.015). In total, this represents a  ∼  10% decrease in information availability following the introduction of EMR systems.

In order to examine the relationship between socio-demographic variables and the main variables, as a first step, a univariate analysis was performed to explore the association with attitudes after the implementation of the EMR. None of the Demographic variables were significant for workload and medication errors ( p  > 0.05), and all of them were significant for information availability ( p  < 0.001) (see Table  2 ).

For each of the primary dependent variables, a delta score was computed by subtracting the value before EMR systems implementation from the value after. The mean for the delta score of medication errors was − 0.92 (SD 0.90), -0.83 (SD 1.03) for workload, and − 0.14 (SD 0.39) for medical information availability. These delta scores were used for correlation analyses. The results here show that the delta score of workload was positively correlated with the delta score of medical information availability ( r  = 0.21, p  < 0.01) and medication errors ( r  = 0.36, p  < 0.01). In other words, a higher increase in workload was associated with more errors and higher availability of information, or vice versa. In addition, the delta score of medication errors was negatively associated with the delta score of medical information availability ( r =-0.37, p  < 0.01), meaning that fewer medication errors are reported with the increase in medical information availability.

Finally, multivariate linear regression was conducted for each of the three main dependent variables separately - medication errors, workload, and information availability. The analysis was performed to predict the dependent variables after implementation of EMR systems. See the complete results in Table  3 .

Qualitative analysis

In the qualitative section of the research, 82 participants answered three open questions (see methodology). The purpose of the questions was to understand how the nursing staff experienced using EMR systems and its effect on their work. It is important to note that there were contrasting reports in answers; for some participants, a certain feature was a disadvantage, but for other participants, it was an advantage. For example, while one participant claimed that EMR wastes a lot of time in her work, another claimed that it saves her a lot of time. It is also interesting to note that in response to the question about the EMR systems’ benefits, only a few participants reported a decrease in medication administration errors as a response. In the analysis, we categorized several themes that appeared repeatedly in the answers, as will be specified below.

Theme #1: additional workload that comes at the expense of patient care time

A large portion of participants (28 out of 82 who responded to the questions) claimed that the EMR systems require them to devote time to operate them at the expense of time for actual care for patients, such as giving support, communicating with the patient, and responding to their needs, especially when compared to the era of pen and paper prescriptions before EMR implementation. For example - “more information about the patients, less time for nursing care”; “It (EMR system) is excellent but leaves less time to treat the patient physically and emotionally”; “Filling out multiple indices and a lot of screen time that should have been used as a quality time with the patient bothers me.” In fact, some of the participants said that EMR systems add to their workload; for example -“Using information systems has added a lot of additional tasks to our work and at the same time, no personnel has been added; the same number of nurses remain on shifts, which makes me working under stressful conditions because you have to complete both the work in front of the computer and the work with the patient and the family.”

In this context, some participants also complained about the requirement to electronically document many details and indices about the patient that, in their opinion, have no medical meaning. Participants said that many unnecessary indices need to be entered into the system due to various administrative requirements and not for medical necessity.

Theme # 2: limitations and technical faults of the systems

Another kind of feedback was related to technical problems or slowness of the systems, for example - “Only the quality of the system and the equipment disturbs me; for example, the slow transition between windows”); Communication failures between systems, connection problems due to internet connection dependency, for example - “very interrupting when there is no Internet access”), and problems during a power outage or the collapse of the system - “Computing failures. System collapse. Power failures. Software failures. Too many versions”; “Everything is fine and lovely until there is a power outage; computer crashes; slow computer. It is just terrible. In the age of paper records, there was less writing and less information. But the basic important information was there. I do not recommend going back to paper, but there’s a need to take care of a good backup system with the necessary information that will come into action in the event of a malfunction”. Participants wrote about other computer malfunctions, such as bugs in the systems that cause them to get stuck and waste a lot of time as a result, for example - “Using Computers is excellent. But the Chameleon system has a lot of bugs and often gets stuck. Wastes a lot of time during the shift…”.

Theme # 3: the human factor as a source of problems in the operation of EMR systems

Finally, a theme related to the human factor emerged from participants’ feedback, namely the use of computerized systems by the medical and nursing staff. It was claimed that the physicians do not enter the medical instructions into the system in a straightforward manner or that necessary instructions are missing, or critical information about the patients is missing, for example - “… there are still lots of mistakes in writing instructions”; “sometimes the staff does not enter information properly, and sometimes critical information about the patients is missing.” Other nurses reported that their colleagues copy data from each other to save time filling them out, for example - “because it takes more time to fill out indices, many times poor indices are copied from nurse to nurse instead of filling out the correct data”). Others stated that older staff members have difficulty acquiring skills for using the EMR systems due lower digital literacy, for example - “You need full control in computer skills, which makes it difficult for older nurses to use them (EMR systems)”; “It is important to note that there are older employees who do not get along with the computer and it will be difficult for them to work and use the computer. This has a negative effect on the work of others in the department”).

The current study examined the effect of implementing EMR systems on the extent of errors in medication administration by qualified nursing staff and on other variables related to patient safety, namely the availability of medical information and the workload imposed on nursing staff. In line with the study hypotheses, we found that EMR systems reduce errors in the administration of medications and reduce workload. These findings correspond with the prevailing position in the literature on the effectiveness of EMR systems in reducing errors in prescriptions and medication administration [ 11 , 41 ]. It is important to emphasize that, unlike most studies on this topic, the extent of errors in the present study was measured based on an approximate perception of nursing staff and not as an exact quantitative measure. However, similar approaches in the literature are reported [ 42 ].

The findings suggest that workload decreased for the most part following the implementation of EMR systems. This decrease in workload can be explained by the fact that computerized systems save the need to physically run around to receive and transfer various materials such as laboratory tests, imaging, drug prescriptions, etc [ 43 ]... Nevertheless, the findings suggest that there is also a disadvantage. According to some participants’ reports, EMR systems require a lot of handling time, which comes at the expense of care for the patients and their families. This finding partially aligns with the findings of a meta-analysis performed by Moore et al. [ 44 ], which concluded that computerized medical systems increase the time nurses spent documenting medical records. Furthermore, in the same meta-analysis, it was found that even after the implementation of the EMR systems, there were nurses who preferred to continue documenting manually and viewing the older pen-and-paper method as faster and more accesible.

However, other studies included in Moore’s meta-analysis [ 44 ] claim that EMR systems contributed to the redistribution of nurses’ working time so that they devoted more time to direct patient care and communication with family members than dealing with medical records. These studies further claim that this resulted in greater satisfaction and a sense of meaning in their work. Arguably, the findings of the current study contradict this. It is possible that part of this discrepancy in findings can be explained by the type of system used since the type of EMR system has a decisive effect on the required documentation time [ 43 ]. Other studies also found, in line with the current study, that EMR systems harm the workflow of the team since they require multi-tasking, distract nurses from their primary work, and reduce the contact and interpersonal relationship with patients, negatively affecting the satisfaction of both the patients and the staff [ 45 ]. Another support for the findings of this current research is found in a study among doctors in the USA who claimed that one of the main reasons for burnout of doctors, which often results in leaving the job, is the need to spend too much time documenting information in EMR systems [ 46 ].

There may be a need to find ways to reduce the required documentation during a shift and document only vital medical information. This is important to avoid a situation where nurses devore extended periods of time during their shifts sitting in front of the computer instead of providing care and attention to patients and communicating with families. It should be noted that although the workload in this study is subjective and relies on the nursing staff’s report, it is, in fact, a preferred measurement for this topic [ 43 ].

In contrast to our hypothesis, medical information availability dropped after implementing EMR systems. These findings are slightly surprising as most studies on the subject found an improvement in the availability of medical information following EMR systems [ 32 ]. This finding may also highlight some of the backlash reported by nurses concerning the difficulty of managing the work with EMR systems during their shifts.

Alongside this, we found that other variables can explain part of the reduction in information availability. For example, nurses responding to our questionnaire who are working in the Intensive care and emergency departments reported significantly less information availability after the introduction of EMR systems. Arguably, in departments dealing with urgent or intense cases, there is a greater need for high-speed information transferring [ 43 ]. It may be critical if the EMR system is slow or gets stuck, as is sometimes the case with such systems and as reported by some of the nurses. Indeed, the literature accounts for technical deficiencies of systems, such as slowness, failures, systems crashes, communication problems, and difficulty integrating between the EMR system and others [ 32 ]. Moreover, the literature reports that EMR systems sometimes contain too many complicated and less vital functions [ 32 ]. It may be necessary to tailor the computerized information systems specifically to these departments so that they offer a “lean” or easier interface that will allow for faster extraction of vital medical information. It is also a good idea to make sure that there is sufficient backing to operate the systems for cases of communication or electricity faults so that crucial information remains available in these situations as well.

The decrease in information availability after EMR implementation can also be explained by insufficient training for staff to use those systems properly. As reported by participants in the qualitative section of the study, departments have elderly staff memebers who have difficulty operating and controlling computerized systems. Similar findings were also found in previous studies [ 32 ]. The findings of the present study are in line with the accumulated findings that indicate a fundamental need to think and redesign some of the EMR systems from the perspective of the end users, as well as to provide appropriate training and support for using them.

Limitations and future directions

This study has several limitations. First, the sampling method in the current study was not probabilistic and was based on convenience and the snowball method exposed the sample to selection bias and may not fully represent the population. Second, the dependent variables were measured subjectively, i.e., as an experience or impression of the study participants. Such tools are naturally exposed to biases since the impressions of the respondents do not necessarily accurately reflect the objective reality in the hospitals. Memory bias should be considered for reports concerning the time before EMR systems implementation. In addition, there may be reporting bias due to the unwillingness to report the actual occurrence of medical errors.

Third, this study measured only three variables. Although these are three main variables in understanding the phenomenon being investigated, it must be assumed that additional variables are required to obtain a broader and more detailed picture of the computerized systems in a hospital. It is useful to specifically and directly examine variables such as the quality and accuracy of medical information [ 32 ] or the time of documentation of medical information [ 47 ]. It is also possible to distinguish between different types of medication errors and examine each of them individually, for example, errors in identifying the patient, dosage, or how the medication is administered.

Conclusions

This study provides mixed results regarding the research hypotheses. The findings support the hypotheses stating that Electronic Medical Records (EMRs) are perceived by Israeli nurses to reduce medical errors and workload, compared to the older pen-and-paper approach. However, the findings do not support the third hypothesis since the findings show that EMRs were perceived to decrease information availability compared to the pen-and-paper era.

The findings in this study show the great benefits of using EMR systems in hospitals in Israel, as well as the difficulties and challenges associated with them. To the best of our knowledge, no systematic research has yet been done on this subject in the State of Israel, and therefore, the findings of the current study are highly important for decision-makers.

The findings show that the implementation of EMR systems in Israel contributes to reducing errors in the administration of medications by qualified nursing staff from the point of view and the direct experience of the nursing staff themselves. This means that these systems contribute to saving lives, and therefore, their importance for hospitals is tremendous. In addition, according to nurses, the systems reduce the workload imposed on the staff. However, the findings present difficulties on two levels. The first is the need for multi-tasking, which harms nurses’ work. This difficulty is manifested in the fact that too much time is required to document medical information in computerized systems, which comes at the expense of time directly caring for patients and their families. This situation may harm the nurses’ morale and may cause burnout at work. The second level is the complexity and slowness of the systems, which may reduce the availability of medical information when it is necessary to retrieve quickly, which is especially problematic in departments of surgery, intensive care, and emergency medicine, where a lot of medical information is needed urgently and immediately.

The findings raise a need for rethinking and redesigning these systems while thinking about the end users, as well as a need for dedicated training for their use by end-users of different digital literacy backgrounds. Future research can focus on developing methods for assimilating knowledge and skills to use computerized systems in a way that considers age and digital literacy and evaluates their effectiveness. In addition, future research will be able to examine the effectiveness of changes and improvements in the computerized systems, particularly the development of “lean” versions of the interfaces for departments where quick information retrieval is required.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Abbreviations

UCE-Q-Carrington-Gephart Unintended Consequences of Electronic Health Record Questionnaire

Electronic Health Record

Electronic Medical Record

Expanding Nursing Stress Scale

PS-Electronic (medication) Prescription Systems

Health Management Organization

World Health Organization

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Acknowledgements

The authors wish to thank Hillel Yafe Medical Center for their support in access to respondents. In addition, we thank the Sourasky Medical Center for its support in recruiting a large number of nurses as respondents. This work was done in the context of a Master of Public Health thesis of the first author under the supervision of the last author.

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RN designed the study, collected the data, analyzed the data, interpreted the results, and wrote the draft of the manuscript. MB supervised the process, approved the methodological approach, critically reviewed the draft, and approved it. All authors read and approved the final manuscript.

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This study was approved by the ethical committee of Tel-Aviv University (approval No. 0003647-1, from 29 July, 2021). All participants completed an informed consent prior to providing their response. All responses were retained anonymously.

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Moran Bodas is a Senior Lecturer at the Department of Emergency & Disaster Management, School of Public Health, Faculty of Medicine, Tel-Aviv University. He is the former director of the National Center for Trauma & Emergency Medicine Research at the Gertner Institute. Raneen Naamneh is a registered nurse who successfully graduated from the School of Public Health after completing her thesis reported in this paper.

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Naamneh, R., Bodas, M. The effect of electronic medical records on medication errors, workload, and medical information availability among qualified nurses in Israel– a cross sectional study. BMC Nurs 23 , 270 (2024). https://doi.org/10.1186/s12912-024-01936-7

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DOI : https://doi.org/10.1186/s12912-024-01936-7

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