Canadian Journal of Nursing Informatics

Factors Affecting the Impact of Barcode Medication Administration Technology in Reducing Medication Administration Errors by Nurses

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by

Deborah Baiden, RGN, BSc

MSc Student, Western University

 deborahbaiden@yahoo.co.uk

Abstract

Barcode medication administration technology (BCMA) was introduced to facilitate medication administration by health professionals, especially nurses. This paper reviewed and assessed the body of literature on the factors affecting the impact of barcode medication administration technology in reducing medication errors by nurses in hospital settings. The socio-technical model by Sittig and Singh (2010) was used as a conceptual framework in the paper. The impact of BCMA in reducing medication administration errors vary based on several factors including clinical setting, technology related setbacks and nurse related problems. Factors contributing to this variation can be linked to six of the eight components of the socio-technical model proposed by Sittig and Singh in 2010. Further research such as qualitative and theory-based studies need to be carried out since there was a paucity of literature in that regard. Nurse leaders should endeavour to be involved in and committed to the implementation of BCMA and other health information technologies at their workplace to improve patient care.

Keywords: barcode medication technology, medication errors, nurses, socio-technical model

Barcode Medication Administration Technology

Introduction

Medication administration errors are a life-threatening concern of public health interest (Wideman, Whittler & Anderson, 2005). Medication refers to “any ordered drug (except oxygen) and intravenous ?uid by any route” (Rodriguez-Gonzalez et al., 2012, p. 73).  Any unintended but avoidable incident that may result in medication misuse, threatens patient safety, and causes unpleasant and serious effects while medication is administered by a patient or health professional is defined as a medication administration error (Shah, Lo, Babich, Tsao & Bansback, 2016). In Canada, the Institute for Safe Medication Practices Canada (ISMP) is responsible for “the collection and analysis of reports of medication errors and the development of recommendations, education, and tools for the enhancement of patient safety” (Wichman, 2005, p.27).

According to Shah et al. (2016), consequences of wrong medication administration cost the Canadian health care system about $6,655 per case. In a study carried out by the John Hopkins University School of Medicine (2016), medical errors are the third major cause of death in the United States of America; Canada’s neighbour to the south, killing over 250,000 people annually.  In March 2017, the World Health Organization (WHO) initiated a global campaign to promote patient safety by reducing medication errors by fifty percent by the year 2022 (WHO, 2017).

Threats to patient safety are of global significance to the nursing profession. Though registered nurses worldwide do not prescribe medications, they are key players in administering medications to patients and in educating them on how to take these medications independently.  In Iran, Cheragi, Manoocheri, Mohammadnejad and Ehsani (2013) revealed in their cross-sectional study on nurses that almost 65% of participants admitted making medication errors and that there was no correlation between the errors made and a nurse’s clinical experience.

Barcode medication administration (BCMA) systems are health information technologies that have been credited for preventing medication errors in health care when used accurately (Shah et al., 2016; Sutherland, 2013). Consistent with other health information technologies, the BCMA technology promotes patient safety by ensuring that patients are accurately identified. Salyer (2014, p.16) emphasizes that “patient identification is the fundamental [bedrock] of patient safety”. A nurse using the BCMA technology scans the patient’s identification band and the barcode of the prescribed medication using a scanning device, the information is then simultaneously cross-checked with the patient’s electronic medication records for accuracy using electromagnetic waves (Sutherland, 2013). This technology electronically validates the process of administering medication by ensuring the “right patient, right dose, right drug, right time, [and] right route—at the patient’s bedside” (Shah et al., 2016, p.394). On the other hand, the traditional medication administration refers to the paper-based method of administering medication whereby the nurse cross-checks the 5 rights of medication administration using the doctor’s orders, the medication and the patient’s chart.

The purpose of this paper is to review and assess the literature on factors affecting the impact of barcode medication administration technology in reducing medication errors by nurses in hospital settings. The use of technology in hospital settings in low and middle-income countries (LMIC) is a solution for advancing their healthcare systems (Burney, Mahmood & Abbas, 2010). There is the need to conduct an integrated review of literature to assess the evidence of factors affecting the impact of the BCMA technology to inform stakeholders in the health sector on implementation programs in LMIC, direct new research, and enhance nursing practice in promoting patient safety.

Conceptual framework

The question of how the capability of BCMA technology in reducing medication administration errors is affected by certain factors is guided by the socio-technical conceptual model (Sittig & Singh, 2010). The authors outlined eight components in the model that frame the understanding and assessment of influences on the successful implementation of a health information technology such as BCMA. These eight components are non-hierarchical though interconnected and affect each care unit distinctively and include “hardware and software computing infrastructure, clinical content, human computer interface, people, workflow and communication, internal organizational policies, procedures and culture, external rules, regulations and pressures, and [finally], system measurement and monitoring” (Sittig & Singh, 2010, p.i4-i6).

Methodology

The following electronic scientific databases were searched extensively for literature: PubMed, ProQuest, CINAHL, and Scopus. Keywords used were combinations of: medication error(s), patient safety, barcode medication administration (BCMA), medication administration, and nurse. Some of the keywords were changed to suit the formats of the various databases searched. Boolean operators such as AND, NOT and OR were used to organize search terms. Studies published in English language that had been peer reviewed were included in the review. This review was limited to include the year range of 2007 to 2017 to analyze current and relevant literature on this topic. Furthermore, the review included studies that were based on nurses using the BCMA technology in hospital settings, excluding those in nursing homes and long-term care settings.

Articles published in a language other than English, those that did not have about 50% of nurses as participants and those using secondary data sources were excluded from the review. Reference lists within selected literature review articles were also searched for potential studies that could be included in this study. The abstracts of articles were initially read and those that met the inclusion criteria were included followed by an in-depth reading. A total of 347 studies were derived from the search, with a final 24 selected for analysis in this review. These studies were selected for analysis because they are appropriate to factors affecting the impact of the use of BCMA technology by nurses in preventing medication errors. Emerging themes from the body of literature were grouped into: nurse contentment, hospital or nursing unit related and technological factors.

Findings

Nurse contentment

Fowler, Sohler and Zarillo (2009) reported that within six months of the introduction of BCMA technology in a trauma centre, the nurses’ contentment was relatively high compared to the use of non-BCMA administration. This is because the nurses perceived that the BCMA technology made it easier to prevent medication errors thus promoted patient safety. However, there was concern from nurses that only four of the five rights of medication administration were met by the BCMA technology, neglecting the right time of administration.

Additionally, Gooder (2011) disclosed that nurses sampled in an acute care setting expressed discontent after the BCMA technology was introduced into their facility. The key factor attributed to this was the nurses’ negative attitudes towards the use of the technology, which hindered its potential to reduce medication errors and simplify work processes.

Hospital or nursing unit related factors

Incidences of medication administration errors were reduced by 54% when BCMA technology was implemented in two cardiac telemetry units and a medical-surgical unit (Paoletti et al., 2007). Hassink, Duisenberg-van Essenberg, Roukema and van den Bemt (2013) also observed a 50% drop in medication administration errors post-BCMA in a surgical unit. Correspondingly, DeYoung, Vanderkooi and Barletta (2009) pointed out there was a 56% decrease in medication errors classified as wrong time administration, with the use of BCMA in an adult medical intensive care unit. Further, BCMA averted almost 67% of medication administration errors in a critical access hospital (Cochran, Barrett & Horn, 2016). Factors recognized by DeYoung, Vanderkooi and Barletta (2009) as facilitators to the reduction in medication administration errors with the use of BCMA technology included “routine quality assurance” (p.1114) and the use of other health information technologies in addition to the BCMA technology. On that account, organizational and nursing unit related factors could impact the effectiveness of the BCMA technology in lowering medication errors in clinical practice.

However, differences exist in the effect of BCMA technology on medication administration errors between care units (Helmons, Wargel & Daniels, 2009; Seibert, Maddox, Flynn & Williams, 2014). Medication error rates were 58% lower on medical-surgical units compared to intensive care units if observations of wrong time medication administration were excluded. In other words, the use of BCMA technology did not affect wrong time medication administration in both nursing units. The variations among care units and hospitals might be attributed to differences in bed capacity, patient condition, access to pharmacy staff, and availability of BCMA technology at the patient bedside (Cochran, Barrett & Horn, 2016; Cochran & Haynatzki, 2013; Seibert et al, 2014). This means that nursing units or hospitals with smaller bed capacities could record a comparatively higher impact of the BCMA technology. In the same vein, care facilities with patients suffering from diseases requiring complex medications or patients with shorter lengths of stay could record a relatively lower impact of BCMA. This is consistent with findings from Helmons et al. (2009) which showed that the dissimilarity between the classifications of medications used in the intensive care units and the medical-surgical units could account for differences in the impact of the BCMA technology on medication errors in these care units.

Furthermore, the types of medication error significantly reduced by the BCMA technology varied across health care facilities. Notably, emergency room nurses were observed to administer the correct drug dosage with efficacy using BCMA (Bonkowski et al., 2013). Hence, the error of wrong drug dosage administration was most positively impacted by the use of the BCMA technology. Bonkowski et al. (2013) disclosed that BCMA was effective in preventing errors associated with medication administration by almost 81% among nurses in the emergency unit. Also, Helmons et al. (2009) uncovered that BCMA technology improved the right documentation rates among nurses in intensive care units compared to medical-surgical units.

Poon et al. (2010) conducted a study in a teaching hospital and identified a reduction in the rates of  giving incorrect medication by about 57%, inaccurate dosage by almost 42% and omitting or wrongly charting medication given by 80.3%, following the introduction of BCMA technology. Notwithstanding, errors in medication administration were markedly lowered in surgical and intensive care units compared to medical units. In spite of this, the BCMA technology was generally effective in the hospital. The authors surmised that hospital- related factors such as effective consultation between staff nurses and clinical administrators, consensus to use the technology, thorough education on how to use the technology, and the availability of resources enhanced smooth adoption and usage of BCMA technology (Poon et al., 2010). It is important to note that in a few studies, findings revealed either no change in the rates of medication errors, an increase in rates, or a decrease that is clinically considered to be inconsequential to patient safety (Bowers et al., 2015; FitzHenry et al., 2011; Sakowski, Newman & Dozier, 2008).

Technological factors

A neonatal intensive care unit documented a 47% reduction in unfavourable outcomes from medication errors following the use of BCMA technology (Morriss et al., 2009). However, Morriss et al. (2009) disclosed that wrong time administration was increased following the use of the technology due to alerts received from the system. Comparatively, FitzHenry et al. (2011) emphasized that no more than 99 out of the 18,393 warfarin doses administered to patients in a US teaching hospital, were medication errors of clinical importance that threatened patient safety when BCMA technology was used. This indicates a reduction in medication errors with the use of the BCMA technology. However, incidences of erroneous alerts of medication errors are recorded by the technology, which are mostly associated with wrong time medication errors (FitzHenry et al., 2011). This made nurses concentrate their time and effort to resolve these erroneous alerts and place more emphasis on administering medications at the right time at the expense of other nursing procedures. According to FitzHenry et al. (2011), the high incidences of erroneous alerts contributed to a “risk for alert fatigue” (p. 440) which could further hinder patient safety and care.

On the other hand, Miller, Fortier and Garrison (2011) showed that alert signals from the BCMA technology helped prevent medication errors by drawing the attention of nurses to potential errors with high-risk medications. Nevertheless, studies uncovered cases in which nurses use the BCMA technology incorrectly by either missing steps in the procedure, carrying out unapproved steps or carrying out steps in an incorrect sequence(Koppel, Wetterneck, Telles & Karsh, 2008; Miller et al, 2011).

BCMA was perceived by nurses to reduce time spent in carrying out medication related procedures since it made it easier to validate the five rights of medication administration thereby expediting nursing workflow (Dwibedi et al., 2011; Huang & Lee, 2011; Tsai, Sun & Taur, 2010). Additionally, nurses observed that BCMA enhanced patient well-being, improved quality of care and augmented nursing care (Tsai et al, 2010). It is important to note that nurses reported that unstable wireless connections were a major barrier in ensuring efficient running of the technology (Huang & Lee, 2011; Tsai et al, 2010; Yen et al., 2015). Hence, a simple technological factor such as a wireless connection can influence the capability of BCMA to decrease medication administration errors.

Findings also revealed that nurses tend to develop tactics to overcome challenges faced while using BCMA technology (Bowers et al., 2015; Hardmeier, Tsourounis, Moore, Abbott & Guglielmo, 2014; Holden et al., 2013; Koppel et al, 2008; Miller et al, 2011). These challenges included omitted or illegible barcodes, power unpredictability, scanning defects, and interrupted wireless connection (Huang & Lee, 2011; Koppel et al, 2008; Snyder, Carter, Jenkins & Fantz, 2010; Tsai et al, 2010; Yen et al., 2015). Given these circumstances, patient safety could possibly be threatened instead of being protected. For instance, Snyder et al. (2010) uncovered cases of incorrect patient validation, where defects in barcodes wrongly identified patients which could be life-threatening.

Discussion

Barcode medication administration technology reduces medication administration errors by 50 to 70 per cent (Cochran et al., 2016; DeYoung et al., 2009; Hassink et al., 2013; Helmons et al., 2009; Paoletti et al., 2007). There are some discrepancies as Bonkowski et al. (2013) uncovered that as high as 81% of medication administration errors were prevented post-BCMA. Additionally, few studies noted that BCMA may actually increase error rates, or have no significant impact on error rates (Bowers et al., 2015; FitzHenry et al., 2011; Sakowski et al., 2008). There are several factors contributing to this, which warrant discussion.

The reviewed studies employed various research methods with quite a number using direct observation. In a study to assess how observation influences the rate of medication errors in NICU, Campino, Lopez-Herrera, Lopez-de-Heredia, and Valls-i-Soler (2008) indicated that errors are meaningfully reduced when medication procedures are observed. This could be linked to the Hawthorne effect in which participants who know that they are being observed act differently than they normally would (Fernald et al., 2012). To improve reliability and validity of findings, observers were trained for a minimum of two hours in all the observational studies reviewed in this paper. Also, some studies employed a technique where the observer was new to the medication administration procedure, but was familiar with patient safety concepts. Thus, pharmacy and nursing students were trained and recruited as observers using this technique. The limitation of this technique is that, certain errors may be missed because of inexperience. However, Cheragi et al., (2013) contended that clinical experience has no bearing on medication administration errors.

According to Fernald et al. (2012), it is essential to eliminate bias from participants to improve research quality. Meanwhile, none of the observational studies discussed how the Hawthorne effect on participants was dealt with. This could affect findings as nurses who are aware that they are being observed may use BCMA technology correctly as much as possible, to eliminate errors. However, had this been the case, results would have recorded almost 100% reduction in medication errors. Anglemyer, Horvath and Bero (2014) on the contrary, stated that observation does not significantly affect the findings in all observational studies. This shows that although observation could affect research findings, it does not apply to every case. Also, Kelly et al. (2016) deduced that compared to surveys and interviews, observation is the preferred method to unveil threats to patient safety associated with the use of BCMA. This may be because observation provides an in-depth description of a phenomenon.

Only one researcher applied a theoretical framework when conducting a case-control study. Gooder (2011) used the diffusion of innovation theory by Rogers (2003, as cited in Gooder, 2011). According to the author, the time frame within which this research was conducted may have affected findings as data collection ended five months after BCMA implementation (Gooder, 2011). This is because, some of the concepts in the theory was not relatable to the findings, and may have been different had the research been conducted at a later period after BCMA implementation. Thus, there is a gap in the application of theory to nursing research to support BCMA implementation and impact which needs to be addressed. Furthermore, nursing educators should consider equipping students with skills in selecting theories or concepts that fit the research topic.

Findings from the literature did reveal some socio-technical factors that affected the capability of BCMA technology to prevent medication administration errors. This supports the socio-technical model for assessing health information technologies as proposed by Sittig and Singh (2010).

There are variations between hospitals or nursing units on the impact of BCMA in reducing medication administration errors (Helmons et al.,2009; Seibert et al., 2014) and the type of medication administration error reduced (Bonkowski et al., 2013; Helmons et al., 2009; Poon et al., 2010). Evidence mined from the review to potentially contribute to this disparity is largely linked to components of the socio-technical model as follows:

  1. Hardware/Software infrastructure: Stability of wireless connection and power supply, scanning defects, and omitted or ineligible barcodes (Huang & Lee, 2011; Koppel et al., 2008; Snyder et al., 2010; Tsai et al., 2010; Yen et al., 2015).

  2. Clinical content: Heterogeneity in patient condition, bed capacity, and classification of medications used (Cochran et al., 2016; Cochran & Haynatzki, 2013; Helmons et al., 2009; Seibert et al., 2014).

  3. Human-computer interface: Nurses overriding alert signals and creating tactics to get over challenges faced while using the BCMA technology (Bowers et al., 2015; Hardmeier et al., 2014; Holden et al., 2013; Koppel et al., 2008; Miller et al., 2011).

  4. Personnel: Attitudes towards the use of BCMA, consensus to use BCMA, and education (Fowler et al., 2009; Gooder, 2011; Poon et al., 2010).

  5. Workflow and communication: Partnership with pharmacy staff and effective consultation between staff nurses and clinical administrators (Cochran et al., 2016; Cochran & Haynatzki, 2013; Poon et al., 2010).

  6. System monitoring: Periodic standard evaluation of BCMA (DeYoung et al., 2009).

Components of the socio-technical model that were not identified in the review are organizational policies and external regulations. It is important to note that some barriers to the successful implementation of BCMA technology can possibly be overcome if organizational or hospital policies and external regulations are in place for guidance. For instance, evidence-based policies and regulations can guide nurses in navigating human-computer interface challenges. This can significantly promote patient safety and deter nurses from developing tactics that could potentially cause medication administration errors, thereby putting patient lives at risk.

On the other hand, this could mean that nurses are developing problem-solving skills to tackle BCMA-related challenges. It also demonstrates that, there may be inadequate evidence-based policies and regulations in this regard or there is insufficient evidence on how BCMA technology is impacted by them.

Before the implementation of BCMA technology or any other health information technology into a healthcare facility, there should be proper planning and extensive consultations. For example, issues such as interrupted power supply and unstable wireless connection (Huang & Lee, 2011; Tsai et al., 2010; Yen et al., 2015) could have been dealt with had it been factored into prior planning. The socioeconomic context into which the technology would be introduced should be considered in planning as well. This is because; studies which revealed issues with power supply and wireless connection were from middle-income countries and should have been anticipated. Power generators and accompanying costs such as fuel and maintenance should be budgeted for, to ensure the successful implementation of BCMA in developing countries. Also, a contingency plan should be devised based on best-practice evidence, to guide nurses in safely administering medications despite unstable wireless connections. It is recommended that a manual contingency plan be activated for “[a] shutdown of longer than 3 hours” (Institute for Safe Medication Practices (ISMP Canada), 2013, p.144).

Extensive collaboration should be carried out with the inclusion of staff nurses, before the implementation of BCMA technology. Some of the selected study findings suggested that nurses were discontent following the use of BCMA technology (Fowler et al., 2009; Gooder, 2011). This attitude can affect nurse productivity and quality of care. It is important to note that staff nurses are directly involved in patient care, and consequently, must be actively involved in the implementation of initiatives centred on patient safety. This can prevent negative attitudes towards the use of technology in patient care. Ideally, a BCMA implementation group should be made up of “leaders from pharmacy and nursing practices, a physician, an administrative representative, and front?line representation from pharmacy and selected patient care areas” (ISMP Canada, 2013, p.137) with support from the Information Technology (IT) department. Though staff nurses are not specifically mentioned, they are part of the “front-line representation from [….] selected patient care areas” (ISMP Canada, 2013, p.137). Additionally, workshops could be organized to continually train nurses on how to use the technology in order to eliminate discontent due to knowledge and skill deficits. Also, regular monitoring could be carried out to include BCMA-related complaints and suggestions from nurses to capture potential sources of dissatisfaction.

Recommendations

Though studies included in this review used various research methods, there were few qualitative or theory-based studies. This suggests a gap in evidence derived from these methods. Further research needs to be conducted using these methods in order to strengthen the quality of evidence. Furthermore, researchers may need to identify measures to help care units or organizations create an organizational culture that supports the BCMA technology in order to maximize impact.

Nurse leaders should be involved in implementing BCMA and other health information technologies to ensure that nursing perspectives are represented and to develop strategies that eliminate nursing workarounds to meet challenges in the human-computer interface. Medication errors related to wrong time administration were the least affected by BCMA technology; therefore nurses should consider following the right medication administration procedure at all times. Nursing organizations could also formulate evidence-based best practices guidelines to regulate barcode medication administration procedures by nurses. Prior to the implementation of BCMA technology, staff nurses should be involved in an interdisciplinary collaboration. Additionally, in-depth planning should be carried out, paying attention to anticipated challenges that may arise and possible workarounds. A contingency plan must be designed to make up for system failures that is communicated to all healthcare professionals involved in medication transcription and administration. Periodic monitoring of BCMA should also be carried out for quality assurance and to strengthen the impact of BCMA.

Last but not the least, training workshops should be carried out to deal with issues of nurse dissatisfaction that may arise from BCMA knowledge or skill deficits.

Conclusion

Findings from this review indicate variations in the impact of BCMA technology in reducing medication administration errors in different clinical settings. Factors contributing to this variation can be linked to six of the eight components of the socio-technical model proposed by Sittig and Singh (2010). This study uncovered the gap in evidence on how the other two components; organizational policies and external regulations affect the role of BCMA in reducing medication administration errors. Nursing researchers are encouraged to employ various research methods including appropriate theoretical frameworks and qualitative research methods to address this gap. Furthermore, system design through proper planning and interdisciplinary collaboration are prerequisites to ensuring successful implementation of BCMA technology.

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AUTHOR BIO

Deborah Baiden is currently a 2nd year MSc. Nursing student at the Western University in London, Ontario. She has a BSc Nursing degree from the University of Ghana in Legon, Ghana (her home country) where she graduated with a First-Class Honors in 2015. She is a Registered General Nurse with the Nursing and Midwifery Council of Ghana, West Africa.  This paper was written as a term paper for the Health informatics class she took in Summer 2017.

 

 

 

 

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