• International Journal of Technology (IJTech)
  • Vol 11, No 1 (2020)

Human Factor Analysis and Classification System (HFACS) in the Evaluation of Outpatient Medication Errors

Ari Widyanti, Assyifa Reyhannisa

Corresponding email: widyanti@mail.ti.itb.ac.id


Cite this article as:
Widyanti, A., Reyhannisa, A., 2020. Human Factor Analysis and Classification System (HFACS) in the Evaluation of Outpatient Medication Errors. International Journal of Technology. Volume 11(1), pp. 167-179

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Ari Widyanti Laboratory for Work System Design and Ergonomics, Department of Industrial Engineering, Bandung Institute of Technology (ITB), Ganesa 10, Bandung 40132, Indonesia
Assyifa Reyhannisa Laboratory for Work System Design and Ergonomics, Department of Industrial Engineering, Bandung Institute of Technology (ITB), Ganesa 10, Bandung 40132, Indonesia
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Abstract
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Medication errors happen frequently, meaning there is an urgent need for a systematic analysis tool to minimize their occurrence. The aim of this study is to implement the Human Factor Analysis and Classification System (HFACS), a tool used in human error identification, in the case of outpatient medication errors. Nine such cases that occurred in a pharmacy unit of an Indonesian hospital were evaluated by 40 participants, consisting of the Head of the Pharmacy Department, the heads of units under this department, pharmacists, and staff of the Patient Safety Unit. An HFACS questionnaire developed by the United States Department of Defense was adopted in an Indonesian context. Each participant was asked to evaluate four or five cases of medication errors based on items in the questionnaire. The results show that the causes of such errors mainly lie in the layers of unsafe acts (performance-based error), precondition of acts (mental awareness), and organizational influence (an organizational instruction or policy which creates an unsafe situation). Breaking down the HFACS into its sublayers, the most prevalent causes of medication error found in this study were information overload and fatigue, although the level of agreement among the participants when giving HFACS ratings was low. The paper concludes by discussing the implications of the results.

HFACS; Medication error; Outpatient; Percentage of agreement

Introduction

To err is human (Kohn et al., 2000); however, when errors are related to human life their negative consequences are crucial, which is particularly relevant in the case of errors occurring in hospitals. Research emphasis has been on errors in hospitals involving doctors, nurses and other hospital or healthcare system workers in relatation to patient safety, defined as “the prevention of harm to patients” (Institute of Medicine/IOM, in Aspden et al., 2004). Patient safety terms include error prevention; learning from errors that do occur; and a safety culture that involves health care professionals, organizations and patients.  There are various types of error in the healthcare system. These can be classified according to where they occurred, incident reports, the individuals involved in the error, and system causes. One common error is related to medication, which is usually referred to as medication error (AHRQ, 2007), which is 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 healthcare professional, patient or consumer. Such events may be related to professional practice, healthcare products, procedures and systems, including prescribing; order communication; product labeling, packaging and nomenclature; compounding; dispensing; distribution; administration; education; monitoring and use” (NCCMERP, 1998).

Medication error can occur in all medication processes, including prescriptions, transcriptions, preparation, dispensation and administration (Hussain and Kao, 2005). Most occur during the administration stage, followed by the prescription, preparation and transcription stages. Prescription errors refer to failures in the prescription writing process that result in wrong instructions regarding the identity of the recipient, the identity of the drug, or the formulation, dose, timing or frequency. Transcription errors are related to handwriting, abbreviation use, and unit misinterpretation, while preparation errors occur when there is a difference between the ordered amount or concentration of a medication and what is actually prepared and administered. Dispensation errors refer to those made during the transfer of a prescription drug to a patient or an intermediary who is responsible for the administration of the drug. Finally, administration errors are related to errors in system checks, as most medications are administered by a single nurse.

Medication errors have endangered the health of millions of people and cost billions $ US in extra medical costs around the world. Furthermore, Hussain and Kao (2005) state that medication errors are important causes of patient morbidity and mortality. Finally, the psychological effect of medication errors on patients should also be emphasized. For all of these reasons, medication errors have been gaining the attention of researchers and efforts are being made to observe the causes and find ways to prevent them.

Most research has employed a survey method; for example, a questionnaire that is completed by nurses and pharmacists to observe the causes of medication errors. Exploratory studies have resulted in various causes of medication errors. The Agency for Healthcare Research and Quality (AHRQ, 2007) identified 246 medication errors reported in the United States related to human factors. These factors regard how humans interact with their environment, including tools, tasks and other people, which ultimately influences human performance. In addition, Gorgich et al. (2016) explain that human factors are not the only cause of medication errors; working and environmental conditions, as well as organizational factors, play important roles in determining them. In short, medication errors are multidimensional problems, and in solving them systematic approaches and methods are needed (Gorgich et al., 2016).

Errors and accidents in various environments and fields have been understood as a complex sociotechnical system (Salmon et al., 2012). Salmon et al. reviewed the three accident causation models predominantly used in analyzing errors and accidents, namely the risk management framework, the System-Theoretic Accident Modelling and Process Model (STAMP), and the Swiss cheese model.

The most frequently used model is the Swiss cheese model (Reason, 1990), which was developed into the Human Factor Analysis and Classification System (HFACS; see Shappell and Wiegmann, 2000), which describes the taxonomies of latent failure and unsafe acts. HFACS is a tool for understanding and mitigating human error in various applied settings. Although it starts with “human factors”, in fact other related factors are considered in the model, as can be seen in Figure 1.

HFACS has several taxonomic categories to represent layers in the system in which errors can occur. In addition, it has the advantage of being able to link failures across the four taxonomic levels (Salmon et al., 2012). Originally, HFACS was designed to investigate errors within aviation contexts. However, with some revisions and adaptations, it has been widely used in different work conditions, such as in operating theaters and medical settings (see Hughes et al., 2013 for an example). HFACS has also demonstrated acceptable levels of inter-rater reliability in some studies (e.g., Li et al., 2008), although it has also shown low levels of reliability in others (Olsen, 2011)

In Indonesia, medication errors also occur frequently. Although there have been no official reports from the Indonesian Ministry of Health, such errors have been reported by several researchers in various areas and cities. For example, Purba et al. (2007) identified medication errors in several hospitals in Jakarta, Bandung, Yogyakarta and Surabaya, with most being missing patient information and wrong prescription. Coupled with the fact that the growth of medicine use in Indonesia is relatively high (i.e., 12%-13% per year), the question of medication errors should be given utmost attention.

The aim of this study is to implement HFACS, one form of sociotechnical analysis tool, in analyzing medication errors in hospital pharmacies, in particular involving outpatients in one sample Indonesian hospital. Considering that research related to medication error is limited, and the fact that HFACS has been successfully implemented in other areas of patient safety, such as identification error in surgery (Cohen et al., 2018) and in helicopter emergency medical services (Cline, 2018), it is hypothesized that HFACS can be implemented to reduce medication error. The results of the study will be valuable in providing information about the causes of medication error for hospital outpatients.


Figure 1 HFACS Classification and Taxonomies (Dod, 2017)


Conclusion

In conclusion, this study provides originality in terms of the use of HFACS to analyze medication errors. To the best of knowledge of the authors, no previous studies have employed HFACS to analyze medication errors involving outpatients, apart from a study conducted by Hughes (2013), who proposed the use of the HFACS to analyze medication errors in emergency medical services. In practice, the study has suggested meaningful improvements for the hospital pharmacy department to minimize medication errors. As Malhotra et al. (2012) state, “Medicines cure, but they can also kill or cause severe adverse reactions if a wrong medicine is administered or if the dosage is wrong. Many disasters have occurred due to the medication errors”. Therefore, any effort to reduce medication errors is valuable and should be undertaken urgently.

In the study, the main causes of medication error found are information overload and fatigue. To overcome the first of these, suggestions made include using computerized systems to reduce errors in reading the handwriting of the doctors and in drug labeling. To minimize fatigue, rearrangement of shift hours as well as rest time is suggested.

Acknowledgement

        The authors thank the Indonesian Ministry of Research, Technology and Higher Education (RISTEKDIKTI) for funding this research under the PTUPT scheme, fiscal years 2018-2019.

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