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Human factor analysis and classification system (HFACS) in the evaluation of outpatient medication errors
Widyanti A.a, Reyhannisa A.a
a Laboratory for Work System Design and Ergonomics, Department of Industrial Engineering, Bandung Institute of Technology (ITB), Bandung, 40132, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© Faculty of Engineering, Universitas Indonesia.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.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]HFACS,Medication error,Outpatient,Percentage of agreement[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.14716/ijtech.v11i1.2278[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]