A conceptual review of human factors frameworks in nursing and patient safety

Ioannis Kouroutzis; Christina Ekavi Vlachou; Pavlos Sarafis; Maria Malliarou; Ioannis Kouroutzis; Christina Ekavi Vlachou; Pavlos Sarafis; Maria Malliarou

doi:10.3934/publichealth.2026055

AIMS Public Health

2026, Volume 13, Issue 4: 1069-1086. doi: 10.3934/publichealth.2026055

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Review

A conceptual review of human factors frameworks in nursing and patient safety

1.
Healthcare Innovation Laboratory, Department of Nursing, University of Thessaly, Greece
2.
Department of Learning, Informatics, Management and Ethics (LIME), Karolinska Institutet, Stockholm, Sweden

Received: 14 March 2026 Revised: 08 July 2026 Accepted: 15 July 2026 Published: 20 October 2026

Purpose
Within the multidisciplinary area of human factors, a variety of frameworks have been proposed and/or applied in patient safety research to analyze risks and guide improvements, each offering a different perspective on system performance. Within the healthcare environment, nursing is one of the most distinct areas that can drive and deliver results in the patient safety arena. This study provides a conceptual review of human factors and ergonomics (HFE) frameworks used in patient safety research.
Design/methodology/approach
A structured literature mapping process identified empirical studies applying named HFE frameworks. This review identified 37 studies that applied HFE frameworks to nursing-related patient safety contexts including workflow analyses, adverse-event investigations, infection prevention, technology-related safety risks, and clinical decision-making. Each framework was examined according to predefined theoretical criteria (unit of analysis, assumptions about safety, representation of clinical work, and role of human performance).
Findings
Among the various reviewed models used by nurses (either working within their discipline or part of multidisciplinary teams), the ones mostly used stem from engineering and aviation. The Systems Engineering Initiative for Patient Safety model was by far the most frequently applied framework, appearing in 26 of the 37 studies. Other frameworks were much less common: the Human Factors Classification Framework appeared in 5 studies. Frameworks such as the Yorkshire Contributory Factors Framework, Health Information Technology Classification System (HIT-CS), Perception–Action Cycle (PAC) model, and Comprehensive Unit-Based Safety Program (CUSP) each appeared in one study, whereas the RIPCHORD-TWA flow-disruption taxonomy appeared in two studies.
Originality/Value
This review offers criteria to guide theoretically informed framework selection in nursing patient safety research and contributes to greater conceptual clarity within the field.
- human factors framework,
- patient safety,
- nursing research,
- clinical practice,
- multidisciplinary clinical teams
Citation: Ioannis Kouroutzis, Christina Ekavi Vlachou, Pavlos Sarafis, Maria Malliarou. A conceptual review of human factors frameworks in nursing and patient safety[J]. AIMS Public Health, 2026, 13(4): 1069-1086. doi: 10.3934/publichealth.2026055

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Abstract

Purpose

Within the multidisciplinary area of human factors, a variety of frameworks have been proposed and/or applied in patient safety research to analyze risks and guide improvements, each offering a different perspective on system performance. Within the healthcare environment, nursing is one of the most distinct areas that can drive and deliver results in the patient safety arena. This study provides a conceptual review of human factors and ergonomics (HFE) frameworks used in patient safety research.

Design/methodology/approach

A structured literature mapping process identified empirical studies applying named HFE frameworks. This review identified 37 studies that applied HFE frameworks to nursing-related patient safety contexts including workflow analyses, adverse-event investigations, infection prevention, technology-related safety risks, and clinical decision-making. Each framework was examined according to predefined theoretical criteria (unit of analysis, assumptions about safety, representation of clinical work, and role of human performance).

Findings

Among the various reviewed models used by nurses (either working within their discipline or part of multidisciplinary teams), the ones mostly used stem from engineering and aviation. The Systems Engineering Initiative for Patient Safety model was by far the most frequently applied framework, appearing in 26 of the 37 studies. Other frameworks were much less common: the Human Factors Classification Framework appeared in 5 studies. Frameworks such as the Yorkshire Contributory Factors Framework, Health Information Technology Classification System (HIT-CS), Perception–Action Cycle (PAC) model, and Comprehensive Unit-Based Safety Program (CUSP) each appeared in one study, whereas the RIPCHORD-TWA flow-disruption taxonomy appeared in two studies.

Originality/Value

This review offers criteria to guide theoretically informed framework selection in nursing patient safety research and contributes to greater conceptual clarity within the field.

Funding

This conceptual review is conducted in the operating framework of the University of Thessaly Innovation, Technology Transfer Unit and Entrepreneurship Center “One Planet Thessaly”, under the “University of Thessaly Grants for Scientific Publication Support” action and is funded by the Special Account of Research Grants of the University of Thessaly.

Authors' contributions

IK: Literature search, data collection, data analysis, and writing—original draft. CEV: Literature screening, data analysis, and writing—original draft. PS: Interpretation of findings, and writing—review and editing. MM: Conceptualization, supervision, methodology, validation, and writing—review and editing. All authors read and approved the final version of the manuscript.

Conflict of interest

Maria Malliarou is the guest editors for special issue of AIMS Public Health and was not involved in the editorial review or the decision to publish this article. All authors declare that there are no competing interests.

References

[1]	Mistri IU, Badge A, Shahu S (2023) Enhancing patient safety culture in hospitals. Cureus 15: e51159. https://doi.org/10.7759/cureus.51159
[2]	Chatzi AV, Malliarou M (2023) The need for a nursing specific patient safety definition, a viewpoint paper. Int J Health Gov 28: 108-116. https://doi.org/10.1108/IJHG-12-2022-0110
[3]	Mahajan P (2021) Pediatric patient safety: Shared learning to improve patient outcomes. Pediatrics 148: e2021051017. https://doi.org/10.1542/peds.2021-051017
[4]	Carayon P, Schoofs Hundt A, Karsh BT, et al. (2006) Work system design for patient safety: the SEIPS model. Qual Saf Health Care 15 Suppl 1: i50-i58. https://doi.org/10.1136/qshc.2005.015842
[5]	National AcademiesTo Err Is Human: Building a Safer Health System (2000). [cited 2025 July 13]. Available from: http://www.nap.edu/catalog/9728
[6]	Leonard M, Graham S, Bonacum D (2004) The human factor: the critical importance of effective teamwork and communication in providing safe care. Qual Saf Health Care 13 Suppl 1: i85-i90. https://doi.org/10.1136/qhc.13.suppl_1.i85
[7]	Flin R (2007) Measuring safety culture in healthcare: A case for accurate diagnosis. Saf Sci 45: 653-667. https://doi.org/10.1016/j.ssci.2007.04.003
[8]	Pronovost PJ, Holzmueller CG, Ennen CS, et al. (2011) Overview of progress in patient safety. Am J Obstet Gynecol 204: 5-10. https://doi.org/10.1016/j.ajog.2010.11.001
[9]	Carayon P, Wetterneck TB, Rivera-Rodriguez AJ, et al. (2014) Human factors systems approach to healthcare quality and patient safety. Appl Ergon 45: 14-25. https://doi.org/10.1016/j.apergo.2013.04.023
[10]	Woods DD, Hollnagel E (2006) Joint Cognitive Systems: Patterns in Cognitive Systems Engineering. CRC Press.
[11]	Hollnagel E, Woods DD, Leveson N (2006) Resilience Engineering: Concepts and Precepts. Ashgate. https://doi.org/10.1201/9781315605685
[12]	Boyce MW, Mathew TA, Roberts SC, et al. (2024) A human factors engineering approach to improving hand hygiene quality. Hum Factors Healthc 6: 100085. https://doi.org/10.1016/j.hfh.2024.100085
[13]	Aaberg OR, Hall-Lord ML, Husebø SIE, et al. (2021) A human factors intervention in a hospital- evaluating the outcome of a TeamSTEPPS program in a surgical ward. BMC Health Serv Res 21: 114. https://doi.org/10.1186/s12913-021-06071-6
[14]	Bethel C, Rainbow JG, Johnson K (2022) A qualitative descriptive study of the COVID-19 pandemic: Impacts on nursing care delivery in the critical care work system. Appl Ergon 102: 103712. https://doi.org/10.1016/j.apergo.2022.103712
[15]	Higham HE, Morgan L, Cooper C, et al. (2024) Adopting human factors in early phase and experimental medicine research: A nested pilot study observing controlled human infection with SARS-CoV-2. Br J Clin Pharmacol 90: 1586-1599. https://doi.org/10.1111/bcp.15949
[16]	Glatkauskas M, Syversen MO, Lea M, et al. (2025) Application of a human factors approach to investigate the hospital to home transition for patients with multiple long-term conditions. Hum Factors Healthc 7: 100100. https://doi.org/10.1016/j.hfh.2025.100100
[17]	Xie A, Carayon P, Cox ED, et al. (2015) Application of participatory ergonomics to the redesign of the family-centred rounds process. Ergonomics 58: 1726-1744. https://doi.org/10.1080/00140139.2015
[18]	Barker AK, Brown K, Siraj D, et al. (2017) Barriers and facilitators to infection control at a hospital in northern India: a qualitative study. Antimicrob Resist Infect Control 6: 35. https://doi.org/10.1186/s13756-017-0189-9
[19]	Safdar N, Parmasad V, Brown R, et al. (2021) Decreasing ICU-associated Clostridioides difficile infection through fluoroquinolone restriction, the FIRST trial: a study protocol. BMJ Open 11: e046480. https://doi.org/10.1136/bmjopen-2020-046480
[20]	Konwinski L, Steenland C, Miller K, et al. (2024) Evaluating independent double checks in the pediatric intensive care unit: A human factors engineering approach. J Patient Saf 20: 209-215. https://doi.org/10.1097/PTS.0000000000001205
[21]	Werner NE, Rutkowski R, Graske A, et al. (2020) Exploring SEIPS 2.0 as a model for analyzing care transitions across work systems. Appl Ergon 88: 103141. https://doi.org/10.1016/j.apergo.2020.103141
[22]	Chua WL, See MTA, Legido-Quigley H, et al. (2018) Factors influencing the activation of the rapid response system for clinically deteriorating patients by frontline ward clinicians: a systematic review. Int J Qual Health Care 30: 492. https://doi.org/10.1093/intqhc/mzy040
[23]	Bugeja SJ, Stewart D, Strath A, et al. (2020) Human Factors approaches to evaluating outpatient parenteral antimicrobial therapy services: A systematic review. Res Soc Adm Pharm 16: 614-627. https://doi.org/10.1016/j.sapharm.2019.08.009
[24]	Keller SC, Gurses AP, Werner N, et al. (2017) Older adults and management of medical devices in the home: Five requirements for appropriate use. Popul Health Manag 20: 278-286. https://doi.org/10.1089/pop.2016.0070
[25]	Guise V, Anderson J, Wiig S (2014) Patient safety risks associated with telecare: a systematic review and narrative synthesis of the literature. BMC Health Serv Res 14: 588. https://doi.org/10.1186/s12913-014-0588-z
[26]	Bernstein SL, Kelechi TJ, Catchpole K, et al. (2021) Prevention of failure to rescue in obstetric patients: A realist review. Worldviews Evid Based Nurs 18: 352-360. https://doi.org/10.1111/wvn.12531
[27]	Santos ALR, Wauben LSGL, Guilavogui S, et al. (2016) Safety challenges of medical equipment in nurse anaesthetist training in Haiti. Appl Ergon 53: 110-121. https://doi.org/10.1016/j.apergo.2015.06.011
[28]	Ballangrud R, Husebø SE, Aase K, et al. (2017) “Teamwork in hospitals”: a quasi-experimental study protocol applying a human factors approach. BMC Nurs 16: 34. https://doi.org/10.1186/s12912-017-0229-z
[29]	Yanke E, Moriarty H, Carayon P, et al. (2021) “The invisible staff”: A qualitative analysis of environmental service workers' perceptions of the VA clostridium difficile prevention bundle using a human factors engineering approach. J Patient Saf 17: e806-e814. https://doi.org/10.1097/PTS.0000000000000500
[30]	Xiao Y, Smith A, Abebe E, et al. (2022) Understanding hazards for adverse drug events among older adults after hospital discharge: Insights from frontline care professionals. J Patient Saf 18: e1174-e1180. https://doi.org/10.1097/PTS.0000000000001046
[31]	Yanke E, Zellmer C, Van Hoof S, et al. (2015) Understanding the current state of infection prevention to prevent Clostridium difficile infection: A human factors and systems engineering approach. Am J Infect Control 43: 241-247. https://doi.org/10.1016/j.ajic.2014.11.026
[32]	Vaughan-Malloy AM, Chan Yuen J, Sandora TJ (2023) Using a human factors framework to assess clinician perceptions of and barriers to high reliability in hand hygiene. Am J Infect Control 51: 514-519. https://doi.org/10.1016/j.ajic.2023.01.013
[33]	Kwan WM, Mok CK, Kwok YT, et al. (2021) Using the systems engineering initiative for patient safety (SEIPS) model to describe the planning and management of the COVID-19 pandemic in Hong Kong. Int J Qual Health Care 33: mzab042. https://doi.org/10.1093/intqhc/mzab042/6157767
[34]	Probst CA, Carter M, Cadigan C, et al. (2017) Utilizing a human factors nursing worksystem improvement framework to increase nurses' time at the bedside and enhance safety. J Nurs Adm 47: 94-100. https://doi.org/10.1097/NNA.0000000000000446
[35]	Yardley S, Williams H, Bowie P, et al. (2022) Which human factors design issues are influencing system performance in out-of-hours community palliative care? Integration of realist approaches with an established systems analysis framework to develop mid-range programme theory. BMJ Open 12: e048045. https://doi.org/10.1136/bmjopen-2020-048045
[36]	Benjamin E, Giuliano KK (2024) Work systems analysis of emergency nurse patient flow management using the systems engineering initiative for patient safety model: Applying findings from a grounded theory study. JMIR Hum Factors 11: e60176. https://doi.org/10.2196/60176
[37]	Munroe B, Curtis K, Fry M, et al. (2023) Impact of an emergency department rapid response system on inpatient clinical deterioration: A controlled pre-post study. Australas Emerg Care 26: 333-340. https://doi.org/10.1016/j.auec.2023.05.001
[38]	Nassief K, Azer M, Watts M, et al. (2021) Emergency department care-related causal factors of in-patient deterioration. Aust Health Rev 46: 35-41. https://doi.org/10.1071/AH21190
[39]	Isaacs A, Raymond A, Kent B (2023) Content analysis of nurses' reflections on medication errors in a regional hospital. Contemp Nurse 59: 202-213. https://doi.org/10.1080/10376178.2023.2220432
[40]	Lee JY, Huang CH, Sie YA, et al. (2025) Applying the human factors analysis and classification system within root cause analysis to prevent medical errors and enhancing patient safety culture: insights from a medical center. Int J Qual Health Care 37: mzaf009. https://doi.org/10.1093/intqhc/mzaf009/8010126
[41]	Ravindran S, Matharoo M, Rutter MD, et al. (2024) Patient safety incidents in endoscopy: a human factors analysis of nonprocedural significant harm incidents from the National Reporting and Learning System (NRLS). Endoscopy 56: 89-99. https://doi.org/10.1055/a-2177-4130
[42]	Goekcimen K, Schwendimann R, Pfeiffer Y, et al. (2023) Addressing patient safety hazards using critical incident reporting in hospitals: A systematic review. J Patient Saf 19: e1-e8. https://doi.org/10.1097/PTS.0000000000001072
[43]	Rahman Jabin MS, Steen M, Wepa D, et al. (2023) Assessing the healthcare quality issues for digital incident reporting in Sweden: Incident reports analysis. Digit Health 9: 20552076231174307. https://doi.org/10.1177/20552076231174307
[44]	Taft T, Rudd EA, Thraen I, et al. (2023) “Are we there yet?” Ten persistent hazards and inefficiencies with the use of medication administration technology from the perspective of practicing nurses. J Am Med Inform Assoc 30: 809-818. https://doi.org/10.1093/jamia/ocad031
[45]	Khan RM, Aljuaid M, Aqeel H, et al. (2017) Introducing the comprehensive unit-based safety program for mechanically ventilated patients in Saudi Arabian intensive care units. Ann Thorac Med 12: 11-16. https://doi.org/10.4103/1817-1737.197765
[46]	Khan A, Shappell SA, Boquet AJ (2025) Using broken windows theory to examine flow disruptions in surgical care: A multispecialty comparison. J Healthc Qual 47: e0469. https://doi.org/10.1097/JHQ.0000000000000469
[47]	Khan A, Shappell SA, Boquet AJ (2025) Characterization of surgical flow disruptions in orthopedic surgery using a human factors approach. Perioper Care Oper R 39: 100488. https://doi.org/10.1016/j.pcorm.2025.100488
[48]	Boquet AJ, Cohen TN, Cabrera JS, et al. (2021) Using broken windows theory as the backdrop for a proactive approach to threat identification in health care. J Patient Saf 17: 182-188. https://doi.org/10.1097/PTS.0000000000000328
[49]	Wiegmann DA, Shappell, Scott A (2017) A Human Error Approach to Aviation Accident Analysis: The Human Factors Analysis and Classification System. Aldershot, UK: Ashgate.
[50]	Shappell SA, Wiegmann DA The human factors analysis and classification system–HFACS (2000).
[51]	Lawton R, McEachan RRC, Giles SJ, et al. (2012) Development of an evidence-based framework of factors contributing to patient safety incidents in hospital settings: a systematic review. BMJ Qual Saf 21: 369-380. https://doi.org/10.1136/bmjqs-2011-000443
[52]	Kato D, Lucas J, Sittig DF (2024) Implementation of a health information technology safety classification system in the Veterans health administration's informatics patient safety office. J Am Med Inform Assoc 31: 1588-1595. https://doi.org/10.1093/jamia/ocae107
[53]	Warm D, Edwards P (2012) Classifying health information technology patient safety related incidents-an approach used in Wales. ApplClin Inform 3: 248-257. https://doi.org/10.4338/ACI-2012-03-RA-0010
[54]	Pronovost PJ, Berenholtz SM, Needham DM (2008) Translating evidence into practice: a model for large scale knowledge translation. BMJ 337: a1714. https://doi.org/10.1136/bmj.a1714
[55]	Fuster JM (2005) Cortex and mind: Unifying cognition. Oxford University Press.
[56]	Fuster JM (2004) Upper processing stages of the perception-action cycle. Trends Cogn Sci 8: 143-145. https://doi.org/10.1016/j.tics.2004.02.004
[57]	Khan A, Farooq A, Elfallal W, et al. (2024) Application of broken windows theory to identify flow disruptions in neurosurgery procedure. J Healthc Risk Manag 43: 7-15. https://doi.org/10.1002/jhrm.21565
[58]	Holden RJ, Scanlon MC, Patel NR, et al. (2011) A human factors framework and study of the effect of nursing workload on patient safety and employee quality of working life. BMJ Qual Saf 20: 15-24. https://doi.org/10.1136/bmjqs.2008.028381
[59]	Gurses AP, Carayon P (2009) Exploring performance obstacles of intensive care nurses. Appl Ergon 40: 509-518. https://doi.org/10.1016/j.apergo.2008.09.003
[60]	Kushniruk AW, Borycki EM (2022) Human factors in healthcare IT: Management considerations and trends. Healthc Manage Forum 36: 72-78. https://doi.org/10.1177/08404704221139219
[61]	Chatzi AV, Kourousis KI (2024) Clarifying misconception of quality and safety in healthcare. Int J Health Gov 29: 377-384. https://doi.org/10.1108/IJHG-06-2024-0064
[62]	Kil Y, Graham M, Chatzi AV (2024) Examination of personality types as predictors of safety attitudes/behaviours, in support of enhancing safety in healthcare: a scoping review. Int J Health Gov 29: 323-341. https://doi.org/10.1108/IJHG-06-2024-0075

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