NUR 659 Module 2 Systems Paper Example

Why Good Nurses Make Errors: Applying Reason's Model and the SEIPS Work System to an Insulin Event

[Student Name]

Southern New Hampshire University

NUR 659: Healthcare Safety, Just Culture, and Regulation

Module Two Systems Paper

[Instructor Name]

[Date]

Why Good Nurses Make Errors: Applying Reason's Model and the SEIPS Work System to an Insulin Event

When a patient is harmed by an error, the question that comes first is usually who made it. At Westbrook Community Hospital, a composite 220-bed hospital, an experienced night nurse on a medical unit gave eight units of rapid-acting insulin to a patient who had not been prescribed it. The patient's blood glucose fell to 32 mg/dL, and she recovered after intravenous dextrose. The nurse had eleven years of experience and no prior errors. Within hours, some colleagues were asking whether she was careless or tired, and the unit manager drafted a written warning. This paper examines the event using two systems models. It argues that the person-focused response would have removed a skilled nurse while leaving in place every condition that made the error likely, and that systems models point to the causes that can actually be changed.

Person and System Approaches

Reason (2000) distinguished two ways of thinking about human error. The person approach focuses on the unsafe acts of individuals, such as forgetting, inattention or poor motivation, and responds with discipline, retraining and exhortation. The system approach starts from the premise that humans are fallible and errors are to be expected even in the best organizations; it asks why defenses failed rather than who failed. Reason described active failures, the unsafe acts committed by people in direct contact with the patient, and latent conditions, the weaknesses created by decisions made elsewhere in the organization, such as understaffing, poor equipment design or unworkable procedures. He illustrated the idea with his well-known image of slices of Swiss cheese: each defensive layer has holes, and harm occurs when the holes in several layers line up. Blaming the individual may feel satisfying, but it leaves the latent conditions in place for the next person.

What Happened That Night

Interviews and a review of the medication record reconstructed the sequence. The unit had two patients with the same last name, in rooms 412 and 421. Staffing that night was one nurse short, so the nurse carried six patients instead of five. At about 2 a.m., she prepared insulin for the patient in 421 based on a glucose reading. The barcode scanner on her workstation had failed to read wristbands several times earlier that shift, as it often did, and she had begun to enter patient identifiers manually. She walked into 412, spoke the last name, received a sleepy nod and administered the insulin. The electronic record accepted the manual override without a second prompt. The patient in 412 was not diabetic. The error was discovered at 4 a.m. when a routine check found the patient sweating and confused.

Mapping the Work System With SEIPS

Carayon et al. (2006) developed SEIPS, a human factors model for patient safety, which describes a work system made up of five interacting components: the person, the tasks, tools and technology, the organization and the physical environment. These shape care processes, which in turn produce outcomes for patients, staff and the organization. The model directs attention to how components interact rather than to any single cause.

Applied to the insulin event, the person was an experienced, conscientious nurse working the fourth of five consecutive nights. The tasks included managing six patients, two of them unstable, with several time-sensitive medications between 1 and 3 a.m. The tools included a barcode scanner that frequently failed and an electronic record that allowed manual overrides without further checks. The organization had left the shift short-staffed, assigned rooms without flagging patients with the same name and had no process for reporting or repairing scanner failures quickly. The environment included dim lighting at night and a sleeping patient who responded to a name. No single component caused the error; their interaction did.

Why Workarounds Happen

The decision to bypass the scanner looks, in hindsight, like a violation. Tucker and Spear (2006) observed hospital nurses over many hours and found that they encountered operational failures, such as missing supplies, equipment that did not work and information that was unavailable, several times in each shift. Nurses usually responded by working around the problem to keep patient care moving, rather than reporting it so it could be fixed, and the organizations rarely learned about the failures. The workarounds let care continue in the moment but left the underlying problem in place. The nurse's manual entry was exactly such a workaround. Colleagues confirmed that manual override was common on nights because scanner failures were frequent and tickets to biomedical engineering took days to resolve. A system that makes the safe path unreliable teaches staff to take the unsafe one.

What the Person Approach Would Have Missed

Had the written warning stood, the nurse would have been disciplined and the unit reminded to scan every wristband. The two patients with the same name would still have been placed in similar room numbers, the scanner would still have failed, the record would still have accepted overrides without a second check, the shift would still have been short and nurses would still have learned that scanning was optional when equipment failed. The next nurse would have faced the same aligned holes. The systems analysis, by contrast, identifies targets for change: repairing or replacing scanners with a same-shift response standard, requiring a second verification when identifiers are entered manually, flagging patients with similar names, reviewing night staffing and creating a simple way for nurses to report equipment failures that leads to visible fixes.

The unit manager withdrew the written warning after the analysis, and the nurse joined the root cause analysis team, where her account of the night proved essential.

Conclusion

An experienced nurse gave insulin to the wrong patient, but the error emerged from a system of unreliable equipment, permissive software, short staffing, similar names and a culture that normalized workarounds. Reason's model and the SEIPS framework make these latent conditions visible, and research on operational failures explains why good nurses work around broken systems. The root cause analysis that follows in the next milestone can build on this analysis to choose actions strong enough to prevent recurrence.

References

Carayon, P., Schoofs Hundt, A., Karsh, B.-T., Gurses, A. P., Alvarado, C. J., Smith, M., & Flatley Brennan, P. (2006). Work system design for patient safety: The SEIPS model. Quality and Safety in Health Care, 15(Suppl. 1), i50-i58. https://doi.org/10.1136/qshc.2005.015842

Reason, J. (2000). Human error: Models and management. BMJ, 320(7237), 768-770. https://doi.org/10.1136/bmj.320.7237.768

Tucker, A. L., & Spear, S. J. (2006). Operational failures and interruptions in hospital nursing. Health Services Research, 41(3, Pt. 1), 643-662. https://doi.org/10.1111/j.1475-6773.2006.00502.x