July 13, 2022By Jill Sanko

Benefits of Creating a Simulated Adverse Event Reporting System for Healthcare Simulation

Medical error is a leading cause of death in the United States (1) and is ranked ahead of COVID-19, accidents, and stroke. The practice of healthcare simulation has proven to be an effective way to train learners and professionals, so that they may be better equipped and aware during the treatment of patients – ultimately increasing patient safety and deterring medical error. This HealthySimulation.com article was authored by Jill Sanko and details a recent experience she had with the healthcare system in which her father was the victim of medical error. She notes how a simulated adverse event reporting system could help to deter similar mistakes in the future.

Recently, my father experienced a medical error that fortunately did not kill him; a nurse pushed a medication on him too quickly causing a rapid rise in his blood pressure and cardiac arrhythmia. In a quest to encourage the institution to educate their nurses (this incident is identical to one he experienced several years ago at the same hospital on the same floor but with a different medication, and different symptoms) the patient safety department was contacted due to the alarming potential for death.

We will never know what the organization does with that information, but this recurring scenario illustrates the commonality of medical errors and the repetitive nature of them. My best guess is that prior errors, as well as this one, were not reported. Not only was the most recent mistake potentially fatal, but the mistake was costly. This is because the healthcare team did not recognize the error made by the nurse, resulting in multiple expensive tests being ordered to rule out a blood clot. (The symptoms from the medication pushed on him mimicked those of a blood clot.)


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Prevention of errors is best achieved when understanding why adverse events occur through a reporting culture. Less than 10% of all medical errors are reported, and even fewer near-miss events are captured through reporting systems. Learning from mistakes can only happen when both types of adverse events are reported, however, the greatest “bang for the buck” comes from reports of near-miss events (those that held harm potential, but an intercedent action prevented this). Generally, adverse events are not one-off events, but rather symptoms of system-wide deficiencies.

The near-miss accident theory suggests that for every harmful event, the same course of events occurred at least 10 times prior – but were caught before they caused harm. This would equate to 10 opportunities to learn how to prevent harm and how to improve the system, but remained “hidden” because a report was never made.

For example, imagine an iceberg (2) mostly underwater – what we can’t see represents the near-miss events. Alternatively, we only see the very small portion of the iceberg that juts out of the water – representing harm causing errors. The industry refers to these as “dark figures.” I love the visual representation because the system remains in the dark each and every time an incident occurs and isn’t reported.

The reasons for underreporting in healthcare are complex, but the literature supports the idea that a culture of blame (3) that permeates the industry contributes. If healthcare desires to change reporting habits, the culture needs to change as well. One of the best ways to begin culture change is to start with those new to a field; those not yet tainted by the “because we have always done it that way” mentality. If novices enter with the idea that reporting is normal and part of the job imperative then a culture shift can occur.


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The aviation industry represents a successful model for change. This industry wasn’t always as safe as today’s standards, but an industry in peril marked by several high-profile crashes in the 1970s and 1980s provided a fulcrum for a culture shift related to reporting adverse events. Born out of necessity and a quest for a safety culture, aviation was able to make important changes to mitigate and prevent errors, by requiring that all adverse events are reported. Today, aviation touts an impeccable safety record of .04 deaths per 100 million miles traveled and can feel proud that among high-reliability industries they are one of the safest.

Healthcare simulation-based education is also a great tool for developing the habit of reporting. This can be accomplished through the creation of a simulated adverse event reporting system incorporated into a clinical simulation program. Such a system can serve an educational purpose and also support quality improvement efforts.

How to Develop a Simulated Adverse Event Reporting System for Healthcare Simulation

The creation of a simulated adverse event reporting system can be easily and cost-effectively done online survey system. A team of healthcare simulation educators at a research university in the Southeast were able to replicate and use such a system successfully as part of their clinical simulation and patient safety initiatives.

The system was created using Qualtrics which was already licensed by the institution therefore there were no additional costs outside of development time for the creation of the system. Access was made through a link provided on the institution’s learning management system, but a scannable QR code can be used as well. Reporting was voluntary and anonymous. Data captured adverse events that occurred during simulation encounters using a streamlined framework of drop-down choices, single-answer choices, multi-select options, and open-ended questions.

The system collected the type (errors, near misses, sentinel) and category (medication, failure to rescue, airway, etc) of events, perceived causes and contributors (knowledge gap, distraction, misunderstanding, etc), and using an open-ended question, prompted students to reflect and share what was learned.

The system’s item drop-down and single/multi-select choices were guided by the literature and mimicked adverse event reporting systems used in U.S. hospitals. Choices were specific to the category of events. For example, if an airway event was noted a list of contributors/causes specific to the airway was generated.

The integration of this system proved to be a successful way to inculcate the habit of reporting when a mistake occurs. The intervention additionally provided a reflection point that could be expanded on during post-healthcare simulation encounter debriefs and an opportunity to identify reasons why the mistake happened and generate ideas about what could have been done differently. Initial data analysis to establish feasibility and assess disruption (4) to the flow of education was carried out.

The analysis demonstrated minimal impacts on the educational flow; most reports were made in under 60 seconds. Data patterns across all reports demonstrated a near-identical pattern of adverse events reported in clinical settings. These two pieces of information provided confidence that data were valid, the system could be used as a proxy to better understand error causation, could be collected without untoward educational impacts, and a case-use example.

Over the course of the nine years, the system was in place thousands of reports were captured. During this time, data provided answers to numerous questions of interest around how and why adverse events occur, illuminated programmatic deficits might be contributors to mistakes and knowledge gaps, and assisted in the discovery of students’ knowledge, skills, and attitudes weaknesses.

Moreover, data allowed for quality improvement of curricula as well as healthcare simulation-based education guided by evidence of data revealing patterns of mistakes made which could then be addressed in the classroom or simulation-center and provided an opportunity to appreciate the development of learners’ thinking processes in important safety-related areas. Using data from medication-related reports educators could for the first time see where knowledge gaps due to classroom knowledge deficiencies translated into performance mistakes. This information then was used to change didactic as well as healthcare simulation encounters.

Another example of how data-informed faculty and shifted approaches was when analysis demonstrated that as students progressed in their education their mistakes shifted. Early in their learning, medical errors often arose from knowledge gaps in the specifics of medications and administration procedures; what you would expect – “rookie mistakes.” Later, as learners approached graduation, mistakes were more commonly reported to be caused by communication and teamwork failures but showed a deeper understanding of medication knowledge; mistakes were more common among more seasoned nurses.



To my knowledge, very few healthcare simulation programs have simulated adverse event reporting systems integrated into their programs. However, if systems existed across a number of healthcare simulation programs pooled data could be used by educators and healthcare systems to gain a broader understanding of educational deficits as well as reasons why adverse events occur.

More importantly and potentially more impactful, broad adoption of simulated adverse event reporting systems across simulation programs nationally would assist in mass inculcation of the habit of reporting and help to shift the safety culture of healthcare.

Care, of course, needs to be taken to ensure learners do not feel unduly burdened by the process, and assurances were taken to keep simulation a safe learning container. The efforts will be worth the work if lives are saved because reporting increases. This is just one way that clinical simulation can impart important habits, change attitudes, and instill knowledge that will be taken into the workplace and change the healthcare culture.

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References:

  1. https://www.bmj.com/content/353/bmj.i2139
  2. https://blog.americandatanetwork.com/patient-safety-analysis-other-events-reveal-3x-higher-mortality-rate-among-key-findings
  3. https://www.mdpi.com/1660-4601/16/23/4826
  4. https://www.nursingsimulation.org/article/S1876-1399(14)00005-X/fulltext

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