Quality improvement (QI) is defined as systematic, data-guided activities designed to bring about immediate, positive changes in the delivery of healthcare. The ultimate goal of QI is to improve patient outcome, through enhancing clinical performance through an understanding of the effects of teamwork, tasks, equipment, workspace, culture, and organisation on human behaviour and abilities and application of that knowledge in clinical settings.
Despite advances in medicine and enhanced training opportunities, medical errors continue to occur, where up to 4% of hospitalised patients in human hospitals have been reported to have serious negative outcomes due to adverse events, and 50% of these events were deemed preventable. A landmark document from the institution of medicine, ‘To err is human,’ acknowledged that medical errors are not a result of isolated individual actions, but rather faulty systems, processes, and conditions that lead people to make mistakes. This has been described in Reason’s Swiss Cheese Model of Error, which differentiates ‘active’ errors such as cognitive errors and ‘latent’ errors, which are systems errors including non-technical skills (e.g., teamwork, leadership, communication, decision making), staffing, equipment design and availability, policies, and environmental factors (e.g., noise, lighting, room layout); all which can contribute to medical errors.
The Agency for Healthcare Research and Quality (AHRQ) has recommended medical simulation as one of the most important safe practice interventions to reduce errors and risks associated with the process of care. People often imagine medical simulation as an exciting and elaborate process involving virtual reality or manikins in a simulation center. However, in situ simulation, which involves undertaking a mock example of practice within the hospital setting can be very rewarding and cost effective for teaching/training and QI. Most common example of in situ simulation in veterinary ECC is a mock CPR code using a basic manikin. Immediately following the simulation, debriefing is important to help identify cognitive processes of participants which may have contributed to latent or active errors. Debriefing will also give opportunities for participants to actively contribute to the QI process by contributing ideas of causes of errors and how to improve processes for the future. Please see the lecture on debriefing for further information and references.
Simulation is particularly beneficial in high risk, low frequency scenarios (e.g., CPR, mechanical ventilation); training new skills; and multidisciplinary team training. This same concept can be applied to the use of in situ simulation for QI. Simulation can be used during analysis of an isolated or repeated incident as a result of a medical error. Simulation can be used to reenact the incident, in the same setting and shift time (often errors are identified during certain shift times, hence timing is important), to find out what latent errors may have contributed to the incident. Examples of latent threats which have been identified during simulation include hospital layout (e.g., not able to work around a table), not enough reception staff, training gaps, crash alarm too quiet, lack of knowledge of medications or location of medications, equipment not available, battery dead, ineffective medical records, ineffective hand-over processes, inappropriate expectations of role, and inconsistencies in protocols, just to name a few.
Once the cause of errors has been identified, a new policy, procedure, or equipment may be introduced to your hospital. Before introducing new changes, simulation can be used to trial the new procedure or equipment in the hospital setting, and further improvements can be made before introducing to real patients. Simulation has also been used for hospital design processes. For example, simulation can be used to assess communication between reception and floor team, test effectiveness of new alarm systems, time taken to move patients, and identify hazards or difficult access to equipment/medications.
Studies in human hospitals have found improvement in CPR success rates, compliance to sepsis protocols, decrease in MRSA infection, and ICU mortality rates with the use of in situ simulation for QI and training. Once changes have been made as a result of the QI process, it is important to undertake data analysis to determine if the introduction of new procedures, systems, or equipment has improved patient outcomes. There are many publications in the human literature on improved outcomes using simulation for QI which can be found in the references. As demonstrated in published literature, this data collection process can be important contributions to scientific literature; however, even without major publication efforts, it can be just as rewarding to analyse the data for hospital systems improvement to ensure and demonstrate success of any changes made. This is an important process, as the data can be presented to the QI committee (if available), and senior members of the hospital which will further help support QI processes and simulation within your hospital.
In summary, simulation can be used as part of QI processes in veterinary hospitals to identify latent threats; trailing new protocols/equipment; and fulfilling training needs identified as part of QI processes.
References
1. Ajmi S, Advani R, Fjetland L, et al. Reducing door-to-needle times in stroke thrombolysis to 13 min through protocol revision and simulation training: a quality improvement project in a Norweigian stroke centre. BMJ Qual Saf. 2019;0:1–10.
2. Brazil V, Purdy E, Bajaj K. Connecting simulation and quality improvement: how can healthcare simulation really improve patient care? BMJ Qual Saf. 2019;28:862–865.
3. Daniels K, Auguste T. Moving forward in patient safety: Multidisciplinary team training. Seminars in Perinatology. 2013;37:146–150.
4. Geis G, Pio B, Pendergrass T, et al. Simulation to assess the safety of new healthcare teams and new facilities. Sim Healthcare. 2011;6:125–133.
5. Guise J, Mladenovic J. In situ simulation: Identification of systems issues. Seminars in Perinatology. 2013;37:161–165.
6. Kobayashi L, Shapiro M, Sucov A. Portable advanced medical simulation for new emergency department testing and orientation. Academic Emerg Med. 2006;13:691–695.
7. Patterson M, Geis G, Falcone R, et al. In situ simulation: detection of safety threats and teamwork training in a high risk emergency department. BMJ Qual Saf. 2013;22:468–477.
8. Shah S, Cusumano C, Ahmed S, et al. In situ simulation to assess pediatric tracheostomy care safety: A novel multicenter quality improvement program. Otolaryngology-Head and Neck Surgery. 2020;163:250–258.
9. Slakey D, Simms E, Rennie K. Using simulation to improve root cause analysis of adverse surgical outcomes. Int J Qual Health Care. 2014;26:144–150.