Free Essay Example: System Engineering Initiative for Patient Safety

The most common types of errors that error in healthcare include: medical errors, errors related to anesthesia, hospital-acquired infections, delayed or missed treatments, inadequate follow-up after treatment, and inadequate monitoring after a procedure among others. Healthcare professionals experience intense psychological effects such as anger, guilt, inadequacy, depression, and suicide due to supposed errors that occur in the healthcare environment. These errors result in impending legal action, loss of clinical confidence, and harm to the patients (Rodziewicz & Hipskind, 2020).

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According to the National Coordinating Council for Medication Error Reporting and Prevention, medical error is ranked as the third leading cause of death in hospitals. A medication error is defined as a preventable occurrence that may cause or lead to incorrect medication use while the medication is in the control of the healthcare professional or a patient (Rodziewicz & Hipskind, 2020). For example, when a patient or a healthcare professional lacks crucial information when needed to guide prescribing decisions resulting in the wrong dose. Medical error is preventable, and some of the measures include; a medication dialogue with the patient including open-ended questioning and active listening to successfully share information, ensuring that the nurses follow the institutional policies related to medication transcription, double-checking of the procedures among others (Rodziewicz & Hipskind, 2020).

The next healthcare errors those related to anesthesia. According to Boquet et al. (2017), error related to anesthesia is reported to have increased in rate for anesthesia-in-training providers as a result of incorrect dose and drug substitution (Boquet et al., 2017). Some of the common mistakes during anesthesia include medication dosing errors, unintentional administration of residual anesthetics, and documentation errors, among others, for example, doctors administering too much anesthesia. The above error is preventable, and some of the measures to mitigate the mistake include; talking with an anesthetic provider during the preoperative meeting by discussing the anesthesia options, healthcare professionals should select the best and safest treatment for anesthesia patients during their operation (Boquet et al., 2017).

Hospital-acquired infections are another type of error that occurs in the healthcare environment. Haque et al. (2018), discussed the above error stating that they are infections that patients get while receiving treatment for medical or surgical conditions. They are commonly caused by viral, bacterial, and fungal pathogens. They include bloodstream infection (BSI), ventilator-associated pneumonia (VAP), urinary tract infection (UTI), and surgical site infection (SSI) (Haque et al. 2018). For example, a patient suffering from an autoimmune disease can infect his or her doctor if the doctor mishandles sharp objects such as needles and scalpels. Some of the measures taken to reduce the error include the creation of an infection-control policy, identification of the contagions as soon as possible, and the use of gloves, among others.

Another healthcare environment error is delayed or missed diagnosis. Bellani, Pham & Laffey (2020), defined delayed treatment as when a patient does not get a medicine whether it be a medication, lab test, physical therapy treatment, or any treatment recommended for them in the time frame in which it was supposed to be delivered. The error is commonly caused by overconfidence, anchoring errors, VIP errors, the momentum of the illness, and personal biases about patients. For example, a patient suffers from brain damage because the doctors missed detecting that the patient had severe neurologic harm (Bellani, Pham & Laffey, 2020). Some of the measures for preventing the mentioned error include; improving health information technology (HIT) to ensure accurate and timely communication of patient information, listing all patients’ active and inactive medical problems and diagnoses, an incorporating diagnostic checklists into the electronic record among others (Bellani, Pham & Laffey, 2020).

Inadequate follow-up after treatment is also another standard error that occurs in the healthcare environment. For instance, not call patients or caregivers of the patients to confirm if they are following instructions given to them by the doctors (Baumgartner, 2018). Some of the measures recommended to reduce the chances of the occurrence of the error include: include maintaining a culture that works toward recognizing safety challenges and applying practical solutions rather than embracing a culture of blame, shame, and punishment; there is also the need to establish a culture of safety focusing on improvement of the system by observing medical errors as challenges that must be overcome (Baumgartner, 2018). Inadequate monitoring in the absence of a treatment protocol leads to an adverse outcome. This error occurs when dealing with elderly patients. For instance, monitoring elderly patients who have undergone any surgical procedure to avoid further infections.

According to Carayon et al. (2020), the Systems Engineering Initiative for Patient Safety (SEIPS) model analyzed how human healthcare factors within the healthcare environment should be configured, engaged, and adapted in different settings. The SEIPS enhances health-related issues by making it easy for healthcare professionals to efficiently deliver good quality services because of the continuous evolvement of the science and practice of human factors in the healthcare domain (Carayon et al., 2020). SEIPS tools include the American Medical Association’s (AMA). The knowledge of this philosophy helps to prevent medical error strategies like medication discussions with the patient, and he or she is advised to follow instructions given on the prescribed medication.

Simsekler, Ward and Clarkson (2018), described the positive impact of the SEIPS tool when applying both engineering and healthcare to reduce the rate of occurrence of the medical error. The strategy helps to improve the notion of a patient-centered approach in a healthcare environment to improve the patient’s safety in a high-risk healthcare setting. The positive impact includes patient researchers recognizing and examining the needs of patients’ safety as well as improving the recommended safety (Simsekler, Ward, and Clarkson, 2018).

McCalman et al. (2018), defined Continuous Quality Improvement (CQI) in Health Care as a designed organizational procedure that includes physicians and other personnel in developing and application of ongoing proactive improvements in processes of care to provide quality health care results. The SEIPS Model is a patient safety method based on an industrial engineering subspecialty of human factors, even though the model focuses on placing the interactions within the work system to involve the person, organization, technology, and environment, among others (McCalman et al., 2018). The relationship between CQI and SEIPS is that they both focus on ways to improve and provide quality healthcare services to patients as well as improve their safety within the high-risk healthcare environment.

The patient-centric approach focuses on establishing partnerships among human factors like physicians, practitioners, patients, and their families to agree on the decisions that will favor both the needs and preferences of the patient. Through the above approach, specific education and support are delivered for the patients to participate in the decision-making process without feeling inferior (Kalra et al., 2019). Improving quality outcomes with a patient-centric focus helps to promote a concern for the common good within the public arena since different personnel are involved in the decision-making process when diagnosing a disease. Still, at the same time, they include the needs and preferences of the patients before concluding (Kalra et al., 2019).

References

Baumgartner, H. (2018). Does frequently inadequate adult care threaten the outcome of congenital heart disease after successful pediatric treatment? European Heart Journal. doi:10.1093/eurheartj/ehy035

Bellani, G., Pham, T., & Laffey, J. G. (2020). Missed or delayed diagnosis of ARDS: a common and severe problem. Intensive Care Medicine, 1-4. https://link.springer.com/content/pdf/10.1007/s00134-020-06035-0.pdf

Boquet, A., Cohen, T., Diljohn, F., Cabrera, J., Reeves, S., & Shappell, S. (2017). A theoretical model of flow disruptions for the anesthesia team during cardiovascular surgery. J Patient Saf, (00), 1-6. https://www.researchgate.net/profile/Albert_Boquet/publication/318203303_A_Theoretical_Model_of_Flow_Disruptions_for_the_Anesthesia_Team_During_Cardiovascular_Surgery/links/5af9b11fa6fdccacab154484/A-Theoretical-Model-of-Flow-Disruptions-for-the-Anesthesia-Team-During-Cardiovascular-Surgery.pdf

Carayon, P., Wooldridge, A., Hoonakker, P., Hundt, A. S., & Kelly, M. M. (2020). SEIPS 3.0: Human-centered design of the patient journey for patient safety. Applied Ergonomics, 84, 103033. https://doi.org/10.1016/j.apergo.2019.103033

Haque, M., Sartelli, M., McKimm, J., & Bakar, M. A. (2018). Healthcare-associated infections–an overview. Disease and drug resistance, 11, 2321. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6245375/

Kalra, M. K., Becker, H. C., Enterline, D. S., Lowry, C. R., Molvin, L. Z., Singh, R., & Rybicki, F. J. (2019). Contrast administration in CT: a patient-centric approach. Journal of the American College of Radiology, 16(3), 295-301. https://doi.org/10.1016/j.jacr.2018.06.026

Get rights and contentMcCalman, J., Bailie, R., Bainbridge, R., McPhail-Bell, K., Percival, N., Askew, D. ... & Tsey, K. (2018). Continuous quality improvement and comprehensive primary health care: a systems framework to improve service quality and health outcomes. Frontiers in public health, 6, 76. https://doi.org/10.3389/fpubh.2018.00076

Rodziewicz, T. L., & Hipskind, J. E. (2020). Medical error prevention. In StatPearls [Internet]. StatPearls Publishing. https://www.ncbi.nlm.nih.gov/books/NBK499956/

Simsekler, M. E., Ward, J. R., & Clarkson, P. J. (2018). Design for patient safety: a systems-based risk identification framework. Ergonomics, 61(8), 1046-1064. https://doi.org/10.1080/00140139.2018.1437224