Analyzing Adverse Events and Near Misses in Nursing- A Case Study and Proposal for Quality Improvement Initiatives

Analyzing Adverse Events and Near Misses in Nursing- A Case Study and Proposal for Quality Improvement Initiatives

An adverse event refers to an unwanted outcome that results from patient treatment. This event results from the treatment process rather than the patient’s underlying condition. A near-miss is a medical error with the potential to harm the patient but is addressed promptly, and no harm occurs (Vincent et al., 2018). Healthcare facilities should formulate strategies and policies to minimize the incidences of adverse events. This is important for the overall well-being of the patient and promotes self-satisfaction among healthcare providers. This paper provides an analysis of an adverse drug event. In addition, it provides the implications and strategies to mitigate adverse events. Hire our assignment writing services in case your assignment is devastating you.

A patient reported to the hospital’s orthopedic departments for his scheduled hip replacement surgery. The orthopedic surgeon pointed out that the patient should receive an extended-release morphine liposomal epidural injection before the surgery. He ordered 10 milligrams (mg) of liposomal morphine to be administered. The perioperative nurse administered 20 milliliters of a 10 mg per milliliter ampoule. This was about twenty times the prescribed dose. The patient suffered from difficulty in breathing, became cyanotic, and entered a comatose state. The antidote, naloxone, was out of stock at the time of overdose. An emergency acquisition was made from the neighboring facility. Intravenous administration of the antidote reversed the respiratory depression partially. The patient had to receive respiratory support for one week. The surgery was rescheduled.

Analysis of the Missed Steps Related to the Adverse Event

Adverse events frequently occur due to an improper framework of health care operations. However, most of these adverse events are not reported. Patients usually experience prolonged stays at the hospital managing adverse events rather than their presenting complaint. A regular departmental audit can help to identify the occurrence of adverse events and put in place mitigative strategies.

In this context, protocol deviations and missed steps significantly contributed to the adverse events. The morphine ampoules present in the medication tray had a strength of 10 mg per milliliter. Each ampoule had a capacity of 20 milliliters. Therefore, each ampoule contained a total of 200 mg of morphine. The nurse did not countercheck the strength of each ampoule. The package label of 10 mg per ml made her assume that the ampoule contained a cumulative dosage of 10 mg. She ought to have confirmed the calculation with her colleagues or brainstormed with the surgeon before administering the medication. Furthermore, morphine is a potent opioid analgesic, and a thorough review should be taken before it is administered.

The nurse and the prescriber should have checked for the presence of an antidote before administering morphine. Owing to its potency, morphine overdose is associated with life-threatening adverse events. Notably, morphine causes respiratory depression. This is caused by the inhibition of the neurokinin-1 receptors in the brain (Kiyatkin, 2019). The ensuing hypoventilation due to reduced oxygen supply to body tissues causes cyanosis. This progresses to coma and death if not managed promptly. The absence of naloxone before the operation is a risk. It demonstrates poor planning. Furthermore, it may indicate a lack of awareness of the importance of the antidote.

This adverse event was preventable. The nurse should have crosschecked her calculations and re-read the labeling of the ampoules to determine the capacity. This would have ensured that an accurate volume of the drug is withdrawn. Furthermore, she would have consulted her colleagues to ensure that the correct quantity was being administered. The absence of naloxone should have prompted consultations with the hospital pharmacy and the administration to acquire the important drug. Therefore, deficiency in communication, collaboration, and analytic skills caused the adverse event.

Morphine and other opioid overdose is a concern in other facilities globally. Studies done in 2019 revealed that approximately 500,000 people lost their lives due to substance abuse (Centers for Disease Control and Prevention, 2019). About 30 percent of the lives were lost due to overdose. More than 100,000 succumbed to opioid overdose, especially heroin, fentanyl, and morphine (Centers for Disease Control and Prevention, 2019). Therefore, morphine overdose is an adverse event of concern.

Implications of Adverse Event on Stakeholders

The adverse event affected all of the stakeholders involved. The patient and his family were impacted acutely and in the long term. The patient suffered from respiratory depression. The patient had to spend more time in the hospital receiving respiratory support. Furthermore, his surgery had to be rescheduled. A prolonged stay implies that the patient and family incurred a financial burden in the form of the hospital bill. His family had to battle the emotional burden of witnessing their patient suffer from a medication error rather than his underlying condition. The patient’s perception of the hospital is likely to have changed. His level of satisfaction with service delivery decreased. The patient and his family are less likely to visit the hospital or refer their friends to the hospital.

The interprofessional team is likely to be demotivated. Furthermore, their level of self-confidence is likely to reduce. They are likely to quit their jobs to avoid continued blame games or legal implications (Bates & Singh, 2018). Furthermore, they are likely to be impacted emotionally. Patients trust their healthcare providers to deliver the best healthcare services. They had failed the patient and are likely to feel guilty. This can negatively affect their subsequent interaction with patients.

The facility is at risk of getting a distorted reputation. The community is most likely to avoid the services offered by the facility. The community is aware of the adverse event that occurred and doesn’t wish to suffer a similar fate. The hospital is also likely to face legal action. The patient and his family could sue the hospital for professional negligence and seek compensation for the financial costs incurred. Such legal proceedings can further influence the community’s perception of the hospital in a negative way.

The changes incorporated into the process and protocol are aimed at quality improvement. Two changes were implemented. Automation of surveillance systems was adopted. This pertains to the patient’s treatment plan, records, and other medical records. This involved displaying all medications on a screen and software with all relevant arithmetic calculations related to the medications. Furthermore, the software facilitated adverse event detection rules and data mining. The second strategy was regular staff training. This was an interdisciplinary initiative and focused on safe medication use.

Evaluation of Quality Improvement Technologies

The hospital adopted an automated surveillance system. This system enabled the execution of three tasks. It permitted access to treatment data and medical records and gave a discharge summary. This enables the healthcare team to have a predictive ability of the problems or errors that are likely to occur (van Rooden et al., 2021). Consequently, adverse events can be avoided and addressed promptly and adequately once they occur. In this context, the hospital uses this system to monitor the use of morphine and other potent opioid analgesics. After monitoring, the hospital contacts the departments and sends an interdisciplinary committee to uphold the safe use of the medication. This system also ensures that appropriate antidotes are available before the administration of the drugs.

The second task facilitated by the automated surveillance system is data mining. Data mining enables healthcare providers to get exclusive information about a drug before using it. This entails looking up the electronic medical record. When a drug is searched, the therapeutic indication and potentially life-threatening adverse events are displayed (van Rooden et al., 2021). This equips staff with medication knowledge and makes them understand the importance of consultation before administering the drug. The third task is adverse event detection rules. Just like data mining, it facilitates the detection of the likelihood of adverse events. However, this uses Boolean operations to facilitate the detection of adverse events.

The automated surveillance system is relevant to the prevention of the occurrence of adverse events. It enables the healthcare providers to make a prospective model of the likelihood of the occurrence of adverse events. It helps to point out key sectors in the clinical setting where errors and consequent adverse events can occur (Tolf et al., 2020). This is relevant in the context of preventing morphine and other opioid-related adverse events. Staff should undergo rigorous training to identify and familiarize themselves with the system. Appropriate incorporation of the system will increase the performance of staff and improve patient outcomes.

Other institutions can embrace quality improvement programs to avert adverse events. They can use the automated surveillance system or other models that promote performance evaluation. Analytic tools that promote data capture, processing, analysis, and presentation are key to the improvement of the performance of health care providers (van Rooden et al., 2021). Staff training should be adequate to facilitate ease of transition to the new technological quality improvement program.

Relevant Metrics of Quality Improvement

Key metrics generated in the facility’s dashboard include treatment data, medical records, and discharge summaries. This information is important in determining the performance of healthcare providers. Treatment data represents the treatment, data mining is conducted, and adverse event detection rules are incorporated. This enables the facility to understand its position in the active involvement of patient care. The dosage, dosage form, and duration of treatment with a particular medication are important. It enables the identification of the relevance of the medication and its appropriate use. Data mining and adverse event detection indicate the efforts incorporated by healthcare providers to prevent the occurrence of adverse events. Data from the institution’s dashboard indicates that there has been an improvement in data mining and adverse event detection. This suggests that health care providers are committed to the delivery of the best patient-centered care services.

Medical records and discharge summary helps to detect any adverse events. The records have the patient’s presenting complaint, treatment administered, and the hospital stay. The interpretation of this data can be used to identify the rationale behind drug use and the effectiveness of medications (Bates & Singh, 2018). The addition of medications that are not pertinent to the patient’s presenting complaint suggests the occurrence of an adverse event. Since the adoption of the automated surveillance system, data demonstrate that the incidence of adverse events has reduced.

Similar results have been reported by the World Health Organization and the Centers for Disease Control and Prevention. The use an elaborate surveillance system has been used to reduce the incidences of adverse events resulting from opioid overdose (Centers for Disease Control and Prevention, 2019). The strategies employed include the use of data tools to facilitate evidence-based decisions, using technology to monitor prescribing trends, and data analysis of opioid overdose incidences (World Health Organization, 2021). This can be achieved by working in concert with hospital administrations. Automated surveillance systems in hospitals and legal drug dispensers such as pharmacy outlets help to provide this key information. The surveillance tools advocate for an interdisciplinary approach to avert over-prescription, promote safe use and avoid adverse events. Therefore, the institution’s data metrics are relevant and help to minimize the occurrence of opioid-related adverse events.

Outline of Quality Improvement Initiative

Currently, the facility uses an automated surveillance system to detect and prevent adverse events. This is a prospective technique that targets the patient’s hospital care. From the hospital experience, key areas where errors are likely to emanate from are identified. The errors are then addressed adequately to prevent the development of an actual threat (van Rooden et al., 2021). The automated surveillance system permits access to treatment data, medical records, and discharge summaries. Furthermore, it allows data mining and adverse event detection. The hospital uses this system to monitor the use of morphine and other potent opioid analgesics. After monitoring, the hospital contacts the departments and sends an interdisciplinary committee to uphold the safe use of the medication. This system also ensures that appropriate antidotes are available before the administration of the drugs. This concerted effort ensures that the performance of the healthcare providers improves.

Other institutions have embraced quality improvement programs to avert adverse events. They use analytic tools that promote data capture, processing, analysis, and presentation, which are key to the improvement of the performance of healthcare providers (Tolf et al., 2020). Staff training is conducted frequently to facilitate ease of transition to the new technological quality improvement program.

Different quality improvement initiatives have been developed to help prevent adverse events. They include the Plan-Do-Study-Act, Value-Based Health Care, and the Non-adoption, Abandonment, Scale-up, Spread, and Sustainability initiatives (Tolf et al., 2020). The Plan-Do-Study-Act model fails to provide data on progress. Consequently, the impact of the model cannot be assessed. Both the Value-Based Health Care and Non-adoption, Abandonment, Scale-up, Spread, and Sustainability initiatives use analysis data to determine the performance of healthcare providers (Tolf et al., 2020). They provide regular feedback through dashboards. Therefore, they enable an analysis of the progress and performance of the healthcare providers.

The health care institution should uphold regular staff training to ensure that the automated surveillance system is a success. The training should aim at promoting a culture of accountability. All of the protocols related to the use of the system should be upheld. The data on the dashboard should be evaluated regularly to monitor the performance of the staff. Furthermore, hospitals should consider adopting synergistic models such as value-based health care.

Conclusion

Adverse events frequently occur due to an improper framework of health care operations. However, most of these adverse events are not reported. Quality improvement programs should be set up to help reduce the incidences of adverse events. An automated surveillance system is a technological advance that can help to prevent adverse events. A regular evaluation of data on the dashboard can help monitor the performance of health care providers.

References

Bates, D. W., & Singh, H. (2018). Two Decades Since To Err is Human: An Assessment of Progress and Emerging Priorities in Patient Safety. Health Affairs, 37(11), 1736–1743. https://doi.org/10.1377/hlthaff.2018.0738

Centers for Disease Control and Prevention. (2019). Understanding the Epidemic. https://www.cdc.gov/drugoverdose/epidemic/index.html

Kiyatkin, E. A. (2019). Respiratory Depression and Brain Hypoxia-Induced by Opioid Drugs: Morphine, Oxycodone, Heroin, and Fentanyl. Neuropharmacology, 151(443), 219–226. https://doi.org/10.1016/j.neuropharm.2019.02.008

Tolf, S., Mesterton, J., Söderberg, D., Amer-Wåhlin, I., & Mazzocato, P. (2020). How can Technology Support Quality Improvement? Lessons Learned from the Adoption of an Analytics Tool for Advanced Performance Measurement in a Hospital Unit. BMC Health Services Research, 20(1), 1–12. https://doi.org/10.1186/s12913-020-05622-7

van Rooden, S. M., Aspevall, O., Carrara, E., Gubbels, S., Johansson, A., Lucet, J. C., Mookerjee, S., Palacios-Baena, Z. R., Presterl, E., Tacconelli, E., Abbas, M., Behnke, M., Gastmeier, P., & van Mourik, M. S. M. (2021). Governance Aspects of Large-Scale Implementation of Automated Surveillance of Healthcare-Associated Infections. Clinical Microbiology and Infection, 27, S20–S28. https://doi.org/10.1016/j.cmi.2021.02.026

Vincent, C., Carthey, J., Macrae, C., & Amalberti, R. (2018). Safety Analysis Over Time: Seven Major Changes to Adverse Event Investigation. Implementation Science, 12(1), 1–10. https://doi.org/10.1186/s13012-017-0695-4

World Health Organization. (2021). Opioid Overdose. https://www.who.int/news-room/fact-sheets/detail/opioid-overdose

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