Root Cause Analysis is a systematic approach to understanding the causes of an adverse event and identifying system flaws that can be corrected so that the error does not repeat itself (Root Cause Analysis). This approach is retrospective; that is, it studies the events of the past. A single linear cause seldom dictates many health care accidents. An integrated system is used, which includes the main six stages. The first step is to determine what happened. In the next step, the ideal outcome of the incident understudy is formulated. The third stage involves untwisting the causal relationships that led to the accident. It also highlights seven factors that can contribute to medical error. In the fourth step, the resulting chain of events is analyzed in direct order of time, identifying the error causes. In the next step, recommendations and suggestions are written out that will help to avoid this case in the future. There are nine main categories of requests, each of which deserves attention in one issue or another. Finally, the last stage involves writing the plan for further improvement by other teams and transferring it to the necessary institutions for implementation.
It is necessary to parse the provided scenario using this approach. Mr. B., 67, died suddenly after arriving at the hospital complaining of pain in his leg. Before that, while the son was in the ward with Mr. B., a warning signal from automatic health control devices sounded twice. After these signals, the patient was defibrillated, various drugs were administered to him, and he was transferred to a specialized institution. Previously, Dr. T. administered a double dose of diazepam and hydromorphone to relieve pain and sedation. A little earlier, Dr. T. was occupied with two other patients while Mr. B. was in the triage ward, where his health indicators were analyzed.
In the ideal development of events, Mr. B. should have been examined immediately, constantly monitoring his health indicators with all possible devices. It should be noted here that the hospital applied a policy of moderate sedation and analgesia, which involves the patient being on continuous B / P, ECG, and pulse oximeter throughout the procedure until the discharge criteria are met. After the first warning signal, the nurse should have transferred Mr. B. to the intensive care unit under the supervision of Dr. T. As a result of all measures. The patient would have remained alive and continued treatment under the control of the medical staff.
However, these actions were not taken because the medical staff was busy with other patients who also required urgent care. Both nurses discharged other people during the patient acceptance process. Dr. T. also responds to reports from emergency rescue paramedics traveling with a 75-year-old patient with acute respiratory distress syndrome. Thus, here we can single out the organizational factor that led to negative consequences.
As for recommendations, the following should be highlighted. Firstly, it is necessary to retrain the staff of the already existing policy of moderate analgesia, which requires constant hardware monitoring of health indicators. Second, there is a need to consider a plan to expand or optimize the performance of nursing staff in complicated situations. Finally, third, simplify the policy compliance process by approving double-checking activities and introducing checklists or mnemonic devices.
Lewin’s Change Theory
Applying the Kurt Lewin model, the defrost stage involves discussing a staff optimization plan and consolidating the current hospital policy. During the movement phase, various approaches to double-checking and cognitive aids are tested. Finally, during the freeze phase, new rules are established and monitored for possible new errors.
Failure Modes and Effects Analysis (FMEA) is a systematic, proactive method of evaluating a process to determine where and how it might fail and to assess the relative impact of different failures to determine which parts of the change process are most in need (Failure Modes and Effects Analysis) Below is a table of analysis of this situation, which lists the identified problems
Table 1. FMEA Model for Scenario
|Steps in the Process||Failure Mode||Failure Causes||Failure Effects||Occurrence||Detection||Severity||Risk Profile Number||Actions to Reduce|
|Adherence to the hospital’s analgesic policy||Staff may not use all hardware to measure health indicators||Without patient B/P or ECG data, an incorrect treatment sequence is possible||The patient can die||4||6||10||240||Staff education|
|Optimization of personnel activities||Staff may miss-prioritize patient care||Delay can worsen the patient’s condition||The patient can die||8||8||10||640||Developing a plan or expanding staff|
|Double-check activities||Human factors can lead to neglected monitoring of any indicator of health||Without patient B/P or ECG data, an incorrect treatment sequence is possible||The patient can die||5||4||5||100||Double-check all possible important decisions|
Testing the proposed plan is possible by assessing the rate of discharged (cured) patients. Also, the results of double-checking and cognitive aids will be tested by asking staff about the convenience and benefits of this approach. Finally, the leadership qualities of the professional nurse will play an essential role in optimizing staff actions and monitoring compliance with hospital policy. Providing quality patient care directly depends on minimizing errors in the above problems, and therefore, treatment results will improve.
Root Cause Analysis. (n.d.) Institute for Healthcare Improvement. Web.
Failure Modes and Effects Analysis. (FMEA) Tool. (n.d.) Institute for Healthcare Improvement. Web.