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An RCA, or root cause analysis, is performed after an event. It takes a step back and looks at what lead to the error, death, injury, etc. and helps prevent it in the future. It is estimated that 44,000 to 98,000 Americans die each year because of medical errors that are preventable, and that it costs the healthcare system around $29 billion (Spath, 2018, p. 194). An RCA team needs to be made up of those that are potentially directly or even directly involved in the event. In the case study they are looking at medication errors, with only two of the three directly involved parties it could benefit from a physician for input on their end of the flow. If medications are difficult to find for the physician, it may also have an effect downstream. Also, in the chart it shows that scanners are defective more often than any other error. If an IT person were available to consult, even over the phone, it would assist in finding out why the scanners keep breaking. It may even be safe to say that the LASA or look-alike-sound-alike drugs and the manual entry errors would be avoided if the scanners worked.
The meeting started off with both parties on the offensive. It quickly changed when they all realized the objective is not to blame but come up with solutions that work for all parties. The goal for all parties involved was patient safety and a reduction to elimination of medication errors. Both parties directly involved wished to be heard and once they felt they would be the willingness to work together became possible. With making the charts to analyze the process, find the most common reasons for errors, and cause/effect leading to the increased number of errors it helped narrow down where and when the errors started. These are very effective tools to determine where to focus efforts for possible training needs and staffing needs.
I have experienced this scenario when our facility first changed EMRs. We purchased all new updated equipment to facilitate ease of medication administration and while not the top of the line it was new and should have functioned. Within the first six months over half the scanners were broken. We were told we must scan our medications to prevent errors but when they just did not work, we did what we had to, and we had more errors. The scanners were under a warranty, so our facility exchanged them for something else, and now they work more often than not. Another topic that was reoccurring was pharmacy burn out. It appears they need better staffing ratios and more ability to have time off. This is tied with the second highest cause of errors so it must get addressed to prevent continuing errors even if the scanners are fixed.
A Root Cause Analysis occurs after a sentinel event. In this case study, a medication error occurred at Downtown Medical, where a patient was administered the incorrect medication. The provider ordered Ultram 50 mg every 6 hours for pain. The medication scanner wasn’t working, so the nurse entered the internal entry number (IEN) into the computer; the computer registered the medication as Ultracet 37.5 mg/325 mg, but the package said Ultram 50 mg. The nurse called the pharmacy and is informed by the pharmacist that because there is only one number difference between these two medications and that the package says that it is Ultram, that it must be Ultram and to administer the medication. The nurse gives the drug, and the patient has an allergic reaction because of a recorded allergy to acetaminophen. A medication error incident report is filed, and a Root Cause Analysis is completed (Walden University, 2016a).
The Root Cause Analysis team consists of the facilitator or risk manager who organizes the meeting and collects information from team members for patent safety. Another RCA team member should be an RN who works full time on the unit who can provide expertise on the scanner and medication administration process. A pharmacy technician would need to be interviewed about how the medication machine is filled in the medication room. The nurse who administered the medication and the pharmacist who spoke to her about the medicine need to be interviewed to determine what led to the error (Walden University, 2016a).
In the video, the pharmacy tech and staff nurse started at odds but eventually agreed on common areas that needed to be improved. Once the facilitator explained what the goal was to be and that they would take the information back to their departments, they were more at ease, and both found that their departments are significantly understaffed. The charts that were created, the Fishbone Cause and Effect, the Pareto, and the Process Flow Chart came from the collaboration with their departments.
The Fishbone Cause and Effect Chart is easy to read and lists why medication errors occur (Walden University, n.d.). It contributes to the Root Cause Analysis by breaking down three significant areas that contributed to including human factors from the pharmacy side, human factors from the nursing side and equipment, and supplies. Some specific causes include look-alike medications, scanners failing to scan, unit dose machines breaking down, and workaround for nursing with a manual entry for medication internal entry numbers (Walden University, n.d.).
To prevent medication errors from occurring in the future, pharmacy needs to ensure that barcode label scanners are in working order and that pharmacists are accessible for nurses to reach by phone. Nurses should be double-checking allergy lists and checking with their charge nurses and pharmacy if they’re feeling uncomfortable with any medication administration. They should also be using the seven rights of medication administration every time they administer a medication. Using these techniques, medication errors should decrease significantly, and patient safety should increase.
Walden University (2016a). Root cause analysis at Downtown Medical [Interactive file]. Walden University Blackboard. https://class.waldenu.edu
Walden University (2016a). RCA dramatization 1 [Video]. Walden University Blackboard. https://class.waldenu.edu
Walden University (n.d.). Fish Bone: Cause Effect Diagram [Document]. Walden University Blackboard. https://class.waldenu.edu