Identifying and Fixing Errors

Statistics in Healthcare The author of this report has been presented with a case study scenario that involves one Ben Davis and another man named Juan de Pacotilla. The former is a young student who has just completed a Statistical Thinking for Business Improvement course and the latter is a pharmacy manager who is ostensibly about to lose his job due to a glut of errors relating to the dispensing of medications that are either the wrong drug or the wrong dosage of the right drug.

Juan has spoken to another statistician but the person has been less than helpful in relation to this problem and Juan is now desperate. He sees Ben as a closer ally because Ben actually works in the pharmacy and thus sees thing first-hand. The ostensible task that Ben has been given is to nail down precisely what is going wrong using statistical data and help noticeably reduce the error rate using the data gleaned from the statistical research.

While some may be daunted by the problem presented in this case, the way to figure out the problem is not all that hard. Analysis The author of this report has first constructed and drawn out a simple process map. This map is shown in the appendix. It shows the basic steps involved with each prescription. To state the obvious, if an error is made it will happen at one or more of those different points in the process.

For example, one potential error point might happen when translating a prescription from a hand-written slip to the system. Indeed, the drug name itself might be copied correctly but the number of doses per day or the amount per dose may be read wrong. Another example of a point at which someone can make a mistake is by reading the prescription wrong after it is in the system while it is being filled.

The thing about this how process is that the two points above are really the only two points where an error could be made. As such, nailing down what precisely is going wrong should not be all that hard to pull off. The first step will be to focus on the prescriptions as they are received. So often, prescriptions are mostly printed out (except for the signature of the physician or practitioner, obviously), they are phoned in or they are sent entirely electronically.

The last of those three should be the most fool-proof given that if anyone makes an error with that prescription, it would probably be the by the doctor and not the pharmacist. Regardless, if there is any doubt about the prescription, there should be research done regarding the perceived accuracy of the slip or other information form that is presented. The history of a person's prescriptions are often a very good clue.

If a person is taking a medicine on a consistent basis, there will likely not be a change unless there is a medical reason for it. If there has been a change, the patient will probably know about it and the patient can be asked. To be even surer, the pharmacy can reach out to the doctor before even filling the prescription to ensure that the prescription was filled out right and/or is being read correctly.

It should be noted that the use of digital prescriptions should be pushed by the pharmacy given that the error/problem rate would be so much lower (HRSA, 2015) Once that threshold is surpassed, there can be a verification that what was keyed into the system matches what was filled. Assuming all is order, the prescription can be filled. Each filled prescription should then be double-checked by a second set of eyes to ensure that the drug and dosage on the bottle is what is in the prescription.

Again, if there are any red flags, they should be figured out as soon as they are identified. As touched upon before, the customer should be asked to confirm that they are expecting a change in dosage or drug. For example, if a person shifts from Zoloft to Celexa, this should be confirmed. If they are shifted from one dosage level of those drugs to another, that should also be confirmed (THA, 2015). If/when an error is made, it needs to be figured out where the mistake occurred.

As noted already, this could happen if/when a prescription is misread or it would happen when the wrong drug is filled despite the prescription being ordered as desired. There is also a possibility that the doctor or practitioner sent the wrong data. Regardless, each and every error should be documented including where in the process there was a breakdown. If the doctor made the goof, this should be documented.

If a document or computer screen was misread, a verification left undone and so forth, that should be documented for each and every case. Further, the person or persons at fault for the error should be identified in each case. In short, the nature of the error and who made the miscue should be documented every single time. If a certain person is making too many errors, they can be retrained or even disciplined/fired if they cannot or will not reduce eliminate their errors.

The statistical observation and tracking must be spot on and it should be exhaustive. This will help document who or what is causing the errors and thus will provide documentation for when someone.