Statistical_Thinking_in_Healthcare

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Statistical_Thinking_in_Healthcare

Case Study: Statistical Thinking in HealthCare

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Any Pharmacies in the world can encounter problems during their day-to-day operations. In the case study provided, Ben Davis is a pharmacist assistant in an irregular problem. His manager, Juan de Pacotilla, fears to lose his job in case an improvement is not done to the day-to-day operations. Juan asks Ben to help him find an opportunity for improvement in the process of filling prescriptions. This case study will provide an explanation to the issue of medication errors that are dispensed in HMO pharmacy. Despite the dispensing error rates being low, more enhancements in pharmacy distribution systems are vital since the pharmacies dispense large volumes of medicines that even a low error can render into a huge number of error which in return may equate to great amounts of lawsuits equaling even bigger sums of money. Advanced research is needed into dispensing errors in and out- patient health care settings, such and community pharmacies worldwide (Salmasi, Long & Khan, 2016).

There are six types of errors that can take place within the pharmacological chain and pharmaceutical patient care thus: dispensing errors, transcription errors, prescribing faults, administration errors, across setting errors and prescription errors. A dispensing error can be described as a discrepancy between the prescription and the medication that the pharmacy distributes to the patient or to the ward on the root of this prescription, such as the dispensing a medicine with substandard pharmaceutical or informational quality (Chua & et.al, 2003).

When dispensing, errors are well-thought-out from the viewpoint that the quality of all pharmacy care on goings should be guaranteed by the pharmacist, this list can be prolonged by the addition of three other groupings: lack of detecting and correcting a prescribed error before dispensing; lack of detecting a manufactured error before dispensing; and lack of providing satisfactory patient counseling so as to prevent administration errors (Teagarden & et.al 2005). These error groupings occur in other sections of the pharmaceutical patient care chain however; they are nonetheless significant when one attempts to do a full assessment of the performance of the pharmacy.

The classifications of dispensing errors are as follows: When medicine is dispensed to the wrong patient, when wrong the medicine is dispensing, When a poor or stronger drug is dispensed, when medicine is dispensed at the wrong time, When wrong quantity of medicine is dispensed as well as the wrong dosage form, when an expired or almost to expiry medicine has been dispensed, if there has been a failure or an omission to dispense, inferior quality of medicine being dispensed an inaccurately compounded medicine being dispensed, wrongly labeling information when dispensing (Anacleto & et. Al, 2007).

Below is a process map describing the prescription filling process for HMO’s pharmacy, that specifies the major problems that the HMO’s pharmacy experiences

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Suppliers

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bill

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Below, is a diagram showing the use of the supplier, input, process steps, output, and customer (SIPOC) model to analyze the HMO pharmacy’s business process.

Process Map for filling a Prescription at HMO Pharmacy

The Causes of dispensing errors can be outlined by making inquiries from the practicing pharmacists through means of a survey or through root-cause analysis. A survey will measure the opinions and perceptions of the pharmacists while the root-cause analysis may come closer to reality. An example is a study done in a UK hospital in which the researchers uses semi structured interviews of pharmacy staff about self-reported dispensing (Anacleto & et. Al, 2007). Totally there were 106 error-producing conditions mentioned in these interviews. The most common causes of error that were mentioned from the most to the least included: being busy (21%), less operating staff members (12%), time limited (11%), tiredness of healthcare providers (11%), disruptions during dispensing (9.4%), and medicines that look-alike/sound-alike (8.5%) (Rickrode & et.al, 2007).

The process has been broken down into various groupings Based on the process map and research done on the subject of errors in medication dispensing cycle. Thus, Ordering, Transcribing, Dispensing, and Administering. In each of these four steps, there are a lot of probable areas for errors to take place. To begin with the ordering process, one can see, a wrong drug, a wrong dose, wrong route/form, an allergy or drug interaction. Secondly, the transcribing process, one can see a wrong dose, wrong patient, wrong route, wrong time, and wrong drug errors occurring (Knudsen et.al, 2007). Dispensing can have errors in wrong patient, wrong dose, wrong time, wrong route, incorrect labeling/drug ID, and allergy/drug interaction. Lastly, administering errors can entails, wrong dose, wrong patient, wrong drug, wrong route, wrong time/omitted and often consists of infusion pumps. Pharmacies have brought about various methods and strategies to reduce dispensing errors, depending on the various working stages of the pharmacies in the medication procedures and the progress of information technologies over the years (Beso, Franklin &Barber, 2005).

In a certain study, a research team investigated self-reports of community pharmacies to find the causes of dispensing errors. The research team recognized four causes: unreadable/ poor handwriting; look-alike and sound-alike medications; lack of operative controls; and lack of attentiveness caused by interruptions (Chua & et.al, 2003).

Medication dispensing has several effective alternatives that can reduce error rates. The use of bar code system which has helped reduce the dispensing error in US hospitals. The use of semi-automated medication cabinets from the use of carousel fill process help reduce rate of dispensing errors from (0.25 to 0.08) % as opposed to the 2 day manually shelving process.

Medication orders which were not automated and not readily available on patient care units are ordered as prescription requests and are faxed by pharmacists. The rate of dispensing error increases because once orders are filled they have to be verified and then transported. The rate of incorrectly filled orders would also increase from an average (2.1 to 2.3) %.

The interdepartmental request fill is a process where medication orders come from departments or clinics associated with the hospital such as cancer center, pain, neurology and others. The dispensing error was noted to be a minimum without the automated system. Despite the zero-margin error when an automated pharmacy carousel system was implemented in the clinics a quantity discrepancy was identified. This was caused by requests which only documented the dispensing errors because of the interdepartmental fills (Salmasi, Long & Khan, 2016). The automated pharmacy carousel system can also consist of bar code scanner, label printer, barcoded medication bins that allow an interface between both in the hospitals pharmacy information system. To finalize the study implementation of a computerized drug interaction system was used and measured in three periods. The first period the pharmacies implemented system but not physicians, second period pharmacies used the system and an average number of physicians, third period the pharmacies and the physician practices used the system. The interaction rate between the second and the third were the highest as compared to the first period and was reduced by an average percentage (Rickrode & et.al, 2007).

In conclusion, the rates of dispensing errors can only be reduced by implementation of an automated system. Most HMO pharmacies have various processing systems for pharmacy distribution but the need for improvement is very important. The checking of prescriptions has to be implemented to reduce the prescription errors and strategies should be implemented and correctly communicated to prevent administrative errors (Beso, Franklin &Barber, 2005).

References

Anacleto, T. A., Perini, E., Rosa, M. B., & César, C. C. (2007). Drug-dispensing errors in the

hospital pharmacy. Clinics, 62(3), 243-250. doi:10.1590/s1807-59322007000300007

Beso, A., Franklin, B. D., & Barber, N. (2005). The Frequency and Potential Causes of

Dispensing Errors in a Hospital Pharmacy. Pharmacy World & Science, 27(3), 182-190. doi:10.1007/s11096-004-2270-8

Chua, S., Wong, I. C., Edmondson, H., Allen, C., Chow, J., Peacham, J., . . . Grantham, J.

(2003). A Feasibility Study for Recording of Dispensing Errors and ???Near Misses??? in Four UK Primary Care Pharmacies. Drug Safety, 26(11), 803-813. doi:10.2165/00002018-200326110-00005

Costa, L. A., Valli, C., & Alvarenga, A. P. (2008). Medication dispensing errors at a public

pediatric hospital. Revista Latino-Americana De Enfermagem Rev. Latino-Am. Enfermagem, 16(5), 812-817. doi:10.1590/s0104-11692008000500003

Knudsen, P., Herborg, H., Mortensen, A. R., Knudsen, M., & Hellebek, A. (2007). Preventing

medication errors in community pharmacy: Frequency and seriousness of medication errors. Quality and Safety in Health Care, 16(4), 291-296. doi:10.1136/qshc.2006.018770

Rickrode, G. A., Williams-Lowe, M. E., Rippe, J. L., & Theriault, R. H. (2007). Internal

reporting system to improve a pharmacy’s medication distribution process. American Journal of Health-System Pharmacy, 64(11), 1197-1202. doi:10.2146/ajhp060166

Salmasi, S., Long, C. M., & Khan, T. M. (2016). Interplay of medication errors and the

separation of dispensing. Research in Social and Administrative Pharmacy, 12(1), 171-172. doi: 10.1016/j.sapharm.2015.07.004

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