Research Paper on Statistics on Health Care Prescription Errors

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23 November 2015

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Research Paper on Statistics on Health Care Prescription Errors


Relation between Error in Healthcare prescription and the inconsistency in Technological information

Background Information

       A lot of errors are occurring within the healthcare field lately. They result from many factors. Among the principle causes of error are related to wrong prescriptions. As indicated by Benjamin (770), one of the elements that play a critical role in this is the use of advanced technological methods. Computers have been used to aid in the computerized entry of prescription orders. For instance, Walgreens pharmacy, where I work is an online drug store that allows customers to purchase drugs over the internet. This poses a great danger of wrong order interpretations, inconsistencies and misfills. In the past, these have resulted in the possession of dangerous drugs, dosing errors and other mix-ups.Depending on the intensity of the prescription, they can result in severe injuries on the patient or even lead to fatality incidences. In turn, they lead to unnecessary court cases and legal suits that eventually cost many healthcare institutions and practitioners a lot of funds that are paid to cater for the damages (Carroll 52-8). For this, there is a necessity to examine the main causes of faulty prescriptions to ensure that such avoidable consequences are kept at their possible minimal rates. This paper explored the occurrence of prescription errors as a result of order entries at Walgreens. The principleconcerns that were dealt with in this study include:

What are the common causes of drug inconsistencies at the pharmacy?

What kind of information technology is used in the provision of proper prescription?

Are there specific actions that are related to inconsistently provided information in the same prescription order entry?

What dispensing errors are most likely to occur in an online drug store?


       The study was prospective as it was comprised of 20 pharmacists from medical centers and Walgreens chemist, which is an online store based in Wasilla in Alaska. For approximately 2 months, they issued a report about the inconsistent order entry of prescriptions. It was principally based on communication. As such, both primary and secondary data collection methodswere employed. Therefore, it included the use of surveys for the collection of first-hand information. In this sense questionnaires and interviews from the participantswereused to gather information for the data. For accuracy and proper validation, these were combined with secondarysources such as the national health statistics (Wu, Pronovost, Morlock 88). It involved the selection of 30 electronically retrieved prescriptions from the free text field for any comments on prescription errors with regard to Walgreens pharmacy. Thus, the study entailed the overall evaluation of 60 prescription records.

Data collection

       The data was used to capture the medication, focus dispensing errors and the types of inconsistencies in error. Among the elements to considered included dosage, incorrect drug, wrong quantity, inappropriate, inadequate and incorrect labelling. The other elements that caused inconsistencies were inadequate directions for use, inappropriate packaging, preparation and storage of medication before dispensing. It was necessary to use predictive values to determine when the prescriptive errors are likely to be higher.

Data analysis

       The data was entered in a Microsoft database. 30 records were selected randomly to validate the data. From research, 99.7% of these are expected to be correct. Descriptive statistics characterized inconsistency. Some of the determinants of error such as inpatients and outpatients, analgesics and antibiotics, those that are less frequently prescribed and those on high alert wereanalyzed. They will be provided for harm categories where t tests and χ2 tests will be used. Categorical variables made use of the Fisher test for categorical variables of 2 levels and the χ2 for those with more than 2. Statistical significance or α =.05 were applied to test predators with the Wald χ2 test. In this study, the regression model of multivariantlogistics method of data analysis will be used. The method will mainly identify different factors in communication prescriptive errors in relation to their severity. It will make use of a generalized approach with estimated equations.


       The results were filled in the table below:

       Similar names and packages Medications not commonly used or prescribed Commonly used medication where patients are allergic Medication that need proper testing for proper therapeutic administration Entry and confirmation of prescription Zeros and abbreviations Organized workforce and reduction of distraction and stress Patient counselling Storage

       Dispensing incorrect drug 40% 20% 2% 2% 10% 5% 10% 11% Dose 20% 30% 10% 5% 20% 10% 5% 5% Dosage form 8% 2% 1% 5% 50% 10% 20% 4% Quantity 1% 20% 1% 3% 10% 30% 20% 15% Administration time 1% 5% 3% 2% 10% 30% 40% 9% Wrong labeling 30% 30% 5% 2% 10% 5% `10% 8% Inadequate directions 5% 20% 10% 10% 5% 2% 10% 38% Inappropriate preparation, packaging and storage 20% 40% 5% 1% 1% 5% 29% 1% Graphical Representation of the results


       It was discovered that at a pharmacy such as Walgreens where about 250 prescriptions entries are made in a day, about 4 errors occur. Reports relate these to a higher rate of inconsistent communication. The principle cause was drug dosage. There were also some drugs that were associated with a higher rate of overdosing and incorrect prescriptions when compared to others. Thus, in relation to this study, it was evident that medical centers that have a higher flow of patients and the chances of admission have higher rates of errors when compared to other private clinics and chemists.


       It is important that the laid down professional ethics are adhered to in different fields. This is especially within the medical field where a slight mistake can lead to devastating consequences. Therefore, healthcare providers are always obligated to use the knowledge that they acquired in their studies as well as new knowledge and practices appropriately. They should ensure that drugs are prescribed in the most appropriate ways to avoid errors. In particular, computerized drug entries should be counterchecked to eliminate disparities. However, owing to the continuous change in the nature of disease processes and hence the production of advanced drug formulas, there is need to conduct more research. These will provide more guidance to guarantee safe drug prescription by providers of healthcare services using new technological methods.


       The employees at Walgreens need to reduce the rates of prescription errors to help retain customers and avoid unnecessary lawsuits. Some of the steps they can take are to ensure the correct entry of prescriptions. These should be confirmed. They should be careful with drugs that look alike and sound alike as well as take care with zeros and abbreviations. They should make the workplace organized and reduce distractions, stress and heavy workloads as much as possible. They should also ensure that drugs are stored properly and check all prescriptions. The most important thing is to ensure that patients are cancelled before taking the drugs.


Benjamin, D. M. Reducing medication errors and increasing patient safety: case studies inclinical pharmacology. Journal of Clinical Pharmacology.2003;43:768–83.

Carroll, P. Medication issues: the bigger picture.RN. 2003;66(1):52–8.

Wu, A. W., Pronovost, P., and Morlock, L. ICU incident reporting systems.Journal of CriticalCare. 2006;17(2):86–94

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Research Paper on Statistics on Health Care Prescription Errors. (23 November 2015). Retrieved from

"Research Paper on Statistics on Health Care Prescription Errors" StudyScroll, 23 November 2015,

StudyScroll. (2015). Research Paper on Statistics on Health Care Prescription Errors [Online]. Available at: [Accessed: 28 January, 2023]

"Research Paper on Statistics on Health Care Prescription Errors" StudyScroll, Nov 23, 2015. Accessed Jan 28, 2023.

"Research Paper on Statistics on Health Care Prescription Errors" StudyScroll, Nov 23, 2015.

"Research Paper on Statistics on Health Care Prescription Errors" StudyScroll, 23-Nov-2015. [Online]. Available: [Accessed: 28-Jan-2023]

StudyScroll. (2015). Research Paper on Statistics on Health Care Prescription Errors. [Online]. Available at: [Accessed: 28-Jan-2023]

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