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    Ben Davis had just completed an intensive course in Statistical Thinking for Business Improvement, which was offered to all employees of a large health maintenance organization. There was no time to celebrate, however, because he was already under a lot of pressure. Ben works as a pharmacist’s assistant in the HMO’s pharmacy, and his manager, Juan de Pacotilla, was about to be fired. Juan’s dismissal appeared to be imminent due to numerous complaints and even a few lawsuits over inaccurate prescriptions. Juan now was asking Ben for his assistance in trying to resolve the problem, preferably yesterday!

    “Ben, I really need your help! If I can’t show some major improvement or at least a solid plan by next month, I’m history.”
    “I’ll be glad to help, Juan, but what can I do? I’m just a pharmacist’s assistant.”
    “I don’t care what your job title is; I think you’re just the person who can get this done. I realize I’ve been too far removed from day-to-day operations in the pharmacy, but you work there every day. You’re in a much better position to find out how to fix the problem. Just tell me what to do, and I’ll do it.”
    “But what about the statistical consultant you hired to analyze the data on inaccurate prescriptions?”
    “Ben, to be honest, I’m really disappointed with that guy. He has spent two weeks trying to come up with a new modeling approach to predict weekly inaccurate prescriptions. I tried to explain to him that I don’t want to predict the mistakes, I want to eliminate them! I don’t think I got through, however, because he said we need a month of additional data to verify the model, and then he can apply a new method he just read about in a journal to identify ‘change points in the time series,’ whatever that means. But get this, he will only identify the change points and send me a list; he says it’s my job to figure out what they mean and how to respond. I don’t know much about statistics — the only thing I remember from my course in college is that it was the worst course I ever took– but I’m becoming convinced that it actually doesn’t have much to offer in solving real problems. You’ve just gone through this statistical thinking course, though, so maybe you can see something I can’t. To me, statistical thinking sounds like an oxymoron. I realize it’s a long shot, but I was hoping you could use this as the project you need to officially complete the course.”

    “I see your point, Juan. I felt the same way, too. This course was interesting, though, because it didn’t focus on crunching numbers. I have some ideas about how we can approach making improvements in prescription accuracy, and I think this would be a great project. We may not be able to solve it ourselves, however. As you know, there is a lot of finger-pointing going on; the pharmacists blame sloppy handwriting and incomplete instructions from doctors for the problem; doctors blame pharmacy assistants like me who actually do most of the computer entry of the prescriptions, claiming that we are incompetent; and the assistants tend to blame the pharmacists for assuming too much about our knowledge of medical terminology, brand names, known drug interactions, and so on.”
    “It sounds like there’s no hope, Ben!”

    “I wouldn’t say that at all, Juan. It’s just that there may be no quick fix we can do by ourselves in the pharmacy. Let me explain how I’m thinking about this and how I would propose attacking the problem using what I just learned in the statistical thinking course.”

    Source: G. C. Britz, D. W. Emerling, L. B. Hare, R. W. Hoerl, & J. E. Shade. “How to Teach Others to Apply Statistical Thinking.” Quality Progress (June 1997): 67–80.

    Assuming the role of Ben Davis, write a three to four (3-4) page paper in which you apply the approach discussed in the textbook to this problem. You’ll have to make some assumptions about the processes used by the HMO pharmacy. Also, please use the Internet and / or Strayer LRC to research articles on common problems or errors that pharmacies face. Your paper should address the following points:

    Develop a process map about the prescription filling process for HMO’s pharmacy, in which you specify the key problems that the HMO’s pharmacy might be experiencing. Next, use the supplier, input, process steps, output, and customer (SIPOC) model to analyze the HMO pharmacy’s business process.
    Analyze the process map and SIPOC model to identify possible main root causes of the problems. Next, categorize whether the main root causes of the problem are special causes or common causes. Provide a rationale for your response.
    Suggest the main tools that you would use and the data that you would collect in order to analyze the business process and correct the problem. Justify your response.
    Propose one (1) solution to the HMO pharmacy’s on-going problem(s) and propose one (1) strategy to measure the aforementioned solution. Provide a rationale for your response.
    Use at least two (2) quality references. Note: Wikipedia and other Websites do not qualify as academic resources.

    Your assignment must follow these formatting requirements:

    Be typed, double spaced, using Times New Roman font (size 12), with one-inch margins on all sides; citations and references must follow APA format. Check with your professor for any additional instructions.
    Include a cover page containing the title of the assignment, the student’s name, the professor’s name, the course title, and the date. The cover page and the reference page are not included in the required assignment page length.

    The specific course learning outcomes associated with this assignment are:

    Describe how organizations use statistical thinking to be more competitive.
    Apply the basic principles of statistical thinking to business processes.
    Apply the SIPOC model to identify OFIs in business processes.
    Use technology and information resources to research issues in business process improvement.
    Write clearly and concisely about business process improvement using proper writing mechanics.






Subject Nursing Pages 5 Style APA


Statistical Thinking in Healthcare (Case Study)


Statistics emerges as a servant discipline that gains relevance in almost all fields including healthcare. For successful application of various notions that are encountered it is imperative to recognize the primacy of the domain’s problem context. This is so because every problem that an applied statistician addresses is usually embedded in a bigger problem, one that could be referred to as the ‘real problem’. Statistical investigations are often carried out since people consider their context knowledge inadequate for their expected and desired uses. As such, the investigations act as a basis for particular actions and decision-making as well as deeper understanding of the prevailing circumstances. This acknowledgment of the role of statistical investigations is used as a point of departure to explore the case study presented, and as such present a suitable approach to the problem at hand. Ben Davis, a pharmacist’s assistant has been approached by Juan, his manager, and is expected to apply his statistical thinking knowledge to give the best approach that would help resolve the problem. Juan faces imminent dismissal due to several complaints and a few lawsuits arising over inaccurate prescriptions. Unless he shows major improvements by next month, he will be dismissed. In this construction, one assumes Ben’s position to develop a process map about the HMO’S pharmacy prescription filling process and use the SIPOC model to analyze it.

In  order that the pharmacy process is improved, need arises to adopt a suitable data driven methodology  that would help identify and eliminate errors or defects within the process. In the context of the assumptions to be made as regards the prescription process under focus, an aspect of the SIPOC model thought applicable is the DMAIC approach. It is indeed suitable especially because of the manner in which it would help identify and define key issues in the process of interest. In as much as it is mostly undertaken to improve profits and reduce costs, it is relevant in the case study when considering the emphasis it places upon customer satisfaction (in this case patient/client satisfaction) (Barone, & Franco, 2012). A data-driven systematic process and improvement cycle, it delivers measurable results and accelerates change. Its flow is as shown below:



MEASURE                    CONTROL


ANALYZE                IMPROVE

The approach involves first defining the case of interest. Here, it appreciated as being that of Juan and the situation he is facing. In other words, the entire prescription filling process that he is part of leaves a lot to be desired. To explore probable solutions, key issues or problems arising in its context must be identified. That would make easier to have the problem clearly stated as that would in turn be imperative in determining what is  critical to quality. One problem that has been identified in the case under study is that of errors arising due to sloppy handwritings by doctors.  It is also possible that from the climate described, patients do not get their deliveries on time, or wrong medications are issued.  A direct result of these is a fall in nursing expectation and general productivity. Other possible problems become clear from a suitable process map for the prescription process. It is presented below.

Note: This process map outlines the prescription process for inpatients.

Order delivered

 Order filled by technician

Label prints in pharmacy

Order verification by pharmacist

Medication order received





From the above process map, the following identified failure modes are clear:

  • Inaccurate/incomplete orders on admission; such call for correction through the pharmacist’s intervention
  • Inaccuracy of due times; such could also be inconsistently entered
  • Lack of tracking of the delivery process
  • Multiple and/or invalid delivery locations
  • Error or confusion by pharmacist during order verification

From the failure modes identified, root causes include sloppy handwritings by doctors, inaccurate or inconsistent entry of delivery times, lack of process visibility, invalid delivery locations, and staff confusion of priorities as well as other human errors . Notably, all that occur due to human error are common causes whereas the rest are special causes. In coming up with possible measures, one must explore the core metrics of the situation or problem. Each metric should be defined and a relevant baseline for each determined. The current state of the process must be mapped out. In the mapping out, care should be taken to avoid regarding the process as it assumed to be, or as it should be. Individuals who understand how the process works should be included since they possess good working knowledge of the same.

Imperatively, statistical thinking is of central interest.  It is in this respect that all relevant data should be collected and analyzed and investigations summarized (Britz, et al., 1997). Such data include the frequency of occurrence of each of the identified problems, causes the problems can be linked to, staff knowledge and competency, and the nature of working relationships amongst staff just to mention but  a few. Root cause analysis should then follow and that should be validated appropriately.  Numerous tools can be employed here including run charts, cause-and-effect diagrams, and the 5 whys. In efforts to make improvements, potential solutions  should be brainstormed, as this would ensure the best decisions are made. The cost, benefit, risk, and complexity of each improvement measure should be explored.  Importantly, solutions should be prioritized (interim Vs long-term solutions). Good solutions should be comprehended and supported by the health organization (Warholak, & Nau, 2010). It should address the various problem containment issues and focus on the elimination and prevention of the root causes. It must also be durable and address the problem for a long time to come.

In the case under focus, a good solution would be to bridge the gap between doctors and pharmacist by ensuring pharmacist are more acquainted with medical terminologies, brand names, and known drug interactions.  This is not to say they are less competent, rather if this is a common cause of problems it should be tackled as such. Doctors could also be talked to so as to see to it that they do not exaggerate their sloppy handwritings. The essence of writing anything is to communicate. If what they write is not readable then their work and that of others becomes fruitless.   As for the inaccurate time entries, a solution would be to enter accurate due times into the pharmacy information system.

Just to focus on the solution suggested for solving the issue of inaccurate due times, the stability of the solution can be determined by employing one or more types of controls. They include documentation (written procedures, process flows), measurement based (scorecard), design (error-proofing),  and periodic checks. Suitable standardization measures should be adopted and such entail relevant technology.

For greater success in the process described in particular and others in the organization, it is important to ensure visibility even as standardization efforts are made. The prescription process should incorporate more staff education to avoid confusions that may arise as insinuated in this construction. Indeed, statistical thinking calls for the employment of such a systemic approach and data driven improvement cycle as described here.  Other aspects of SIPOC are equally important and should be considered in the healthcare setting. However, owed to the scope of this paper, it may not be possible to examine them exhaustively.







Barone, S., & Franco, E. L. (2012). Statistical and managerial techniques for Six Sigma methodology: Theory and application. Chichester, West Sussex, United Kingdom: Wiley.

Britz, G., Emerling, D., Hare, L., Hoerl , R., & Shade, J. (January 01, 1997). How to Teach Others to Apply Statistical Thinking.  Quality Progress, 30, 6,67-80.

Warholak, T.L., & Nau, D.P. (2010). Quality and safety in pharmacy practice. New York: McGraw Hill Medical.








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