Statistical Thinking in Health Care

The process map of the prescription filling process for the Health Maintenance Organization (HMO) is shown below: 

Pharmacist assistant receives medication 

Physician enters the prescription 

Physician selects medication and dosage 

Physician determines medication required 

Assistant gives medication to the patient 

Assistant hands prescription to pharmacist 

Pharmacists hand medication to assistant 

Assistant checks prescription 

Pharmacist selects the medication 

Pharmacist measures the medication 

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The SIPOC model, comprising supplier, inputs, process steps, outputs, and customers) for the HMO is shown below: 

The process map and the SIPOC mode shows the entire services offered by the HMO pharmacy. The map shows the points along the process that represent the five SIPOC elements (Britz et al., 1997). To understand the cause of the prescription errors, it is vital to analyze the SIPOC model of the pharmacy. The model starts with the doctor prescribing the medication and the accurate dosage to the patient. The patient giving medication to the pharmacy assistant at the pharmacy counter follows it. The assistant then inputs the prescription onto the system and hands over to the pharmacist. Finally, the assistant prepares the medication and hands it to the patient. 

After analyzing the process and the SIPOC model, it is evident that the causes of the prescription inaccuracies reside in many areas of the model. First, the pharmacists do not verify the prescription. The pharmacist must check the information presented by the patient at the counter against the doctor's notes to ensure that they are prescribing the right medication. Errors may be caused by the pharmacist's failure to interpret the doctor's prescription due to poor handwriting (Britz et al., 1997). 

Secondly, poor data management characterizes the pharmacy’s process model. At no point is the prescription checked against the patient's record to ensure that medication is not swapped with another patient's medication. Since pharmacy assistants do the computer entry all medications, they must check the information against the patient's records to prevent swapping medications. Furthermore, checking prescriptions against the patient's record ensures that the right medication is prescribed because pharmacist assistants may not understand all the medical terminologies, drug interactions, and all brand names. 

Another cause of the prescription errors may be due to the pharmacists' failure to measure medication accurately. It is possible that the equipment used by pharmacists to measure the medications are faulty. The errors may also be due to giving the wrong medication to the pharmacy assistant at the output stage to give it to the patient. Failure to verify that the medication is given to the right patient may lead to swapping of medications at the counter. Finally, there is no evidence of excellent customer service at the pharmacy. The HMO should strive for excellent customer service, which is associated with all successful businesses (Hoerl & Snee, 2012). The HMO needs to provide excellent customer services by describing to patients how to take medication and to seek medical assistance in case of adverse effects. Failure to provide clear and correct instructions to the patient regarding drug use may lead to adverse effects, which in turn contribute to complaints against the HMO. It is possible to assume that adverse effects experienced by patients were the cause of the complaints that were exerting pressure ion the manager. 

The causes of the incorrect prescriptions at the pharmacy are common causes. They are common problems because failure to put proper measures can lead to their occurrence. Additionally, these problems are not exclusive to the HMO pharmacy alone because they can be experienced in any pharmacy. If these common causes are not eliminated or reduced, they can lead to special causes such as giving patients the wrong prescriptions, which can lead to adverse health conditions or even death. 

To come up with a solution, it is important that statistics about patient complaints are collected along all the phases of the PIPOC model. By analyzing the data collected, it is possible to determine where the errors occur along the SIPOC model. The HMO pharmacy can utilize data analysis tools like statistical Packages for Social Scientists (SPSS) to determine the relationship between inaccurate prescriptions and patient complaints. 

To solve the problem, the HMO pharmacy should replace manual prescriptions with an automated system comparing bar-code scanners, bar-coded medicine bins, a label printer, software that facilitates interface with the HMO's information system, and a drug interaction alerting system (Beso, Franklin, Barber, 2005). The automated system reduces the probability of erroneous prescriptions. Additionally, the pharmacy must flag medications that are easily confused due to similarities in name, color, or shape to avoid wrong prescriptions. It will enable pharmacist and pharmacist assistants to cross-check this medication before giving them to the patient. Finally, the HMO pharmacy needs to purchase digital measuring equipment to measure drugs accurately. 

Implementing statistical thinking in healthcare is important because it can help pharmacies reduce the probability of erroneous prescriptions (Hoerl & Snee, 2012). Implementing statistical thinking involves constant evaluations to ensure that points of errors along the SIPIC model are eliminated. Therefore, data collection about patient complaints will be critical in reducing errors because it allows pharmacies to identify the causes of incorrect prescriptions. Although various techniques for reducing incorrect prescriptions are available, automated systems offer the best chance of lowering inaccuracies. Automated systems reduce errors long the process map because it facilitates sufficient communication between doctors and pharmacy staff. 

References 

Beso, A., Franklin B.D., Barber N. (2005). The frequency and potential causes of dispensing errors in a hospital pharmacy. Pharm World Sci . 27:182–90. 

Britz, G.C., Emerling, D.W., Hare, L.B., Hoerl, R.W & Shade, J.E (1997). "How to Teach Others to Apply Statistical Thinking." Quality Progress ; 67--80. 

Hoerl, R., & Snee, R. D. (2012). Statistical Thinking: Improving Business Performance . New York: Wiley.