Sample Healthcare Paper on The Effectiveness of Pyxis Machine in all Patients’ Rooms

Title: How the Pyxis Machine can prevent medical errors

Thesis: Inspecting the effectiveness of using Pyxis machines in all patients’ rooms compared to one central Pyxis machine in preventing medication errors in the medical-surgical unit

  1. Introduction
  • Defining of terms such as medical errors and Pyxis machine.
  • Thesis statement
  • Literature review- medical errors and invention of the Pyxis machine
  1. Body
  • Methods
  • Results
  • Nursing implications
  • Conclusion
  • Recommendations
  • conclusion

The Effectiveness of Pyxis Machine in all Patients’ Rooms Compared to One Central Pyxis Machine in Preventing Medication Errors in the Medical-Surgical Unit.

Several medical practitioners have tried to address medication errors that occur in medical-surgical units.  These errors mostly result from medication administration by a single nurse and lack of equipment to infuse drugs. Various factors contribute to making errors in medication. First, nurses may be suffering from shift fatigue due to long working hours. Secondly, medical practitioners may lack knowledge of the administered drug. Additionally, the documentation workload may confuse and lead to medication errors.

In an attempt to prevent such errors, most hospitals in the United States have adapted to Pyxis machines. Pyxis machines refer to systems that dispense medication automatically. This research paper seeks to outline the evidence-based effectiveness of Pyxis machines in all patients’ rooms compared to one central Pyxis machine in preventing medication errors in the medical-surgical unit.

                                                              Literature Review.         

Medical errors refer to significant effects of care that can be prevented but are harmful to the patient. These errors arise due to either incomplete diagnosis of a disease, inaccurate or incomplete treatment of ailments and infections. Many medical errors were occurring until, in 1999, the Institute of Medicine addressed the issue, with a title; To Err is Human: Building a Safer Health System. Since then, attempts by several researchers have been made to address the issue. According to the Centre for Disease Control and Prevention (CDC) National Centre for Health Statistics report in 2013, 9.5% of the total people hospitalized die due to medical errors (251,454 out of a total of 35,416,020).

There arose a need to improve nursing efficiencies (Kamal, 2019). A drive to lean process and enhance the difficulty in the process of medication administration. Pharmacy, too, had concerns about being unable to track inventory of medications on hand throughout the medical facilities, especially in incidences, where there was a shortage of drugs. To reduce deaths caused by medical errors, several hospitals have adapted to technology to minimize the mistakes.

The introduction of automated electronic reconciliation of medication, barcode medication administration, and personal health records are among the efforts made in technology use. For instance, the use of Pyxis machines has helped a great deal. Pyxis machines were invented in 1990 by San Diego Company by Ronald R. Taylor and investor Tim Wollaeger (Seltzer, 2020). The devices enhance decentralized medication management by helping the nurses disperse correct medicines to the right patients and at the right time. Therefore, is it useful to equip Pyxis machines in all patients’ rooms in preventing medication errors in the medical-surgical units rather than using only one in a central place?


A state has risen where there is a need to re-evaluate the Pyxis machines usage to optimize the number of machines in surgical rooms, lower medication waste due to expiry, and increase performance efficiency. Therefore, various scholarly articles were reviewed on how Pyxis machines have reduced medical errors. Time and motion were used to record medication retrieval (Roman et al., 2019). Roman et al. (2019) examined chance in medication retrieval times and the number of medication retrieved, and staff perceptions before and after installing Pyxis machines in Australian Emergency and Trauma Centre.


In a different case, a study was carried out to identify and summarize literature materials reporting on the economic value of Automatic Dispensing machines. Literature searches were conducted in MEDLINE, Embase, and Cochrane library to identify literature materials investigating the use of Automatic Dispensing devices in inpatient medical facilities (Batson et al., 2020). The results were then taken down, and the necessary analysis was made.


A total of 954 medical retrievals (1030 medications) were recorded before implementing the Automatic Dispensing Machine (Roman et al., 2019). After the implementation of Pyxis machines, 842 out of 991 observations were recorded. The mean time taken to retrieve medication was significantly longer after Pyxis machines’ performance compared to before use (+5.7 seconds; p<0.01). Additionally, the average number of medicines per retrieval indicated a slight increase after implementing Pyxis devices.

A qualitative summary of the results was reported in the second case since there was inconsistent reporting in many primary sources leading to possible outcomes. A total of 4320 publications were identified.  1050 duplicates were resulting in the remaining 3270, which were screened by title and abstract. Only 45 out of 175 full publications screened after eliminating 3095 (Batson et al., 2020). Grey literature searching led to the identification of 3 publications. Hence, a total of 48 publications were relevant for inclusion in the study.

In 35 publications included in the sample, they reported on Pyxis machines, whereby 13 of them said based on pharmacy-based dispensing systems. An additional 13 publications investigated Automatic Dispensing Systems integrated with other technologies (Batson et al., 2020). Five publications talked about dispensing systems and e-prescribing, and three on dispensing systems and barcode medication administration. The remaining five analyzed an integration of Pyxis machines with barcode scanning for dispensing. All studies were carried out through observation.

A prospective study was carried out on thirty-three of all reviews. Forty of the studies were comparative, comparing pre-intervention periods with post-intervention periods or the automated dispensing technology in parallel with manual dispensing (Batson et al., 2020). All studies were conducted in the inpatient setting.

The findings generally indicate improvements in economic outcomes. For instance, in the US- based study, time- savings associated with using Pyxis machine resulted in a total decrease of 35 labor hours per week, thus saving $64 300 for labor annually. An additional study conducted in Thai- land reported a reduction in pharmacy technician requirements from 132.66 to 55.38 full-time equivalents (FTEs) post-implementation of Pyxis device. However, this study also reported an increase in the need for pharmacists from 46.84 to 117.67.

Nursing Implications

Technology applications in health care have developed rapidly, including Automated Dispenser Machine (ADM). Therefore, concerns about cost, patient safety, and access to medications have been raised. The primary reason why most hospitals, 89%, have adapted to the use of Pyxis machines to reduce medication errors. The use of technology has improved the way nurses administer medication to patients.

Before most health facilities consider using such machines, the safety of both the patients and health providers is considered. The innovation of Pyxis machines has led to the simplification of processes. For instance, when computerized software is used to order drugs for patients, time is saved for nurses and pharmacists (Suryadinata, 2017). It also reduces the incorrect reading of handwritten orders (Fanning & Manias, 2016). Besides, it ensures that patients are not given medication that they are allergic to by alerting the pharmacist.

However, using Pyxis machines may have some challenges; Training of staff is necessary. Some staff may lack computer knowledge leading, which is required to operate the automated dispensing machines (Seltzer, 2019). This may eventually lead to patients getting the wrong doses and untimely medication administration, thus endangering the patient’s safety.

Additionally, incorrect programming of the Pyxis machines may occur at times. In case a health provider is in a hurry to administer drugs to patients and mistakenly programs the wrong dose, it results in a medication error (Fanning & Manias, 2016). Also, failing to set up the machine correctly may hinder patients from receiving correct medication for their specified ailments, thus impacting patients’ overall health.

Sometimes, critical mistakes by nurses on the automated machines may lead to patients unnecessary fatalities. For instance, patients are usually given morphine drips after surgery to reduce pain. If the drugs are administered excessively, the patient may experience difficulties in breathing and succumb. The use of technology in hospitals by health providers is prone to making mistakes at some point.



Since there were concerns regarding using a single Pyxis machine in administering medication, there was a necessity of using each device per patient to enhance effectiveness. Such issues arising from using a centralized Automated Dispenser Machine were incorrect programming of machines, unskilled medical staff (Seltzer, 2019). Also, wrong timing and wrong dosage resulted in medical errors.

Equipping all patient rooms with Pyxis machines will ensure that each device is programmed accurately according to the patient being administered. Hence, there will be limited chances of making medication errors due to incorrect programming. Additionally, the specific machine assigned to a particular patient will ensure that timing is accurately recorded. There is no need for adjustments unless the patient is shifted to another location or a change of patients’ positions.

Although Pyxis machines are expensive to buy and it will be difficult to equip all patient rooms with them, it is recommended that all medical stakeholders and governmental institutions should come together to enhance the process of providing all patient rooms in surgical units with Pyxis machines rather than using only one centralized device. This will not only increase efficiency but also improve patient safety (Suryadinata, 2017). Furthermore, extensive training should be administered to nurses to enhance accuracy in using the machines.





It is more effective to equip all patient rooms with Pyxis machines than placing them at a centralized position in surgical units. This will limit the time wasted in reprogramming the devices and also limit the chances of incorrect dosage. Eventually, there will be an improvement in patient safety and medication administration at large.





Batson, S., Herranz, A., Rohrbacj, N., Canobbio, M., Mitchell, S. A., & Bonnabry, P. (2020). Automation of in-hospital pharmacy dispensing: a systematic review. European Journal of Hospital Pharmacy.


Fanning, L., Jones, N., & Manias, E. (2016). Impact of automated dispensing cabinets on medication selection and preparation error rates in an emergency department: a prospective and direct observational before‐and‐after study. Journal of evaluation in clinical practice, 22(2), 156-163.


Roman, C., Poole, S., Walker, C., & Dooley, M. J. (2016). A ‘time and motion’ evaluation of automated dispensing machines in the emergency department. Australasian Emergency Nursing Journal, 19(2), 112-117.


Seltzer, BouDiab, J. K. (2019). A quantitative study on the training given to registered nurses on the new PYXIS system at AUBMC.

Suryadinata, H. U. (2017). The benefits of automated dispensing machines for hospital pharmacy in Indonesia: situation, implementation, and feasibility. GHMJ (Global Health Management Journal), 1(1), 15-22.