Robotic Pharmacy Implementation and Outcomes in Saudi Arabia: A 21-Month Usability Study

Assessment of satisfaction of attendees of healthcare centers in Jordan with community pharmacy services of pharmacies they usually use

Before extending the range of services provided, maximizing the usefulness of current procedures within community pharmacy settings is needed, as the scope of pharmacy services is evolving in different dimensions. The present study aims to assess the degree of factors affecting the satisfaction of traditional community pharmacy services using population data collected from patients attending academic and public healthcare centers in Jordan. A validated, pretested, and adapted survey instrument has been utilized to assess the satisfaction of contemporary services delivered by community pharmacists in different dimensions. Linear regression analysis evaluated the predictors associated with higher total satisfaction scores with community pharmacy services. The present study included 642 patients attending healthcare centers. Different dimension scores, such as explanation and consideration, scored similarly, with values ranging from 64.5% - 69.7% of the maximum possible score. The mean total scale score was 67.2% of the total possible scores. Using the linear regression analysis, respondents who were satisfied with their treatment plans were likely to have higher satisfaction with community pharmacy services. The increased number of prescription medications and increased age were associated with lower satisfaction with community pharmacy services. Results indicated that healthcare policymakers might be confident in the services within the community pharmacy setting; however, there is always room for more robust quality control activities.

Evaluation of the automated dispensing cabinets users' level of satisfaction and the influencing factors in Al-Ahsa hospitals

Automated dispensing cabinets (ADCs) are decentralized, computer-controlled systems used to store, distribute, and track medications at the point of care in the wards.

Objective

The objective of the current study is to evaluate how healthcare practitioners are satisfied with ADCs and scrutinize some influencing factors that could affect this satisfaction.

Material

A cross-sectional survey study was designed and distributed online to healthcare providers in Al-hasa hospitals.

Results

A total of 166 participants. Regarding the frequency and pattern of ADC use, around 79.5% used ADC and 85.4% were informed about using ADC on a daily basis. As for the level of satisfaction with ADC, an exact 81.9% gave a high rate for overall satisfaction, 81.3% were highly satisfied with the system's accuracy, and 74.7% were highly satisfied with the time it takes to complete the task. Regarding usability of the system, 69.8% thought it was easy whereas 36.8% agreed that the time required for reloading medication is longer than before ADC. Furthermore, 79.5% agreed that ADC allowed them to accomplish their job safely, and 67.4% agreed that it improved their productivity. Regarding challenges, 74.7% agreed that all drawer types assure safe access and removal of medications, and 18.7% agreed that there is a significant potential for loss of data.

Conclusion

This study investigated healthcare staff's perceptions and satisfaction with ADCs in Al-hasa hospitals. The healthcare participants were mostly highly satisfied with the use of the ADCs which translated into better patient care and improved patient safety as well as higher productivity.

Community pharmacists awareness, perceptions, and opinions of artificial intelligence: A cross-sectional study in Riyadh, Saudi Arabia

BACKGROUND

Several revolutions are currently taking place in the healthcare industry to provide accurate, reliable, and valid healthcare to patients. Among these is artificial intelligence (AI).

OBJECTIVE

This study aimed to assess the CP's awareness, perceptions, and opinions of AI in health care among community pharmacists.

METHODS

This cross-sectional survey-based study was conducted over 3 months in 2023 using structured prevalidated 34 items questionnaires.

RESULTS

In this study, 94.5% (n= 258) of the CPs were aware of AI, yet 25.6% (n= 70) believed that AI would eventually replace healthcare professionals. However, 63.4% (n= 173) of the CPs concurred that AI is a technology that supports healthcare workers. 12.8% of the CPs believed that there is a risk of losing their jobs if AI is widely used in Saudi Arabia, but 68.9% (n= 188) of them considered that healthcare professionals will benefit from the extensive use of AI. Eighty-four percent of CPs (n= 232) agreed or strongly agreed that AI decreases drug mistakes in clinical practice. Similarly, 86% of the CPs (n= 235) concurred that AI makes it easier for patients to access the service. In contrast, almost 58% of the CPs (n= 232) agreed that AI makes it easier for healthcare professionals to acquire information, and 87.9% of the CPs (n= 240) said that AI helps them make better decisions.

CONCLUSION

This study concluded that most of the CPs were aware of AI and agreed that AI is a tool that helps healthcare professionals. In addition, the majority of the CPs thought that AI adoption in healthcare practice will benefit healthcare practitioners.

Improving Inpatient Medication Dispensing with an Automated System

Introduction

Medication inventory management and error prevention are complex issues. Single interventions are insufficient to make improvement across the spectrum. A uniform system for dispensing and distributing medications can help reduce the risk of medication errors, improve efficiency, and minimize waste. This quality improvement project aims to: 1) decrease - the time from ordering medication to administration, including delay incidents, by > 70%; and 2) decrease the inpatient monthly total medication consumption by > 20% and ward medication stock items by > 70%, including decreasing returned items and loss from in-house expired medications by > 70%.

Methods

A Six-Sigma approach was applied to eliminate deficiencies throughout the medication management process. Failure mode effect analysis and staff surveys were used to evaluate implementation of automated dispensing cabinet (ADCs) and reengineered workflows for expensive, misused, and restricted medications.

Results

After the new processes were implemented, the turnaround time from ordering medication to administration was reduced by 83%, with zero delay incidents reported. Most nurses (64%) and pharmacists (67%) stated that implementation of ADCs increased their productivity by more than 40%. Monthly medication consumption was reduced by 24%, with an estimated annual saving of $4,100,000 USD. The number of returned items per month was reduced by 72%, and the estimated annual savings from loss of in-house expired medications was $750,000 USD.

Conclusions

This quality improvement project positively impacted stock control while reducing costs and turnaround time for inpatient medication dispensing. Medication delay incidents were reduced, and staff satisfaction levels were positive. Next steps are to reengineer narcotic, anesthesia, and refrigerated products' management.

Assessment of Awareness, Perceptions, and Opinions towards Artificial Intelligence among Healthcare Students in Riyadh, Saudi Arabia

Background and Objective: The role of the pharmacist in healthcare society is unique, since they are providers of health information and medication counseling to patients. Hence, this study aimed to evaluate Awareness, Perceptions, and Opinions towards Artificial intelligence (AI) among pharmacy undergraduate students at King Saud University (KSU), Riyadh, Saudi Arabia. Materials and Methods: A cross-sectional, questionnaire-based study was conducted between December 2022 and January 2023 using online questionnaires. The data collection was carried out using convenience sampling methods among senior pharmacy students at the College of Pharmacy, King Saud University. Statistical Package for the Social Sciences version 26 was used to analyze the data (SPSS). Results: A total of one hundred and fifty-seven pharmacy students completed the questionnaires. Of these, most of them (n = 118; 75.2%) were males. About 42%, (n = 65) were in their fourth year of study. Most of the students (n = 116; 73.9%) knew about AI. In addition, 69.4% (n = 109) of the students thought that AI is a tool that helps healthcare professionals (HCP). However, more than half 57.3% (n = 90) of the students were aware that AI would assist healthcare professionals in becoming better with the widespread use of AI. Furthermore, 75.1% of the students agreed that AI reduces errors in medical practice. The mean positive perception score was 29.8 (SD = 9.63; range-0-38). The mean score was significantly associated with age (p = 0.030), year of study (p = 0.040), and nationality (p = 0.013). The gender of the participants was found to have no significant association with the mean positive perception score (p = 0.916). Conclusions: Overall, pharmacy students showed good awareness of AI in Saudi Arabia. Moreover, the majority of the students had positive perceptions about the concepts, benefits, and implementation of AI. Moreover, most students indicated that there is a need for more education and training in the field of AI. Consequently, early exposure to content related to AI in the curriculum of pharmacy is an important step to help in the wide use of these technologies in the graduates' future careers.

Transforming Primary Care: Developing Health Precincts as Models for Sustainable Integrated Community-Based Healthcare

Holistic healthcare precincts are an emerging service model to address the growing health service demands of ageing consumers and an increasing prevalence of chronic diseases. In Australia and similar countries with universal publicly funded Medicare systems, the first point of access to healthcare is provided by general medical practitioners. This case report focuses on successful components of a private, integrated, patient-centred primary care model located in a low socioeconomic population in North Brisbane, Queensland. Successful components included a focus on sustainability, general practice as an anchor tenant in the health precinct, the integration of multiple services, team-based care for shared clinical services, flexible expansion options, the use of MedTech, support for small businesses and a cluster structure. The Morayfield Health Precinct (MHP) offers appropriate, safe and individualised healthcare to residents across their life continuum. Its success was built on a foundation of pre-planning, to ensure the design/build, anchor tenant and collaborative ecosystem were sustainable in the long term. MHP planning was based on an adaptation of the WHO-IPCC framework supporting true patient-centred, integrated care. Its shared vision and collaborative care are supported by its internal governance structure, tenant selection, established and emerging referral networks and partnerships. Evidence-based and informed care is further supported by internal and external research and education partnerships.

Access to non-prescription medicines via vending machines: key considerations to help transfer the self-care concept to the next generation while managing safety risks

Objectives

Non-prescription vending machines are automated self-service systems that are increasingly used to dispense these medicines. Whilst regulatory health academics have devoted considerable attention to non-pharmacy medication outlets in Gulf Cooperation Council countries and others, the public health literature on these vending machines remains lacking. Whilst non-prescription vending machines undoubtedly provide a number of benefits, they are not without their risks, which include polypharmacy and medication interactions.

Methods

The purpose of this article is to provide a framework for further investigation of the function, advantages, and practical constraints of non-prescription vending machines.

Key findings

Overall, more research is required to determine the optimal balance between achieving the benefits of non-prescription vending machines whilst avoiding unnecessary constraints on regulatory bodies and vending machine providers but minimizing patient harm.

Conclusions

Further studies are also required to assess the consequences of these policy experiments. Specifically, there is a need to better understand the extent to which vending machines can provide beneficial and reasonable access to non-prescription medicines to enhance the quality of life of the population especially during pandemics.

A Survey of Near-Miss Dispensing Errors in Hospital Pharmacies in Japan: DEPP-J Study-Multi-Center Prospective Observational Study

The aim of this study was to determine the proportion of near-miss dispensing errors in hospital pharmacies in Japan. A prospective multi-center observational study was conducted between December 2018 and March 2019. The primary objective was to determine the proportion of near-miss dispensing errors in hospital pharmacy departments. The secondary objective was to determine the predictive factors for near-miss dispensing errors using multiple logistic regression analysis. The study was approved by the ethical committee at The Institute of Medical Sciences, University of Tokyo, Japan. A multi-center prospective observational study was conducted in 20 hospitals comprising 8862 beds. Across the 20 hospitals, we assessed data from 553 pharmacists and 53039 prescriptions. A near-miss dispensing error proportion of 0.87% (n = 461) was observed in the study. We found predictive factors for dispensing errors in day-time shifts: a higher number of drugs in a prescription, higher number of quantified drugs, such as liquid or powder formula, in a prescription, and higher number of topical agents in a prescription; but we did not observe for career experience level for clinical pharmacists. For night-time and weekend shifts, we observed a negative correlation of near-miss dispensing errors with clinical pharmacist experience level. We found an overall incidence of near-miss dispensing errors of 0.87%. Predictive factors for errors in night-time and weekend shifts was inexperienced pharmacists. We recommended that pharmacy managers should consider education or improved work flow to avoid near-miss dispensing errors by younger pharmacists, especially those working night or weekend shifts.

Impact of automated drug dispensing system on patient safety

Objectives

Automated drug dispensing system (ADDs) is an emerging technology positively impacts drug dispensing efficiency by minimizing medication errors. However, the pharmacist perception of the impact of ADDs on patient safety is not well-established. This cross-sectional observational study aimed to evaluate the dispensing practice and pharmacist perception of ADDs towards patient safety through a validated questionnaire.

Methods

A self-designed questionnaire was validated and the pharmacist perception of dispensing practice was compared between two hospitals adopting ADDs and traditional drug dispensing system (TDDs).

Results

The developed questionnaire had an excellent internal consistency (both Cronbach's α and McDonald's ω coefficients were >0.9). Factor analysis retained three significant factors (subscales) that explained pharmacist perception of dispensing system, dispensing practice, and patient counseling (p<0.001 for each factor). The average number of prescriptions dispensed per day, drugs contained in each prescription, average time for labeling each prescription and inventory management were significantly varied between ADDs and TDDs (p=0.027, 0.013 0.044 and 0.004, respectively). The perception of pharmacists using ADDs on three domains were higher than the TDDs. The pharmacists in ADDs agreed that they had enough time to review the medications before dispensing than TDDs and this difference was found to be statistically significant (p=0.028).

Conclusions

ADDs was highly effective in improving dispensing practice and medication review; however, the pharmacists need to emphasize the importance of ADDs to translate the pharmacists' freed-time towards patient care.

An Overview of the Current State and Perspectives of Pharmacy Robot and Medication Dispensing Technology

It has been widely reported that a large number of patients die from cases of errors in the issuing of medication prescriptions. These cases occur due to a wide range of things, but the common denominator in all of the cases is humans. A hospital pharmacy has a very critical task, especially with growing patient numbers. The increasing number of prescriptions needed to be filled daily reduces the amount of time that the staff can use to focus on each individual prescription, which may increase the human error ratio. The need for robotic-assisted pharmacies is arising from here to distribute drugs to eradicate or substantially reduce human error. The pharmacy robot is one of the most significant technologies that play a prominent role in the advancement of hospital pharmacy systems. The purpose of this review paper is to cover the pharmacy robot concept and the published literature reporting on pharmacy robot technology as one of the most important applications of artificial intelligence (AI) in pharmacology. Although the outcomes of the impact of the pharmacy robot have been increasingly beneficial in overall improvement, staff morale, and functionality of pharmacies, there are still mechanical errors occurring. The errors, in turn, require human intervention. The key takeaway from this study is that robots or machines cannot replace human duties in their entirety. This in turn means that those human interventions will have an impact on the workflow and throughput.

The Introduction of Robotics to an Outpatient Dispensing and Medication Management Process in Saudi Arabia: A Pharmacy-led Multidisciplinary Six Sigma Performance Improvement Project. (Preprint)

Background

Outpatient pharmacy management aims for improved patient safety, improved quality of service, and cost reduction. The Six Sigma method improves quality by eliminating variability, with the goal of a nearly error-free process. Automation of pharmacy tasks potentially offers greater efficiency and safety.

Objective

The goal was to measure the impact that integration of automation made to service, safety and efficiency, staff reallocation and reorientation, and workflow in the outpatient pharmacy department. The Six Sigma problem definition to be resolved was as follows: The current system of outpatient dispensing denies quality to patients in terms of waiting time and contact time with pharmacy professionals, incorporates risks to the patient in terms of mislabeling of medications and the incomplete dispensing of prescriptions, and is potentially wasteful in terms of time and resources.

Methods

We described the process of introducing automation to a large outpatient pharmacy department in a university hospital. The Six Sigma approach was used as it focuses on continuous improvement and also produces a road map that integrates tracking and monitoring into its process. A review of activity in the outpatient department focused on non-value-added (NVA) pharmacist tasks, improving the patient experience and patient safety. Metrics to measure the impact of change were established, and a process map analysis with turnaround times (TATs) for each stage of service was created. Discrete events were selected for correction, improvement, or mitigation. From the review, the team selected key outcome metrics, including storage, picking and delivery dispensing rates, patient and prescription load per day, average packs and lines per prescription, and lines held. Our goal was total automation of stock management. We deployed 2 robotic dispensing units to feed 9 dispensing desks. The automated units were integrated with hospital information technology (HIT) that supports appointments, medication records, and prescriptions.

Results

Postautomation, the total patient time in the department, including the time interacting with the pharmacist for medication education and counseling, dropped from 17.093 to 11.812 digital minutes, with an appreciable increase in patient-pharmacist time. The percentage of incomplete prescriptions dispensed versus orders decreased from 3.0% to 1.83%. The dispensing error rate dropped from 1.00% to 0.24%. Assessed via a “basket” of medications, wastage cost was reduced by 83.9%. During implementation, it was found that NVA tasks that were replaced by automated processes were responsible for an extensive loss of pharmacist time. The productivity ratio postautomation was 1.26.

Conclusions

The Six Sigma methodology allowed for rapid transformation of the medication management process. The risk priority numbers (RPNs) for the “wrong patient-wrong medication error” reduced by a ratio of 5.25:1 and for “patient leaves unit with inadequate counseling” postautomation by 2.5:1. Automation allowed for ring-fencing of patient-pharmacist time. This time needs to be structured for optimal effectiveness.