Critical Evaluation of Pharmacy Automation and Robotic Systems: A Call to Action

Boyd, Angela R.; Chaffee, Bruce W.

doi:10.1177/0018578718786942

Cited by 24 publications

(23 citation statements)

References 37 publications

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“…Because automation can't be spread in a large area in a short period of time, most hospital pharmacies still use people-centered dispensing mode at present. With the deepening of arti cial intelligence and information technology, pharmacies will develop towards intelligence and automation in the future [17,18]. So, we have made a thorough analysis of the data available in the outpatient pharmacy and made full use of the intelligent control system to improve the e ciency of pharmacists and shorten the waiting time for patients to take medicine, improve service satisfaction of outpatient pharmacy.…”

Section: Discussionmentioning

confidence: 99%

Optimize Outpatient Pharmacy Service Process: Shorten Waiting Time and Improve Patient Satisfaction

He¹,

Qian²,

Yang³

et al. 2020

Preprint

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Background: To provide scientific decision-making basis for managers to improve management methods, so about make outpatient pharmacy service flow smoother and more efficient, shorten the waiting time for patients to take medicine and improve patient satisfaction.Methods: Based on the concept of BI, the existing data onto outpatient pharmacy in our hospital were analyzed in depth, and the time distribution rule of prescription dispensing was found. By real-time analysis of the number of patients in the upstream link to the medication withdrawal step, the early warning of the number of patients was realized. Regularity and real-time early warning of the number of medicines users should establish a flexible and efficient scheduling system for pharmacists, so about maximize the use efficiency of human resources in outpatient pharmacies. Mean while, rearranged the medicines shelves according to the relevancy analysis of medicines in the same prescription, to reduce the walking distance of staff.Results: Based on the optimization of outpatient service process of large data, the waiting time for patients to take medicine was shortened from more than 15 minutes to less than 10 minutes, satisfaction increased from less than 65% to more than 85%, and the use of personnel was maximized.Conclusions: Through in-depth analysis and deep excavation of the real-time monitoring of outpatient prescription volume, managers can improve the outpatient service process, and through the monitoring and early warning of outpatient prescription volume, employees can be arranged, which is helpful to realize the digital, refined and intelligent management of the hospital.

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Section: Discussionmentioning

confidence: 99%

Optimize Outpatient Pharmacy Service Process: Shorten Waiting Time and Improve Patient Satisfaction

He¹,

Qian²,

Yang³

et al. 2020

Preprint

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“…Clinical psychology and psychiatry are also expected to benefit from advances in AI [ 15 , 16 ], which will include psycho-oncology applications. Automation and robotics have been widely adopted in pharmacy, though assessment of those technologies is ongoing [ 17 ]. Current topics in AI-related research in pharmacy include drug design and discovery, robotics, and oncological treatment planning [ 18 ].…”

Section: Introductionmentioning

confidence: 99%

Teaching cross-cultural design thinking for healthcare

2020

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Objectives Artificial intelligence (AI) is poised to transform breast cancer care. However, most scientists, engineers, and clinicians are not prepared to contribute to the AI revolution in healthcare. In this paper, we describe our experiences teaching a new undergraduate course for American students that aims to prepare the next generation for cross-cultural designthinking, which we believe is crucial for AI to achieve its full potential in breast cancer care. Materials and methods The key course activities are planning, conducting, and interpreting interviews of healthcare professionals from both Portugal and the United States. Since the course is offered as a short-term faculty-led study abroad program in Portugal, students are able to explore the impact of culture on healthcare delivery and the design of healthcare technologies. Results The learning assessments demonstrated student growth in several areas pertinent for future development of AI for breast cancer care. With respect to understanding breast cancer care, prior to taking this course, most students had underestimated the impact of cancer and its treatment on women’s quality of life and most were unaware of the importance of multidisciplinary care teams. Regarding AI in medicine, students became more mindful of data privacy issues and the need to consider the effect of AI on healthcare professionals. Conclusion This course illustrates the potential benefits for AI in medicine of introducing future scientists, engineers, and clinicians to cross cultural design-thinking early in their educational experiences.

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Section: Introductionmentioning

confidence: 99%

“…Boyde et al [ 9 ] challenge the reported benefits, suggesting the available literature may be favourably biased, setting overly optimistic expectations of PRDS performance. [ 9 ] Negative results and challenges associated with the implementation are potentially under reported and not well‐ understood. [ 9 ] The introduction of new technology can create new, unexpected tasks and problems for the pharmacy to manage such as fault resolution, support and maintenance tasks, and staff training requirements.…”

Section: Introductionmentioning

confidence: 99%

“…[ 9 ] Negative results and challenges associated with the implementation are potentially under reported and not well‐ understood. [ 9 ] The introduction of new technology can create new, unexpected tasks and problems for the pharmacy to manage such as fault resolution, support and maintenance tasks, and staff training requirements. [ 1,8,9 ] Staff can feel their role is devalued postimplementation and the additional tasks increase workplace stress.…”

Section: Introductionmentioning

confidence: 99%

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Factors influencing acceptance of robotics in hospital pharmacy: a longitudinal study using the Extended Technology Acceptance Model

Hogan

Grant

Kelly

et al. 2020

International Journal of Pharmacy Practice

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Objectives To explore factors influencing hospital pharmacy staff acceptance of a pharmacy robotic dispensing system during implementation and over time. Methods A single centred, prospective, longitudinal cohort quantitative study was conducted in an Australian tertiary public hospital using the Extended Technology Acceptance Model (ETAM). Staff were surveyed during the implementation of a pharmacy dispensing robot (May 2016) and again after working with the system for fifteen months (August 2017). Fishers exact test and correlation analysis of paired responses were used to identify significant factors influencing use of the system between the two time points. Key findings Sixty four respondents completed surveys during implementation (n=64) and 34-paired surveys were collected fifteen months later. Respondents were predominantly young, female with a tertiary qualification. Initial perceptions did not change over time, with the exception of reliability. Departmental leaders had greatest influence on technology acceptance during implementation and over time. Other key factors correlating with acceptance included: how useful the robot was perceived to be; ease of use and how relevant the robot was for an individual role. Higher levels of education had a negative association with usage during implementation and age was not a factor. Conclusion This study identified critical insights influencing staff acceptance of pharmacy robots that will help inform future implementation. The influence of pharmacy leaders emerged as key influence on technology acceptance. Leveraging on this influence a communication strategy prior to implementation should include information on useful functions and known benefits of the system customised for individual roles.

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Critical Evaluation of Pharmacy Automation and Robotic Systems: A Call to Action

Cited by 24 publications

References 37 publications

Optimize Outpatient Pharmacy Service Process: Shorten Waiting Time and Improve Patient Satisfaction

Optimize Outpatient Pharmacy Service Process: Shorten Waiting Time and Improve Patient Satisfaction

Teaching cross-cultural design thinking for healthcare

Factors influencing acceptance of robotics in hospital pharmacy: a longitudinal study using the Extended Technology Acceptance Model

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