Technology is growing its importance in the development of health care provision. Like many other professions, nursing is also going to be impacted by the emergence of technology and, in particular, robots. Delivery robots are an innovative approach to patient care that might positively influence healthcare. I have chosen this particular technology because it addresses a topical issue in the nursing sphere, which is workforce shortage. The implementation of delivery robots contributes to improving the efficiency in nursing by reducing staff workload and managing the growing workforce shortage in patient care.
Annotated Bibliography
Law, M., Ahn, H. S., Broadbent, E., Peri, K., Kerse, N., Topou, E., Gasteiger N. & MacDonald, B. (2021). Case studies on the usability, acceptability, and functionality of autonomous mobile delivery robots in real-world healthcare settings. Intelligent Service Robotics, 1-12.
This case study examined the ease of use, acceptability, and functionality of two GoCart delivery robots in two different medical environments. The GoCart robot sent blood and urine samples to the pathology laboratory for two weeks to help deliver the food to the care facility. A total of fifty people were asked (direct and indirect users and managers) about their experience with robots, their design and functionality, safety, ease of use, and their general attitude towards using robots. Participants from both locations agreed that robots could be a useful addition to the facility in order to increase efficiency and reduce staff workload. Robots have been more actively accepted in nursing homes than in pathology laboratories. Before implementing GoCarts in the long run, there was a need to make improvements to adapt the robot to each location, such as resizing and screen changes. These case studies show how autonomous mobile delivery robots can be a valuable addition to nursing homes and pathology laboratories. Overall, this study adds to the increased amount of information that indicates potential uses for delivery robots, highlighting important design considerations.
Being usable, safe and functional, the results of the case study show that the GoCart delivery robot is a useful addition to two different locations. This shows that the autonomous mobile delivery robot can be used in environments other than the normal hospital environment, demonstrating its adaptability. However, to use GoCarts permanently in these situations, you will need to upgrade further, including adaptation to each location.
Kumaran, D. N. M., & Arshadh, H. (2019). Design and Fabrication of Medicine Delivery Robots for Hospitals.
This paper introduces the design and manufacture of drug delivery robots for hospitals. Automation has spread to virtually all service-oriented industries and is now a field that extends to healthcare. The purpose of this article is to develop a robot that distributes mountains on behalf of nurses. The care robot uses a line trace method to find a way to use two infrared proximity sensors to identify the lane and an RFID card to identify the patient’s room number. It also uses an ultrasonic sensor to identify the locked room and a voice playback kit to talk to the patient about the drug. By integrating pressure and temperature sensors, patient pressure and temperature can also be monitored and stored in the hospital’s patient database. This is an additional advantage of this model. This shows that it provides a robust and reliable system while reducing manufacturing costs. The Arduino Mega 2560 was used to build this robot, and the Arduino IDE was used for programming.
According to the results of the study, Atmega2560 is recommended over other boards as it is the most common board used to create robots. Care robots help patients take their medication at the right time. The robot moves from one place to another based on the timing. Use IR sensors to track movement and RFID to identify each room. The mobility of the robot is controlled by a DC motor, so it can move freely in all four directions. If there is an obstacle, the obstacle IR sensor can easily detect it.
Edelman, L. S., McConnell, E. S., Kennerly, S. M., Alderden, J., Horn, S. D., & Yap, T. L. (2020). Mitigating the effects of a pandemic: facilitating improved nursing home care delivery through technology. JMIR Aging, 3(1), e20110.
The epidemic of coronavirus disease was extremely difficult for staff and nursing home residents. The exception to Centers for Medicare & Medicaid Services puts a strain on employees and impacts care. Residents suffer from social isolation, which can lead to physical and behavioral health problems, especially for people with dementia. Technology tweaks can help you overcome some of these problems. A fully integrated electronic patient recording system can improve the quality of workflow and care. Telemedicine supports access to third-party providers, remote monitoring, and social connectivity. End-of-life planning and information exchange between nursing home staff and family members can be done using electronic and video tools. Online learning systems and other online resources provide flexible opportunities for staff training and development. By investing and adopting technology during and after the COVID19 crisis, you can reduce staff stress and improve the quality of care in your nursing home.
The extraordinary failure of the COVID19 pandemic accidentally defames and puts a particularly heavy burden on nursing home staff who have few resources in the pre-pandemic period. At the same time, the vast majority of nursing home employees are unaware of their commitment and willingness to make sacrifices. Today, more than ever, it is more important to help nursing home workers, especially those in need, which directly care for the most vulnerable older people during the most difficult times. Technology provides the opportunity to address the issues these employees are currently facing. There is more support for the vulnerable elderly and those who care for them. It also calls for investment in technology and other resources to help older people and caregivers during epidemics.
Suhail, M., Khan, A., Rahim, M. A., Naeem, A., Fahad, M., Badshah, S. F., Jabar, A. & Janakiraman, A. K. (2021). Micro and nanorobot-based drug delivery: An overview. Journal of Drug Targeting, 1-10.
Many breakthroughs within the drug transport gadget had been made within the last few decades, ensuing in extra green remedy transport. Micro and nanorobots are each concepts to be advanced remedy transport gadgets due to the fact they convert different styles of strength into propulsion and movement. It may additionally be useful due to the fact its miles are directed to unique places underneath physiological settings and situations. They have been proven to be able to encapsulate, transport, and turn in healing contents at once to contamination places, enhancing healing performance whilst decreasing dangerous remedy systemic facet effects. The work discusses an important innovation in medical technology and mentions benefits that it could bring. According to the discussion, micro-and nanorobots make nurses’ work easier to organize and reduce workflow. Moreover, they increase the quality of patient care due to lowering cases of human errors in work. This article examines the usage of micro and nanorobots in sickness analysis and management, in addition to the numerous styles of micro-and nanorobots, the characteristic of robots in drug administration, and their biomedical applications.
Kavirayani, S., Uddandapu, D. S., Papasani, A., & Krishna, T. V. (2020, October). Robots for delivery of medicines to patients using artificial intelligence in health care. In 2020 IEEE Bangalore Humanitarian Technology Conference (B-HTC) (pp. 1-4). IEEE.
In this paper, an artificial intelligence approach is used to investigate the distribution of robotic medicines in the ward and address the safety and medical concerns of patients and patients who deliver medicines in a timely manner. The robot uses intelligent algorithms based on sensors and indicators located in the ward on the shortest route prior to departure to navigate the ward where the drug needs to be administered. This algorithm also prevents the robot from colliding with other robots or humans along the way and looks for signs that the drug needs to be administered quickly. In this way, the infection can be prevented from being transmitted during dosing rather than time-consuming manual labor. The features and algorithms of this proposed method have been evaluated in the prototype arena and have been shown to be successful in the laboratory using Firebird V robots. The proposed solution saves time and personnel and can be easily implemented with external monitoring at the hospital reception.
In the future, self-driving systems will be the cutting edge technology for in-house drug supply in hospitals. Robotic Medicine Delivery Systems are similar to the autonomous driving systems commonly found in the basements of shopping malls, technology parks, apartments, and other commercial facilities. Working speed, accuracy, safety, reliability, economy, comfort, and space are the most important parameters. Efficiency and environmental friendliness are also important in these systems. This is a difficult operation because it interferes with the distribution of the drug to some patients. Research in these areas has been significantly reduced due to the lack of qualified professionals to perform RMDS tasks efficiently. The total time it takes a vehicle to fill and dispense a drug is the most important factor in determining logistics.
Conclusion
In conclusion, all of the studies showed that the implementation of delivery robots technology would facilitate improvement in the sphere of healthcare and patient care. Nursing will mostly benefit from the emergence of robots in working with patients since it reduces the time and effort needed to provide quality care for the patients. However, some of the technologies still need more investigation and improvements in the operating systems.
References
Edelman, L. S., McConnell, E. S., Kennerly, S. M., Alderden, J., Horn, S. D., & Yap, T. L. (2020). Mitigating the effects of a pandemic: facilitating improved nursing home care delivery through technology. JMIR Aging, 3(1), e20110.
Kavirayani, S., Uddandapu, D. S., Papasani, A., & Krishna, T. V. (2020). Robots for delivery of medicines to patients using artificial intelligence in health care. In 2020 IEEE Bangalore Humanitarian Technology Conference (B-HTC) (pp. 1-4). IEEE. Web.
Kumaran, D. N. M., & Arshadh, H. (2019). Design and Fabrication of Medicine Delivery Robots for Hospitals. Web.
Law, M., Ahn, H. S., Broadbent, E., Peri, K., Kerse, N., Topou, E., Gasteiger N. & MacDonald, B. (2021). Case studies on the usability, acceptability, and functionality of autonomous mobile delivery robots in real-world healthcare settings. Intelligent Service Robotics, 1-12. Web.
Suhail, M., Khan, A., Rahim, M. A., Naeem, A., Fahad, M., Badshah, S. F.,… & Janakiraman, A. K. (2021). Micro and nanorobot-based drug delivery: An overview. Journal of Drug Targeting, 1-10. Web.