Beneficent dehumanization: Employing artificial intelligence and carebots to mitigate shame‐induced barriers to medical care

Bioethics ◽  
2021 ◽  
Author(s):  
Amitabha Palmer ◽  
David Schwan
Keyword(s):  
Artificial Intelligence ◽  
Medical Care

AIRA, an Artificial Intelligence Realistic Assistant that will save your time, a before-and-after study during Pandemic (Preprint)

2021 ◽  
Author(s):  
Kaio Bin ◽  
Adler Araújo Ribeiro Melo ◽  
José Guilherme Franco Da Rocha ◽  
Renata Pivi De Almeida ◽  
Vilson Cobello Junior ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Electronic Health Record ◽  
Medical Care ◽  
Health Screening ◽  
Urgent Care ◽  
Health Record ◽  
Before And After ◽  
Electronic Health ◽  
The Impact ◽  
Before And After Study

BACKGROUND AIRA is an AI designed to reduce the time that doctors dedicate filling out EHR, winner of the first edition of MIT Hacking Medicine held in Brazil in 2020. As a proof of concept, AIRA was implemented in administrative process before its application in a medical process. OBJECTIVE The aim of the study is to determinate the impact of AIRA by eliminating the Medical Care Registration (MCR) on Electronic Health Record (EHR) by Administrative Officer. METHODS This is a comparative before-and-after study following the guidance “Evaluating digital health products” from Public Health England. An Artificial Intelligence named AIRA was created and implemented at CEAC (Employee Attention Center) from HCFMUSP. A total of 25,507 attendances were evaluated along 2020 for determinate AIRA´s impact. Total of MCR, time of health screening and time between the end of the screening and the beginning of medical care, were compared in the pre and post AIRA periods. RESULTS AIRA eliminated the need for Medical Care Registration by Administrative Officer in 92% (p<0.0001). The nurse´s time of health screening increased 16% (p<0.0001) during the implementation, and 13% (p<0.0001) until three months after the implementation, but reduced in 4% three months after implementation (p<0.0001). The mean and median total time to Medical Care after the nurse’ Screening was decreased in 30% (p<0.0001) and 41% (p<0.0001) respectively. CONCLUSIONS The implementation of AIRA reduced the time to medical care in an urgent care after the nurse´ screening, by eliminating non-value-added activity the Medical Care Registration on Electronic Health Record (EHR) by Administrative Officer.

scholarly journals Will Artificial Intelligence Translate Big Data Into Improved Medical Care or Be a Source of Confusing Intrusion? A Discussion Between a (Cautious) Physician Informatician and an (Optimistic) Medical Informatics Researcher

10.2196/16272 ◽  
2019 ◽  
Vol 21 (11) ◽  
pp. e16272 ◽  
Author(s):  
Qing Zeng-Treitler ◽  
Stuart J Nelson
Keyword(s):  
Artificial Intelligence ◽  
New England ◽  
Medical Care ◽  
Data Driven ◽  
Single Individual ◽  
Physician Burnout ◽  
Problem Space ◽  
The Past ◽  
Challenges And Opportunities ◽  
Development And Utilization

Artificial intelligence (AI), the computerized capability of doing tasks, which until recently was thought to be the exclusive domain of human intelligence, has demonstrated great strides in the past decade. The abilities to play games, provide piloting for an automobile, and respond to spoken language are remarkable successes. How are the challenges and opportunities of medicine different from these challenges and how can we best apply these data-driven techniques to patient care and outcomes? A New England Journal of Medicine paper published in 1980 suggested that more well-defined “specialized” tasks of medical care were more amenable to computer assistance, while the breadth of approach required for defining a problem and narrowing down the problem space was less so, and perhaps, unachievable. On the other hand, one can argue that the modern version of AI, which uses data-driven approaches, will be the most useful in tackling tasks such as outcome prediction that are often difficult for clinicians and patients. The ability today to collect large volumes of data about a single individual (eg, through a wearable device) and the accumulation of large datasets about multiple persons receiving medical care has the potential to apply to the care of individuals. As these techniques of analysis, enumeration, aggregation, and presentation are brought to bear in medicine, the question arises as to their utility and applicability in that domain. Early efforts in decision support were found to be helpful; as the systems proliferated, later experiences have shown difficulties such as alert fatigue and physician burnout becoming more prevalent. Will something similar arise from data-driven predictions? Will empowering patients by equipping them with information gained from data analysis help? Patients, providers, technology, and policymakers each have a role to play in the development and utilization of AI in medicine. Some of the challenges, opportunities, and tradeoffs implicit here are presented as a dialog between a clinician (SJN) and an informatician (QZT).

scholarly journals Impact of artificial intelligence on waiting time for medical care in an urgent care service for Covid-19. (Preprint)

10.2196/29012 ◽  
2021 ◽  
Author(s):  
Kaio Bin ◽  
Adler Araújo Ribeiro Melo ◽  
José Guilherme Franco Da Rocha ◽  
Renata Pivi De Almeida ◽  
Vilson Cobello Jr ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Medical Care ◽  
Waiting Time ◽  
Care Service ◽  
Urgent Care

Ethical Aspects of Information-Based Medicine (With a Focus on Mental Health)

2022 ◽  
pp. 42-70
Author(s):  
Jan Kalina ◽  
Nicole Tobišková
Keyword(s):  
Artificial Intelligence ◽  
Medical Care ◽  
Medical Information ◽  
Mental Healthcare ◽  
Developed Countries ◽  
Clinical Applications ◽  
Ethical Aspects ◽  
Concept Of Information ◽  
Based Medicine

Modern advanced tools of artificial intelligence assist healthcare professionals in a variety of complex tasks related to medical care. Digitalization and automation accelerate the development and deployment of innovative artificial intelligence tools tailor-made for clinical applications; decision support systems represent an important example of such tools. This chapter is devoted to discussing the role of artificial intelligence in current and prospective medical care and ethical aspects of their deployment. As developed countries currently go through remarkable transforms of medical care involving informatization and centering around medical information and knowledge, this chapter also discusses future ideals of medical care characterized by the concept of information-based medicine. Ethical and patient safety implications of using artificial intelligence within information-based medicine are overviewed here. Specific attention is paid to mental healthcare and ethical aspects of using artificial intelligence in its context.

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