Redefining The Doctor-Patient Relationship in the Era of Artificial Intelligence – Modern Medicine’s Dilemma

2021 ◽  
Vol 66 (Special Issue) ◽  
pp. 150-150
Author(s):  
Roxana Elena Rusu ◽  
◽  
Beatrice Gabriela Ioan ◽  
◽  
◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Patient Relationship ◽  
Ethical Aspects ◽  
Medical Field ◽  
Doctor Patient Relationship ◽  
Diverse Background ◽  
Therapeutic Recommendations ◽  
Triangular Relationship ◽  
The Right

"Nowadays, the traditional relationship between doctors and patients is changed by the artificial intelligence (AI) and its involvement in the medical act – ranging from diagnosis to therapeutic recommendations or personalized treatment. The balance in this triangular relationship is hard to find especially in a digitalized world, in which patients have access to unfiltered information that may lead to inaccurate self-diagnosis. When it comes to the diverse background of a disease, only a doctor will be able to draw the right conclusion. It is hard to imagine that AI will soon be able to recognize problems such as domestic violence or mental illness. Ultimately, this means that AI is only a means to an end and the responsibility of any taken decision lies with the doctor. Doctors are more than decision making machines and the emotional intelligence cannot be replaced, but the advantages of using AI in the medical field are widely recognized and ultimately the goal is to ensure the best care for the patient. The purpose of this paper is to point out ethical aspects that rise from the involvement of AI in the doctor-patient relationship and to describe the new roles of the doctor and the patient in the era of AI. "

scholarly journals Decision-Making of Older Patients in Context of the Doctor-Patient Relationship: A Typology Ranging from “Self-Determined” to “Doctor-Trusting” Patients

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Jennifer Wrede-Sach ◽  
Isabel Voigt ◽  
Heike Diederichs-Egidi ◽  
Eva Hummers-Pradier ◽  
Marie-Luise Dierks ◽  
...  
Keyword(s):  
Decision Making ◽  
Shared Decision Making ◽  
Information Seeking ◽  
Older Patients ◽  
Self Determination ◽  
Shared Decision ◽  
Patient Relationship ◽  
Doctor Patient Relationship ◽  
Good Doctor ◽  
Patient Decision Making

Background. This qualitative study aims to gain insight into the perceptions and experiences of older patients with regard to sharing health care decisions with their general practitioners. Patients and Methods. Thirty-four general practice patients (≥70 years) were asked about their preferences and experiences concerning shared decision making with their doctors using qualitative semistructured interviews. All interviews were analysed according to principles of content analysis. The resulting categories were then arranged into a classification grid to develop a typology of preferences for participating in decision-making processes. Results. Older patients generally preferred to make decisions concerning everyday life rather than medical decisions, which they preferred to leave to their doctors. We characterised eight different patient types based on four interdependent positions (self-determination, adherence, information seeking, and trust). Experiences of a good doctor-patient relationship were associated with trust, reliance on the doctor for information and decision making, and adherence. Conclusion. Owing to the varied patient decision-making types, it is not easy for doctors to anticipate the desired level of patient involvement. However, the decision matter and the self-determination of patients provide good starting points in preparing the ground for shared decision making. A good relationship with the doctor facilitates satisfying decision-making experiences.

Decision Support Software

2009 ◽  
pp. 440-447
Author(s):  
John Wang ◽  
Huanyu Ouyang ◽  
Chandana Chakraborty
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Mathematical Logic ◽  
Decision Support ◽  
Support Systems ◽  
Scientific Methods ◽  
Simulation And Optimization ◽  
Business Software ◽  
The Right ◽  
Support Software

Throughout the years many have argued about different definitions for DSS; however they have all agreed that in order to succeed in the decision-making process, companies or individuals need to choose the right software that best fits their requirements and demands. The beginning of business software extends back to the early 1950s. Since the early 1970s, the decision support technologies became the most popular and they evolved most rapidly (Shim, Warkentin, Courtney, Power, Sharda, & Carlsson, 2002). With the existence of decision support systems came the creation of decision support software (DSS). Scientists and computer programmers applied analytical and scientific methods for the development of more sophisticated DSS. They used mathematical models and algorithms from such fields of study as artificial intelligence, mathematical simulation and optimization, and concepts of mathematical logic, and so forth.

Artificial Intelligence Inroads Into HR

2022 ◽  
pp. 231-246
Author(s):  
Swati Bansal ◽  
Monica Agarwal ◽  
Deepak Bansal ◽  
Santhi Narayanan
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Human Resources ◽  
Generation Y ◽  
Industry 4.0 ◽  
Career Aspirations ◽  
Work Life ◽  
Human Decision ◽  
The Right ◽  
Talent Acquisition

Artificial intelligence is already here in all facets of work life. Its integration into human resources is a necessary process which has far-reaching benefits. It may have its challenges, but to survive in the current Industry 4.0 environment and prepare for the future Industry 5.0, organisations must penetrate AI into their HR systems. AI can benefit all the functions of HR, starting right from talent acquisition to onboarding and till off-boarding. The importance further increases, keeping in mind the needs and career aspirations of Generation Y and Z entering the workforce. Though employees have apprehensions of privacy and loss of jobs if implemented effectively, AI is the present and future. AI will not make people lose jobs; instead, it would require the HR people to upgrade their skills and spend their time in more strategic roles. In the end, it is the HR who will make the final decisions from the information that they get from the AI tools. A proper mix of human decision-making skills and AI would give organisations the right direction to move forward.

Models of the Doctor-Patient Relationship and the Ethics Committee: Part One

1992 ◽  
Vol 1 (1) ◽  
pp. 11-31 ◽  
Author(s):  
David C. Thomasma
Keyword(s):  
Decision Making ◽  
Ethical Issues ◽  
Ethics Committee ◽  
Patient Relationship ◽  
Doctor Patient Relationship ◽  
Patient Decision Making ◽  
Deontological Ethics ◽  
Ethical Discussion ◽  
Patient Decision

Models of the doctor-patient relationship determine which value will predominate in the interaction of the parties. That value then significantly colors and even sometimers alters the nature of the ethical discussion. For example, if an institution predominately prides it-self on its competitive posture, ethical issues arising therein will necessarily be colored by entrepreurial rather than deontological ethics. By contrast, a physician who underlines patient decision making will tend to place autonomy first above all other principles, casting that relationship in a libertarian tone.

ARTIFICIAL INTELLIGENCE AND "PREDICTED JUSTICE": FOREIGN EXPERIENCE

Lex Russica ◽  
2019 ◽  
pp. 79-87
Author(s):  
P. N. Biryukov
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Relevant Information ◽  
Final Decision ◽  
Legal Information ◽  
The Right ◽  
Task Interpretation ◽  
Short Time ◽  
Analytical Tools

The paper deals with the problems of application of artificial intelligence (AI) in the field of justice. Present day environment facilitates the use of AI in law. Technology has entered the market. As a result, "predicted justice" has become possible. Once an overview of the possible future process is obtained, it is easier for the professional to complete the task-interpretation and final decision-making (negotiations, litigation). It will take a lot of work to bring AI up to this standard. Legal information should be structured to make it not only readable, but also effective for decision-making. "Predicted justice" can help both the parties to the case and the judges in structuring information, and students and teachers seeking relevant information. The development of information technology has led to increased opportunities for "predicted justice" programs. They take advantage of new digital tools. The focus is on two advantages of the programs: a) improving the quality of services provided; b) simultaneously monitoring the operational costs of the justice system. "Predicted justice" provides algorithms for analyzing a huge number of situations in a short time, allowing you to predict the outcome of a dispute or at least assess the chances of success. It helps: choose the right way of defense, the most suitable arguments, estimate the expected amount of compensation, etc. Thus, it is not about justice itself, but only about analytical tools that would make it possible to predict future decisions in disputes similar to those that have been analyzed.

Decision of palliative chemotherapy in late-stage cancer: The doctor-patient relationship and the decision-making process as seen by an oncologist.

2016 ◽  
Vol 34 (26_suppl) ◽  
pp. 48-48
Author(s):  
Florian Scotte ◽  
Marie Pechard ◽  
Ivan Krakowski ◽  
Christophe Tournigand ◽  
marcel-Louis Viallard
Keyword(s):  
Decision Making ◽  
Late Stage ◽  
Palliative Chemotherapy ◽  
Specific Treatment ◽  
Decision Making Process ◽  
Patient Relationship ◽  
University Hospitals ◽  
Doctor Patient Relationship ◽  
Medical Progress ◽  
Late Stage Cancer

48 Background: We conducted a literature review on the administration of palliative chemotherapy in cancer patients at advanced stage. We wondered about ethical tensions encountered by the oncologists during the decision process to meet or not the patients' demand to have access to a palliative chemotherapy at a late stage of the disease. Methods: We conducted a multicenter, qualitative study of senior oncologists in university hospitals and cancer centers in France, by carrying out interviews with eleven oncologists. Results: The study are consistent with the literature showing that factors are in favor of treatment continuation: the patient's age, his desire to continue treatment and his life expectancy. The decision making process of chemotherapy discontinuation is marked by uncertainties, personal representations of the doctor and subjectivity in front of the objective facts that could make this decision difficult. The working conditions in cancer care and the valuation of the chemotherapy prescription can impact the decision. The constant medical progress in oncology make more complex the decision of stopping specific treatments. This study showed the singularity of the doctor-patient relationship in oncology. This can explain the difficulty to stop chemotherapy. Conclusions: The oncologist can use the collegiality which are necessary for decision to limit specific treatment. The objective is to propose the adequate care to the patient in all its dimensions. Some actions can be proposed to improve our practice: early use of palliative care for patients, analysis of practices and training to deal with uncertainty and the limits of possibilities in clinical practice.

Finding Cost-Effective Applications for Expert Systems

1993 ◽  
Vol 115 (1) ◽  
pp. 56-61
Author(s):  
P. J. Hartman
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Expert Systems ◽  
Processing Speed ◽  
Development Process ◽  
Cost Effective ◽  
Risk Assessments ◽  
Problem Complexity ◽  
Practical Application ◽  
The Right

Expert systems are one of the few areas of artificial intelligence which have successfully made the transition from research and development to practical application. The key to fielding a successful expert system is finding the right problem to solve. AI costs, including all the development and testing, are so high that the problems must be very important to justify the effort. This paper develops a systematic way of trying to predict the future. It provides robust decision-making criteria, which can be used to predict the success or failure of proposed expert systems. The methods focus on eliminating obviously unsuitable problems and performing risk assessments and cost evaluations of the program. These assessments include evaluation of need, problem complexity, value, user experience, and the processing speed required. If an application proves feasible, the information generated during the decision phase can be then used to speed the development process.

Striking the Right Balance: Patient's Rights and Opposing Interests with Regard to Health Information

2007 ◽  
Vol 14 (2) ◽  
pp. 165-176 ◽  
Author(s):  
Mette Hartlev
Keyword(s):  
Health Information ◽  
Patient Relationship ◽  
Good Care ◽  
Doctor Patient Relationship ◽  
Administrative Efficiency ◽  
Patient’S Rights ◽  
Professional Interest ◽  
The Right

AbstractIn this article, the author explores the nature of confidentiality in the doctor-patient relationship and discusses the extent to which patient's rights to confidentiality, privacy and autonomy are balanced by a professional interest in good care and the organizational interest in administrative efficiency.

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