© 2021 Vadim Vadimovich Ryabikov
2021 – № 2 (22)
Ryabikov V. V. (2021). Kiberneticheskie i chelovekorazmernye sistemy v zdravoohranenii (o nekotoryh principah ocenki ih poleznosti) [Cybernetic and Human-dimension Systems in Health Care (on Some Principles of Their Usefulness Evaluation)]. Medicinskaja antropologija i biojetika [Medical Anthropology and Bioethics], 2 (22).
Vadim Vadimovich Ryabikov is an independent researcher.
Keywords: VUCA (Variability, Uncertainty, Complexity, Ambiguity), CDSS (Clinical Decision Support Systems), cybernetic man-machine systems, human-dimension systems, adaptiveness resources, efficiency, ethical criteria, economic criteria
Abstract. Introduction into the health care system of technologies based on artificial intelligence implies emergence in it of complicated cybernetic and human-dimension systems that have the human as their main element. These systems are characterized by their ability to self-organize and sense of purpose. When evaluating the usefulness of the introduction of these technologies into health care, it is important to be guided by ethical criteria informed by humanistic values. In the conditions when economic criteria are prioritized, the introduction of clinical decision support systems (CDSS) paradoxically makes it more likely that adaptive capacities of health care as a whole may drop.
The health care system is designed to ensure the high professional efficiency of doctors in situations of uncertainty. To define such situations, there is a technical term VUCA (Variability, Uncertainty, Complexity, Ambiguity). This acronym was created by US elite special forces and is now widely used to refer to such situations in business management.
For the health care system, VUCA situations should be considered normal. They arise in connection with pandemics, epidemics, natural disasters, catastrophes of various types, armed conflicts, etc., but also the dynamics of the state of an individual patient, or the dynamics of the state of a flow of patients. Especially when it comes to patients requiring emergency medical intervention and being brought to hospitals by ambulance service. The main resource for the adaptability of the health care system in these situations is:
– the level of education of doctors;
– their experience, intuition, and skill;
– their responsibility (inseparable from certain tactical freedom during treatment);
– professional ethics;
– a general culture of doctors (including humanitarian);
– the general level of moral values and humanity;
– search and cognitive activity of doctors;
– the ingenuity of doctors;
– doctors’ collegiality;
-the ability of doctors to act in a state of group flow.
All these qualities and abilities cannot be adequately assessed by quantitative indicators, and largely depend on the ability of doctors to act as agents (subjects) of action, to be independent of other people and circumstances.
According to S. L. Rubinshtein, the subject is characterized by such qualities as activity, the ability to develop and integrate, self-determination, self-regulation, self-promotion, and self-improvement. In the case of a decrease in the level of the subjectivity of doctors, the level of the main adaptive resources in the health care system begins to decline. This process is difficult to reverse.
A shortage of adaptability resources in the health care system can be observed either in the case of a decrease in the qualifications of doctors and a partial loss of their professional and human qualities or in the case of extremely high requirements for highly qualified doctors due to an increasing workload when there is not enough time for making medical decisions and the professional burnout syndrome makes itself felt.
Can medical clinical decision support systems (CDSS or DSS), based on artificial intelligence (AI) technologies, compensate for the lack of adaptability resources, if it occurs in the health care system?
The introduction of technology is carried out in a specific geographical (place, location, where?), social, technosphere (level of development of the technosphere in a particular place), economic, political, noospheric (cultural, educational, etc.), infospheric contexts.
Contexts are connected by direct and reverse links. Technology interacts with contexts in the same way. That is, through direct and reverse links. Maintenance of technology requires the involvement of people of various competencies, financial and organizational resources. People, finance, information, technology in this situation begin to intertwine and interact with each other as actors. The connected interaction forms a system.
This system exists in the flows of patients, information, and finances. If these flows disappear, the system ceases to exist, and the technology is “taken to the warehouse”.
A system that originated in a specific location, but is connected to global networks, can be considered a cybernetic “man-machine”.
These local systems, being connected by direct and feedback links with local administrations, ministries, entire industries, IT companies, form not just a network, but a larger-scale system that reveals new, emergent system properties and purposefulness. The emerging system should be considered as human-dimension. This type of system includes all social objects considered in the aspect of not only functioning but also development. A person with his intellect, psycho-physiological qualities, professional knowledge and skills, experience, attitude to work, value orientations, etc. becomes the main element of this system.
Depending on the chosen ethical priorities and criteria for evaluating the usefulness of CDSS, the introduction and widespread use of such technologies can lead to both an increase of the adaptability resource and its catastrophic decrease. The effect of the introduction of technology in different societies can be diametrically opposite.
The system that has emerged as a result of the introduction of CDSS in the health care system, the situation of a shortage of adaptation resources becomes beneficial since it gives it a chance to prove its usefulness and effectiveness.
The cost-effectiveness and practical benefits of CDSS will be obvious if, for example, the number of full-time doctors is reduced, the duties of the remaining staff doctors are still fulfilled, and they are connected to CDSS. Naturally, in the conditions of lack of time, the doctor will turn to the system of prompts offered by the SPPVR. Especially if the responsibility for making decisions is removed from him, and shifted to AI. In a situation of excessive workload, the doctor will make more mistakes without the CDSS. While in a hurry, he will be forced to rely on CDSS and follow the logic of algorithms, neglecting his intuition and experience. The accuracy and adequacy of his decisions will correspond to machine logic. His cognitive system will gradually but inevitably hybridize with AI. The quality of medical decisions will decrease, but due to emerging feedback, this will be beneficial for a human-dimension system with AI. Because it is the lack of adaptation resources that justifies its existence and an argument in favor of obtaining new subsidies for its development.
Accordingly, when CDSS is introduced into the health care system in circumstances where it is dominated by economic priorities, and efficiency is assessed solely by quantitative criteria, the level of its adaptive resources will decrease. And the economic performance indicators will look quite acceptable. One doctor hybridized with AI will be able to serve more patients per unit of time. The degradation of the system will be imperceptible, but inevitable.
It will show up in another VUCA situation on a regional or global scale when the health care system will be chaotic.
To avoid such a sad fate, the priority of ethical values over economic ones should be approved in the health care system.
Begum, Sh., Ahmed, M.U., Funk, P., Xiong, N., Folke, M. (2011) Case-based reasoning systems in the health sciences: a survey of recent trends and developments, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), Vol. 41, No. 4, р. 421–434. DOI: 10.1109/TSMCC.2010.2071862.
Black, A.D., Car, J., Pagliari, C., Anandan, C., Cresswell, K., Bokun, T., McKinstry, B., Procter, R., Majeed, A., Sheikh, A. (2011) The impact of eHealth on the quality and safety of health care: A systematic overview, PLoS Medicine journal, Vol. 8, No. 1. DOI: 10.1371/journal.pmed.1000387.
Csikszentmihalyi, M. (2011) Potok: Psihologija optimal’nogo perezhivanija [Flow: The Psychology of Optimal Experience], Moscow: Smysl.
Guryev, N. D. (2000) Strasti i ih voploshhenie v boleznjah (somaticheskih i nervno-psihicheskih)[Passion and their embodiment in diseases (somatic and neuropsychic)], Moscow: Ecosprom.
Mahsa, S., Taha, S.-S., Samad, Sh, V., Peyman R. (2018). Decision support system for triage management: A hybrid approach using rule-based reasoning and fuzzy logic. International Journal of Medical Informatics. 114. 10.1016/j.ijmedinf.2018.03.008.
Maslow, A. (1999) Novye rubezhi chelovecheskoj prirody [New frontiers of human nature], Moscow: Smysl.
Moja, L., Kwag, K.H., Lytras, T., Bertizzolo, L., Brandt, L., Pecoraro, V., Rigon, G., Vaona, A., Ruggiero, F., Mangia, M., Iorio, A., Kunnamo, I., Bonovas, S. (2014) Effectiveness of computerized decision support systems linked to electronic health records: a systematic review and meta-analysis, American Journal of Public Health, Vol. 104, No. 12, р.35–44. DOI: 10.2105/AJPH.2014.302164.
Naydenov, M.I. (2010) Formirovanie refleksivnogo upravlenija v organizacijah [Formation of reflexive management in organizations], Abstract of the dissertation, Kiev: G.S. Kostyuk Institute of Psychology.
Podkolozin, V.A. (2019) Medicinskaja fizika [Medical Physics]. Textbook, Saratov: Saratov University Press.
Rubinstein, S. L. (2003) Bytie i soznanie. Chelovek i mir [Being and Consciousness. Man and the World], St. Petersburg: Peter.
Stepin, V.S. (2009) Klassika, neklassika, postneklassika: kriterii razlichenij. [Classics, non-classical, post-non-classical: criteria of distinction], Postneklassika: filosofija, nauka, kul’tura [Post-non-classical: philosophy, science, culture], St. Petersburg: Mir, p. 249–295.