scholarly journals Cognitive Computing-Based CDSS in Medical Practice

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Jun Chen ◽  
Chao Lu ◽  
Haifeng Huang ◽  
Dongwei Zhu ◽  
Qing Yang ◽  
...  

Importance. The last decade has witnessed the advances of cognitive computing technologies that learn at scale and reason with purpose in medicine studies. From the diagnosis of diseases till the generation of treatment plans, cognitive computing encompasses both data-driven and knowledge-driven machine intelligence to assist health care roles in clinical decision-making. This review provides a comprehensive perspective from both research and industrial efforts on cognitive computing-based CDSS over the last decade. Highlights. (1) A holistic review of both research papers and industrial practice about cognitive computing-based CDSS is conducted to identify the necessity and the characteristics as well as the general framework of constructing the system. (2) Several of the typical applications of cognitive computing-based CDSS as well as the existing systems in real medical practice are introduced in detail under the general framework. (3) The limitations of the current cognitive computing-based CDSS is discussed that sheds light on the future work in this direction. Conclusion. Different from medical content providers, cognitive computing-based CDSS provides probabilistic clinical decision support by automatically learning and inferencing from medical big data. The characteristics of managing multimodal data and computerizing medical knowledge distinguish cognitive computing-based CDSS from other categories. Given the current status of primary health care like high diagnostic error rate and shortage of medical resources, it is time to introduce cognitive computing-based CDSS to the medical community which is supposed to be more open-minded and embrace the convenience and low cost but high efficiency brought by cognitive computing-based CDSS.

2009 ◽  
Vol 29 (5) ◽  
pp. 606-618 ◽  
Author(s):  
Karen E. Lutfey ◽  
Carol L. Link ◽  
Lisa D. Marceau ◽  
Richard W. Grant ◽  
Ann Adams ◽  
...  

The authors examined physician diagnostic certainty as one reason for cross-national medical practice variation. Data are from a factorial experiment conducted in the United States, the United Kingdom, and Germany, estimating 384 generalist physicians’ diagnostic and treatment decisions for videotaped vignettes of actor patients depicting a presentation consistent with coronary heart disease (CHD). Despite identical vignette presentations, the authors observed significant differences across health care systems, with US physicians being the most certain and German physicians the least certain (P < 0.0001). Physicians were least certain of a CHD diagnoses when patients were younger and female (P < 0.0086), and there was additional variation by health care system (as represented by country) depending on patient age (P < 0.0100) and race (P < 0.0021). Certainty was positively correlated with several clinical actions, including test ordering, prescriptions, referrals to specialists, and time to follow-up.


2008 ◽  
Vol 36 (1) ◽  
pp. 95-118 ◽  
Author(s):  
Giles R. Scofield

As everybody knows, advances in medicine and medical technology have brought enormous benefits to, and created vexing choices for, us all – choices that can, and occasionally do, test the very limits of thinking itself. As everyone also knows, we live in the age of consultants, i.e., of professional experts who are ready, willing, and able to give us advice on any and every conceivable question. One such consultant is the medical ethics consultant, or the medical ethicist who consults.Medical ethics consultants involve themselves in just about every aspect of health care decision making. They help legislators and judges determine law, hospitals formulate policies, medical schools develop curricula, etc. In addition to educating physicians, nurses, and lawyers, amongst others, including medical, nursing, and law students, they participate in clinical decision making at the bedside.


2016 ◽  
Vol 25 (4) ◽  
pp. 453-469 ◽  
Author(s):  
Jennifer Horner ◽  
Maria Modayil ◽  
Laura Roche Chapman ◽  
An Dinh

PurposeWhen patients refuse medical or rehabilitation procedures, waivers of liability have been used to bar future lawsuits. The purpose of this tutorial is to review the myriad issues surrounding consent, refusal, and waivers. The larger goal is to invigorate clinical practice by providing clinicians with knowledge of ethics and law. This tutorial is for educational purposes only and does not constitute legal advice.MethodThe authors use a hypothetical case of a “noncompliant” individual under the care of an interdisciplinary neurorehabilitation team to illuminate the ethical and legal features of the patient–practitioner relationship; the elements of clinical decision-making capacity; the duty of disclosure and the right of informed consent or informed refusal; and the relationship among noncompliance, defensive practices, and iatrogenic harm. We explore the legal question of whether waivers of liability in the medical context are enforceable or unenforceable as a matter of public policy.ConclusionsSpeech-language pathologists, among other health care providers, have fiduciary and other ethical and legal obligations to patients. Because waivers try to shift liability for substandard care from health care providers to patients, courts usually find waivers of liability in the medical context unenforceable as a matter of public policy.


1999 ◽  
Vol 15 (3) ◽  
pp. 585-592 ◽  
Author(s):  
Alicia Granados

This paper examines the rationality of the concepts underlying evidence—based medicineand health technology assessment (HTA), which are part of a new current aimed at promoting the use of the results of scientific studies for decision making in health care. It describes the different approaches and purposes of this worldwide movement, in relation to clinical decision making, through a summarized set of specific HTA case studies from Catalonia, Spain. The examples illustrate how the systematic process of HTA can help in several types of uncertainties related to clinical decision making.


Author(s):  
Ken J. Farion ◽  
Michael J. Hine ◽  
Wojtek Michalowski ◽  
Szymon Wilk

Clinical decision-making is a complex process that is reliant on accurate and timely information. Clinicians are dependent (or should be dependent) on massive amounts of information and knowledge to make decisions that are in the best interest of the patient. Increasingly, information technology (IT) solutions are being used as a knowledge transfer mechanism to ensure that clinicians have access to appropriate knowledge sources to support and facilitate medical decision making. One particular class of IT that the medical community is showing increased interest in is clinical decision support systems (CDSSs).


2020 ◽  
Vol 18 (4) ◽  
pp. 2033
Author(s):  
Roxana De las Salas ◽  
Javier Eslava-Schmalbach ◽  
Claudia Vaca-González ◽  
Dolores Rodríguez ◽  
Albert Figueras

Objective: The aim of this study was to develop and validate a stepwise tool to aid primary health care professionals in the process of deprescribing potentially inappropriate medication in older persons. Methods: We carried out a systematic review to identify previously published tools. A composite proposal of algorithm was made by following the steps from clinical experience to deprescribe medications. A 2-round electronic Delphi method was conducted to establish consensus. Eighteen experts from different countries (Colombia, Spain and Argentina) accepted to be part of the panel representing geriatricians, internists, endocrinologist, general practitioners, pharmacologists, clinical pharmacists, family physicians and nurses. Panel members were asked to mark a Likert Scale from 1 to 9 points (1= strongly disagree, 9= strongly agree). The content validity‏ ratio, item-level content validity, and Fleiss’ Kappa statistics was measured to establish reliability. The same voting method was used for round 2. Results: A 7-question algorithm was proposed. Each question was part of a domain and conduct into a decision. In round 1, a consensus was not reached but statements were grouped and organized. In round 2, the tool met consensus. The inter-rater reliability was between substantial and almost perfect for questions with Kappa=0.77 (95% CI 0.60-0.93), for domains with Kappa= 0.73 (95%CI 0.60-0.86) and for decisions with Kappa= 0.97 (95%CI 0.90-1.00). Conclusions: This is a novel tool that captures and supports healthcare professionals in clinical decision-making for deprescribing potentially inappropriate medication. This includes patient’s and caregiver’s preferences about medication. This tool will help to standardize care and provide guidance on the prescribing/deprescribing process of older persons’ medications. Also, it provides a holistic way to reduce polypharmacy and inappropriate medications in clinical practice.


2002 ◽  
Vol 7 (1) ◽  
pp. 65-67 ◽  
Author(s):  
Rosalind Raine

The British National Health Service and other publicly funded health systems operate on the principle that health care should be provided solely on the basis of need. Yet the literature abounds with reports of bias in health care use. In order to defend such a charge, two conditions must be met. The first condition is that treatment decisions must be shown to be unfair in that they are not made solely on the basis of need. This paper demonstrates the importance of considering the fair distribution of health care from two, related, perspectives. The first is that people with equal needs should be treated the same (equal use for equal need). This is referred to as the achievement of horizontal equity. The alternative perspective is that people with greater needs should have more treatment than those with lesser needs (unequal use for unequal need). This is referred to as the achievement of vertical equity. Although these perspectives are logically linked, demonstration of equal use for equal need does not necessarily indicate unequal use for unequal need. This is because it cannot be assumed that equal use occurs at every level of need. The second condition that must be met is that clinical judgement must be shown to be influenced by prejudicial notions about patients. Such research is fraught with methodological difficulties, and the charge of biased clinical decision-making is usually made as a result of a process of exclusion. Methods that could be used to examine the extent to which inequalities in health care use are due to bias are described.


Science ◽  
2015 ◽  
Vol 350 (6266) ◽  
pp. 1397-1397
Author(s):  
R. Rosenquist Brandell ◽  
O. Kallioniemi ◽  
A. Wedell

2020 ◽  
Vol 27 (12) ◽  
pp. 2011-2015 ◽  
Author(s):  
Tina Hernandez-Boussard ◽  
Selen Bozkurt ◽  
John P A Ioannidis ◽  
Nigam H Shah

Abstract The rise of digital data and computing power have contributed to significant advancements in artificial intelligence (AI), leading to the use of classification and prediction models in health care to enhance clinical decision-making for diagnosis, treatment and prognosis. However, such advances are limited by the lack of reporting standards for the data used to develop those models, the model architecture, and the model evaluation and validation processes. Here, we present MINIMAR (MINimum Information for Medical AI Reporting), a proposal describing the minimum information necessary to understand intended predictions, target populations, and hidden biases, and the ability to generalize these emerging technologies. We call for a standard to accurately and responsibly report on AI in health care. This will facilitate the design and implementation of these models and promote the development and use of associated clinical decision support tools, as well as manage concerns regarding accuracy and bias.


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