Literature DB >> 2290072

Why the standard view is standard: people, not machines, understand patients' problems.

R A Miller1.   

Abstract

The 'Standard View' regarding computer-based medical diagnostic decision support programs is that, while such systems may be useful adjuncts to human decision-making, they cannot replace human diagnosticians. Mazoué (1990) disputes this viewpoint. He notes that human diagnosis is prone to a variety of errors, and claims that the processes of data collection for diagnosis and the intellectual task of making a diagnosis are independent. Mazoué believes that recent progress in computer-based diagnosis has been encouraging enough to consider the concept of "human-assisted computer diagnosis". This commentary explains why the Standard View should remain standard. Diagnosis is a complex process more involved than producing a nosological label for a set of patient descriptors. Efficient and ethical diagnostic evaluation requires a broad knowledge of people and of disease states. The state of the art in computer-based medical diagnosis does not support the optimistic claim that people can now be replaced by more reliable diagnostic programs.

Entities:  

Keywords:  Professional Patient Relationship

Mesh:

Year:  1990        PMID: 2290072     DOI: 10.1093/jmp/15.6.581

Source DB:  PubMed          Journal:  J Med Philos        ISSN: 0360-5310


  9 in total

1.  Medical informatics and the concept of disease.

Authors:  K F Schaffner
Journal:  Theor Med Bioeth       Date:  2000-01

2.  Effect of CPOE user interface design on user-initiated access to educational and patient information during clinical care.

Authors:  S Trent Rosenbloom; Antoine J Geissbuhler; William D Dupont; Dario A Giuse; Douglas A Talbert; William M Tierney; W Dale Plummer; William W Stead; Randolph A Miller
Journal:  J Am Med Inform Assoc       Date:  2005-03-31       Impact factor: 4.497

3.  Critical appraisal skills teaching in UK dental schools.

Authors:  B Hong; E Plugge
Journal:  Br Dent J       Date:  2017-02-10       Impact factor: 1.626

Review 4.  Medical diagnostic decision support systems--past, present, and future: a threaded bibliography and brief commentary.

Authors:  R A Miller
Journal:  J Am Med Inform Assoc       Date:  1994 Jan-Feb       Impact factor: 4.497

5.  Breast cancer risk estimation with artificial neural networks revisited: discrimination and calibration.

Authors:  Turgay Ayer; Oguzhan Alagoz; Jagpreet Chhatwal; Jude W Shavlik; Charles E Kahn; Elizabeth S Burnside
Journal:  Cancer       Date:  2010-07-15       Impact factor: 6.860

6.  Recommendations for responsible monitoring and regulation of clinical software systems. American Medical Informatics Association, Computer-based Patient Record Institute, Medical Library Association, Association of Academic Health Science Libraries, American Health Information Management Association, American Nurses Association.

Authors:  R A Miller; R M Gardner
Journal:  J Am Med Inform Assoc       Date:  1997 Nov-Dec       Impact factor: 4.497

7.  Sicily statement on classification and development of evidence-based practice learning assessment tools.

Authors:  Julie K Tilson; Sandra L Kaplan; Janet L Harris; Andy Hutchinson; Dragan Ilic; Richard Niederman; Jarmila Potomkova; Sandra E Zwolsman
Journal:  BMC Med Educ       Date:  2011-10-05       Impact factor: 2.463

8.  Clinical decision support system RHINA in the diagnosis and treatment of acute or chronic rhinosinusitis.

Authors:  L Hart; A Polášková; P Schalek
Journal:  BMC Med Inform Decis Mak       Date:  2021-08-09       Impact factor: 2.796

9.  CDSS-RM: a clinical decision support system reference model.

Authors:  Dimitrios Zikos; Nailya DeLellis
Journal:  BMC Med Res Methodol       Date:  2018-11-16       Impact factor: 4.615

  9 in total

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