2021, Number 39
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Inv Ed Med 2021; 10 (39)
Use of a Clinical Decision Support System (DXplain) by Medical Students
Martínez-Franco AI, Vives-Varela T, Martínez-González A, Sánchez-Mendiola M
Language: Spanish
References: 33
Page: 71-78
PDF size: 424.24 Kb.
ABSTRACT
Introduction: Diagnosis is the main challenge in physicians’
duties, and it is fundamental to obtain optimal
clinical results in patients. Physician professional activities
require varying degrees of skills, but few are as difficult
to cultivate as the ability to achieve a correct diagnosis.
Clinical Decision Support Systems (CDSS) can be used
for this processes during medical training.
Objective: To explore medical students’ opinions on using
a CDSS (DXplain) as learning material to analyze clinical
cases.
Method: Observational study with a mixed sequential
method. Second-year medical students of 3 generations (n
= 3,132) of the National Autonomous University of Mexico
Faculty of Medicine, participated using SADC (DXplain)
in the Biomedical Informatics course. Students answered
an online questionnaire of 12 statements with 4 response
options: very inadequate, inadequate, adequate, and very
adequate. The qualitative portion of the study used focus
groups. For statistical analysis, the
χ
2 test was used.
Results: The majority of users (84.9%) found DXplain
system’s inclusion in the Biomedical Informatics course
adequate or very adequate, and 92.3% would recommend
DXplain to other students for their learning. By
triangulating the quantitative and qualitative results, 3
categories related to the use of DXplain were found: 1)
teachers who support its use, 2) motivation for clinical
reasoning, and 3) usefulness for learning.
Conclusions: The students’ opinions were favorable regarding
the use of DXplain as teaching material, at the
initial stage of their career. DXplain must be efficiently
implemented and used as supplement for developing
clinical reasoning.
REFERENCES
Brennan TA, Leape LL, Laird N, Hebert L, Localio AR, Lawthers A, et al. Incidence of Adverse Events and Negligence in Hospitalized Patients Results of the Harvard Medical Practice Study. N Engl J Med. 1991;324:370-376.
WHO, Walton M, Woodward H, Van Staalduinen S, Lemer C, Greaves F, et al. The WHO patient safety curriculum guide for medical schools. Qual Saf Health Care. 2010;19:1-258.
Aranaz-Andrés JM, Aibar-Remón C, Vitaller-Burillo J, Requena- Puche J, Terol-García E, Kelley E, et al. Impact and preventability of adverse events in Spanish public hospitals: results of the Spanish National Study of Adverse Events (ENEAS). Int J Qual Health Care. 2009;21:408-14.
Aranaz-Andrés JM, Aibar-Remón C, Limón-Ramírez R, Amarilla A, Restrepo FR, Urroz O, et al. Prevalence of adverse events in the hospitals of five Latin American countries: results of the ‘Iberoamerican Study of Adverse Events’ (IBEAS). BMJ Qual Saf. 2011;20:1043-51.
Ministerio de Sanidad y Consumo. Estudio APEAS. Estudio Franco 78 Investigación en Educación Médica | Facmed | UNAM sobre la seguridad de los pacientes en atención primaria de salud. Ministerio de Sanidad y Consumo: Madrid; 2008.
Britten N, Stevenson FA, Barry CA, Barber N, Bradley CP. Misunderstandings in prescribing decisions in general practice: qualitative study. Br Med J. 2000;320:484-8.
Guly HR. Diagnostic errors in an accident and emergency department. Emerg Med J. 2001;18:263-9.
Runciman WB, Roughead EE, Semple SJ, Adams RJ. Adverse drug events and medication errors in Australia. Int J Qual Heal Care. 2003;15:49i-59.
Barrows HS, Feltovich PJ. The clinical reasoning process. Med Educ. 1987;21:86-91.
Eva KW, Hatala RM, Leblanc VR, Brooks LR. Teaching from the clinical reasoning literature: combined reasoning strategies help novice diagnosticians overcome misleading information. Med Educ. 2007;41:1152-8.
Norman G. Building on Experience — The Development of Clinical Reasoning. N Engl J Med. 2006;355:2251-2.
Shortliffe EH. President’s column: subspecialty certification in clinical informatics. J Am Med Inform Assoc. 2011;18:890-1.
Kawamoto K, Houlihan CA, Balas EA, Lobach DF. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ. 2005;330:765.
Elkin PL, Liebow M, Bauer BA, Chaliki S, Wahner-Roedler D, Bundrick J, et al. The introduction of a diagnostic decision support system (DXplainTM) into the workflow of a teaching hospital service can decrease the cost of service for diagnostically challenging. Int J Med Inform. 2010;79:772-7.
Schiff GD, Kim S, Abrams R, Cosby K, Lambert B, Elstein AS, et al. Diagnosing Diagnosis Errors: Lessons from a Multiinstitutional Collaborative Project. Agency for Healthcare Research and Quality (US), 2005. Disponible en: http://www. ncbi.nlm.nih.gov/pubmed/21249820.
Garg AX, Adhikari NKJ, McDonald H, Rosas-Arellano MP, Devereaux PJ, Beyene J, et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA. 2005;293: 1223-38.
Miller RA, Masarie FE. The demise of the ‘Greek Oracle’ model for medical diagnostic systems. Methods Inf Med. 1990;29:1-2.
Aspden P, Bootman JL, Cronenwett LR. Preventing Medication Errors (Quality Chasm Series.) By the Committee on Identifying and Preventing Medication Errors and the Board on Health Care Services. The National Academies Press, 2007. doi:10.17226/11623.
Trowbridge R, Weingarten S. Chapter 53. Clinical Decision Support Systems. AHRQ. 2001. Disponible en: https://archive. ahrq.gov/clinic/ptsafety/chap53.htm.
Ammenwerth E, Schnell-Inderst P, Machan C, Siebert U. The effect of electronic prescribing on medication errors and adverse drug events: a systematic review. J Am Med Inform Assoc. 2008;15:585-600.
Eslami S, Abu-Hanna A, de Keizer NF. Evaluation of outpatient computerized physician medication order entry systems: a systematic review. J Am Med Inform Assoc. 2007;14:400-6.
Wolfstadt JI, Gurwitz JH, Field TS, Lee M, Kalkar S, Wu W, et al. The effect of computerized physician order entry with clinical decision support on the rates of adverse drug events: a systematic review. J Gen Intern Med. 2008;23:451-8.
Barnett GO, Cimino JJ, Hupp JA, Hoffer EP. DXplain: An Evolving Diagnostic Decision-Support System. JAMA J Am Med Assoc. 1987;258:67-74.
Feldman MJ, Octo Barnett G. An approach to evaluating the accuracy of DXplain. Comput Methods Programs Biomed. 1991;35:261-6.
Hoffer EP, Feldman MJ, Kim RJ, Famiglietti KT, Barnett GO. DXplain: Patterns of Use of a Mature Expert System. AMIA Annu Symp Proc. 2005:321-5.
Bauer BA, Lee M, Bergstrom L, Wahner-Roedler DL, Bundrick J, Litin S, et al. Internal medicine resident satisfaction with a diagnostic decision support system (DXplain) introduced on a teaching hospital service. Proc AMIA Symp. 2002:31-5.
Lincoln MJ, Turner CW, Haug PJ, Warner HR, Williamson JW, Bouhaddou O et al. Iliad training enhances medical students’ diagnostic skills. J Med Syst. 1991;15:93-110.
Grum CMC, Miller JGJ, Wolf FMF. Computer-based problem solving for primary-care diagnosis in an internal medicine clerkship. Acad Med. 1994;69:429-30.
Martinez-Franco AI, Sanchez-Mendiola M, Mazon-Ramirez JJ, Hernandez-Torres I, Rivero-Lopez C, Spicer T et al. Diagnostic accuracy in Family Medicine residents using a clinical decision support system (DXplain): a randomized-controlled trial. Diagnosis. 2018;0. doi:10.1515/dx-2017-0045.
Martínez-González A, Lifshitz-Guinzberg A, Trejo-Mejía JA, Torruco-García U, Fortoul-van der Goes TITI, Flores- Hernández F et al. Diagnostic and formative assessment of competencies at the beginning of undergraduate medical internship. Gac Med Mex. 2017;153:6-15.
Sánchez-Mendiola M, Martínez-Franco AI, Rosales-Vega A, Villamar-Chulin J, Gatica-Lara F, García-Durán R et al. Development and implementation of a biomedical informatics course for medical students: challenges of a largescale blended-learning program. J Am Med Inform Assoc. 2013;20:381-7.
Childs S, Blenkinsopp E, Hall A, Walton G. Effective e-learning for health professionals and students-barriers and their solutions. A systematic review of the literature-findings from the HeXL project. Health Info Libr J. 2005;22:20-32.
Kanthan R, Senger JL. The impact of specially designed digital games-based learning in undergraduate pathology and medical education. Arch Pathol Lab Med. 2011;135:135-42.