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DOI: 10.15265/IY-2016-055
Computerized Clinical Decision Support: Contributions from 2015
Correspondence to:
Publication History
10 November 2016
Publication Date:
06 March 2018 (online)
Summary
Objective: To summarize recent research and select the best papers published in 2015 in the field of computerized clinical decision support for the Decision Support section of the IMIA yearbook.
Method: A literature review was performed by searching two bibliographic databases for papers related to clinical decision support systems (CDSSs) and computerized provider order entry (CPOE) systems. The aim was to identify a list of candidate best papers from the retrieved papers that were then peer-reviewed by external reviewers. A consensus meeting between the two section editors and the IMIA editorial team was finally conducted to conclude in the best paper selection.
Results: Among the 974 retrieved papers, the entire review process resulted in the selection of four best papers. One paper reports on a CDSS routinely applied in pediatrics for more than 10 years, relying on adaptations of the Arden Syntax. Another paper assessed the acceptability and feasibility of an important CPOE evaluation tool in hospitals outside the US where it was developed. The third paper is a systematic, qualitative review, concerning usability flaws of medication-related alerting functions, providing an important evidence-based, methodological contribution in the domain of CDSS design and development in general. Lastly, the fourth paper describes a study quantifying the effect of a complex, continuous-care, guideline-based CDSS on the correctness and completeness of clinicians’ decisions.
Conclusions: While there are notable examples of routinely used decision support systems, this 2015 review on CDSSs and CPOE systems still shows that, despite methodological contributions, theoretical frameworks, and prototype developments, these technologies are not yet widely spread (at least with their full functionalities) in routine clinical practice. Further research, testing, evaluation, and training are still needed for these tools to be adopted in clinical practice and, ultimately, illustrate the benefits that they promise.
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Keywords
Medical informatics - International Medical Informatics Association - yearbook - clinical decision support systems
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References
- 1 Coiera E, Ash J, Berg M. The unintended consequences of health information technology revisited.. Yearb Med Inform 2016; 163-9.
- 2 Lamy JB, Séroussi B, Griffon N, Kerdelhué G, Jaulent MC, Bouaud J. Toward a formalization of the process to select IMIA Yearbook best papers.. Methods Inf Med 2015; 54 (Suppl. 02) 135-44.
- 3 Bouaud J, Koutkias V. Computerized Clinical Decision Support: Contributions from 2014.. Yearb Med Inform 2015; 119-24.
- 4 Anand V, Carroll AE, Biondich PG, Dugan TM, Downs SM. Pediatric decision support using adapted Arden Syntax.. Artif Intell Med 2015 Oct 1.
- 5 Anand V, Biondich PG, Liu G, Rosenman M, Downs SM. Child health improvement through computer automation: the CHICA system.. Stud Health Technol Inform 2004; 107 (Suppl. 01) 187-91.
- 6 Cho I, Lee JH, Choi SK, Choi JW, Hwang H, Bates DW. Acceptability and feasibility of the Leapfrog computerized physician order entry evaluation tool for hospitals outside the United States.. Int J Med Inform 2015; Sep 84 (Suppl. 09) 694-701.
- 7 Jung M, Hoerbst A, Hackl WO, Kirrane F, Borbolla D, Jaspers MW. et al. Attitude of physicians towards automatic alerting in computerized physician order entry systems. A comparative international survey.. Methods Inf Med 2013; 52 (Suppl. 02) 99-108.
- 8 Marcilly R, Ammenwerth E, Vasseur F, Roehrer E, Beuscart-Zéphir MC. Usability flaws of medication-related alerting functions: A systematic qualitative review.. J Biomed Inform 2015; Jun 55: 260-71.
- 9 Shalom E, Shahar Y, Parmet Y, Lunenfeld E. A multiple-scenario assessment of the effect of a continuous-care, guideline-based decision support system on clinicians’ compliance to clinical guidelines.. Int J Med Inform 2015; Apr 84 (Suppl. 04) 248-62.
- 10 Wilk S, Kezadri-Hamiaz M, Rosu D, Kuziemsky C, Michalowski W, Amyot D, Carrier M. Using Semantic Components to Represent Dynamics of an Interdisciplinary Healthcare Team in a Multi-Agent Decision Support System.. J Med Syst 2016; Feb 40 (Suppl. 02) 42.
- 11 Khazaei H, McGregor C, Eklund JM, El-Khatib K. Real-Time and Retrospective Health-Analytics-as-a-Service: A Novel Framework.. JMIR Med Inform 2015; Nov 18 3 (Suppl. 04) e36.
- 12 Bettencourt-Silva JH, Clark J, Cooper CS, Mills R, Rayward-Smith VJ, de la Iglesia B. Building Data-Driven Pathways From Routinely Collected Hospital Data: A Case Study on Prostate Cancer.. JMIR Med Inform. 2015; Jul 10 3 (Suppl. 03) e26.
- 13 Sarker A, Mollá D, Paris C. Automatic evidence quality prediction to support evidence-based decision making.. Artif Intell Med 2015; Jun 64 (Suppl. 02) 89-103.
- 14 Li Q, Kirkendall ES, Hall ES, Ni Y, Lingren T, Kaiser M. et al., Automated detection of medication administration errors in neonatal intensive care.. J Biomed Inform 2015 Jul 17.
- 15 Shoshi A, Hoppe T, Kormeier B, Ogultarhan V, Hofestädt R. GraphSAW: a web-based system for graphical analysis of drug interactions and side effects using pharmaceutical and molecular data.. BMC Med Inform Decis Mak 2015; Feb 28 15: 15.
- 16 Sukums F, Mensah N, Mpembeni R, Massawe S, Duysburgh E, Williams A. et al. Promising adoption of an electronic clinical decision support system for antenatal and intrapartum care in rural primary healthcare facilities in sub-Saharan Africa: The QUALMAT experience.. Int J Med Inform 2015; Sep 84 (Suppl. 09) 647-57.
- 17 Cho I, Slight SP, Nanji KC, Seger DL, Maniam N, Fiskio JM. et al. The effect of provider characteristics on the responses to medication-related decision support alerts.. Int J Med Inform 2015; Sep 84 (Suppl. 09) 630-9.
- 18 Slight SP, Eguale T, Amato MG, Seger AC, Whitney DL, Bates DW, Schiff GD. The vulnerabilities of computerized physician order entry systems: a qualitative study.. J Am Med Inform Assoc 2016; Mar 23 (Suppl. 02) 311-6.
- 19 Dekarske BM, Zimmerman CR, Chang R, Grant PJ, Chaffee BW. Increased appropriateness of customized alert acknowledgement reasons for overridden medication alerts in a computerized provider order entry system.. Int J Med Inform 2015; Dec 84 (Suppl. 12) 1085-93.
- 20 Czock D, Konias M, Seidling HM, Kaltschmidt J, Schwenger V, Zeier M. et al. Tailoring of alerts substantially reduces the alert burden in computerized clinical decision support for drugs that should be avoided in patients with renal disease.. J Am Med Inform Assoc 2015; Jul 22 (Suppl. 04) 881-7.
Correspondence to:
-
References
- 1 Coiera E, Ash J, Berg M. The unintended consequences of health information technology revisited.. Yearb Med Inform 2016; 163-9.
- 2 Lamy JB, Séroussi B, Griffon N, Kerdelhué G, Jaulent MC, Bouaud J. Toward a formalization of the process to select IMIA Yearbook best papers.. Methods Inf Med 2015; 54 (Suppl. 02) 135-44.
- 3 Bouaud J, Koutkias V. Computerized Clinical Decision Support: Contributions from 2014.. Yearb Med Inform 2015; 119-24.
- 4 Anand V, Carroll AE, Biondich PG, Dugan TM, Downs SM. Pediatric decision support using adapted Arden Syntax.. Artif Intell Med 2015 Oct 1.
- 5 Anand V, Biondich PG, Liu G, Rosenman M, Downs SM. Child health improvement through computer automation: the CHICA system.. Stud Health Technol Inform 2004; 107 (Suppl. 01) 187-91.
- 6 Cho I, Lee JH, Choi SK, Choi JW, Hwang H, Bates DW. Acceptability and feasibility of the Leapfrog computerized physician order entry evaluation tool for hospitals outside the United States.. Int J Med Inform 2015; Sep 84 (Suppl. 09) 694-701.
- 7 Jung M, Hoerbst A, Hackl WO, Kirrane F, Borbolla D, Jaspers MW. et al. Attitude of physicians towards automatic alerting in computerized physician order entry systems. A comparative international survey.. Methods Inf Med 2013; 52 (Suppl. 02) 99-108.
- 8 Marcilly R, Ammenwerth E, Vasseur F, Roehrer E, Beuscart-Zéphir MC. Usability flaws of medication-related alerting functions: A systematic qualitative review.. J Biomed Inform 2015; Jun 55: 260-71.
- 9 Shalom E, Shahar Y, Parmet Y, Lunenfeld E. A multiple-scenario assessment of the effect of a continuous-care, guideline-based decision support system on clinicians’ compliance to clinical guidelines.. Int J Med Inform 2015; Apr 84 (Suppl. 04) 248-62.
- 10 Wilk S, Kezadri-Hamiaz M, Rosu D, Kuziemsky C, Michalowski W, Amyot D, Carrier M. Using Semantic Components to Represent Dynamics of an Interdisciplinary Healthcare Team in a Multi-Agent Decision Support System.. J Med Syst 2016; Feb 40 (Suppl. 02) 42.
- 11 Khazaei H, McGregor C, Eklund JM, El-Khatib K. Real-Time and Retrospective Health-Analytics-as-a-Service: A Novel Framework.. JMIR Med Inform 2015; Nov 18 3 (Suppl. 04) e36.
- 12 Bettencourt-Silva JH, Clark J, Cooper CS, Mills R, Rayward-Smith VJ, de la Iglesia B. Building Data-Driven Pathways From Routinely Collected Hospital Data: A Case Study on Prostate Cancer.. JMIR Med Inform. 2015; Jul 10 3 (Suppl. 03) e26.
- 13 Sarker A, Mollá D, Paris C. Automatic evidence quality prediction to support evidence-based decision making.. Artif Intell Med 2015; Jun 64 (Suppl. 02) 89-103.
- 14 Li Q, Kirkendall ES, Hall ES, Ni Y, Lingren T, Kaiser M. et al., Automated detection of medication administration errors in neonatal intensive care.. J Biomed Inform 2015 Jul 17.
- 15 Shoshi A, Hoppe T, Kormeier B, Ogultarhan V, Hofestädt R. GraphSAW: a web-based system for graphical analysis of drug interactions and side effects using pharmaceutical and molecular data.. BMC Med Inform Decis Mak 2015; Feb 28 15: 15.
- 16 Sukums F, Mensah N, Mpembeni R, Massawe S, Duysburgh E, Williams A. et al. Promising adoption of an electronic clinical decision support system for antenatal and intrapartum care in rural primary healthcare facilities in sub-Saharan Africa: The QUALMAT experience.. Int J Med Inform 2015; Sep 84 (Suppl. 09) 647-57.
- 17 Cho I, Slight SP, Nanji KC, Seger DL, Maniam N, Fiskio JM. et al. The effect of provider characteristics on the responses to medication-related decision support alerts.. Int J Med Inform 2015; Sep 84 (Suppl. 09) 630-9.
- 18 Slight SP, Eguale T, Amato MG, Seger AC, Whitney DL, Bates DW, Schiff GD. The vulnerabilities of computerized physician order entry systems: a qualitative study.. J Am Med Inform Assoc 2016; Mar 23 (Suppl. 02) 311-6.
- 19 Dekarske BM, Zimmerman CR, Chang R, Grant PJ, Chaffee BW. Increased appropriateness of customized alert acknowledgement reasons for overridden medication alerts in a computerized provider order entry system.. Int J Med Inform 2015; Dec 84 (Suppl. 12) 1085-93.
- 20 Czock D, Konias M, Seidling HM, Kaltschmidt J, Schwenger V, Zeier M. et al. Tailoring of alerts substantially reduces the alert burden in computerized clinical decision support for drugs that should be avoided in patients with renal disease.. J Am Med Inform Assoc 2015; Jul 22 (Suppl. 04) 881-7.