2016: IMIA Yearbook 2016

Journal: IMIA Yearbook
ISSN: 0943-4747
Topic:

Unintended Consequences: New Problems and New Solutions


61 articles
21.

Section 2: Human Factors and Organizational Issues

Survey

G. A. Wildenbos (1), L. W. Peute (1), M. W. M. Jaspers (1)

(1) Academic Medical Center, University of Amsterdam, Department of Medical Informatics, Center for Human Factors Engineering of Health Information Technology (HIT-Lab), The Netherlands

Yearb Med Inform 2016 : 113-119

https://doi.org/10.15265/IY-2016-031

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22.

Section 2: Human Factors and Organizational Issues

Working Group Contribution

A. Kushniruk (1, 2), C. Nohr (2), E. Borycki (1)

(1) School of Health Information Science, University of Victoria, Victoria, Canada; (2) Department of Development and Planning, Aalborg University, Aalborg, Denmark

Yearb Med Inform 2016 : 120-125

https://doi.org/10.15265/IY-2016-024

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23.

Section 2: Human Factors and Organizational Issues

Synopsis

S. Pelayo (1), R. Santos (2)

(1) INSERM CIC-IT 1403 Evalab, CHU Lille, UDSL EA 2694, Lille University, Lille, France; (2) HOSPITAL DA LUZ – LEARNING HEALTH, Lisboa, Portugal

Yearb Med Inform 2016 : 126-129

https://doi.org/10.15265/IY-2016-043

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24.

Section 2: Human Factors and Organizational Issues

Ammenwerth E. Evidence-based Health Informatics: How Do We Know What We Know? Methods Inf Med 2015;54(4):298-307. https://dx.doi.org/10.3414/ME14-01-0119

Furniss D, Masci P, Curzon P, Mayer A, Blandford A. Exploring medical device design and use through layers of Distributed Cognition: How a glucometer is coupled with its context? J Biomed Inform 2015;53:330-41. https://dx.doi.org/10.1016/j.jbi.2014.12.006

Jensen S, Kushniruk AW, Nohr C. Clinical simulation: A method for development and evaluation of clinical information systems. J Biomed Inform 2015;54:65-76. https://dx.doi.org/10.1016/j.jbi.2015.02.002

Singh H, Sittig DF. Measuring and improving patient safety through health information technology: The Health IT Safety Framework. BMJ Qual Saf 2015;0:1-7. https://dx.doi.org/10.1136/bmjqs-2015-004486

Vincent CJ, Blandford A. Usability standards meet scenario-based design: Challenges and opportunities. J Biomed Inform 2015;53:243-50. https://dx.doi.org/10.2196/mhealth.3918

Yearb Med Inform 2016 : 128-129

[Summary]
25.

Section 3: Clinical Information Systems

Survey

U. Sax (1), M. Lipprandt (2), R. Röhrig (2)

(1) Department of Medical Informatics, University Medical Center Göttingen, Göttingen, Germany; (2) Institute of Medical Informatics, Carl von Ossietzky University, Oldenburg, Germany

Yearb Med Inform 2016 : 130-137

https://doi.org/10.15265/IY-2016-038

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26.

Section 3: Clinical Information Systems

Working Group Contribution

H. Liyanage (1), S.-T. Liaw (2), C. T. Di Iorio (3), C. Kuziemsky (4), R. Schreiber (5), A. L. Terry (6), S. de Lusignan (1)

(1) Department of Clinical & Experimental Medicine, University of Surrey, Guildford, Surrey, UK; (2) School of Public Health & Community Medicine, UNSW Medicine Australia, NSW, Australia; (3) Legal consultant, Serectrix snc, Pescara, Italy; (4) Telfer School of Management, University of Ottawa, Ottawa, Ontario, Canada; (5) Holy Spirit Hospital—A Geisinger Affiliate, Camp Hill, PA, USA; (6) Centre for Studies in Family Medicine, Department of Family Medicine, Interfaculty Program in Public Health, Department of Epidemiology & Biostatistics; Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada

Yearb Med Inform 2016 : 138-145

https://doi.org/10.15265/IY-2016-035

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27.
New Problems - New Solutions: A Never Ending Story
Findings from the Clinical Information Systems Perspective for 2015

Section 3: Clinical Information Systems

Synopsis

W. O. Hackl (1), T. Ganslandt (2)

(1) Institute of Biomedical Informatics, UMIT-University of Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria; (2) Medical Center for Information and Communication, Erlangen University Hospital, Erlangen, Germany

Yearb Med Inform 2016 : 146-151

https://doi.org/10.15265/IY-2016-054

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28.

Section 3: Clinical Information Systems

Pickering BW, Dong Y, Ahmed A, Giri J, Kilickaya O, Gupta A, Gajic O, Herasevich V. The implementation of clinician designed, human-centered electronic medical record viewer in the intensive care unit: a pilot step-wedge cluster randomized trial. Int J Med Inform 2015 May;84(5):299-307. https://dx.doi.org/10.1016/j.ijmedinf.2015.01.017

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(2):311-6. https://dx.doi.org/10.1093/jamia/ocv135

Varpio L, Rashotte J, Day K, King J, Kuziemsky C, Parush A. The EHR and building the patient’s story: A qualitative investigation of how EHR use obstructs a vital clinical activity. Int J Med Inform 2015 Dec;84(12):1019-28. https://dx.doi.org/10.1016/j.ijmedinf.2015.09.004

Wright A, McCoy AB, Hickman TT, Hilaire DS, Borbolla D, Bowes WA 3rd, Dixon WG, Dorr DA, Krall M, Malholtra S, Bates DW, Sittig DF. Problem list completeness in electronic health records: A multisite study and assessment of success factors. Int J Med Inform 2015 Oct;84(10):784-90. https://dx.doi.org/10.1016/j.ijmedinf.2015.06.011

Yearb Med Inform 2016 : 150-151

[Summary]
29.

Section 4: Sensor, Signal and Imaging Informatics

Survey

J. Kabil (1), L. Belguerras (1), S. Trattnig (2), C. Pasquier (1, 3), J. Felblinger (1, 4), A. Missoffe (1)

(1) IADI U947, INSERM, Université de Lorraine, CHRU Nancy, France; (2) Department of Biomedical Imaging and Image-guided Therapy, Centre of Excellence, High-Field MR, Medical University of Vienna, Vienna, Austria; (3) Healtis, Nancy, France; (4) CIC-IT 1433, INSERM, CHRU Nancy, France

Yearb Med Inform 2016 : 152-158

https://doi.org/10.15265/IY-2016-016

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30.

Section 4: Sensor, Signal and Imaging Informatics

Synopsis

C. Hughes (1), S. Voros (2, 3), A. Moreau-Gaudry (4, 3)

(1) Univ. Grenoble Alpes, INSERM, CIC 1406; CHU Grenoble, Pôle Recherche, Grenoble, France; (2) Univ. Grenoble Alpes, CNRS, INSERM, TIMC-IMAG, Grenoble, France; (3) Section Editors for the IMIA Yearbook Section on Sensor Signal and Imaging Informatics; (4) INSERM CIC 1406; Univ. Grenoble Alpes, CNRS, TIMC-IMAG; CHU de Grenoble, Pôle Santé Publique, Grenoble, France

Yearb Med Inform 2016 : 159-162

https://doi.org/10.15265/IY-2016-053

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31.

Section 4: Sensor, Signal and Imaging Informatics

Chen Z, Strange H, Oliver A, Denton ER, Boggis C, Zwiggelaar R. Topological Modeling and Classification of Mammographic Microcalcification Clusters. IEEE Trans Biomed Eng 2015;62(4):1203–14. https://dx.doi.org/10.1109/TBME.2014.2385102

Ha S, Mueller K. Low dose CT image restoration using a database of image patches. Phys Med Biol 2015;60(2):869-82. https://dx.doi.org/10.1088/0031-9155/60/2/869

Liu C, van Netten JJ, van Baal JG, Bus SA, van der Heijden F. Automatic detection of diabetic foot complications with infrared thermography by asymmetric analysis. J Biomed Opt 2015;20(2):26003. https://dx.doi.org/10.1117/1.JBO.20.2.026003

Mert S, Özbek E, Ötünçtemur A, Çulha M. Kidney tumor staging using surface-enhanced Raman scattering. J Biomed Opt 2015;20(4):47002. https://dx.doi.org/10.1117/1.JBO.20.4.047002

Yearb Med Inform 2016 : 161-162

[Summary]
32.

Section 5: Decision Support

Survey

E. Coiera (1), J. Ash (2), M. Berg (3)

(1) Australian Institute of Health Innovation, Macquarie University, Australia; (2) Department of Medical Informatics and Clinical Epidemiology, School of Medicine, Oregon Health & Science University, USA; (3) Principal, Advisory, KPMG LLP (US)

Yearb Med Inform 2016 : 163-169

https://doi.org/10.15265/IY-2016-014

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33.

Section 5: Decision Support

Synopsis

V. Koutkias (1, 2), J. Bouaud (3, 4)

(1) Institute of Applied Biosciences, Centre for Research & Technology Hellas, Thermi, Thessaloniki, Greece; (2) Lab of Computing and Medical Informatics, Department of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece; (3) AP-HP, Department of Clinical Research and Development, Paris, France; (4) INSERM, Sorbonne Université, UPMC Univ Paris 06, Université Paris 13, Sorbonne Paris Cité, UMRS 1142, LIMICS, Paris, France

Yearb Med Inform 2016 : 170-177

https://doi.org/10.15265/IY-2016-055

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34.

Section 5: Decision Support

Anand V, Carroll AE, Biondich PG, Dugan TM, Downs SM. Pediatric decision support using adapted Arden Syntax. Artif Intell Med 2015 Oct 1. https://dx.doi.org/10.1016/j.artmed.2015.09.006

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(9):694-701. https://dx.doi.org/10.1016/j.ijmedinf.2015.05.011

Marcilly R, Ammenwerth E, Vasseur F, Roehrer E, Beuscart-Zéphir MC. Usability flaws of medicationrelated alerting functions: A systematic qualitative review. J Biomed Inform 2015 Jun;55:260-71. https://dx.doi.org/10.1016/j.jbi.2015.03.006

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(4):248-62. https://dx.doi.org/10.1016/j.ijmedinf.2015.01.004

Yearb Med Inform 2016 : 176-177

[Summary]
35.

Section 6: Knowledge Representation and Management

Survey

M. Barros (1), F. M. Couto (1)

(1) LaSIGE, Faculdade de Ciências, Universidade de Lisboa, Portugal

Yearb Med Inform 2016 : 178-183

https://doi.org/10.15265/IY-2016-022

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36.
Efficient Results in Semantic Interoperability for Health Care
Findings from the Section on Knowledge Representation and Management

Section 6: Knowledge Representation and Management

Synopsis

L. F. Soualmia (1, 2), J. Charlet (2, 3)

(1) Normandie Universités, Univ. Rouen, NormaSTIC FR CNRS 3638, IRIB and LITIS EA 4108, Information Processing in Biology & Health, Saint Étienne du Rouvray, France; (2) INSERM, UMR_S 1142, LIMICS, Paris, France; Sorbonne Universités, Univ. Paris 06, Paris, France; (3) AP-HP, Dept. of Clinical Research and Development, Paris, France

Yearb Med Inform 2016 : 184-187

https://doi.org/10.15265/IY-2016-051

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37.

Section 6: Knowledge Representation and Management

Alonso-Calvo R, Perez-Rey D, Paraiso-Medina S, Clearhout B, Hennebert P, Bucur A. Enabling semantic interoperability in multi-centric clinical trials on breast cancer. Computer Methods Programs Biomed 2015;118:322–9. https://dx.doi.org/10.1016/j.cmpb.2015.01.003

Chi YL, Chen TY, Tsai WT. A chronic disease dietary consultation system using OWL-based ontologies and semantic rules. J Biomed Inform 2015;53:208–19. https://dx.doi.org/10.1016/j.jbi.2014.11.001

Groza T, Köhler S, Moldenhauer D, Vasilevsky N, Baynam G, Zemojtel T, Schriml LM, Kibbe WA, Schofield PN, Beck T, Vasant D, Brookes AJ, Zankl A, Washington NL, Mungall CJ, Lewis SE, Haendel MA, Parkinson H, Robinson PN. The Human Phenotype Ontology: semantic unification of common and rare disease. Am J Hum Genet 2015;97:111–24. https://dx.doi.org/10.1016/j.ajhg.2015.05.020

Mortensen JM, Minty EP, Januszyk M, Sweeney TE, Rector AL, Noy NF, Musen MA. Using the widsom of the crouds to find critical errors in biomedical ontologies: a study of SNOMED CT. J Am Med Inform Assoc 2015;22:640–8. https://dx.doi.org/10.1136/amiajnl-2014-002901

Yearb Med Inform 2016 : 187-187

[Summary]
38.

Section 7: Consumer Health Informatics

Synopsis

L. Fernandez-Luque (1), P. Staccini (2)

(1) Qatar Computing Research Institute, HBKU, Qatar Foundation, Doha, Qatar; (2) INSERM UMR 912 SESSTIM, IRIS Dept, UFR Médecine, Université Nice-Sophia Antipolis, France

Yearb Med Inform 2016 : 188-193

https://doi.org/10.15265/IY-2016-045

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39.

Section 7: Consumer Health Informatics

Huckvale K, Prieto JT, Tilney M, Benghozi P-J, Car J. Unaddressed privacy risks in accredited health and wellness apps: a cross-sectional systematic assessment. BMC Med 2015;13(1):214. https://dx.doi.org/10.1186/s12916-015-0444-y

Lau AY. Why Didn’t it Work? Lessons From a Randomized Controlled Trial of a Web-based Personally Controlled Health Management System for Adults with Asthma. J Med Internet Res 2015;17: e283. https://dx.doi.org/10.2196/jmir.4734

Minto C, Bauce B, Calore C, Rigato I, Folino F, Soriani N, Hochdorn A, Iliceto S, Gregori D. Is Internet use associated with anxiety in patients with and at risk for cardiomyopathy? Am Heart J 2015;170(1):87–95. https://dx.doi.org/10.1016/j.ahj.2015.02.024

Rozental A, Boettcher J, Andersson G, Schmidt B, Carlbring P. Negative Effects of Internet Interventions: A Qualitative Content Analysis of Patients’ Experiences with Treatments Delivered Online. Cogn Behav Ther 2015;44(3):223–36. https://dx.doi.org/10.1080/16506073.2015.1008033

Zhang Z, Zhang Z, Li H. Predictors of the authenticity of Internet health rumours. Health Info Libr J 2015;32(3):195–205. https://dx.doi.org/10.1111/hir.12115

Yearb Med Inform 2016 : 191-193

[Summary]
40.

Section 8: Bioinformatics and Translational Informatics

Survey

N. Pouladi (1, 2, 3), I. Achour (1, 2, 3), H. Li (1, 2, 3), J. Berghout (1, 2, 3), C. Kenost (1, 2, 3), M. L. Gonzalez-Garay (1, 2, 3), Y. A. Lussier (1, 2, 3, 4)

(1) BIO5 Institute, The University of Arizona, Tucson, AZ, USA; (2) Center for Biomedical Informatics and Biostatistics, The University of Arizona, Tucson, AZ, USA; (3) Department of Medicine, The University of Arizona, Tucson, AZ, USA; (4) University of Arizona Cancer Center, The University of Arizona, Tucson, AZ, USA

Yearb Med Inform 2016 : 194-206

https://doi.org/10.15265/IY-2016-040

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