JMIR Medical Informatics Clinical informatics, decision support for health professionals, electronic health records, and eHealth infrastructures Volume 6 (2018), Issue 4 ISSN: 2291-9694 Contents Original Papers Using Blockchain Technology to Manage Clinical Trials Data: A Proof-of-Concept Study (e11949) David Maslove, Jacob Klein, Kathryn Brohman, Patrick Martin. 4 Most Influential Qualities in Creating Satisfaction Among the Users of Health Information Systems: Study in Seven European Union Countries (e11252) Shahryar Eivazzadeh, Johan Berglund, Tobias Larsson, Markus Fiedler, Peter Anderberg. 11 Novel Approach to Cluster Patient-Generated Data Into Actionable Topics: Case Study of a Web-Based Breast Cancer Forum (e45) Josette Jones, Meeta Pradhan, Masoud Hosseini, Anand Kulanthaivel, Mahmood Hosseini. 30 Extraction of Information Related to Adverse Drug Events from Electronic Health Record Notes: Design of an End-to-End Model Based on Deep Learning (e12159) Fei Li, Weisong Liu, Hong Yu. 40 Predictive Modeling of 30-Day Emergency Hospital Transport of Patients Using a Personal Emergency Response System: Prognostic Retrospective Study (e49) Jorn op den Buijs, Mariana Simons, Sara Golas, Nils Fischer, Jennifer Felsted, Linda Schertzer, Stephen Agboola, Joseph Kvedar, Kamal Jethwani. 54 Utilization of Electronic Medical Records and Biomedical Literature to Support the Diagnosis of Rare Diseases Using Data Fusion and Collaborative Filtering Approaches (e11301) Feichen Shen, Sijia Liu, Yanshan Wang, Andrew Wen, Liwei Wang, Hongfang Liu. 68 Predicting Current Glycated Hemoglobin Values in Adults: Development of an Algorithm From the Electronic Health Record (e10780) Brian Wells, Kristin Lenoir, Jose-Franck Diaz-Garelli, Wendell Futrell, Elizabeth Lockerman, Kevin Pantalone, Michael Kattan. 84 Assessing the Impacts of Integrated Decision Support Software on Sexual Orientation Recording, Comprehensive Sexual Health Testing, and Detection of Infections Among Gay and Bisexual Men Attending General Practice: Observational Study (e10808) Denton Callander, Christopher Bourne, Handan Wand, Mark Stoové, Jane Hocking, John de Wit, John Kaldor, Basil Donovan, Catherine Pell, Robert Finlayson, David Baker, Bradley Forssman, BK Tee, Bill Kefalas, Tim Duck, Rebecca Guy. 95 Impact of Electronic Versus Paper Vital Sign Observations on Length of Stay in Trauma Patients: Stepped-Wedge, Cluster Randomized Controlled Trial (e10221) David Wong, Julia Knight, Jacqueline Birks, Lionel Tarassenko, Peter Watkinson. 105 JMIR Medical Informatics 2018 | vol. 6 | iss. 4 | p.1 XSL·FO RenderX Processing of Electronic Medical Records for Health Services Research in an Academic Medical Center: Methods and Validation (e10933) Nabilah Rahman, Debby Wang, Sheryl Ng, Sravan Ramachandran, Srinath Sridharan, Astrid Khoo, Chuen Tan, Wei-Ping Goh, Xin Tan. 116 Development of an eHealth System to Capture and Analyze Patient Sensor and Self-Report Data: Mixed-Methods Assessment of Potential Applications to Improve Cancer Care Delivery (e46) Alexander Lucas, Michael Bass, Nan Rothrock, Mary O©Connor, Mia Sorkin, Jason Nawyn, Fahd Albinali, Lynne Wagner. 136 Identifying Principles for the Construction of an Ontology-Based Knowledge Base: A Case Study Approach (e52) Xia Jing, Nicholas Hardiker, Stephen Kay, Yongsheng Gao. 149 Identifying Patients Who Are Likely to Receive Most of Their Care From a Specific Health Care System: Demonstration via Secondary Analysis (e12241) Gang Luo, Peter Tarczy-Hornoch, Adam Wilcox, E Lee. 164 Benefits and Costs of Digital Consulting in Clinics Serving Young People With Long-Term Conditions: Mixed-Methods Approach (e48) Sung Kim, Jason Madan, Melina Dritsaki, Carol Bryce, Vera Forjaz, Joe Fraser, Frances Griffiths, Kathryn Hamilton, Caroline Huxley, Jackie Sturt. 176 Using an Internet-Based Hospital to Address Maldistribution of Health Care Resources in Rural Areas of Guangdong Province, China: Retrospective and Descriptive Study (e51) Cui He, Qiru Zhou, Wei Chen, Junzhang Tian, Lihua Zhou, Hong Peng, Shuo Luan, Shengfei Wang. 187 A Computerized Method for Measuring Computed Tomography Pulmonary Angiography Yield in the Emergency Department: Validation Study (e44) Safiya Richardson, Philip Solomon, Alexander O©Connell, Sundas Khan, Jonathan Gong, Alex Makhnevich, Guang Qiu, Meng Zhang, Thomas McGinn. 202 Appropriateness of Hospital Admission for Emergency Department Patients with Bronchiolitis: Secondary Analysis (e10498) Gang Luo, Michael Johnson, Flory Nkoy, Shan He, Bryan Stone. 208 Health Data for Research Through a Nationwide Privacy-Proof System in Belgium: Design and Implementation (e11428) Nicolas Delvaux, Bert Aertgeerts, Johan van Bussel, Geert Goderis, Bert Vaes, Mieke Vermandere. 218 Clinical Named Entity Recognition From Chinese Electronic Health Records via Machine Learning Methods (e50) Yu Zhang, Xuwen Wang, Zhen Hou, Jiao Li. 241 Effect of a Multimedia Patient Decision Aid to Supplement the Informed Consent Process of a Peripherally Inserted Central Venous Catheter Procedure: Pre-Post Quasi-Experimental Study (e11056) Azizeh Sowan, Arlienita Beraya, Adrian Carrola, Charles Reed. 255 Validation and Testing of Fast Healthcare Interoperability Resources Standards Compliance: Data Analysis (e10870) Jason Walonoski, Robert Scanlon, Conor Dowling, Mario Hyland, Richard Ettema, Steven Posnack. 264 JMIR Medical Informatics 2018 | vol. 6 | iss. 4 | p.2 XSL·FO RenderX Proposal Contextual Anonymization for Secondary Use of Big Data in Biomedical Research: Proposal for an Anonymization Matrix (e47) John Rumbold, Barbara Pierscionek. 228 JMIR Medical Informatics 2018 | vol. 6 | iss. 4 | p.3 XSL·FO RenderX JMIR MEDICAL INFORMATICS Maslove et al Original Paper Using Blockchain Technology to Manage Clinical Trials Data: A Proof-of-Concept Study David M Maslove1, MD, MS; Jacob Klein2; Kathryn Brohman3, PhD; Patrick Martin2, PhD 1Department of Critical Care Medicine, Queen©s University, Kingston, ON, Canada 2School of Computing, Queen©s University, Kingston, ON, Canada 3Smith School of Business, Queen©s University, Kingston, ON, Canada Corresponding Author: David M Maslove, MD, MS Department of Critical Care Medicine Queen©s University Kingston General Hospital 76 Stuart St. Kingston, ON, K7L 2V7 Canada Phone: 1 613 650 7311 Email: [email protected] Abstract Background: Blockchain technology is emerging as an innovative tool in data and software security. Objective: This study aims to explore the role of blockchain in supporting clinical trials data management and develop a proof-of-concept implementation of a patient-facing and researcher-facing system. Methods: Blockchain-based Smart Contracts were built using the Ethereum platform. Results: We described BlockTrial, a system that uses a Web-based interface to allow users to run trials-related Smart Contracts on an Ethereum network. Functions allow patients to grant researchers access to their data and allow researchers to submit queries for data that are stored off chain. As a type of distributed ledger, the system generates a durable and transparent log of these and other transactions. BlockTrial could be used to increase the trustworthiness of data collected during clinical research with benefits to researchers, regulators, and drug companies alike. In addition, the system could empower patients to become more active and fully informed partners in research. Conclusions: Blockchain technology presents an opportunity to address some of the common threats to the integrity of data collected in clinical trials and ensure that the analysis of these data comply with prespecified plans. Further technical work is needed to add additional functions. Policies must be developed to determine the optimal models for participation in the system by its various stakeholders. (JMIR Med Inform 2018;6(4):e11949) doi:10.2196/11949 KEYWORDS blockchain; clinical trial; informatics; data accuracy; data collection of the rigor of their work and represent important academic Introduction achievements. For companies, considerable investment in Clinical trials generate data used in the preparation of research and development may be at stake along with the peer-reviewed journal papers and applications to regulatory prospect of future earnings, both of which typically count in bodies for approval of new treatments. In both cases, the the billions of dollars. In brief, both publishers and regulators integrity of these data is important to numerous stakeholders, need to trust the data presented to them. including academic researchers, journal editors and publishers, Several threats to the validity of clinical trials data stand to drug and device companies, government regulators, and most undermine this trust [1]. First, data can be altered or lost, either importantly, prospective patients and the general public. For accidentally or by nefarious intent. Though redundancy exists researchers, published papers serve as a key external validator in many database systems, these are often opaque to outside http://medinform.jmir.org/2018/4/e11949/ JMIR Med Inform 2018 | vol. 6 | iss. 4 | e11949 | p.4 (page number not for citation purposes) XSL·FO RenderX JMIR MEDICAL INFORMATICS Maslove et al observers. Second, there is a risk that the published analysis is We discuss some design considerations and describe a not a true representation of the analysis that was initially planned proof-of-concept system for patient enrollment and data [2]. Reasons for variation include failing to report all outcomes retrieval. measured,