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Yearb Med Inform 2017; 26(01): 193-200
DOI: 10.15265/IY-2017-022
Section 9: Clinical Research Informatics
Survey
Georg Thieme Verlag KG Stuttgart

Clinical Research Informatics: Supporting the Research Study Lifecycle

S. B. Johnson
Weitere Informationen

Publikationsverlauf

18. August 2017

Publikationsdatum:
11. September 2017 (online)

   Lizenzen und Reprints

Summary

Objectives: The primary goal of this review is to summarize significant developments in the field of Clinical Research Informatics (CRI) over the years 2015-2016. The secondary goal is to contribute to a deeper understanding of CRI as a field, through the development of a strategy for searching and classifying CRI publications.

Methods: A search strategy was developed to query the PubMed database, using medical subject headings to both select and exclude articles, and filtering publications by date and other characteristics. A manual review classified publications using stages in the “research study lifecycle”, with key stages that include study definition, participant enrollment, data management, data analysis, and results dissemination.

Results: The search strategy generated 510 publications. The manual classification identified 125 publications as relevant to CRI, which were classified into seven different stages of the research lifecycle, and one additional class that pertained to multiple stages, referring to general infrastructure or standards. Important cross-cutting themes included new applications of electronic media (Internet, social media, mobile devices), standardization of data and procedures, and increased automation through the use of data mining and big data methods.

Conclusions: The review revealed increased interest and support for CRI in large-scale projects across institutions, regionally, nationally, and internationally. A search strategy based on medical subject headings can find many relevant papers, but a large number of non-relevant papers need to be detected using text words which pertain to closely related fields such as computational statistics and clinical informatics. The research lifecycle was useful as a classification scheme by highlighting the relevance to the users of clinical research informatics solutions.

Keywords

Biomedical research - informatics - clinical studies as topic - review literature as topic
 

  • References

  • 1 Dugas M. Clinical Research Informatics: Recent Advances and Future Directions. Yearb Med Inform 2015; 10: 174-7.
    PubMedGoogle Scholar
  • 2 Embi PJ. Clinical Research Informatics: Survey of Recent Advances and Trends in a Maturing Field. Yearb Med Inform 2013; 08: 178-84.
    PubMedGoogle Scholar
  • 3 Richesson RL, Horvath MM, Rusincovitch SA. Clinical Research Informatics and Electronic Health Record Data. Yearb Med Inform 2014; 09: 215-23.
    PubMedGoogle Scholar
  • 4 Weng C, Kahn MG. Clinical Research Informatics for Big Data and Precision Medicine. Yearb Med Inform 2016; (01) 211-8.
    PubMedGoogle Scholar
  • 5 Crowley Jr. WF, Sherwood L, Salber P, Scheinberg D, Slavkin H, Tilson H. et al. Clinical Research in the United States at a Crossroads: Proposal for a Novel Public-Private Partnership to Establish a National Clinical Research Enterprise. JAMA 2004; 291 (09) 1120-6.
    PubMedGoogle Scholar
  • 6 Sung NS, Crowley Jr. WF, Genel M, Salber P, Sandy L, Sherwood LM. et al. Central Challenges Facing the National Clinical Research Enterprise. JAMA 2003; 289 (10) 1278-87.
    PubMedGoogle Scholar
  • 7 Payne PR, Johnson SB, Starren JB, Tilson HH, Dowdy D. Breaking the Translational Barriers: the Value of Integrating Biomedical Informatics and Translational Research. J Investig Med 2005; 53 (04) 192-200.
    PubMedGoogle Scholar
  • 8 Johnson SB, Farach FJ, Pelphrey K, Rozenblit L. Data Management in Clinical Research: Synthesizing Stakeholder Perspectives. J Biomed Inform 2016; 60: 286-93.
    PubMedGoogle Scholar
  • 9 De Moor G, Sundgren M, Kalra D, Schmidt A, Dugas M, Claerhout B. et al. Using Electronic Health Records for Clinical Research: the Case of the EHR4CR Project. J Biomed Inform 2015; 53: 162-73.
    PubMedGoogle Scholar
  • 10 Ohmann C, Canham S, Danielyan E, Robertshaw S, Legre Y, Clivio L. et al. ‘Cloud computing’ and Clinical Trials: Report from an ECRIN Workshop. Trials 2015; 16: 318.
    PubMedGoogle Scholar
  • 11 Auffray C, Balling R, Barroso I, Bencze L, Benson M, Bergeron J. et al. Making Sense of Big Data in Health Research: Towards an EU Action Plan. Genome Med 2016; 08 (01) 71.
    PubMedGoogle Scholar
  • 12 Dymek C, Gingold J, Shanbhag A, Fridsma D, Yong PL. A National Data Infrastructure for Patient-centered Outcomes Research. J Comp Eff Res 2015; 04 (01) 75-87.
    PubMedGoogle Scholar
  • 13 Hazlehurst BL, Kurtz SE, Masica A, Stevens VJ, McBurnie MA, Puro JE. et al. CER Hub: An Informatics Platform for Conducting Comparative Effectiveness Research using Multi-Institutional, Heterogeneous, Electronic Clinical Data. Int J Med Inform 2015; 84 (10) 763-73.
    PubMedGoogle Scholar
  • 14 Budin-Ljosne I, Burton P, Isaeva J, Gaye A, Turner A, Murtagh MJ. et al. DataSHIELD: an Ethically Robust Solution to Multiple-Site Individual-level Data Analysis. Public Health Genomics 2015; 18 (02) 87-96.
    PubMedGoogle Scholar
  • 15 Lautenschlager R, Kohlmayer F, Prasser F, Kuhn KA. A Generic Solution for Web-based Management of Pseudonymized Data. BMC Med Inform Decis Mak 2015; 15: 100.
    PubMedGoogle Scholar
  • 16 Redd A, Pickard S, Meystre S, Scehnet J, Bolton D, Heavirland J. et al. Evaluation of PHI Hunter in Natural Language Processing Research. Perspect Health Inf Manag 2015; 12: 1f.
    PubMedGoogle Scholar
  • 17 Dugas M, Neuhaus P, Meidt A, Doods J, Storck M, Bruland P. et al. Portal of Medical Data Models: Information Infrastructure for Medical Research and Healthcare. Database. Oxford: 2016: 2016.
    Google Scholar
  • 18 Meeker D, Jiang X, Matheny ME, Farcas C, D’Arcy M, Pearlman L. et al. A System to Build Distributed Multivariate Models and Manage Disparate Data Sharing Policies: Implementation in the Scalable National Network for Effectiveness Research. J Am Med Inform Assoc 2015; 22 (06) 1187-95.
    PubMedGoogle Scholar
  • 19 Siesling S, Louwman WJ, Kwast A, van den Hurk C, O’Callaghan M, Rosso S. et al. Uses of Cancer Registries for Public Health and Clinical Research in Europe: Results of the European Network of Cancer Registries Survey among 161 Population-based Cancer Registries during 2010-2012. Eur J Cancer 2015; 51 (09) 1039-49.
    PubMedGoogle Scholar
  • 20 Choquet R, Maaroufi M, de Carrara A, Messiaen C, Luigi E, Landais P. A Methodology for a Minimum Data Set for Rare Diseases to Support National Centers of Excellence for Healthcare and Research. J Am Med Inform Assoc 2015; 22 (01) 76-85.
    PubMedGoogle Scholar
  • 21 Lavigne J, Sharr C, Ozonoff A, Prock LA, Baumer N, Brasington C. et al. National Down Syndrome Patient Database: Insights from the Development of a Multi-center Registry Study. Am J Med Genet A 2015; 167A (11) 2520-6.
    PubMedGoogle Scholar
  • 22 Rasooly RS, Akolkar B, Spain LM, Guill MH, Del Vecchio CT, Carroll LE. The National Institute of Diabetes and Digestive and Kidney Diseases Central Repositories: a Valuable Resource for Nephrology Research. Clin J Am Soc Nephrol 2015; 10 (04) 710-5.
    PubMedGoogle Scholar
  • 23 Antman EM, Benjamin EJ, Harrington RA, Houser SR, Peterson ED, Bauman MA. et al. Acquisition, Analysis, and Sharing of Data in 2015 and Beyond: A Survey of the Landscape: A Conference Report From the American Heart Association Data Summit 2015. J Am Heart Assoc. 2015 04. 11
    PubMedGoogle Scholar
  • 24 Neugebauer R, Schmittdiel JA, Zhu Z, Rassen JA, Seeger JD, Schneeweiss S. High-dimensional Propensity Score Algorithm in Comparative Effectiveness Research with Time-varying Interventions. Stat Med 2015; 34 (05) 753-81.
    PubMedGoogle Scholar
  • 25 Goldenholz DM, Moss R, Scott J, Auh S, Theodore WH. Confusing Placebo Effect with Natural History in Epilepsy: A Big Data Approach. Ann Neurol 2015; 78 (03) 329-36.
    PubMedGoogle Scholar
  • 26 Hesse K, MacIsaac RL, Abdul-Rahim AH, Lyden PD, Bluhmki E, Lees KR. et al. Online Tool to Improve Stratification of Adverse Events in Stroke Clinical Trials. Stroke 2016; 47 (03) 882-5.
    PubMedGoogle Scholar
  • 27 Sugitani T, Bretz F, Maurer W. A Simple and Flexible Graphical Approach for Adaptive Group-Sequential Clinical Trials. J Biopharm Stat 2016; 26 (02) 202-16.
    PubMedGoogle Scholar
  • 28 Pouwels KB, Mulder B, Hak E. Moderate Concordance was found between Case-only and Parallel Group Designs in Systematic Comparison. J Clin Epidemiol 2016; 71: 18-24.
    PubMedGoogle Scholar
  • 29 Lehrach H. Virtual Clinical Trials, an Essential Step in Increasing the Effectiveness of the Drug Development Process. Public Health Genomics 2015; 18 (06) 366-71.
    PubMedGoogle Scholar
  • 30 Soto-Rey I, Trinczek B, Amo JI, Bauselas J, Dugas M, Fritz F. Web-based Multi-site Feasibility Questionnaire Tool. Stud Health Technol Inform 2015; 212: 88-93.
    PubMedGoogle Scholar
  • 31 Kury FS, Cimino JJ. Identifying Repetitive Institutional Review Board Stipulations by Natural Language Processing and Network Analysis. Stud Health Technol Inform 2015; 216: 579-83.
    PubMedGoogle Scholar
  • 32 Teitcher JE, Bockting WO, Bauermeister JA, Hoefer CJ, Miner MH, Klitzman RL. Detecting, Preventing, and Responding to “fraudsters” in Internet Research: Ethics and Tradeoffs. J Law Med Ethics 2015; 43 (01) 116-33.
    PubMedGoogle Scholar
  • 33 Klungel OH, Kurz X, de Groot MC, Schlienger RG, Tcherny-Lessenot S, Grimaldi L. et al. Multi-centre, Multi-database Studies with Common Protocols: Lessons Learnt from the IMI PROTECT Project. Pharmacoepidemiol Drug Saf 2016; 25 (Suppl. 01) 156-65.
    PubMedGoogle Scholar
  • 34 He Z, Carini S, Sim I, Weng C. Visual Aggregate Analysis of Eligibility Features of Clinical Trials. J Biomed Inform 2015; 54: 241-55.
    PubMedGoogle Scholar
  • 35 Patrao DF, Oleynik M, Massicano F, Morassi ASasso. Recruit--An Ontology Based Information Retrieval System for Clinical Trials Recruitment. Stud Health Technol Inform 2015; 216: 534-8.
    PubMedGoogle Scholar
  • 36 Shivade C, Hebert C, Lopetegui M, de Marneffe MC, Fosler-Lussier E, Lai AM. Textual Inference for Eligibility Criteria Resolution in Clinical Trials. J Biomed Inform. 2015 58 Suppl: S211-8.
    PubMedGoogle Scholar
  • 37 Afrin LB, Oates JC, Kamen DL. Improving Clinical Trial Accrual by Streamlining the Referral Process. Int J Med Inform 2015; 84 (01) 15-23.
    PubMedGoogle Scholar
  • 38 Schreiweis B, Bergh B. Requirements for a Patient Recruitment System. Stud Health Technol Inform 2015; 210: 521-5.
    PubMedGoogle Scholar
  • 39 Doods J, Lafitte C, Ulliac-Sagnes N, Proeve J, Botteri F, Walls R. et al. A European Inventory of Data Elements for Patient Recruitment. Stud Health Technol Inform 2015; 210: 506-10.
    PubMedGoogle Scholar
  • 40 Cuggia M, Campillo-Gimenez B, Bouzille G, Besana P, Jouini W, Dufour JC. et al. Automatic Selection of Clinical Trials Based on A Semantic Web Approach. Stud Health Technol Inform 2015; 216: 564-8.
    PubMedGoogle Scholar
  • 41 Schreiweis B, Bergh B. Applicability of different types of Patient Records for Patient Recruitment Systems. Stud Health Technol Inform 2015; 216: 884.
    PubMedGoogle Scholar
  • 42 Ni Y, Kennebeck S, Dexheimer JW, McAneney CM, Tang H, Lingren T. et al. Automated Clinical Trial Eligibility Prescreening: Increasing the Efficiency of Patient Identification for Clinical Trials in the Emergency Department. J Am Med Inform Assoc 2015; 22 (01) 166-78.
    PubMedGoogle Scholar
  • 43 Rahne T, Buthut F, Plossl S, Plontke SK. A Software Tool for Puretone Audiometry. Classification of Audiograms for Inclusion of Patients in Clinical Trials. English version. HNO 2016; 64 (Suppl. 01) S1-6.
    PubMedGoogle Scholar
  • 44 Miotto R, Weng C. Case-based Reasoning using Electronic Health Records Efficiently identifies Eligible Patients for Clinical Trials. J Am Med Inform Assoc 2015; 22 (e1): e141-50.
    PubMedGoogle Scholar
  • 45 Ni Y, Wright J, Perentesis J, Lingren T, Deleger L, Kaiser M. et al. Increasing the Efficiency of Trial-patient Matching: Automated Clinical Trial Eligibility Pre-screening for Pediatric Oncology Patients. BMC Med Inform Decis Mak 2015; 15: 28.
    PubMedGoogle Scholar
  • 46 Abel GA, Cronin AM, Earles K, Gray SW. Accessibility and Quality of Online Cancer-Related Clinical Trial Information for Naive Searchers. Cancer Epidemiol Biomarkers Prev 2015; 24 (10) 1629-31.
    PubMedGoogle Scholar
  • 47 Rimel BJ, Lester J, Sabacan L, Park D, Bresee C, Dang C. et al. A Novel Clinical Trial Recruitment Strategy for Women’s Cancer. Gynecol Oncol 2015; 138 (02) 445-8.
    PubMedGoogle Scholar
  • 48 Rocker C, Cappelletti L, Marshall C, Meunier CC, Brooks DW, Sherer T. et al. Use of an Online Portal to Facilitate Clinical Trial Recruitment: a Preliminary Analysis of Fox Trial Finder. J Parkinsons Dis 2015; 05 (01) 55-66.
    PubMedGoogle Scholar
  • 49 Refolo P, Sacchini D, Minacori R, Daloiso V, Spagnolo AG. E-recruitment Based Clinical Research: Notes for Research Ethics Committees/Institutional Review Boards. Eur Rev Med Pharmacol Sci 2015; 19 (05) 800-4.
    PubMedGoogle Scholar
  • 50 Khatri C, Chapman SJ, Glasbey J, Kelly M, Nepogodiev D, Bhangu A. et al. Social Media and Internet driven Study Recruitment: Evaluating a New Model for Promoting Collaborator Engagement and Participation. PLoS One 2015; 10 (03) e0118899.
    CrossrefPubMedGoogle Scholar
  • 51 Jackson D, Waine ML, Hutchinson M. Blogs as a Way to Elicit Feedback on Research and Engage Stakeholders. Nurse Res 2015; 22 (03) 41-7.
    PubMedGoogle Scholar
  • 52 Tan KM, Flack FS, Bear NL, Allen JA. An Evaluation of a Data Linkage Training Workshop for Research Ethics Committees. BMC Med Ethics 2015; 16: 13.
    PubMedGoogle Scholar
  • 53 Haugen M, Gasber E, Leonard M, Landier W. Harnessing Technology to Enhance Delivery of Clinical Trials Education for Nurses: a Report from the Children’s Oncology Group. J Pediatr Oncol Nurs 2015; 32 (02) 96-102.
    PubMedGoogle Scholar
  • 54 Sehovic I, Gwede CK, Meade CD, Sodeke S, Pentz R, Quinn GP. A Web-Based Platform for Educating Researchers About Bioethics and Biobanking. J Cancer Educ 2016; 31 (02) 397-404.
    PubMedGoogle Scholar
  • 55 Lamas E, Salinas R, Vuillaume D. A New Challenge to Research Ethics: Patients-Led Research (PLR) and the Role of Internet Based Social Networks. Stud Health Technol Inform 2016; 221: 36-40.
    PubMedGoogle Scholar
  • 56 Bouzille G, Sylvestre E, Campillo-Gimenez B, Renault E, Ledieu T, Delamarre D. et al. An Integrated Workflow For Secondary Use of Patient Data for Clinical Research. Stud Health Technol Inform 2015; 216: 913.
    PubMedGoogle Scholar
  • 57 Mitchell SG, Schwartz RP, Alvanzo AA, Weisman MS, Kyle TL, Turrigiano EM. et al. The Use of Technology in Participant Tracking and Study Retention: Lessons Learned From a Clinical Trials Network Study. Subst Abus 2015; 36 (04) 420-6.
    PubMedGoogle Scholar
  • 58 Geller NL, Kim DY, Tian X. Smart Technology in Lung Disease Clinical Trials. Chest 2016; 149 (01) 22-6.
    PubMedGoogle Scholar
  • 59 Akmatov MK, Rubsamen N, Schultze A, Kemmling Y, Obi N, Gunther K. et al. Diverse Recruitment Strategies Result in Different Participation Percentages in a Web-based Study, but in Similar Compliance. Int J Public Health 2015; 60 (08) 937-43.
    PubMedGoogle Scholar
  • 60 Stephens TM, Gunther ME. Twitter, Millennials, and Nursing Education Research. Nurs Educ Perspect 2016; 37 (01) 23-7.
    PubMedGoogle Scholar
  • 61 Park JY, Kim DR, Haldar B, Mallick AH, Kim SA, Dey A. et al. Use of the Data System for Field Management of a Clinical Study Conducted in Kolkata, India. BMC Res Notes 2016; 09: 20.
    PubMedGoogle Scholar
  • 62 Lee H, Chapiro J, Schernthaner R, Duran R, Wang Z, Gorodetski B. et al. How I do it: a Practical Database Management System to Assist Clinical Research Teams with Data Collection, Organization, and Reporting. Acad Radiol 2015; 22 (04) 527-33.
    PubMedGoogle Scholar
  • 63 Long E, Huang B, Wang L, Lin X, Lin H. Construction of Databases: Advances and Significance in Clinical Research. Eye Sci 2015; 30 (04) 184-9.
    PubMedGoogle Scholar
  • 64 Adkinson JM, Casale MT, Kim JY, Khavanin N, Gutowski KA, Gosain AK. So You Have a Research Idea: A Survey of Databases Available for Plastic Surgery Research. Plast Reconstr Surg 2016; 137 (02) 680-9.
    PubMedGoogle Scholar
  • 65 Baili P, Torresani M, Agresti R, Rosito G, Daidone MG, Veneroni S. et al. A Breast Cancer Clinical Registry in an Italian Comprehensive Cancer Center: an Instrument for Descriptive, Clinical, and Experimental Research. Tumori 2015; 101 (04) 440-6.
    PubMedGoogle Scholar
  • 66 Kaka H, Ayearst R, Tran M, Touma Z, Bagovich M, Vinik O. et al. Developing an Ipad(R) Application for Data Collection in a Rheumatology Research Clinic. Int J Technol Assess Health Care 2015; 31 (1-2): 99-102.
    PubMedGoogle Scholar
  • 67 Huang CW, Lu R, Iqbal U, Lin SH, Nguyen PA, Yang HC. et al. A richly Interactive Exploratory Data Analysis and Visualization Tool using Electronic Medical Records. BMC Med Inform Decis Mak 2015; 15: 92.
    PubMedGoogle Scholar
  • 68 Mayer MA, Furlong LI, Torre P, Planas I, Cots F, Izquierdo E. et al. Reuse of EHRs to Support Clinical Research in a Hospital of Reference. Stud Health Technol Inform 2015; 210: 224-6.
    PubMedGoogle Scholar
  • 69 Legaz-Garcia CMdel, Minarro-Gimenez JA, Menarguez-Tortosa M, Fernandez-Breis JT. Lessons Learned in the Generation of Biomedical Research Datasets using Semantic Open Data technologies. Stud Health Technol Inform 2015; 210: 165-9.
    PubMedGoogle Scholar
  • 70 Tuti T, Bitok M, Paton C, Makone B, Malla L, Muinga N. et al. Innovating to Enhance Clinical Data Management using Non-commercial and Open Source Solutions across a Multi-center Network supporting Inpatient Pediatric Care and Research in Kenya. J Am Med Inform Assoc 2016; 23 (01) 184-92.
    PubMedGoogle Scholar
  • 71 Voss EA, Makadia R, Matcho A, Ma Q, Knoll C, Schuemie M. et al. Feasibility and Utility of Applications of the Common Data Model to Multiple, Disparate Observational Health Databases. J Am Med Inform Assoc 2015; 22 (03) 553-64.
    PubMedGoogle Scholar
  • 72 Hripcsak G, Duke JD, Shah NH, Reich CG, Huser V, Schuemie MJ. et al. Observational Health Data Sciences and Informatics (OHDSI): Opportunities for Observational Researchers. Stud Health Technol Inform 2015; 216: 574-8.
    PubMedGoogle Scholar
  • 73 Houston L, Probst Y, Humphries A. Measuring Data Quality Through a Source Data Verification Audit in a Clinical Research Setting. Stud Health Technol Inform 2015; 214: 107-13.
    PubMedGoogle Scholar
  • 74 Elkhenini HF, Davis KJ, Stein ND, New JP, Delderfield MR, Gibson M. et al. Using an Electronic Medical Record (EMR) to Conduct Clinical Trials: Salford Lung Study feasibility. BMC Med Inform Decis Mak 2015; 15: 8.
    PubMedGoogle Scholar
  • 75 Yoon D, Schuemie MJ, Kim JH, Kim DK, Park MY, Ahn EK. et al. A Normalization Method for Combination of Laboratory Test Results from Different Electronic Healthcare Databases in a Distributed Research Network. Pharmacoepidemiol Drug Saf 2016; 25 (03) 307-16.
    PubMedGoogle Scholar
  • 76 Miller TP, Troxel AB, Li Y, Huang YS, Alonzo TA, Gerbing RB. et al. Comparison of Administrative/ Billing Data to Expected Protocol-mandated Chemotherapy Exposure in Children with Acute Myeloid Leukemia: a Report from the Children’s Oncology Group. Pediatr Blood Cancer 2015; 62 (07) 1184-9.
    PubMedGoogle Scholar
  • 77 Yan L, Hicks M, Winslow K, Comella C, Ludlow C, Jinnah HA. et al. Secured Web-based Video Repository for Multicenter Studies. Parkinsonism Relat Disord 2015; 21 (04) 366-71.
    PubMedGoogle Scholar
  • 78 McGregor C, Heath J, Choi Y. Streaming Physiological Data: General Public Perceptions of Secondary Use and Application to Research in Neonatal Intensive Care. Stud Health Technol Inform 2015; 216: 453-7.
    PubMedGoogle Scholar
  • 79 Deserno TM, Deserno V, Haak D, Kabino K. Digital Imaging and Electronic Data Capture in Multi-Center Clinical Trials. Stud Health Technol Inform 2015; 216: 930.
    PubMedGoogle Scholar
  • 80 Jankowska MM, Schipperijn J, Kerr J. A Framework for Using GPS Data in Physical Activity and Sedentary Behavior Studies. Exerc Sport Sci Rev 2015; 43 (01) 48-56.
    PubMedGoogle Scholar
  • 81 Jang D, Lee S, Lee J, Kim K, Lee D. Inferring New Drug Indications using the Complementarity between Clinical Disease Signatures and Drug Effects. J Biomed Inform 2016; 59: 248-57.
    PubMedGoogle Scholar
  • 82 Shah BR, Lipscombe LL. Clinical Diabetes Research using Data Mining: a Canadian Perspective. Can J Diabetes 2015; 39 (03) 235-8.
    PubMedGoogle Scholar
  • 83 Alnazzawi N, Thompson P, Batista-Navarro R, Ananiadou S. Using Text Mining Techniques to Extract Phenotypic Information from the PhenoCHF Corpus. BMC Med Inform Decis Mak 2015; 15 (Suppl. 02) S3.
    PubMedGoogle Scholar
  • 84 Karystianis G, Sheppard T, Dixon WG, Nenadic G. Modelling and Extraction of Variability in Free-text Medication Prescriptions from an Anonymised Primary Care Electronic Medical Record Research Database. BMC Med Inform Decis Mak 2016; 16: 18.
    PubMedGoogle Scholar
  • 85 Taglang G, Jackson DB. Use of “Big Data” in Drug Discovery and Clinical Trials. Gynecol Oncol 2016; 141 (01) 17-23.
    PubMedGoogle Scholar
  • 86 Tilve CMAlvarez, Ayora APais, Ruiz CRomero, Llamas DGomez, Carrajo LGarcia, Blanco FJGarcia. et al. Integrating Medical and Research Information: a Big Data Approach. Stud Health Technol Inform 2015; 210: 707-11.
    PubMedGoogle Scholar
  • 87 Murphy SN, Herrick C, Wang Y, Wang TD, Sack D, Andriole KP. et al. High Throughput Tools to access Images from Clinical Archives for Research. J Digit Imaging 2015; 28 (02) 194-204.
    PubMedGoogle Scholar
  • 88 Bakken S, Reame N. The Promise and Potential Perils of Big Data for Advancing Symptom Management Research in Populations at Risk for Health Disparities. Annu Rev Nurs Res 2016; 34: 247-60.
    PubMedGoogle Scholar
  • 89 Owen J, Imel ZE. Introduction to the Special Section “Big’er’ Data”: Scaling up Psychotherapy Research in Counseling Psychology. J Couns Psychol 2016; 63 (03) 247-8.
    PubMedGoogle Scholar
  • 90 Mertz L. The Case for Big Data: New York City’s Kalvi HUMAN Project Aims to Use Big Data in Resolving Big Health Questions. IEEE Pulse 2016; 07 (05) 45-7.
    PubMedGoogle Scholar
  • 91 Brennan PF, Bakken S. Nursing Needs Big Data and Big Data Needs Nursing. J Nurs Scholarsh 2015; 47 (05) 477-84.
    PubMedGoogle Scholar
  • 92 Goldacre B, Gray J. OpenTrials: Towards a Collaborative Open Database of all Available Information on all Clinical Trials. Trials 2016; 17: 164.
    PubMedGoogle Scholar
  • 93 Hecht A, Busch-Heidger B, Gertzen H, Pfister H, Ruhfus B, Sanden PH. et al. Quality Expectations and Tolerance Limits of Trial Master Files (TMF) -Developing a Risk-based Approach for Quality Assessments of TMFs. Ger Med Sci 2015; 13: Doc23.
    PubMedGoogle Scholar
  • 94 Nicholls SG, Quach P, von Elm E, Guttmann A, Moher D, Petersen I. et al. The REporting of Studies Conducted Using Observational Routinely-Collected Health Data (RECORD) Statement: Methods for Arriving at Consensus and Developing Reporting Guidelines. PLoS One 2015; 10 (05) e0125620.
    PubMedGoogle Scholar
  • 95 O’Reilly EK, Hassell NJ, Snyder DC, Natoli S, Liu I, Rimmler J. et al. ClinicalTrials.gov Reporting: Strategies for Success at an Academic Health Center. Clin Transl Sci 2015; 08 (01) 48-51.
    PubMedGoogle Scholar
  • 96 Dissemination Beyond Publication. Nurse Res 2015; 22 (06) 5.
    PubMedGoogle Scholar
  • 97 Wu DT, Hanauer DA, Mei Q, Clark PM, An LC, Proulx J. et al. Assessing the Readability of ClinicalTrials.gov. J Am Med Inform Assoc 2016; 23 (02) 269-75.
    PubMedGoogle Scholar
  • 98 Dufka FL, Munch T, Dworkin RH, Rowbotham MC. Results Availability for Analgesic Device, Complex Regional Pain Syndrome, and Post-stroke Pain Trials: Comparing the RReADS, RReACT, and RReMiT Databases. Pain 2015; 156 (01) 72-80.
    PubMedGoogle Scholar
  • 99 Williams RS, Lotia S, Holloway AK, Pico AR. From Scientific Discovery to Cures: Bright Stars within a Galaxy. Cell 2015; 163 (01) 21-3.
    PubMedGoogle Scholar
  • 100 Kapp JM, Hensel B, Schnoring KT. Is Twitter a Forum for Disseminating Research to Health Policy Makers?. Ann Epidemiol 2015; 25 (12) 883-7.
    PubMedGoogle Scholar
  • 101 Cihoric N, Tsikkinis A, Miguelez CG, Strnad V, Soldatovic I, Ghadjar P. et al. Portfolio of Prospective Clinical Trials Including Brachytherapy: an Analysis of the ClinicalTrials.gov Database. Radiat Oncol 2016; 11: 48.
    PubMedGoogle Scholar
  • 102 Jeong S, Han N, Choi B, Sohn M, Song YK, Chung MW. et al. Construction of a Database for Published Phase II/III Drug Intervention Clinical Trials for the Period 2009-2014 Comprising 2,326 Records, 90 Disease Categories, and 939 Drug Entities. Int J Clin Pharmacol Ther 2016; 54 (06) 416-25.
    PubMedGoogle Scholar
  • 103 Waffenschmidt S, Guddat C. Searches for Randomized Controlled Trials of Drugs in MEDLINE and EMBASE Using Only Generic Drug Names Compared with Searches Applied in Current Practice in Systematic Reviews. Res Synth Methods 2015; 06 (02) 188-94.
    PubMedGoogle Scholar
  • 104 Cohen JF, Korevaar DA, Wang J, Spijker R, Bossuyt PM. Should we Search Chinese Biomedical Databases when Performing Systematic Reviews?. Syst Rev 2015; 04: 23.
    PubMedGoogle Scholar
  • 105 Grande AJ, Hoffmann T, Glasziou P. Searching for Randomized Controlled Trials and Systematic Reviews on Exercise. A Descriptive Study. Sao Paulo Med J 2015; 133 (02) 109-14.
    PubMedGoogle Scholar
  • 106 Durao S, Kredo T, Volmink J. Validation of a Search Strategy to Identify Nutrition Trials in PubMed Using the Relative Recall Method. J Clin Epidemiol 2015; 68 (06) 610-6.
    PubMedGoogle Scholar
  • 107 Scherer RW, Huynh L, Ervin AM, Dickersin K. Using ClinicalTrials.gov to Supplement Information in Ophthalmology Conference Abstracts about Trial Outcomes: a Comparison Study. PLoS One 2015; 10 (06) e0130619.
    PubMedGoogle Scholar
  • 108 Nankervis H, Devine A, Williams HC, Ingram JR, Doney E, Delamere F. et al. Validation of the Global Resource of Eczema Trials (GREAT Database). BMC Dermatol 2015; 15: 4.
    PubMedGoogle Scholar
  • 109 Fredericks S. Questioning the Efficacy of ‘Gold’ Open Access to Published Articles. Nurse Res 2015; 22 (06) 8-10.
    PubMedGoogle Scholar
  • 110 Perneger TV. Online Accesses to Medical Research Articles on Publication Predicted Citations up to 15 Years Later. J Clin Epidemiol 2015; 68 (12) 1440-5.
    PubMedGoogle Scholar
  • 111 Anderson ML, Chiswell K, Peterson ED, Tasneem A, Topping J, Califf RM. Compliance with Results Reporting at ClinicalTrials.gov. N Engl J Med 2015; 372 (11) 1031-9.
    PubMedGoogle Scholar
  • 112 Williams RJ, Tse T, DiPiazza K, Zarin DA. Terminated Trials in the ClinicalTrials.gov Results Database: Evaluation of Availability of Primary Outcome Data and Reasons for Termination. PLoS One 2015; 10 (05) e0127242.
    PubMedGoogle Scholar
  • 113 Viergever RF, Li K. Trends in Global Clinical Trial Registration: an Analysis of Numbers of Registered Clinical Trials in Different Parts of the World from 2004 to 2013. BMJ Open 2015; 05 (09) e008932.
    PubMedGoogle Scholar
  • 114 Schoenthaler M, Miernik A, Wilhelm K, Schlager D, Schoeb DS, Adams F. et al. Level of Evidence, Sponsorship, Conflict of Interest Policy and Commercial Impact of PubMed-listed Clinical Urolithiasis-related Trials in 2014. BJU Int 2016; 117 (05) 787-92.
    PubMedGoogle Scholar
  • 115 Vodicka E, Kim K, Devine EB, Gnanasakthy A, Scoggins JF, Patrick DL. Inclusion of Patient-Reported Outcome Measures in Registered Clinical Trials: Evidence from ClinicalTrials.gov (2007-2013). Contemp Clin Trials 2015; 43: 1-9.
    CrossrefPubMedGoogle Scholar
  • 116 DiMasi JA, Hermann JC, Twyman K, Kondru RK, Stergiopoulos S, Getz KA. et al. A Tool for Predicting Regulatory Approval After Phase II Testing of New Oncology Compounds. Clin Pharmacol Ther 2015; 98 (05) 506-13.
    PubMedGoogle Scholar
  • 117 Vucic K, Jelicic AKadic, Puljak L. Survey of Cochrane Protocols Found Methods for Data Extraction from Figures not Mentioned or Unclear. J Clin Epidemiol 2015; 68 (10) 1161-4.
    PubMedGoogle Scholar
  • 118 Marshall IJ, Kuiper J, Wallace BC. RobotReviewer: Evaluation of a System for Automatically Assessing Bias in Clinical Trials. J Am Med Inform Assoc 2016; 23 (01) 193-201.
    PubMedGoogle Scholar
  • 119 Hao T, Weng C. Adaptive Semantic Tag Mining from Heterogeneous Clinical Research Texts. Methods Inf Med 2015; 54 (02) 164-70.
    PubMedGoogle Scholar
  • 120 Mo Y, Kontonatsios G, Ananiadou S. Supporting Systematic rReviews Using LDA-based Document Representations. Syst Rev 2015; 04: 172.
    PubMedGoogle Scholar
  • 121 Polepalli BRamesh, Sethi RJ, Yu H. Figure-associated Text Summarization and Evaluation. PLoS One 2015; 10 (02) e0115671.
    PubMedGoogle Scholar
  • 122 Cohen AM, Smalheiser NR, McDonagh MS, Yu C, Adams CE, Davis JM. et al. Automated Confidence Ranked Classification of Randomized Controlled Trial Articles: an Aid to Evidence-Based Medicine. J Am Med Inform Assoc 2015; 22 (03) 707-17.
    PubMedGoogle Scholar
  • 123 Liu RL. Passage-Based Bibliographic Coupling: an Inter-Article Similarity Measure for Biomedical Articles. PLoS One 2015; 10 (10) e0139245.
    PubMedGoogle Scholar
  • 124 Demner-Fushman D, Mork JG. Extracting Characteristics of the Study Subjects from Full-Text Articles. AMIA Annu Symp Proc 2015; 2015: 484-91.
    PubMedGoogle Scholar
  • 125 Shao W, Adams CE, Cohen AM, Davis JM, McDonagh MS, Thakurta S. et al. Aggregator: a Machine Learning Approach to Identifying MEDLINE Articles that Derive from the Same Underlying Clinical Trial. Methods 2015; 74: 65-70.
    PubMedGoogle Scholar
  • 126 Neville J, Kopko S, Broadbent S, Aviles E, Stafford R, Solinsky CM. et al. Development of a Unified Clinical Trial Database for Alzheimer’s Disease. Alzheimers Dement 2015; 11 (10) 1212-21.
    PubMedGoogle Scholar
  • 127 Sydes MR, Johnson AL, Meredith SK, Rauchen-berger M, South A, Parmar MK. Sharing Data from Clinical Trials: the Rationale for a Controlled Access Approach. Trials 2015; 16: 104.
    PubMedGoogle Scholar
  • 128 Vickers AJ. Sharing Raw Data from Clinical Trials: What Progress Since we First Asked “Whose Data Set is it Anyway?”. Trials 2016; 17 (01) 227.
    PubMedGoogle Scholar
  • 129 Blankers M, Smit ES, van der Pol P, de Vries H, Hoving C, van Laar M. The Missing=Smoking Assumption: A Fallacy in Internet-Based Smoking Cessation Trials?. Nicotine Tob Res 2016; 18 (01) 25-33.
    PubMedGoogle Scholar
  • 130 Hugh-Yeun K, Cheung WY. Leveraging the Power of Pooled Data for Cancer Outcomes Research. Chin J Cancer 2016; 35 (01) 74.
    PubMedGoogle Scholar
  • 131 Wang SV, Verpillat P, Rassen JA, Patrick A, Garry EM, Bartels DB. Transparency and Reproducibility of Observational Cohort Studies Using Large Healthcare Databases. Clin Pharmacol Ther 2016; 99 (03) 325-32.
    PubMedGoogle Scholar