There is increasing concern that current informed consent models linnet the ability of patients to exercise their preferences for data sharing. In th context of healthcare data, this is particularly complicated because informed consent for care may include provisions for allowing data to be shared for research, as long as the use complies with state and federal laws. Some authors have declared that it is impractical to implement a system for tiered informed consent in which patients can indicate their preferences for whom they want to share their data with and for what types of research. The wide dissemination of electronic health record systems and derived clinical data warehouses has created an abundant pool of data that can be used in certain types of research. Clinical data warehouses could be used to store patient preferences and this would create an opportunity to verify whether tiered informed consent is indeed impractical. As patients start getting familiar with patient portals, itis possible to use them to elicit preferences. In this study, we will implement an electronic tiered informed consent system and evaluate it in a single center, single blinded randomized controlled trial. Specifically, we will develop iCONCUR (informed CONsent for Clinical record Use in Research), a software system to assist with patient informed consent of clinical data sharing for research. The system includes: a. A look-up registry for patients to inspect which studies used which parts of their data. b. A tiered informed consent option for patients to selectively opt-out partially or entirely from data sharing. Additionally, we will estimate financial costs of implementing a scalable system. We will also collect data on patient, provider, researcher, and institutional satisfaction. For this study, we will use an academic internal medicine clinic that treats patients a high proportion of ethnic minorities as the setting. The open-source software developed for this study will be made freely available. The results from our study will help elucidate whether the current consent for care forms are adequately capturing patient preferences.

Public Health Relevance

There is increasing concern that current informed consent processes do not allow patients to fully express their preferences for clinical data sharing. We will build and conduct a preliminary evaluation of a system designed to assist patients in selecting their preferences for use of their clinical data in research, such as which data can be shared, with whom, and for what purposes.

National Institute of Health (NIH)
National Heart, Lung, and Blood Institute (NHLBI)
Specialized Center--Cooperative Agreements (U54)
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Special Emphasis Panel (ZRG1-HDM-B (90))
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Larkin, Jennie E
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University of California San Diego
Internal Medicine/Medicine
Schools of Medicine
La Jolla
United States
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Wang, Lichang; Fang, Yong; Aref, Dima et al. (2016) PALME: PAtients Like My gEnome. AMIA Jt Summits Transl Sci Proc 2016:219-24
Levy, Eric; Marty, Rachel; Gárate Calderón, Valentina et al. (2016) Immune DNA signature of T-cell infiltration in breast tumor exomes. Sci Rep 6:30064
Wang, Shuang; Zhang, Yuchen; Dai, Wenrui et al. (2016) HEALER: homomorphic computation of ExAct Logistic rEgRession for secure rare disease variants analysis in GWAS. Bioinformatics 32:211-8
Wang, Shuang; Jiang, Xiaoqian; Singh, Siddharth et al. (2016) Genome privacy: challenges, technical approaches to mitigate risk, and ethical considerations in the United States. Ann N Y Acad Sci :
Shi, Eileen; Chmielecki, Juliann; Tang, Chih-Min et al. (2016) FGFR1 and NTRK3 actionable alterations in ""Wild-Type"" gastrointestinal stromal tumors. J Transl Med 14:339
Farhan, Wael; Wang, Zhimu; Huang, Yingxiang et al. (2016) A Predictive Model for Medical Events Based on Contextual Embedding of Temporal Sequences. JMIR Med Inform 4:e39
Tang, Haixu; Jiang, Xiaoqian; Wang, Xiaofeng et al. (2016) Protecting genomic data analytics in the cloud: state of the art and opportunities. BMC Med Genomics 9:63
Azad, Priti; Zhao, Huiwen W; Cabrales, Pedro J et al. (2016) Senp1 drives hypoxia-induced polycythemia via GATA1 and Bcl-xL in subjects with Monge's disease. J Exp Med 213:2729-2744
Doan, Son; Maehara, Cleo K; Chaparro, Juan D et al. (2016) Building a Natural Language Processing Tool to Identify Patients With High Clinical Suspicion for Kawasaki Disease from Emergency Department Notes. Acad Emerg Med 23:628-36
Shi, Haoyi; Jiang, Chao; Dai, Wenrui et al. (2016) Secure Multi-pArty Computation Grid LOgistic REgression (SMAC-GLORE). BMC Med Inform Decis Mak 16 Suppl 3:89

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