Privacy in the Genomic Era

Genome sequencing technology has advanced at a rapid pace and it is now possible to generate highly-detailed genotypes inexpensively. The collection and analysis of such data has the potential to support various applications, including personalized medical services. While the benefits of the genomics revolution are trumpeted by the biomedical community, the increased availability of such data has major implications for personal privacy; notably because the genome has certain essential features, which include (but are not limited to) (i) an association with traits and certain diseases, (ii) identification capability (e.g., forensics), and (iii) revelation of family relationships. Moreover, direct-to-consumer DNA testing increases the likelihood that genome data will be made available in less regulated environments, such as the Internet and for-profit companies. The problem of genome data privacy thus resides at the crossroads of computer science, medicine, and public policy. While the computer scientists have addressed data privacy for various data types, there has been less attention dedicated to genomic data. Thus, the goal of this paper is to provide a systematization of knowledge for the computer science community. In doing so, we address some of the (sometimes erroneous) beliefs of this field and we report on a survey we conducted about genome data privacy with biomedical specialists. Then, after characterizing the genome privacy problem, we review the state-of-the-art regarding privacy attacks on genomic data and strategies for mitigating such attacks, as well as contextualizing these attacks from the perspective of medicine and public policy. This paper concludes with an enumeration of the challenges for genome data privacy and presents a framework to systematize the analysis of threats and the design of countermeasures as the field moves forward

Network analysis of unstructured EHR data for clinical research.

In biomedical research, network analysis provides a conceptual framework for interpreting data from high-throughput experiments. For example, protein-protein interaction networks have been successfully used to identify candidate disease genes. Recently, advances in clinical text processing and the increasing availability of clinical data have enabled analogous analyses on data from electronic medical records. We constructed networks of diseases, drugs, medical devices and procedures using concepts recognized in clinical notes from the Stanford clinical data warehouse. We demonstrate the use of the resulting networks for clinical research informatics in two ways-cohort construction and outcomes analysis-by examining the safety of cilostazol in peripheral artery disease patients as a use case. We show that the network-based approaches can be used for constructing patient cohorts as well as for analyzing differences in outcomes by comparing with standard methods, and discuss the advantages offered by network-based approaches

Status and recommendations of technological and data-driven innovations in cancer care:Focus group study

Background: The status of the data-driven management of cancer care as well as the challenges, opportunities, and recommendations aimed at accelerating the rate of progress in this field are topics of great interest. Two international workshops, one conducted in June 2019 in Cordoba, Spain, and one in October 2019 in Athens, Greece, were organized by four Horizon 2020 (H2020) European Union (EU)-funded projects: BOUNCE, CATCH ITN, DESIREE, and MyPal. The issues covered included patient engagement, knowledge and data-driven decision support systems, patient journey, rehabilitation, personalized diagnosis, trust, assessment of guidelines, and interoperability of information and communication technology (ICT) platforms. A series of recommendations was provided as the complex landscape of data-driven technical innovation in cancer care was portrayed. Objective: This study aims to provide information on the current state of the art of technology and data-driven innovations for the management of cancer care through the work of four EU H2020-funded projects. Methods: Two international workshops on ICT in the management of cancer care were held, and several topics were identified through discussion among the participants. A focus group was formulated after the second workshop, in which the status of technological and data-driven cancer management as well as the challenges, opportunities, and recommendations in this area were collected and analyzed. Results: Technical and data-driven innovations provide promising tools for the management of cancer care. However, several challenges must be successfully addressed, such as patient engagement, interoperability of ICT-based systems, knowledge management, and trust. This paper analyzes these challenges, which can be opportunities for further research and practical implementation and can provide practical recommendations for future work. Conclusions: Technology and data-driven innovations are becoming an integral part of cancer care management. In this process, specific challenges need to be addressed, such as increasing trust and engaging the whole stakeholder ecosystem, to fully benefit from these innovations

Electronic Medical Record-Assisted Telephone Follow-Up of Breast Cancer Survivors During the COVID-19 Pandemic: A Single Institution Experience

PURPOSE: The COVID-19 outbreak rapidly became a public health emergency and led to radical changes in patient management. From the start of the pandemic, we used electronic medical record-assisted telephone follow-up (E-TFU) of cancer survivors (CS) to minimize hospital exposure. The aim of this prospective study was to assess how breast cancer survivors (bCSs) perceived E-TFU. MATERIALS AND METHODS: A 15-item survey was e-mailed to bCSs who had been managed with E-TFU. The responses were measured using Likert-like scales and were correlated with the main characteristics of the bCS using Pearson's test. RESULTS: One hundred thirty-seven of 343 bCSs (40%) completed the survey between March 9 and June 2, 2020. Their median age was 59 years. Although 80.3% of bCSs were satisfied with E-TFU, only 43.8% would like to have E-TFU in the future. A low educational level was correlated with higher COVID-19-related anxiety (P = .025). An older age (P = .002) and a low educational level (P < .0001) were correlated with the need to be accompanied to reach the hospital. A personal history of second cancer was inversely correlated with understanding medical advice (P = .015) and the expectation of feeling relief after a follow-up visit (P = .0027). Furthermore, pandemic phase II was correlated with satisfaction with E-TFU (P = .010). CONCLUSION: E-TFU was an important means of avoiding hospital contacts during the COVID-19 pandemic, and the majority of bCSs in the survey were satisfied with this procedure. Further studies are needed to investigate the implementation of telemedicine even outside an emergency situation