A qualitative study of big data and the opioid epidemic: recommendations for data governance.
A qualitative study of big data and the opioid epidemic: recommendations for data governance.
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DOI：
10.1186/s12910-020-00544-9
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发表时间：
2020-10-21
影响因子：
2.7
通讯作者：
Goldstein DM
中科院分区：
文献类型：
--
作者：
Evans EA;Delorme E;Cyr K;Goldstein DM
阿片类药物的流行使人们能够迅速和无与伦比地使用阿片类药物使用障碍患者的大数据来设计应对公共卫生危机的举措，通常没有受影响社区的充分投入。利用大数据所做的努力正在拯救生命，产生巨大的效益。大数据的使用还可能破坏公众对政府的信任，并造成其他意想不到的伤害。我们的目标是确定有关如何以道德方式使用阿片类药物使用大数据的问题和建议。2019年，我们对39名大数据利益相关者（守门人、研究人员、患者倡导者）进行了焦点小组和访谈，他们对马萨诸塞州公共卫生部维护的公共卫生数据仓库感兴趣或有所了解。对阿片类药物使用大数据的担忧根源于潜在的隐私侵犯，这是由于以前不同的数据系统之间的联系，分析和监视能力的增加，无限的寿命以及缺乏明确的知情同意。同样存在问题的是，受影响群体无法控制大数据的使用方式，尽管数据匿名化，大数据仍有可能增加对受影响者的污名化和歧视，以及忽视或延续偏见的使用。参与者支持大数据流程，保护和尊重患者和社会，确保正义，并促进患者和公众对公共机构的信任。道德大数据治理的建议提供了缩小大数据鸿沟的方法（例如，优先考虑健康公平，设定禁区主题/方法，识别盲点），制定共享数据治理（例如，建立社区咨询委员会），培养公众信任并获得大数据使用的社会许可证（例如，制定保障措施和其他管理责任，让公众参与，宣传更大的利益），并重新关注道德方法。使用大数据来解决阿片类药物流行带来了伦理问题，如果不加以解决，可能会破坏其益处。调查结果可以为如何进行道德大数据治理提供指导，并以保护和尊重患者和社会的方式，确保正义，并促进患者和公众对公共机构的信任。
The opioid epidemic has enabled rapid and unsurpassed use of big data on people with opioid use disorder to design initiatives to battle the public health crisis, generally without adequate input from impacted communities. Efforts informed by big data are saving lives, yielding significant benefits. Uses of big data may also undermine public trust in government and cause other unintended harms. We aimed to identify concerns and recommendations regarding how to use big data on opioid use in ethical ways. We conducted focus groups and interviews in 2019 with 39 big data stakeholders (gatekeepers, researchers, patient advocates) who had interest in or knowledge of the Public Health Data Warehouse maintained by the Massachusetts Department of Public Health. Concerns regarding big data on opioid use are rooted in potential privacy infringements due to linkage of previously distinct data systems, increased profiling and surveillance capabilities, limitless lifespan, and lack of explicit informed consent. Also problematic is the inability of affected groups to control how big data are used, the potential of big data to increase stigmatization and discrimination of those affected despite data anonymization, and uses that ignore or perpetuate biases. Participants support big data processes that protect and respect patients and society, ensure justice, and foster patient and public trust in public institutions. Recommendations for ethical big data governance offer ways to narrow the big data divide (e.g., prioritize health equity, set off-limits topics/methods, recognize blind spots), enact shared data governance (e.g., establish community advisory boards), cultivate public trust and earn social license for big data uses (e.g., institute safeguards and other stewardship responsibilities, engage the public, communicate the greater good), and refocus ethical approaches. Using big data to address the opioid epidemic poses ethical concerns which, if unaddressed, may undermine its benefits. Findings can inform guidelines on how to conduct ethical big data governance and in ways that protect and respect patients and society, ensure justice, and foster patient and public trust in public institutions.
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影响因子：
2.7
作者：
Aitken M;de St Jorre J;Pagliari C;Jepson R;Cunningham-Burley S
通讯作者：
Cunningham-Burley S
影响因子：
4.1
作者：
Kalkman S;van Delden J;Banerjee A;Tyl B;Mostert M;van Thiel G
通讯作者：
van Thiel G
影响因子：
5.4
作者：
Curtis, S;Gesler, W;Washburn, S
通讯作者：
Washburn, S
影响因子：
4.2
作者：
Chatterjee, Avik;Larochelle, Marc R.;Bagley, Sarah M.
通讯作者：
Bagley, Sarah M.
影响因子：
13.8
作者：
Kiang, Mathew V.;Basu, Sanjay;Alexander, Monica J.
通讯作者：
Alexander, Monica J.