Did I Tell You That? Ethical Issues Related to Using Computational Methods to Discover Non-Disclosed Patient Characteristics

Abstract

Background Widespread availability of large data sets through warehousing of electronic health records coupled with increasingly sophisticated information technology and related statistical methods offer great potential for a variety of applications for health and disease surveillance, developing predictive models and advancing decision support for clinicians. However, use of such ‘big data’ mining and discovery techniques has also raised ethical issues such as how to balance privacy and autonomy with the wider public benefits of data sharing. More specifically, electronic data are being increasingly used to identify individual characteristics which can be useful for clinical prediction and management, but that were not previously disclosed to a clinician. This process in computer parlance is called electronic phenotyping, and has a number of ethical implications. Approach Using the Belmont Report’s principles of respect for persons, beneficence, and justice as a framework, we examined the ethical issues posed by electronic phenotyping. Findings Ethical issues identified include the ability of the patient to consent for the use of their information, the ability to suppress pediatric information, ensuring that the potential benefits justify the risks of harm to patients, and acknowledging that the clinician’s biases or stereotypes, conscious or unintended, may also become a factor in the therapeutic interaction. We illustrate these issues with two vignettes, using the person characteristic of gender minority status (i.e., transgender identity) and the health history characteristic of substance abuse. Conclusion Big data mining has the potential to uncover patient characteristics previously obscured which can provide clinicians with beneficial clinical information. Hence, ethical guidelines must be updated to ensure that electronic phenotyping supports the principles of respect for persons, beneficence, and justice.

Examination and diagnosis of electronic patient records and their associated ethics: a scoping literature review

“…Some consider ethical issues that are associated with characteristics common to all EPR systems such as the nature of digital data [32,60,61], the confidentiality of health information [33,39] or the use of the copy-paste functionality [38,62,63]. Others focus on ethical issues around a particular EPR use, such as health insurance claims [64], clinical governance [65], medical education [35,[66][67][68][69], health research [36,[70][71][72][73], predictive analytics [74], learning health system [41], genomics, biomarkers and photos [31,34,[75][76][77][78], public health policies or surveillance [79][80][81], health service monitoring, evaluation and planning [82,83]. The concept of providing patients access to their own medical record via electronic portals was of interest in many sources, particularly in relation to patients understanding the content of the record, provision of sufficient controls for patients to manage privacy, and patient responsibility for the accuracy of information in their healthcare record [31,37,[84][85][86][87][88][89]…”

“…However, consent and the type of consent appears more critical when using EPR-based information outside the clinical doctor-patient relationship [ 46 , 108 ]. Such secondary uses include research [ 31 , 71 – 73 , 80 , 128 ], and clinical training when medical students track patients to learn about their on-going treatment and outcomes [ 66 ].…”

“…Ethical considerations required a favourable benefits/risks balance of EPRs [30,76,[132][133][134][135][136] and many saw this balance as a challenge [30,58,80,94,123,[136][137][138]. Some discussed EPR technology in terms of harm to the patient [30,39,62,64,66,80,118,123,131,137] or mentioned patient safety [57,122,138]. Concepts of 'quality' and 'efficiency', instruments to obtaining the benefits from EPR systems, were also explored [65,122,139,140].…”

Big Data and discrimination: perils, promises and solutions. A systematic review

“…Four papers discussed data linkage, that is, the possibility of automatically obtaining, linking, and disclosing personal and sensitive information as an important cause of discrimination. Two articles [19,91] described how the use of electronic health records could result in the automatic disclosure of sensitive data without the patient's explicit agreement or to re-identification. Others [64,74] also highlighted that discrimination is not created by a data collection system (such as social and health registries) in itself, but is made easier by the linkage and aggregation potentiality embedded in the data.…”

Precision public health to inhibit the contagion of disease and move toward a future in which microbes spread health

“…Rational discussions about policy and human rights should be informed by facts [52]. Not all infections spread between individuals are harmful or neutral.…”