Research Article: Caring for trafficked and unidentified patients in the EHR shadows: Shining a light by sharing the data

Date Published: March 14, 2019

Publisher: Public Library of Science

Author(s): Sara H. Katsanis, Elaine Huang, Amanda Young, Victoria Grant, Elizabeth Warner, Sharon Larson, Jennifer K. Wagner, Alejandro Arrieta.


Healthcare providers have key roles in the prevention of, detection of, and interventions for human trafficking. Yet caring for trafficked persons is particularly challenging: patients whose identities are unknown, unreliable, or false could receive subpar care from providers delivering care in a vacuum of relevant information. The application of precision medicine principles and integration of biometric data (including genetic information) could facilitate patient identification, enable longitudinal medical records, and improve continuity and quality of care for this vulnerable patient population. Scant empirical data exist regarding healthcare system preparedness and care for the needs of this vulnerable population nor data on perspectives on the use and risks of biometrics or genetic information for trafficked patients.

To address this gap, we conducted mixed-methods research involving semi-structured interviews with key informants, which informed a subsequent broad survey of physicians and registered nurses.

Our findings support the perception that trafficked persons obtain care yet remain unnoticed or undocumented in the electronic health record. Our survey findings further reveal that healthcare providers remain largely unaware of human trafficking issues and are inadequately prepared to provide patient-centered care for trafficked and unidentified patients.

Meaningful efforts to design and implement precision medicine initiatives in an inclusive way that optimizes impacts are unlikely to succeed without concurrent efforts to increase general awareness of and preparedness to care for trafficked persons. Additional research is needed to examine properly the potential utility for biometrics to improve the delivery of care for trafficked patients.

Partial Text

Over the past decade, scientists have increasingly placed faith (and resources) in the potential for genomic science and health information technologies to transform medicine from a reactive endeavor to a proactive, anticipatory one [1–6]. A more holistic approach to preventing, diagnosing, and treating diseases as well as promoting health relies heavily upon the integration of large amounts of data from clinical and non-clinical sources and the responsible sharing of those data broadly in order to maximize the potential insights (for individuals and populations) that can be gleaned. While genomics and health information technologies offer great promise to improve health care and advance science, there are legitimate concerns that everyone will not share equitably in the process or the progress (e.g., [7–13]). Historically recognized and emerging vulnerable populations require specific attention as health systems implement the components for precision medicine in order to mitigate known health disparities and prevent their exacerbation. With appropriate attention during the design stages and regular critical assessment during implementation stages, precision medicine efforts could achieve the desired human-centered process and outcomes. Among the vulnerable populations deserving of attention are trafficked persons, for whom the net benefits of the application of precision medicine principles and use of biometric data could be substantial and for whom the ethical, legal, and social implications of such applications of biometric data might necessitate special procedural and/or substantive considerations to prevent harm. Risks to using biometric data including genetic information in the EHR might include (a) reduced personal or familial privacy; (b) reduced trust in healthcare professionals and institutions; (c) secondary uses of data by law enforcement or government entities; and (d) the unintentional disclosure of unknown or hidden relationships detected through biometric data; whereby the benefit of using biometrics is in the ability to connect medical records for individuals and thereby provide continuity of care to a population that frequents hospital systems and might use false identities upon admission.

The main motivation for this study was to investigate applications and implications for precision medicine tools and principles—specifically genetic information, health information technologies and integration of data from clinic and non-clinic sources, and data sharing issues within and across health systems—as they relate to healthcare delivery for a specific vulnerable population: trafficked and unidentified patients. The study design was developed with a mixed-methods approach with three components. The first component was a preparatory-to-research EHR data pull (i.e., a non-hypothesis-testing review of EHR data) facilitated by a data broker to gauge informally, through participant observation, the feasibility of conducting HT research using data readily available from the EHR. The second component involved a series of key informant interviews of stakeholders from diverse healthcare settings (an integrated health system; an independent community hospital; and an academic medical center) to explore perspectives about HT as a public health problem, learn operational details regarding the current delivery of healthcare for trafficked and unidentified patients and perceived barriers to care, and elicit opinions (including individual, institutional, societal, legal, and scientific/technical issues) regarding biometrics and data sharing efforts intended to improve identification and continuity of care for this vulnerable population. The key informant interviews also were intended to provide an opportunity to pilot, validate questions, and inform a survey instrument for use as the third component of this study: a broad survey of physicians and nurses. We elaborate on each mixed-methods component below.

Our initial data pull on EHR for records on potential cases of HT was unsuccessful. Since our study, HT-specific ICD-10 codes have been released, but the lack of data on trafficking cases in the Geisinger health system indicated a need for a broader investigation into how cases of trafficking are documented. This is what prompted our mixed-methods research involving (1) key informant interviews, and (2) subsequent survey of physicians and registered nurses to examine how HT is recognized in healthcare systems and subsequently communicated through patient care. A major impetus for this study was to explore perspectives regarding the potential application of tools developing as part of the precision medicine movement (namely, biometrics such as genetic data and EHR data-sharing infrastructure) to improve the care of trafficked patients and begin to consider the foreseeable ethical, legal, and social issues (including but not limited to privacy, contextual integrity, and management of risks associated with unintended secondary data access and use) that would need to be addressed in order for such an application to be designed and implemented responsibly. Such studies remain difficult to pursue because of the continued under-recognition of HT as a local problem and persistent biases about HT in healthcare settings. Implicit and explicit bias continue in healthcare settings, limiting the identification of (and subsequent assistance provided to) trafficked persons. Leveraging precision medicine tools to improve care of trafficked patients will remain ineffective if their development does not coincide with a broader effort to improve acknowledgment of HT as a serious public health matter.




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