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A great concern regarding the use of data science in any field is privacy. Adequately protecting individuals from the negative effects of maliciously shared personal identifying information is essential. It is however, also important to understand the positive role that protected and shared information can play. This chapter provides a basic understanding of how the concept of privacy has developed in the United States (US) and suggests that continued development of that understanding and the protections provided will occur.

Reusing existing data sets of health information for public health or medical research has much to recommend it. Much data repurposing in medical or public health research or practice involves information that has been stripped of individual identifiers but some does not. In some cases, there may have been consent to the reuse but in other cases consent may be absent and people may be entirely unaware of how the data about them are being used. Data sets are also being combined and may contain information with very different sources, consent histories, and individual identifiers. Much of the ethical and policy discussion about the permissibility of data reuse has centered on two questions: for identifiable data, the scope of the original consent and whether the reuse is permissible in light of that scope, and for de-identified data, whether there are unacceptable risks that the data will be reidentified in a manner that is harmful to any data subjects. Prioritizing these questions rests on a picture of the ethics of data use as primarily about respecting the choices of the data subject. We contend that this picture is mistaken; data repurposing, especially when data sets are combined, raises novel questions about the impacts of research on groups and their implications for individuals regarded as falling within these groups. These impacts suggest that the controversies about de-identification or reconsent for reuse are to some extent beside the point. Serious ethical questions are also raised by the inferences that may be drawn about individuals from the research and resulting risks of stigmatization. These risks may arise even when individuals were not part of the original data set being repurposed. Data reuse, repurposing, and recombination may have damaging effects on others not included within the original data sets. These issues of justice for individuals who might be regarded as indirect subjects of research are not even raised by approaches that consider only the implications for or agreement of the original data subject. This chapter argues that health information should be available for reuse, information should be available for use, but in a way that does not yield unexpected surprises, produce direct harm to individuals, or violate warranted trust.

This chapter more clearly identifies the distinction between Electronic Health Record (EHR) and Electronic Medical Record (EMR), and states their value in obtaining individual-level data. Synthetic medical records may be used as a surrogate for EHR data in order to ensure digital data privacy is maintained during the development of the LHS. Synthea is an open-source simulation tool available through GitHub.¹ Extensive descriptive analysis of synthesized data is provided as a foundation for the analysis in Chapter 7.

Several emergency public health issues have a tremendous impact on and rely upon close coordination with law enforcement officials. Most interactions involve law enforcement personnel providing security, crowd control, and/or traffic control during public health related incidents. However, as varied chemical and biological threats have emerged over the years, this interaction has increased to include joint investigations between the two disciplines. Certain biological threats, such as pandemics, pose direct threats to the law enforcement agency operations. Understanding the role of public health in emergencies, the overlapping missions, and the threats at all levels allows law enforcement professionals to better prepare themselves and their organizations for coordinating operations and maintaining continuity of law enforcement services.

This mixed methods multiple case study examines the knowledge, understanding, and awareness of 25 health board/facility oversight managers and 20 health professional association directors about privacy and security issues important to achieving health information exchange (HIE) in the state of Nebraska. Within case analyses revealed that health board/facility oversight managers were unaware of key elements of the federal agenda; their concerns about privacy encompassed broad definitions both of what constituted a “health record” and “regulations centeredness.” Alternatively, health professional association leaders were keenly aware of national initiatives. Despite concerns about HIE, they supported information exchange believing that patient care quality and safety would improve. Cross-case analyses revealed a perceptual disconnect between board/facility oversight managers and professional association leaders; however, both favored HIE. Understanding state-level stakeholder perceptions helps us further understand our progress toward achieving the national health information interoperability goal. There is an ongoing need to assure adequate patient privacy protection. Licensure and facility boards at the state level are likely to have a major role in the assurance of patient protections through facility oversight and provider behavior. The need for these boards to take an active role in oversight of patient rights and protections is imminent. Similarly, professional associations are the major vehicles for post-graduate education of practicing health professionals. Their engagement is essential to maintaining health professions knowledge. States will need to understand and engage both of these key stakeholders to make substantial progress in moving the HIE agenda forward.

At the beginning of the 21st century, multiple and diverse social entities, including the public (consumers), private and nonprofit healthcare institutions, government (public health) and other industry sectors, began to recognize the limitations of the current fragmented healthcare system paradigm. Primary stakeholders, including employers, insurance companies, and healthcare professional organizations, also voiced dissatisfaction with unacceptable health outcomes and rising costs. Grand challenges and wicked problems threatened the viability of the health sector. American health systems responded with innovations and advances in healthcare delivery frameworks that encouraged shifts from intra- and inter-sector arrangements to multi-sector, lasting relationships that emphasized patient centrality along with long-term commitments to sustainability and accountability. This pathway, leading to a population health approach, also generated the need for transformative business models. The coproduction of health framework, with its emphasis on cross-sector alignments, nontraditional partner relationships, sustainable missions, and accountability capable of yielding return on investments, has emerged as a unique strategy for facing disruptive threats and challenges from nonhealth sector corporations. This chapter presents a coproduction of health framework, goals and criteria, examples of boundary spanning network alliance models, and operational (integrator, convener, aggregator) strategies. A comparison of important organizational science theories, including institutional theory, network/network analysis theory, and resource dependency theory, provides suggestions for future research directions necessary to validate the utility of the coproduction of health framework as a precursor for paradigm change.

What sets health sciences librarians apart from other academic librarians when it comes to partnering with health-focused innovators? Do health-related innovators have different information needs or space requirements? This chapter illustrates some of the major issues and topics health sciences librarians consider as they offer information services to entrepreneurs and innovators. Health sciences innovators must be aware of relevant policies and laws such as HIPAA, the Health Insurance Portability and Accountability Act of 1996. They also need to meet federal safety regulations required by the Food and Drug Administration; moreover, device materials must be biocompatible. Those developing therapeutic games and apps in this arena need to ensure their products are supported by current literature and scientific evidence. In many cases, these new technologies require clinical trials and testing to ensure their safety and efficacy. Health sciences librarians guide innovators to relevant resources, knowledge, and experts on these and other topics. This navigator role is extremely valuable to students, who may not understand the healthcare landscape and its processes. Additionally, librarians assist innovators with identifying dissemination venues for their scholarly output. They provide instruction and guidance on how to write and tailor conference proposals to meet specific professional association criteria. A retired health sciences library director shares her experiences. Tips and lessons learned are highlighted so others may gain an understanding of the unique information needs of health innovators.

Deliberative procedures can be useful when researchers need (a) an informed opinion that is difficult to obtain using other methods, (b) individual opinions that will benefit from group discussion and insight, and/or (c) group judgments because the issue at hand affects groups, communities, or citizens qua citizens. Deliberations generally gather non-professional members of the public to discuss, deliberate, and learn about a topic, often forming a policy recommendation or casting an informed vote. Researchers can collect data on these recommendations, and/or individuals’ preexisting or post hoc knowledge or opinions. This chapter presents examples of deliberative methods and how they may inform bioethical perspectives and reviews methodological issues deserving special attention.

The authors have previously validated a design of the health-care supply chain which treats patients as inventory without loss of respect for the patients. This work continues examination of patients as inventory while addressing the dual objectives of reducing redundancy in services and creating greater efficiency in the health-care supply chain. Historical data is used to forecast health care needs in light of the increasingly specialized health-care professionals, which have resulted in much more flexible and expensive supply chains. The lack of common data storage, or electronic medical records (EMRs), has created a need for redundancy (or rework) in medical testing. The use of EMR will also enhance our ability to forecast needs in the future. We perform simulations using SigmaFlow software to address our goals relative to the resource constraints, monetary constraints, and the overall culture of the medical supply chain. The simulation outcomes lead us to recommendations for data warehousing as well as providing mechanisms, like inventory postponement strategies, to establish structures for more efficiency, and reduced flexibility in the supply chains.