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This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

Innovation in a decentralized blockchain infrastructure can be used by medicine as a prerequisite for the exchange of patient data. Developments in the medical device industry that support the technology of the internet of things and wireless sensor networks also facilitate the examination of patient medical records that no longer require visits to the practice of doctors or hospitals which in some cases takes in a considerable time. Not to mention the consideration of traffic congestion and busy routine in the work. Patients can check their healthcare concerns using only sensors such as e-Health Sensor Shield Platform which then sends recording results through the transmission line to the data lakes. However, this patient’s medical record data is very confidential and may only be accessed by certain parties only. This required the design of the concept of security in the transmission of data so that the data does not leak to parties who are not eligible. This paper attempts to provide an overview of the concept of using encryption with an asymmetric key for securing data from sensors to data lakes before forwarding to a decentralized, interconnected blockchain infrastructure.

Potentially major shifts in privacy norms are taking place as a result of advances in genetic technologies. This chapter identifies a spillover effect in the form of the inadvertent emergence of new norms and introduces an original typology developed in response to these new norms regarding privacy. It focuses on the emerging practice of compelling access to genetic information of biologically related persons to gain information about a particular individual. This chapter highlights the recent practice in child lead paint poisoning cases in which defendants seek to discover medical and I.Q. records of biologically related non-parties to establish alternate genetic causation of low I.Q. It concludes that greater attention should be given to the spillover effect and the emergence of shadow norms.

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.

Big Data is one of the most promising area where it can be applied to make a change is health care. Healthcare analytics have the potential to reduce the treatment costs, forecast outbreaks of epidemics, avoid preventable diseases, and improve the quality of life. In general, the lifetime of human is increasing along world population, which poses new experiments to today’s treatment delivery methods. Health professionals are skillful of gathering enormous volumes of data and look for best approaches to use these numbers. Big data analytics has helped the healthcare area by providing personalized medicine and prescriptive analytics, medical risk interference and predictive analytics, computerized external and internal reporting of patient data, homogeneous medical terms and patient registries, and fragmented point solutions. The data generated level within healthcare systems is significant. This includes electronic health record data, imaging data, patient-generated data, etc. While widespread information in health care is now mostly electronic and fits under the big data as most is unstructured and difficult to use. The use of big data in health care has raised substantial ethical challenges ranging from risks for specific rights, privacy and autonomy, to transparency and trust.

Purpose – Health information technology (HIT) holds promise for improving the quality of health care and reducing health care system inefficiencies. Numerous studies have examined HIT availability, specifically electronic health records (EHRs), and utilization among physicians in individual countries. However, no one has examined EHR use among physicians who train in one country and move to practice in another country. In the United States, physicians who complete medical school outside the country but practice within the United States are commonly referred to as International Medical Graduates (IMGs). IMGs have a growing presence in the United States, yet little is known about the availability and use of HIT among these physicians. The purpose of this study is to explore the availability and use of HIT among IMGs practicing in United States.

Design/methodology/approach – The Health Tracking Physician Survey (2008) was used to examine the relationship between availability and use of HIT and IMG status controlling for several physician and practice characteristics. Our analysis included responses from 4,720 physicians, 20.7% of whom were IMGs.

Findings – Using logistic regression, controlling for physician gender, specialty, years in practice, practice type, ownership status and geographical location, we found IMGs were significantly less likely to have a comprehensive EHR in their practices (OR=0.84; p=0.005). In addition, findings indicate that IMGs are more likely to have and use several so-called first generation HIT capabilities, such as reminders for clinicians about preventive services (OR=1.31; p=0.001) and other needed patient follow-up (OR=1.26; p=0.007).

Originality/value – This study draws attention to the need for further research regarding barriers to HIT adoption and use among IMGs.

Tremendous measure of data lakes with the exponential mounting rate is produced by the present healthcare sector. The information from differing sources like electronic wellbeing record, clinical information, streaming information from sensors, biomedical image data, biomedical signal information, lab data, and so on brand it substantial as well as mind-boggling as far as changing information positions, which have stressed the abilities of prevailing regular database frameworks in terms of scalability, storage of unstructured data, concurrency, and cost. Big data solutions step in the picture by harnessing these colossal, assorted, and multipart data indexes to accomplish progressively important and learned patterns. The reconciliation of multimodal information seeking after removing the relationship among the unstructured information types is a hotly debated issue these days. Big data energizes in triumphing the bits of knowledge from these immense expanses of information. Big data is a term which is required to take care of the issues of volume, velocity, and variety generally seated in the medicinal services data. This work plans to exhibit a survey of the writing of big data arrangements in the medicinal services part, the potential changes, challenges, and accessible stages and philosophies to execute enormous information investigation in the healthcare sector. The work categories the big healthcare data (BHD) applications in five broad categories, followed by a prolific review of each sphere, and also offers some practical available real-life applications of BHD solutions.

This chapter explains how fundamental organisational change in the UK National Health Service (NHS) is being effected by new practices of digitised information gathering and use. It analyses the taken-for-granted IT infrastructures that lie behind digitisation and considers the relationship between digitisation and big data.

Qualitative research methods including discourse analysis, ethnography of software and key informant interviews were used. Actor-network theories, as developed by Science and technology Studies (STS) researchers were used to inform the research questions, data gathering and analysis. The chapter focuses on the aftermath of legislation to change the organisation of the NHS.

The chapter shows the benefits of qualitative research into specific manifestations information technology. It explains how apparently ‘objective’ and ‘neutral’ quantitative data gathering and analysis is mediated by complex software practices. It considers the political power of claims that data is neutral.

The chapter provides insight into a specific case of healthcare data and. It makes explicit the role of politics and the State in digitisation and shows how STS approaches can be used to understand political and technological practice.