Nursing, Ethics, and Healthcare Policy

This chapter examines and analyzes ethical problems associated with the global nursing shortage, the international recruitment of nurses, and the strategies healthcare systems and governments use to minimize the impact of the nursing shortage within their borders. An argument is made that a more appropriate solution to the U.S. nursing shortage is not to pull from already burdened systems, but rather to recruit and provide financial aid to potential nursing students, especially underrepresented and economically disadvantaged students, from within the United States. Implications for migration, education, and healthcare policy are explored. Resulting challenges for nursing leadership and demands on nursing education are addressed, as well as approaches for addressing the issues of providing safe patient care, a satisfying work environment, and professional development.

Caught in the Web

The social consequences of the internet are profound. Evidence of this can easily be found in the enormous body of literature discussing its impact on democracy, globalization, social networking, and education. The implications of the internet for medicine have likewise received a great deal of attention from policy makers, clinicians and technology theorists. Medical privacy, in particular, has garnered the lion’s share of attention. Nevertheless, research in this area has been lacking because it either fails to unpack the conceptual and ethical complexities of privacy or overestimates the power of technology and policy to protect our medical privacy. The aims of this chapter are twofold. The first is to provide a nuanced explication of the concept of privacy, and, second, to argue that e-medicine and the policies supposedly designed to protect the privacy and confidentiality of personal health information fail to do so and in some instances make their violations easier to commit.

Implementation Issues on a National Electronic Health Record Network

The United States congress and the past several administrations have dedicated considerable funding for incentives focused on accelerating the adoption by the healthcare industry of Health Information Technology (HIT) solutions. The most recent effort towards these objectives includes a focus on the creation of a National Health Information Network that will support large scale exchange of health information. This chapter explores the technical, security and privacy implications of the advent of such an integrated network and the steps towards its successful completion.

Why Doesn’t Information Systems Vision Exist in the Healthcare Sector?

The nature of healthcare provision has changed dramatically and irreversibly over the past two decades. The focus has shifted from inward-looking supervision of medical care with substantial protection and defensive attitude to globally oriented, patient-centric facilitation of medical care and preventive services. Information technologies are increasingly playing a key role in reforming healthcare globally. How much of this reform addresses the primary goal of healthcare institutions? This chapter questions current expectations that information technology could bring benefits to healthcare sector—for which governments around the world are mandating and increasing investment in IT initiatives. There has been a remarkable expansion of information technology capabilities resulting in many ambitious IT projects in various healthcare institutions. The most sophisticated ones seem to concentrate on relatively simple coordination, resource allocation and documentation aspects of healthcare delivery process. There is little emphasis on the management of treatment process or optimization of resource use because definitive models do not exist for patient treatment processes. The major question being presented for open discussion here is whether these IT projects coincide with the primary goals of healthcare organizations. Is there an overall vision for IT in healthcare? If so, what is it? How does such vision contribute to the primary objectives of healthcare? Finding answers to these questions increases our understanding of current IT initiatives and considers the implications of the organizing vision for further development and diffusion of healthcare IS.

A Medical Data Trustworthiness Assessment Model

Electronic Health Record systems are being introduced to overcome the limitations associated with paper-based and isolated Electronic Medical Record systems. This is accomplished by aggregating medical data and consolidating them in one digital repository. Though an EHR system provides obvious functional benefits, there is a growing concern about reliability trust (trustworthiness) of Electronic Health Records. Security requirements such as confidentiality, integrity, and availability can be satisfied by traditional data security mechanisms. However, measuring data trustworthiness is an issue that cannot be solved with traditional mechanisms, especially since degrees of trust change over time. In this chapter, a Medical Data Trustworthiness Assessment model to assist an EHR system to validate the trustworthiness of received/stored medical data based on who entered the data and when is presented. The MDTA model uses a statistical approach that depends on the observed experiences available to the EHR system. In order to provide an accurate trustworthiness estimate for historical medical data, a time scope around the time when the data was entered was used. This scope enables the model to capture the dynamic behavior of the data entry agent’s trustworthiness. To conduct this assessment medical metadata is used to extract information about the medical data sources (e.g. timestamps, and the identities of healthcare agents and medical practitioners) and, thereafter, this information is used in a statistical process to derive a trustworthiness value for the medical data. The result can then be expressed in the displayed health record by manipulating the EHR’s metadata to alert the medical practitioner to possible trustworthiness problems.

Health Kiosk Technologies

This chapter examines the recent rise in the adoption and spread of kiosks in UK healthcare: The leading players in the healthcare market, their technologies, the main uses of the kiosks and software, including possible future developments into clinical care.

Hippocratic Database and Active Enforcement

There are an increasing number of laws and statutes being passed globally to protect the privacy of sensitive healthcare information. This complexity of legislation creates legal concerns for those stakeholders in the healthcare systems that collect and store this sensitive data. This chapter seeks to explore some technology based solutions for managing these complexities and that aim to mitigate some of the potential legal concerns associated with these activities.

Will Comparative Effectiveness Research Lead to Healthcare Rationing?

The Affordable Healthcare for America Bill that was signed into law in March 2010 includes support for activities that come under the heading of ‘comparative effectiveness’ research. The bill attempts to accelerate the conversion to electronic health records by all payers and providers who participate in the healthcare payment data stream. Conversion to electronic health data collection and storage solutions will create a large amount of treatment and payment data that is increasingly standardized by health standards organizations which reduces integration issues between technologies. There are federal advisory committees at work on designing the infrastructure needed to support a National Health Information Network (NHIN) that will support the healthcare data exchange required for comparative effectiveness research. The theory behind this work is that the availability of a large portion of existing health data will make it possible for researchers to identify therapies that lead to superior patient outcomes. It is assumed that the superior therapy would become the ‘best practice’ approach to treating a particular ailment. Supporters of comparative effectiveness see this as a strategy for making the system more effective both in terms of good medicine and also in terms of decreased cost. Opponents of comparative effectiveness see it as healthcare rationing and an inappropriate injection of government into the healthcare decision making process. Supporters and opponents have identified both positive and negative consequences to comparative effectiveness and this chapter will analyze the impact and propose some ways to optimize the results of this work.

The Nationwide Health Information Network

The Nationwide Health Information Network (NHIN) promises many benefits, but may be prone to a new phenomenon in healthcare fraud now rapidly drawing attention and commonly referred to as medical identity theft. As the medical industry continues down the path towards overall infrastructure digitization, it is anticipated that associated electronic records will become more portable hence facilitating efficient exchange. Problem however is, the enhanced transferability may also open a new vista of advantages to fraudsters. To address this risk, the NHIN implementers must implement stringent access control measures. One such solution is using a biometric cryptosystem-based solution. For defense-in-depth, a security strategy suggesting successive layers of controls, the PKI cryptographic scheme is recommended to intrinsically protect medical records when in use, storage or even in the event they are successfully stolen.

E-Discovery and Health Care IT

The increase in electronic health records has introduced an increase risk of litigation related to collection, storage and exchange of health information. This chapter explores the issues associated with activities involving legal discovery that can result from failure to properly manage this stored data. It offers insights into strategies that organizations can use to protect against litigation resulting from failure to properly consider and mitigate against unexpected outcomes involving legal discovery involving stored health data.