Accountability, Beneficence, and Self-Determination

Author(s):  
Tina Saryeddine

Existing literature often addresses the ethical problems posed by health informatics. Instead of this problem-based approach, this chapter explores the ethical benefits of health information systems in an attempt to answer the question “can health information systems make organizations more accountable, beneficent, and more responsive to a patient’s right to self determination?” It does so by unpacking the accountability for reasonableness framework in ethical decision making and the concepts of beneficence and self-determination. The framework and the concepts are discussed in light of four commonly used health information systems, namely: Web-based publicly accessible inventories of services; Web-based patient education; telemedicine; and the electronic medical record. The objective of this chapter is to discuss the ethical principles that health information systems actually help to achieve, with a view to enabling researchers, clinicians, and managers make the case for the development and maintenance of these systems in a client-centered fashion.

2011 ◽  
pp. 913-932
Author(s):  
Aisha Naseer ◽  
Lampros K. Stergioulas

Healthcare is a vast domain encapsulating not only multiple sub-domains or sub-sectors but also many diverse operations and logistics within each sub-sector. This diversity needs to be handled in a systematic and well-characterized manner in order to maintain consistency of various healthcare tasks. Integration of health information systems within each healthcare sub-sectors is crucial for ubiquitous access and sharing of information. The emerging technology of HealthGrids holds the promise to successfully integrate health information systems and various healthcare entities onto a common, globally shared and easily accessible platform. Many different types of HealthGrids exist but there lacks a taxonomy to classify them into a hierarchical order. This chapter presents a well-characterized taxonomy of different types of HealthGrid and classifies them into four major types, namely BioGrid, MediGrid, PharmaGrid and CareGrid. Each of these HealthGrids possesses dedicated features and functionalities. The proposed taxonomy serves to better understand the realtionship among various HealthGrid types and would lay a basis for future research.


2009 ◽  
Vol 18 (01) ◽  
pp. 153-157
Author(s):  
A. Vero ◽  
L. Bessonart ◽  
A. Barbiel ◽  
M. Ferla ◽  
A. Margolis

Summary Objectives Health Information systems training is one of the bottlenecks in clinical systems implementation. In this article, a strategy to massively create and train interdisciplinary coordinating teams is described for a project in Uruguay at FEMI, a non-academic setting which includes 23 health care institutions across the country and a tertiary referral center in Montevideo. Methods A series of educational activities were designed for the local coordinating teams. They included both onsite and online formats, site visits, integrated with some of the project tasks. Results In total, 128 professionals from all the Institutions participated in one or more of the training sessions (onsite and online) and 87 of them accomplished one of the forms of training. Conclusions Massive basic health informatics training was possible in Uruguay through collaboration with academic institutions at the country and regional level. Next steps include an active involvement of nurses in the educational events and planning of massive training of end users.


Author(s):  
Aisha Naseer ◽  
Lampros K. Stergioulas

Healthcare is a vast domain encapsulating not only multiple sub-domains or sub-sectors but also many diverse operations and logistics within each sub-sector. This diversity needs to be handled in a systematic and well-characterized manner in order to maintain consistency of various healthcare tasks. Integration of health information systems within each healthcare sub-sectors is crucial for ubiquitous access and sharing of information. The emerging technology of HealthGrids holds the promise to successfully integrate health information systems and various healthcare entities onto a common, globally shared and easily accessible platform. Many different types of HealthGrids exist but there lacks a taxonomy to classify them into a hierarchical order. This chapter presents a well-characterized taxonomy of different types of HealthGrid and classifies them into four major types, namely BioGrid, MediGrid, PharmaGrid and CareGrid. Each of these HealthGrids possesses dedicated features and functionalities. The proposed taxonomy serves to better understand the realtionship among various HealthGrid types and would lay a basis for future research.


Author(s):  
Christina Ilioudi ◽  
Athina Lazakidou

The development of Internet technology and Web-based applications made health information more accessible than ever before from many locations by multiple health providers and health plans. In this chapter, security in health information systems is put into perspective. The further penetration of information technology into healthcare is discussed, and it is concluded that information systems have already become a vital component, not only for the logistics of the healthcare institution but also for the rendering of care and cure.


2020 ◽  
Vol 30 (Suppl 1) ◽  
pp. 193-202
Author(s):  
Karen Wang ◽  
Ian Hambleton ◽  
Erika Linnander ◽  
Luis Marenco ◽  
Saria Hassan ◽  
...  

Precision medicine seeks to leverage technology to improve the health for all individuals. Successful health information systems rely fundamentally on the integra­tion and sharing of data from a range of disparate sources. In many settings, basic infrastructure inequities exist that limit the usefulness of health information systems. We discuss the work of the Yale Transdis­ciplinary Collaborative Center for Health Disparities focused on Precision Medicine, which aims to improve the health of people in the Caribbean and Caribbean diaspora by leveraging precision medicine approaches. We describe a participatory informatics ap­proach to sharing data as a potential mecha­nism to reducing inequities in the existing data infrastructure.Ethn Dis. 2020;30(Suppl 1):193-202; doi:10.18865/ed.30.S1.193


Author(s):  
Tugrul U. Daim ◽  
Leong Chan ◽  
Muhammad Amer ◽  
Fahad Aldhaban

Author(s):  
Sundeep Sahay ◽  
T Sundararaman ◽  
Jørn Braa

Establishment of health information systems has been a central objective of health sector reform in nearly all LMICs over the last two to three decades. Historically, reform processes have taken introduction of health information systems as inhertently strengthening health sector performance. But today it is more appropriate to talk of health sector strengthening as co-evolving with health information systems strengthening, each reinforcing the performance and reform agendas of the other. The need to build synergies is heightened as there are a multitude of global and national health reform processes underway, like those assoicated with the sustainable development goals or with universal health coverage and each of these have expanded informational needs, requiring robust, flexible, and evolving health information systems. An understanding of the challenges faced by efforts at health systems strengthening helps provide meaningful inputs into health information systems design and vice versa. Such an understanding will enrich public health informatics as an academic discipline, as an area of practice, and as a policy domain.


2010 ◽  
Vol 4 (1) ◽  
pp. 181-187 ◽  
Author(s):  
E.M Borycki ◽  
A.W Kushniruk

The purpose of this paper is to argue for an integration of cognitive and socio-technical approaches to assessing the impact of health information systems. Historically, health informatics research has examined the cognitive and socio-technical aspects of health information systems separately. In this paper we argue that evaluations of health information systems should consider aspects related to cognition as well as socio-technical aspects including impact on workflow (i.e. an integrated view). Using examples from the study of technology-induced error in healthcare, we argue for the use of simulations to evaluate the cognitive-socio-technical impacts of health information technology [36]. Implications of clinical simulations and analysis of cognitive-social-technical impacts are discussed within the context of the system development life cycle to improve health information system design, implementation and evaluation.


Author(s):  
Ericka Silva Holmes ◽  
Sérgio Ribeiro dos Santos ◽  
Alexandra Fraga Almeida ◽  
Jéssica Helena Dantas de Oliveira ◽  
Gyl Dayara Alves de Carvalho ◽  
...  

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