scholarly journals Representation of People’s Decisions in Health Information Systems

2017 ◽  
Vol 56 (S 01) ◽  
pp. e13-e19 ◽  
Author(s):  
Fernan Gonzalez Bernaldo de Quiros ◽  
Adriana Dawidowski ◽  
Silvana Figar

SummaryObjectives: In this study, we aimed: 1) to conceptualize the theoretical challenges facing health information systems (HIS) to represent patients’ decisions about health and medical treatments in everyday life; 2) to suggest approaches for modeling these processes.Methods: The conceptualization of the theoretical and methodological challenges was discussed in 2015 during a series of interdisciplinary meetings attended by health informatics staff, epidemiologists and health professionals working in quality management and primary and secondary prevention of chronic diseases of the Hospital Italiano de Buenos Aires, together with sociologists, anthropologists and e-health stakeholders.Results: HIS are facing the need and challenge to represent social human processes based on constructive and complexity theories, which are the current frameworks of human sciences for understanding human learning and socio-cultural changes. Computer systems based on these theories can model processes of social construction of concrete and subjective entities and the interrelationships between them. These theories could be implemented, among other ways, through the mapping of health assets, analysis of social impact through community trials and modeling of complexity with system simulation tools.Conclusions: This analysis suggested the need to complement the traditional linear causal explanations of disease onset (and treatments) that are the bases for models of analysis of HIS with constructive and complexity frameworks. Both may enlighten the complex interrelationships among patients, health services and the health system. The aim of this strategy is to clarify people’s decision making processes to improve the efficiency, quality and equity of the health services and the health system.

2020 ◽  
Vol 9 ◽  
pp. 1792
Author(s):  
Hamid Moghaddasi ◽  
Reza Rabiei ◽  
Farkhondeh Asadi ◽  
Ali Mohammadpour

Background: The National Health Information Network (NHIN) is one of the key issues in health information systems in any country. However, the development of this network should be based on an appropriate framework. Unfortunately, the conducted projects of health information systems in the Ministry of Health of Iran do not fully comply with the concept of NHIN. The present study was aimed to develop a general framework for NHIN in Iran. Materials and Methods: In this study, in the first stage, the required information about the concept of the NHIN framework and related NHIN documents in the USA and the UK were collected based on a literature review. Then, according to the results of the first stage and with regards to the structure of the Iranian health system, a general framework for Iranian NHIN was proposed. The Delphi technique was conducted to verify the framework. Results: The proposed framework for Iranian NHIN includes three dimensions; components, principles, and architecture. Over 80% of experts have evaluated all three aspects of the framework at an acceptable scale. In total, the proposed framework has been evaluated by 83.8% of the experts at an acceptable scale. Conclusion: The proposed framework was expected to serve as the starting point for moving towards the design and creation of Iranian NHIN. At any rate, the framework could be criticized, and it could only be used for the countries whose health system is similar to the structure of the health system in Iran. [GMJ.2020;9:e1792]


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.


2020 ◽  
pp. 183335832092872 ◽  
Author(s):  
Klesta Hoxha ◽  
Yuen W Hung ◽  
Bridget R Irwin ◽  
Karen A Grépin

Background: Routine health information systems (RHISs) are crucial to informing decision-making at all levels of the health system. However, the use of RHIS data in low- and middle-income countries (LMICs) is limited due to concerns regarding quality, accuracy, timeliness, completeness and representativeness. Objective: This study systematically reviewed technical, behavioural and organisational/environmental challenges that hinder the use of RHIS data in LMICs and strategies implemented to overcome these challenges. Method: Four electronic databases were searched for studies describing challenges associated with the use of RHIS data and/or strategies implemented to circumvent these challenges in LMICs. Identified articles were screened against inclusion and exclusion criteria by two independent reviewers. Results: Sixty studies met the inclusion criteria and were included in this review, 55 of which described challenges in using RHIS data and 20 of which focused on strategies to address these challenges. Identified challenges and strategies were organised by their technical, behavioural and organisational/environmental determinants and by the core steps of the data process. Organisational/environmental challenges were the most commonly reported barriers to data use, while technical challenges were the most commonly addressed with strategies. Conclusion: Despite the known benefits of RHIS data for health system strengthening, numerous challenges continue to impede their use in practice. Implications: Additional research is needed to identify effective strategies for addressing the determinants of RHIS use, particularly given the disconnect identified between the type of challenge most commonly described in the literature and the type of challenge most commonly targeted for interventions.


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):  
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.


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