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Recent studies indicated that the level of adoption of health data standards in healthcare organisations remains frustratingly low worldwide although health data standards have been perceived to be an essential tool for interoperability barriers within health information systems. The relevant literature still lacks significant studies concerning the issues of the adoption process of health data standards in healthcare organisations, and in particular those in developing nation. In addressing this gap in knowledge, the purpose of this paper is to investigate the adoption decision of health data standards in tertiary healthcare organisations in Saudi Arabia, and to develop a technology-organisation-environment list that contains the critical factors influencing their adoption.

A multiple-case study methodology was conducted in Saudi Arabia and different data collection methods were used included semi-structured interviews with different decision makers at various levels and departments of the subject organisations, and documents analysis to identify critical factors to the adoption decision of health data standards.

The findings demonstrated a list of key factors from different aspects impacting the adoption decision of health data standards in the subject organisations. The technological factors are complexity and compatibility of health data standards, IT infrastructure, switching costs, market uncertainties, systems integration and enhancing the use of advanced systems. The main organisational factors are the lack of adequate policies and procedures and information management plan, resistance to change, data analysis and accreditation. The core environmental factors are the lack of national regulator and data exchange plan, national healthcare system and the shortage of professionals.

The results from the qualitative data were difficult to generalise to other populations. For example, the structure of the health sector varies from country to country as each health sector has its own characteristics that affect and are affected by national circumstances. In order to provide a more grounded theory resulting from a qualitative study, further examination by conducting quantitative studies is required. In addition, the TOE approach does not take into account the sociotechnical issues and further research is required in this area.

The investigation into the adoption decision of health data standards in tertiary healthcare organisations in Saudi Arabia has led to the development of a technology-organisation-environment list that contains the critical factors influencing their adoption. The research outcome has addressed the gap in knowledge of the adoption of health data standards in healthcare organisations. It also provides the decision maker, and in particular those in developing nations, with better understanding of the adoption process of those standards to better judge and to develop suitable strategy of adoption interventions.

Although recent studies indicated that the level of adoption of health data standards in healthcare organisations remains frustratingly low, the prior studies related to health data standards missed out on the exploration of the adoption decision of different types of health data standards in healthcare organisations and the critical factors influencing their adoption. Research on health data standards adoption based out of a developing country such as Saudi Arabia can also potentially provide several new insights on standards practices.

This paper seeks to carry out a critical study of health data standards and adoption process with a focus on Saudi Arabia.

Many developed nations have initiated programs to develop, promote, adopt and customise international health data standards to the local needs. The current status of, and future plans for, health data and related standards in developing countries are still questionable due to the absence of government actions, plans and related studies. However, the development of interoperable standards not only technically defines a method of interoperation between the different systems in a network but most importantly represents a proposal for the future of complex socio‐technical systems that is the shape of a national health information network and therefore a complex balance between different types of requirements including organisational, social and managerial aspects must be managed. This reaffirms the need for a more in‐depth study to evaluate the adoption of health information technology‐related standards at the decision‐making stage in developing countries. Based on diffusion of innovation theory and the theories surrounding the economics of standards, a case study method was applied in Saudi Arabia to study the adoption process of health data standards.

The preliminary analysis findings revealed that there are 18 factors influencing the decision‐making adoption process of acquiring certain standards.

Qualitative study methods have been employed in the present study that have shed light on the many issues that need to be addressed in this field. Studies involving other countries including advanced nations should be done for which the present results have economic, social and educational implications.

The present study and findings should help inform policy and decision makers in developing health systems with the potential creation of information and structure that can sustain future and improved systems.

This paper makes a novel contribution at both academic and practical levels since both the academics and practitioners, who are devoted to the ongoing use of health data standards, still lack a significant body of evidence with regard to the factors that influence their adoption.

The current trend in Big Data analytics and in particular health information technology is toward building sophisticated models, methods and tools for business, operational and clinical intelligence. However, the critical issue of data quality required for these models is not getting the attention it deserves. The purpose of this paper is to highlight the issues of data quality in the context of Big Data health care analytics.

The insights presented in this paper are the results of analytics work that was done in different organizations on a variety of health data sets. The data sets include Medicare and Medicaid claims, provider enrollment data sets from both public and private sources, electronic health records from regional health centers accessed through partnerships with health care claims processing entities under health privacy protected guidelines.

Assessment of data quality in health care has to consider: first, the entire lifecycle of health data; second, problems arising from errors and inaccuracies in the data itself; third, the source(s) and the pedigree of the data; and fourth, how the underlying purpose of data collection impact the analytic processing and knowledge expected to be derived. Automation in the form of data handling, storage, entry and processing technologies is to be viewed as a double-edged sword. At one level, automation can be a good solution, while at another level it can create a different set of data quality issues. Implementation of health care analytics with Big Data is enabled by a road map that addresses the organizational and technological aspects of data quality assurance.

The value derived from the use of analytics should be the primary determinant of data quality. Based on this premise, health care enterprises embracing Big Data should have a road map for a systematic approach to data quality. Health care data quality problems can be so very specific that organizations might have to build their own custom software or data quality rule engines.

Today, data quality issues are diagnosed and addressed in a piece-meal fashion. The authors recommend a data lifecycle approach and provide a road map, that is more appropriate with the dimensions of Big Data and fits different stages in the analytical workflow.

The move toward e-health care in various countries is envisaged to reduce the cost of provision of health care, improve the quality of care and reduce medical errors. The most significant problem is the protection of patients’ data privacy. If the patients are reluctant or refuse to participate in health care system due to lack of privacy laws and regulations, the benefit of the full-fledged e-health care system cannot be materialized. The purpose of this paper is to investigate the available e-health data privacy protection laws and the perception of the people using the e-health care facilities.

The researchers used content analysis to analyze the availability and comprehensive nature of the laws and regulations. The researchers also used survey method. Participants in the study comprised of health care professionals (n=46) and health care users (n=187) who are based in the Dubai, United Arab Emirates. The researchers applied descriptive statistics mechanisms and correlational analysis to analyze the data in the survey.

The content analysis revealed that the available health data protection laws are limited in scope. The survey results, however, showed that the respondents felt that they could trust the e-health services systems offered in the UAE as the data collected is protected, the rights are not violated. The research also revealed that there was no significance difference between the nationality and the privacy data statements. All the nationality agreed that there is protection in place for the protection of e-health data. There was no significance difference between the demographic data sets and the many data protection principles.

The findings on the users’ perception could help to evaluate the success in realizing current strategies and an action plan of benchmarking could be introduced.

Information and communication technologies can transform how services can be and are delivered as has already happened in other arenas, such as civil aviation, financial services and retailing. Most modern health care is heavily dependent on e-health, including record keeping, targeted information sharing and digital diagnostic and imaging techniques. However, there remains little scientific knowledge base for optimal system content and function in primary health care, particularly for children. Models of Child Health Appraised (MOCHA) aimed to establish the current e-health situation in children’s primary care services. Electronic health records (EHRs) are in regular use in much of northern and western Europe and in some newer European Union Member States, but other countries lag behind. MOCHA investigated the use of unique identifiers, the use of case-based public health EHRs and the capability of record linkage, linkage of information with school health data and monitoring of social media influences, such as health websites and health apps. A widespread lack of standards underlined a lack of research enquiry into this issue in terms of children’s health data and health knowledge. Health websites and apps are a growing area of healthcare delivery, but there is a worrying lack of safeguards in place. The challenge for policy-makers and practitioners is to be aware and to lead on the innovative harnessing of new technologies, while protecting child users against new harms.

General Data Protection Regulation (GDPR) of the European Union (EU) was passed to protect data privacy. Though the GDPR intended to address issues related to data privacy in the EU, it created an extra-territorial effect through Articles 3, 45 and 46. Extra-territorial effect refers to the application or the effect of local laws and regulations in another country. Lawmakers around the globe passed or intensified their efforts to pass laws to have personal data privacy covered so that they meet the adequacy requirement under Articles 45–46 of GDPR while providing comprehensive legislation locally. This study aims to analyze the Malaysian and Saudi Arabian legislation on health data privacy and their adequacy in meeting GDPR data privacy protection requirements.

The research used a systematic literature review, legal content analysis and comparative analysis to critically analyze the health data protection in Malaysia and Saudi Arabia in comparison with GDPR and to see the adequacy of health data protection that could meet the requirement of EU data transfer requirement.

The finding suggested that the private sector is better regulated in Malaysia than the public sector. Saudi Arabia has some general laws to cover health data privacy in both public and private sector organizations until the newly passed data protection law is implemented in 2024. The finding also suggested that the Personal Data Protection Act 2010 of Malaysia and the Personal Data Protection Law 2022 of Saudi Arabia could be considered “adequate” under GDPR.

The research would be able to identify the key principles that could identify the adequacy of the laws about health data in Malaysia and Saudi Arabia as there is a dearth of literature in this area. This will help to propose suggestions to improve the laws concerning health data protection so that various stakeholders can benefit from it.

This study aims to analyze a conspicuous corpus of literature related to the field of technology-based intensive care research and to develop an architecture model of the future smart intensive care unit (ICU).

Papers related to the topics of electronic health record (EHR), big data, data flow and clinical decision support in ICUs were investigated. These concepts have been analyzed in combination with secondary use of data, prediction models, data standardization and interoperability challenges. Based on the findings, an architecture model evaluated using MIMIC III is proposed.

Research identified issues regarding implementation of systems, data sources, interoperability, management of big data and free text produced in ICUs and lack of accuracy of prediction models. ICU should be treated as part of a greater system, able to intercommunicate with other entities.

The research examines the current needs of ICUs in interoperability and data management. As environment changes dynamically, continuous assessment and evaluation of the model with other ICU databases is required.

The proposed model improves ICUs interoperability in national health system, ICU staff intercommunication, remote access and decision support. Its modular approach ensures that ICUs can have their own particularities and specialisms while ICU functions provide ongoing expertise and training to upgrade its staff.

Along with technology-based ecosystems, healthcare start-ups are expanding multi-fold. On the other hand, underlying uncertainties pose several challenges for these health-tech enterprises at macro-meso-micro level, influencing their business circumstances and profitability. The current study aims to comprehend the macro-, meso- and micro-level barriers that make it difficult for enterprises to set up healthcare technology start-ups. The study also observed the perceived effect of these challenges on firms' performance and cost structure over time. Using the theory of behaviour under uncertainty, the study revealed multiple systemic, sector-related, human and implementation barriers that hinder business growth and lead to uncertainties for health-tech start-ups.

Using a grounded theory approach, the study collected the views of 51 health tech start-ups in the UK using an online participants pool. The data was collected using qualitative data techniques in the form of open-ended essays, and a content analysis using thematic coding process was conducted. The questions centered around the different institutional uncertainties or barriers while setting up or running a healthcare start-up.

The study revealed several macro-, meso- and micro-level barriers these technology-based enterprises perceive in the healthcare industry. These are recognised as systemic barriers, such as lack of funding and procedural issues; sector-related barriers, such as market-related impediments; human barriers, including psychological barriers and resistance to new technology; and implementation barriers, such as operational and personnel issues.

The study used qualitative, open-ended essay techniques to collect the data. Future studies may use a mixed-methods approach to provide holistic insights. The study is conducted in a single developed country, the UK. Future work may expand these findings by comparing developed market challenges with those of emerging markets and by assessing the viewpoints of healthcare start-ups.

This research will assist the healthcare sector and government understand health tech start-up hurdles and uncertainty. Policymakers must assist start-ups and encourage entrepreneurial innovation. Regulating and enabling policies will help. The paper examines start-ups' macro, meso and micro uncertainties. Policymakers promoting sector entrepreneurship must consider these barriers while designing policy guidelines.

The study contributes to the existing literature on technology start-ups, particularly in the healthcare industry, and identifies significant barriers these start-ups face. The study synthesizes research on health-tech start-up uncertainty and bridges the gap between theory and practice by applying empirical findings.

Purpose – The purpose of this article is to investigate one core research question: How can health information technology (HIT) be assessed in a national health care system context?

Design/methodology – We examine this question by taking a systematic approach within a national care system, in which the purpose of HIT is to contribute to a common national health care system's goal: to promote population health in an efficient way. Based on this approach we first develop a framework and our criteria of assessment, and then using Taiwan as a case study, demonstrate how one can apply this framework to assess a national system's HIT. The five criteria we developed are how well does the HIT (1) provide accessible and accurate public health and health care information to the population; (2) collect and provide population health and health care data for government and researchers to analyze population health and processes and outcomes of health care services; (3) provide accessible and timely information that helps to improve provision of cost-effective health care at an institutional level and promotes system-wide efficiency; (4) minimize transaction and administrative costs of the health care system; and (5) establish channels for population participation in governance while also protecting individual privacy.

Findings – The results indicate that Taiwan has high levels of achievement in two criteria while falling short in the other three. Major lessons we learned from this study are that HIT exists to serve a health care system, and the national health care system context dictates how one assesses its HIT.

Originality/value – There is a large body of literature published on the implementation of HIT and its impact on the quality and cost of health care delivery. The vast majority of the literature, however, is focused on a micro institutional level such as a hospital or a bit higher up, on an HMO or health insurance firm. Few have gone further to evaluate the implementation of HIT and its impact on a national health care system. The lack of such research motivated this study. The major contributions of this study are (i) to develop a framework that follows systems thinking principles and (ii) propose a process through which a nation can identify its objectives for HIT and systematically assess its national HIT system. Using Taiwan's national health care system as a case study, this paper demonstrated how it can be done.

Informatics work introduces information professionals to taxonomies and other classification systems outside the boundaries of traditional bibliographic systems. This paper aims to provide an overview of the International Statistical Classification of Diseases and Related Health Problems (ICD) for informaticians and information professionals who may not have worked with the system previously.

In this paper, the author reviews the purpose, history, current use and future trends of the ICD classification system.

ICD is used globally as a standard vocabulary for medical diagnoses and, in the USA, for medical procedures in hospitals. Understanding the classification system is vital to working with clinical medical data.

The ICD classification system is not commonly used by information professionals. This paper provides a brief overview that will familiarize the information professional with the standard and its uses related to medical practice.