Towards a Unified Framework for Information and Interoperability Governance

Challenges in health data interoperability have highlighted overall health care system inefficiencies. Many organizations struggle to establish a robust data governance infrastructure to meet the increasing demands of advanced data uses, let alone sharing it with a large number of other organizations. There is a need for health care organizations to adopt information governance frameworks that encapsulates interoperability as a core attribute as this can improve data processing, knowledge translation and participation in the larger health data ecosystem. To establish interoperability between healthcare organizations, standards must exist in relation to how information is governed and circulates in the healthcare system, not just on how it is structured, stored and used within an organization. In this paper we demonstrate that interoperability between organizations cannot coherently exist without consideration of information governance within organizations. Lack of coherence can lead to lack of data accessibility, decreased organizational efficiencies, and poor data quality. With this in mind, we propose a unified framework that integrates the principles of both information and interoperability governance to increase the adaptability, flexibility, and efficiency of health information usage across the entire healthcare system.

Evolutionary game model based on cumulative prospect theory for information management mechanism in SIoT

As nodes in Social Internet of Things (SIoT) become more intelligent, malicious information occurs more frequently and spreads more widely. This problem can severely affect the trustworthiness of services and applications in SIoT. Methods to effectively control malicious information spreading in SIoT are essential and necessary. Reputation mechanism provides a powerful tool to tackle this challenge. In this paper, we propose a reputation-based mechanism to activate the self-purification capacity of the SIoT network by balancing information conflicts triggered by reporters and supporters. In order to find the best rewarding and punishment strategy, a bilateral cumulative-prospect-based evolutionary game model of SIoT network information conflict is constructed. Using local stability analysis and numerical simulation, the evolutionary trends of the proposed game model under different theoretical application scenarios are analyzed. The findings indicate that the basic income and deposit of both sides, the popularity of information as well as the importance of the conformity effect all have a significant impact on the system's steady state and evolutionary path. The specific conditions that both participating sides of the game tend to treat conflicts relatively rationally are analyzed. Dynamic evolution analysis and sensitivity analysis of selected parameters show that basic income is positively related to smart object's feedback strategies, while deposit is negatively related to that. While weight of conformity effect or the information popularity goes up, the rising of feedback probability is observed. Based on the above results, suggestions on dynamic reward and punishment strategies are given. The proposed model is a helpful attempt to model the evolution of information spreading in SIoT networks, with the ability to simulate several well-known regularities of message dissemination. Proposed model and suggested quantitative strategies can be helpful to build feasible malicious information control facilities in SIoT networks.

Sharing real-world data for public benefit: a qualitative exploration of stakeholder views and perceptions

BACKGROUND

There has been an increasing interest in the use of "real-world" data to inform care decision making that could lead to public health benefit. Routinely collected service and activity data associated with the administration of care services and service-users (such as electronic health records or electronic social care records), hold potential to better inform effective and responsive decision-making about health and care services provided to national and local populations. This study sought to gain an in-depth understanding regarding the potential to unlock real world data that was held in individual organisations, to better inform public health decision-making. This included sharing data between and within health service providers and local governing authorities, but also with university researchers to inform the evidence base.

METHODS

We used qualitative methods and carried out a series of online workshops and interviews with stakeholders (senior-level decision-makers and service leads, researchers, data analysts, those with a legal and governance role, and members of the public). We identified recurring themes in initial workshops, and explored these with participants in subsequent workshops. By this iterative process we further refined the themes identified, compared views and perceptions amongst different stakeholder groups, and developed recommendations for action.

RESULTS

Our study identified key elements of context and timing, the need for a different approach, and obstacles including governmental and legal, organisational features, and process factors which adversely affect the sharing of real world data. The findings also highlighted a need for improved communication about data for secondary uses to members of the public.

CONCLUSION

The Covid-19 pandemic context and changes to organisational structures in the health service in England have provided opportunities to address data sharing challenges. Change at national and local level is required, within current job roles and generating new jobs roles focused on the use and sharing of real-world data. The study suggests that actions can be taken to unlock the potential of real-world data for public health benefit, and provides a series of recommendations at a national level, for organisational leaders, those in data roles and those in public engagement roles.

Gentle or rude? A study on China's publicity of epidemic prevention and governance of urban and rural areas based on anti-epidemic slogans

COVID-19 has swept through the world, challenging countries' ability to respond to crises and their public governance. One of the difficulties of public governance in China is the knowledge gap caused by the urban-rural dual structure. This study takes anti-epidemic slogans in China, a traditional means of information governance as its research object in the context of COVID-19. Independent sample tests and cluster analysis were conducted to measure the knowledge gap between urban and rural residents in acquiring epidemic information, and compare the different slogans posted in urban and rural areas, as well as the feedback they received. Based on this, the study explores the different logic of urban and rural governance in China. The results show that, although slogans cannot convey the latest information, they can make the public aware of the severity of the epidemic. Urban residents were found to give lower evaluations to slogans, although they acknowledged that slogans had the effect of rendering an anti-epidemic atmosphere, whereas rural residents were more accepting of rude and threatening slogans and control measures. Slogans with scientific guidance were more likely to trigger changes in their awareness and behavior. The study is significant as it can be a reference for other regions' and countries' publicity work and governance approaches in the prevention and control of infectious diseases.

An Effective Approach for Extending Medical Data to the Cloud Through Synthetic Data Generation for Educational Environments

When taking advantage of technology, healthcare is often met with considerably more barriers to entry than business. Cloud platforms can offer great benefits such as scalability, reduced cost and the ability to effortlessly collaborate across services, and indeed, across the world [6] yet healthcare has been slow to take advantage of these gains. This paper explores the challenges faced by healthcare, how using synthetic data can avoid the initial information governance barriers, provide the experience to effectively evaluate cloud platforms, enable effective research collaboration with education and industry, and support the digital transformation journey.

Developing a Model for National Health Information Governance Program in Iran

With regard to the importance of health Information Governance (IG) programs in improving the quality and reducing the cost of healthcare services and the lack of a coherent health IG program in Iran’s health system, this study aimed to develop a model for national health information governance program in Iran.

The present research was an applied, cross-sectional descriptive study that was done in three steps, including literature review, development of a model for national health IG program in Iran, and model validation. In the third step, we used a questioner to validate the model through the Delphi method. Data analysis was done by descriptive statistics.

The model for the national IG program in Iran was developed in 3 main sections consisting of 13 components, 12 principles, natural and judicial authorities of the health IG program, and their job description. Findings from the validation of the initial model showed that most experts (93%) confirmed the components and sub-components, principles, and natural and legal bodies supervising the national health IG program and their job description in the proposed model.

Considering the structure of the Iranian health system, it was recommended to establish a health IG council in the Ministry of Health and Medical Education in order to develop guidelines and give advice to health care providers. Based on the proposed model, directors and staff of different departments of health care centers, especially those involved in health IG, are also responsible for the better implementation of the national health IG program.

Narrative Devices: Neurotechnologies, Information, and Self-Constitution

This article provides a conceptual and normative framework through which we may understand the potentially ethically significant roles that information generated by neurotechnologies about our brains and minds may play in our construction of our identities. Neuroethics debates currently focus disproportionately on the ways that third parties may (ab)use these kinds of information. These debates occlude interests we may have in whether and how we ourselves encounter information about our own brains and minds. This gap is not yet adequately addressed by most allusions in the literature to potential identity impacts. These lack the requisite conceptual or normative foundations to explain why we should be concerned about such effects or how they might be addressed. This article seeks to fill this gap by presenting a normative account of identity as constituted by embodied self-narratives. It proposes that information generated by neurotechnologies can play significant content-supplying and interpretive roles in our construction of our self-narratives. It argues, to the extent that these roles support and detract from the coherence and inhabitability of these narratives, access to information about our brains and minds engages non-trivial identity-related interests. These claims are illustrated using examples drawn from empirical literature reporting reactions to information generated by implantable predictive BCIs and psychiatric neuroimaging. The article concludes by highlighting ways in which information generated by neurotechnologies might be governed so as to protect information subjects' interests in developing and inhabiting their own identities.

Use of public datasets in the examination of multimorbidity: Opportunities and challenges

The interrogation of established, large-scale datasets presents great opportunities in health data science for the linkage and mining of potentially disparate resources to create new knowledge in a fast and cost-efficient manner. The number of datasets that can be queried in the field of multimorbidity is vast, ranging from national administrative and audit datasets, large clinical, technical and biological cohorts, through to more bespoke data collections made available by individual organisations and laboratories. However, with these opportunities also come technical and regulatory challenges that require an informed approach. In this review, we outline the potential benefits of using previously collected data as a vehicle for research activity. We illustrate the added value of combining potentially disparate datasets to find answers to novel questions in the field. We focus on the legal, governance and logistical considerations required to hold and analyse data acquired from disparate sources and outline some of the solutions to these challenges. We discuss the infrastructure resources required and the essential considerations in data curation and informatics management, and briefly discuss some of the analysis approaches currently used.

Confidential image transfer: an ethico-legal dilemma

Clinical photographs aid decision-making and represent important medicolegal records. Storage and transfer of images of the facial area must adhere to Caldicott Principles. Outside working hours, clinical photography services are often limited. Our Trust has introduced a Secure Clinical Image Transfer (SCIT) app allowing clinicians to take photographs on personal devices to be securely uploaded to the patient's electronic health record. To evaluate whether clinicians were taking clinical images in an insecure manner, clinicians completed an anonymous questionnaire before and after introduction of the SCIT app. The standard was 100% knowledge of, and adherence to, trust information governance guidelines. Response rate was 100% in both cycles. Introduction of the SCIT app reduced inappropriate clinical photography on personal devices. Our completed audit cycle shows that the SCIT app allows convenient, secure information capture on personal devices and automatic secure synchronisation to trust electronic health records.

Foundations of information governance for smart manufacturing

The manufacturing systems of the future will be even more dependent on data than they are today. More and more data and information are being collected and communicated throughout product development lifecycles and across manufacturing value chains. To enable smarter manufacturing operations, new equipment often includes built-in data collection capabilities. Older equipment can be retrofitted inexpensively with sensors to collect a wide variety of data. Many manufacturers are in a quandary as to what to do with increasing quantities of data. Much hype currently surrounds the use of AI to process large data sets, but manufacturers struggle to understand how AI can be applied to improve manufacturing system performance. The gap lies in the lack of good information governance practices for manufacturing. This paper defines information governance in the manufacturing context as the set of principles that allow for consistent, repeatable, and trustworthy processing and use of data. The paper identifies three foundations for good information governance that are needed in the manufacturing environment-data quality, semantic context, and system context-and reviews the surrounding and evolving body of work. The work includes a broad base of standard methods that combines to create reusable information from raw data formats. An example from an additive manufacturing case study is used to show how those detailed specifications create the governance needed to build trust in the systems.

A critique of the regulation of data science in healthcare research in the European Union

The EU offers a suitable milieu for the comparison and harmonisation of healthcare across different languages, cultures, and jurisdictions (albeit with a supranational legal framework), which could provide improvements in healthcare standards across the bloc. There are specific ethico-legal issues with the use of data in healthcare research that mandate a different approach from other forms of research. The use of healthcare data over a long period of time is similar to the use of tissue in biobanks. There is a low risk to subjects but it is impossible to gain specific informed consent given the future possibilities for research. Large amounts of data on a subject present a finite risk of re-identification. Consequently, there is a balancing act between this risk and retaining sufficient utility of the data. Anonymising methods need to take into account the circumstances of data sharing to enable an appropriate balance in all cases. There are ethical and policy advantages to exceeding the legal requirements and thereby securing the social licence for research. This process would require the examination and comparison of data protection laws across the trading bloc to produce an ethico-legal framework compatible with the requirements of all member states. Seven EU jurisdictions are given consideration in this critique.

On moving targets and magic bullets: Can the UK lead the way with responsible data linkage for health research?

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We explore key elements of good governance in health linkage.

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Adaptive reflexive governance models are essential.

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Two examples illustrate how we can achieve standardisation of practice.

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Distinct elements of governance compiled in a composite fashion tend to challenges.

Purpose

To provide an overview of essential elements of good governance of data linkage for health-related research, to consider lessons learned so far and to examine key factors currently impeding the delivery of good governance in this area. Given the considerable hurdles which must be overcome and the changing landscape of health research and data linkage, a principled, proportionate, risk-based approach to governance is advocated.

Discussion

In light of the considerable value of data linkage to health and well-being, the United Kingdom aspires to design and deliver good governance in health-related research. A string of projects have been asking: what does good governance look like in data linkage for health research? It is argued here that considerable progress can and must be made in order to develop the UK’s contribution to future health and wealth economies, particularly in light of mis-start initiatives such as care.data in NHS England. Discussion centres around lessons learned from previous successful health research initiatives, identifying those governance mechanisms which are essential to achieving good governance.

Conclusion

This article suggests that a crucial element in any step-increase of research capability will be the adoption of adaptive governance models. These must recognise a range of approaches to delivering safe and effective data linkage, while remaining responsive to public and research user expectations and needs as these shift and change with time and experience. The targets are multiple and constantly moving. There is not – nor should we seek – a single magic bullet in delivering good governance in health research.

Patient and public attitudes towards informed consent models and levels of awareness of Electronic Health Records in the UK

BACKGROUND

The development of Electronic Health Records (EHRs) forms an integral part of the information strategy for the National Health Service (NHS) in the UK, with the aim of facilitating health information exchange for patient care and secondary use, including research and healthcare planning. Implementing EHR systems requires an understanding of patient expectations for consent mechanisms and consideration of public awareness towards information sharing as might be made possible through integrated EHRs across primary and secondary health providers.

OBJECTIVES

To explore levels of public awareness about EHRs and to examine attitudes towards different consent models with respect to sharing identifiable and de-identified records for healthcare provision, research and planning.

METHODS

A cross-sectional questionnaire survey was administered to adult patients and members of the public in primary and secondary care clinics in West London, UK in 2011. In total, 5331 individuals participated in the survey, and 3157 were included in the final analysis.

RESULTS

The majority (91%) of respondents expected to be explicitly asked for consent for their identifiable records to be accessed for health provision, research or planning. Half the respondents (49%) did not expect to be asked for consent before their de-identified records were accessed. Compared with White British respondents, those from all other ethnic groups were more likely to anticipate their permission would be obtained before their de-identified records were used. Of the study population, 59% reported already being aware of EHRs before the survey. Older respondents and individuals with complex patterns of interaction with healthcare services were more likely to report prior awareness of EHRs. Individuals self-identifying as belonging to ethnic groups other than White British, and those with lower educational qualifications were less likely to report being aware of EHRs than White British respondents and respondents with degree-level education, respectively. Those who reported being aware of EHRs were less likely to say they expected explicit consent to be sought before use of their de-identified record.

CONCLUSIONS

A large number of patients remain unaware of EHRs, while preference for implicit consent is stronger among those who report previous awareness. Differences in awareness levels and consent expectations between groups with different socio-demographic characteristics suggest that public education and information campaigns should target specific groups to increase public awareness and ensure meaningful informed consent mechanisms.

Disaster easily averted? Data confidentiality and the hospital desktop computer

OBJECTIVE

We specifically identified the hospital desktop computer as a potential source of breaches in confidentiality. We aimed to evaluate if there was accessible, unprotected, confidential information stored on the desktop screen on computers in a district general hospital and if so, how a teaching intervention could improve this situation.

DESIGN

An unannounced spot check of 59 ward computers was performed. Data were collected regarding how many had confidential information stored on the desktop screen without any password protection. An online learning module was mandated for healthcare staff and a second cycle of inspection performed.

SETTING

A district general hospital.

PARTICIPANTS

Two doctors conducted the audit. Computers in clinical areas were assessed. All clinical staff with computer access underwent the online learning module.

INTERVENTION

An online learning module regarding data protection and confidentiality.

RESULTS

In the first cycle, 55% of ward computers had easily accessible patient or staff confidential information stored on their desktop screen. This included handovers, referral letters, staff sick leave lists, audits and nursing reports. The majority (85%) of computers accessed were logged in under a generic username and password. The intervention produced an improvement in the second cycle findings with only 26% of computers being found to have unprotected confidential information stored on them.

CONCLUSIONS

The failure to comply with appropriate confidential data protection regulations is a persistent problem. Education produces some improvement but we also propose a systemic approach to solving this problem.

Delivering proportionate governance in the era of eHealth: Making linkage and privacy work together

This article advances a principled proportionate governance model (PPGM) that overcomes key impediments to using health records for research. Despite increasing initiatives for maximising benefits of data linkage, significant challenges remain, including a culture of caution around data sharing and linkage, failure to make use of flexibilities within the law and failure to incorporate intelligent iterative design. The article identifies key issues for consideration and posits a flexible and accessible governance model that provides a robust and efficient means of paying due regard to both privacy and the public interests in research. We argue that proportionate governance based on clear guiding principles accurately gauges risks associated with data uses and assigns safeguards accordingly. This requires a clear articulation of roles and responsibilities at all levels of decision-making and effective training for researchers and data custodians. Accordingly, the PPGM encourages and supports defensible judgements about data linkage in the public interest.