Data Protection Requirements Research Articles

Record linkage as a vital key player for the COVID-19 syndemic

Abstract Chronicity, comorbidities, and social context influence COVID-19 risk and prognosis, drawing attention to a syndemic dimension. We discuss how linking routinely collected data and data collected through observational population-based cohorts can contribute to advance knowledge on the association between COVID-19 and chronic diseases and social indicators. Record linkage as a multidimensional tool may ultimately enable defining and optimizing of integrated strategies, which may create multilevel public health measures to foster solidarity on health in all policies when ethical and legal barriers under prerequisite data protection and privacy can be overcome. Legal discrepancies have been proving detrimental to research in member states, including those which already had established a margin for research for the common good without explicit consent. We hence call for further harmonization of data protection requirements for scientific research activities in the EU/EEA, focusing in particular on health-related research. A proposed framework demonstrates the role of record linkage as a trailblazing key player in research optimization due to its multidimensional possibilities calling for harmonization. Key messages • Further harmonization of data protection requirements for scientific research may create multilevel public health measures. • As a multidimensional tool, it optimizes integrated strategies and fosters solidarity on Health in All Policies (HiAP).

Communication-Efficient Wireless Traffic Prediction with Federated Learning

Wireless traffic prediction is essential to developing intelligent communication networks that facilitate efficient resource allocation. Along this line, decentralized wireless traffic prediction under the paradigm of federated learning is becoming increasingly significant. Compared to traditional centralized learning, federated learning satisfies network operators’ requirements for sensitive data protection and reduces the consumption of network resources. In this paper, we propose a novel communication-efficient federated learning framework, named FedCE, by developing a gradient compression scheme and an adaptive aggregation strategy for wireless traffic prediction. FedCE achieves gradient compression through top-K sparsification and can largely relieve the communication burdens between local clients and the central server, making it communication-efficient. An adaptive aggregation strategy is designed by quantifying the different contributions of local models to the global model, making FedCE aware of spatial dependencies among various local clients. We validate the effectiveness of FedCE on two real-world datasets. The results demonstrate that FedCE can improve prediction accuracy by approximately 27% with only 20% of communications in the baseline method.

Mechanisms of interaction between banking institutions and aviation enterprises

It is shown that the main mechanisms of interaction between banks and aviation enterprises are: loans, leasing, collateral financing, risk hedging, project financing, financial consultations and services, factoring, guarantees and insurance. The global aerospace market has been proven to have significant growth potential due to an increase in global GDP, growth in global air traffic and record numbers of new aircraft orders. Innovation, efficiency gains and the development of new markets contribute to the sector's long-term positive outlook. It is shown that the aviation industry is subject to strict regulation at the national and international levels, including requirements for safety, ecology, product quality, data protection and many other aspects. Failure to comply with these requirements can result in serious legal consequences, financial loss and reputational damage. Long supply chains have been found to be an integral part of the aviation industry, ensuring the supply of components and materials for aircraft manufacturing. They have their own advantages and challenges that require effective management and coordination. The use of modern technologies, the development of partnership relations and strategic risk management contribute to increasing the efficiency and sustainability of these chains. It has been determined that the management of the risks of execution of key contracts is extremely important for aviation enterprises. Implementation of effective risk management strategies helps reduce the possibility of problems, ensure timely and high-quality fulfillment of obligations to customers, as well as maintain financial stability and competitiveness in the market. It has been proven that the interaction of banks and aviation companies brings numerous advantages to both parties. Aviation enterprises get access to the necessary financing, risk management and consulting services, which contributes to their development and increased efficiency. Banks, in turn, expand their customer base, increase profitability, develop new products and strengthen their reputation. Such cooperation is an important component of the success of both the aviation industry and the banking sector.

Regulating data: Evidence from corporate America

AbstractUsing the enforcement of the General Data Protection Regulation (GDPR) as our empirical setting, we examine how stricter data privacy and data protection requirements affect shareholder wealth, firms’ investment decisions, and data breaches. Consistent with consumer privacy negatively affecting firms, we find that U.S. firms exposed to the GDPR lose 0.7%–1.1% in market value relative to unexposed firms in the week in which the regulation became enforceable. We find that the decrease in market value is partially attributable to a decrease in sales growth. GDPR‐exposed firms increase their investment above that of control firms and become less likely to report a data breach post‐regulation. The decrease in data breach likelihood is statistically and economically significant, resulting in up to 34 million records not being leaked, which costs between $205 million and $561 million to firms in breach mitigation expenses per year. The results of this study should be of interest to academics and regulators worldwide by examining the costs and benefits of regulating data.

Understanding the GDPR from a requirements engineering perspective—a systematic mapping study on regulatory data protection requirements

AbstractData protection compliance is critical from a requirements engineering (RE) perspective, both from a software development lifecycle (SDLC) perspective and regulatory compliance. Not including these requirements from the early phases of the SDLC can prove costly and challenging afterward. The general data protection regulation (GDPR) from the European Union (EU) sets a list of requirements that organizations working within its scope should satisfy. However, these requirements are complex to work with, as legal prose tends to be vague and imprecise, and not all requirements have received the same attention from researchers. This study aims to identify the research published in RE for helping compliance with regulatory data protection requirements. We gathered and analyzed 90 articles from 2016 to 2022 through a systematic mapping study. We analyzed key trends in the sample, such as year of publication, publication venue, type of research, interdisciplinarity in the author’s background, GDPR focus of compliance element, and type of proposal. Our main findings show ongoing interest, mostly published in conferences, in achieving overall compliance with the GDPR and consent as the most popular topics. Other topics, such as cookies or children’s data, did not receive significant attention. Research over the whole RE process has been done. 20 (22%) of the papers have authors affiliated with non-computer science; however, most research seems not interdisciplinary. We finally discuss gaps in the literature, possible future areas of research, and the importance of interdisciplinary research for regulatory data protection requirements in RE.

Data sovereignty and security in network engineering: A conceptual framework for compliance

Data sovereignty and security are critical issues in network engineering, particularly in an era of increasing data breaches and regulatory scrutiny. This concept paper presents a conceptual framework for understanding and ensuring compliance with data sovereignty and security requirements in network engineering. The framework begins by defining data sovereignty and security in the context of network engineering, highlighting the importance of protecting data from unauthorized access and ensuring that it is stored and processed in compliance with applicable laws and regulations. Next, the framework explores key concepts and principles related to data sovereignty and security, such as data localization, encryption, and access control. It also discusses the role of international agreements and standards in shaping data sovereignty and security requirements. The framework then guides how organizations can implement measures to protect data sovereignty and security in their network engineering practices. This includes conducting risk assessments, implementing appropriate security controls, and ensuring compliance with relevant laws and regulations. Finally, the framework outlines future trends and challenges in data sovereignty and security, such as the impact of emerging technologies like 5G and the Internet of Things (IoT) on data protection requirements. Overall, this concept paper provides a comprehensive overview of data sovereignty and security in network engineering, offering practical guidance for organizations seeking to protect their data and comply with relevant laws and regulations.

Метод і засоби вибору сервісів тестування на проникнення

The methods of assessing the security of information systems (IS) with the help of special means of penetration testing (PT) and services that provide the corresponding tools (Penetration Testing as a Service, PTaaS) are analyzed. The indicators to compare PTaaS tools and services are substantiated, namely: provision of a report on compliance of the tested product with data protection requirements, availability of security certificates, use of appropriate testing methodologies, etc. A method has been developed for selecting a PTaaS service according to the customer’s requirements to increase IS cyber security by improving the completeness and reliability of penetration testing, as well as reducing the search time for PT tools. A cloud service is proposed that supports the implementation of the method and provides the option of choosing PTaaS. It was determined that the use of the proposed method and service enables users to quickly and conveniently choose PTaaS according to the requirements and work model of organizations or digital products.

Enforcement of data breaches in the Dutch and British healthcare sector: a contribution to clarifying requirements of data protection by design?

ABSTRACT Within the healthcare sector, highly sensitive personal data, including data concerning health, is processed. The careless handling of such data can have a significant impact on the fundamental rights and freedoms of natural persons. It is central that data protection principles, including data protection by design, are followed by the healthcare sector. When these requirements are not met, it is crucial that enforcement action is taken to prevent personal data breaches. This article compares the enforcement carried out in the Netherlands and in the UK for breaches in the healthcare sector of the General Data Protection Regulation and the UK Data Protection Act 2018. The author reflects on whether more effective enforcement measures would lead to healthcare developments that are compliant with the data protection by design obligation (Article 25 of the GDPR). It is argued that in turn,compliance with this obligation can prevent personal data breaches and data protection complaints, rendering enforcement, and consequently recovery, superfluous.

Application of the screening method for estimating COVID-19 vaccine effectiveness using routine surveillance data: Germany's experience during the COVID-19 pandemic, July 2021 to March 2023.

The screening method represents a simple, quick, and practical tool for estimating vaccine effectiveness (VE) using routine disease surveillance and vaccine coverage data, even if these data cannot be linked. In Germany, where notification data, laboratory testing data, and vaccine coverage data cannot be linked due to strict data protection requirements, the screening method was used to assess COVID-19 VE continuously between July 2021 and March 2023. During this period, when Delta and Omicron variants circulated, VE estimates were produced in real-time for different age groups and clinical outcomes. Here we describe the country's overall positive experience using the screening method, including its strengths and limitations, and provide practical guidance regarding a few issues, such as case definition stringency, testing behaviour, and data stratification, that require careful consideration during data analysis and the interpretation of the results.

P20 Clinical metagenomics from cell-free DNA: overview and lessons learned from 4 years as a clinical metagenomics provider

Abstract Background Clinical metagenomics emerges more and more from academic research to clinical practice. Here, we share an overview of the field of clinical metagenomics on cell-free DNA found in the blood of patients with severe infections and share a few learning points regarding the implementation as a routine lab service and CE-IVD marked software running in the cloud. Methods We use next-generation sequencing of cell-free DNA to digitally determine relevant pathogens from patients with systemic infections in blood and other bodily fluids using our CE-IVD marked DISQVER diagnostic platform. Until now we have collected microbial data from several thousand samples within 4 years of routine service. Results The set up of the DISQVER test is within the regulatory framework of CE-IVD marking of software as a service (SaaS) and ISO 13485 accreditation. This brings practical implications on database quality, software lock-in/development/testing, change and risk management, technical documentation, requiring substantial resources. Also the wetlab process runs within tightly defined and controlled QM boundaries, pre-set by extensive analytical validations. We clinically validated our test for pathogen identification from blood within 8 clinical trials for intensive care medicine, haematology and coinfection in COVID-19, showing 2- to 3-fold higher identification rates for pathogens in comparison to standard of care blood culture. Furthermore, several case reports/ case series from different clinical backgrounds, frequently with difficult to diagnose pathogens, have been published. From the analysis of our routine processes with several thousand samples, we could show that the turn-around time of our mNGS process is very fast and can detect more species than blood culture. In particular, the relatively high proportion of fungi and dsDNA viruses indicates superiority of the method compared with the standard diagnostic pathway. Conclusions To bridge the gap between academic research and clinical implementation, many aspects of regulatory, technical and data protection requirements need to be addressed. Within the timeframe of commercial availability DISQVER from cell-free DNA found in the blood of infected patients is increasingly becoming a useful tool for infection diagnostics.

Використання блокчейну першого рівня LTO Network для автоматизації міжорганізаційних бізнес-процесів

The article is devoted to the consideration of blockchain technology as a means of automating inter-organizational business processes. It is noted that the digitalization and automation of internal business processes bring significant benefits in terms of increasing productivity and reducing costs. However, organizations face difficulties when trying to obtain such benefits for inter-organizational processes, partly due to a lack of trust. This paper considers a blockchain approach to address this problem. Bitcoin has demonstrated how blockchain can provide a distributed system without the need for trust through cryptography and decentralization. LTO extends this approach with a decentralized workflow engine for ad-hoc collaboration. Information is exchanged between participants through private event chains for each process and hashed on a public blockchain. This hybrid approach allows organizations to comply with data protection requirements and avoid scalability issues typical of blockchain projects. The advantages of LTO live contracts over Ethereum smart contracts are discussed. Live contracts do not contain values directly, but describe the interaction between the parties, unlike the cryptographic "boxes" of smart contracts. Modeling live contracts as finite state machines allows visualizing them in the form of a flowchart. Alternative modeling techniques such as Petri nets and BPMN are discussed. The article describes a scenario-based approach to defining a workflow containing states, actions, participants, assets, and embedded data objects. The features of data objects, participant identifiers, process execution and its adaptability are detailed. The author explains the operation of a private event chain as an ad-hoc private blockchain that ensures the consistency of the process state between nodes. Methods of ensuring data privacy are discussed. The second part of the article is devoted to the global public blockchain LTO to confirm information from private event chains. The consensus algorithm is explained based on the importance of token ownership and its use to prevent abuse. Optimizations, such as the NG protocol and aggregation blocks, are discussed to scale with a large number of transactions. The last part describes the architecture of the platform and its components: microservices, application layers, container orchestration. The platform makes it easy to digitalize and automate inter-organizational interactions using live contracts on the blockchain.

Effectiveness of Homeopathic Medicine in Canine Urinary Incontinence: Outcomes of Owner Response Survey

With advances in data collection via electronic surveys, they have become a popular tool for researchers especially with the changes in normalcy caused by the Coronavirus pandemic. During this pandemic period, previously collected traditional format paper data on Homeopet ™ ‘Leaks No More’ was collated, analysed, written up, reviewed, and published Farrington TJ and Smith . The current study was again an owner response survey like the previous studies but done electronically. In the case of this Homeopet™ 'Leaks No More' survey, the selection criteria used to identify eligible participants who had purchased the product directly from the manufacturer's website helped to ensure that the responses collected were from genuine product users including first time and repeat users. This helped to eliminate potential bias in the responses and ensured that the data collected was of high quality. It ensured elimination of spurious responses and replies from unverified users. The use of gratuities only to those who agreed to provide fully completed surveys containing a true assessment of their pets' responses with an email and other contact details including agreement to be contacted helped to improve the response rate and quality of data collected. In fact the normal verifying of email addresses and names of respondents was turned off for data protection requirements after collection before sending data to analyst and authors removing only from them ability to cross-reference to an original mail shot offering the survey to people who had joined the mailing list on Homeopets own sales site, the researchers were after completion of the paper able to ensure that the data collected was authentic and reliable without exposing any personal data for the participants from the survey collection while still ensuring it was verifiable. Despite striving to write the survey questionnaire in a balanced inclusive way so that it would resonate with a wide range of perspectives and viewpoints across a broad range of views, one can assume that those who filled it out were more likely to have been open to complementary medicine or to have a pet who had failed to respond or responded poorly to conventional therapy. It also meant that emails and names could be verified and if necessary, through the email DNS, and thus could be contacted to complete any missing data needed, which thanks to response numbers was not necessary so the data remained completely confidential. As Homeopet ™ ‘Leaks No More’ is an OTC (Over the Counter) retail product which during the pandemic sold primarily online through various online retailers due to the restricted access to bricks and mortar retailers, shops, and stores there was little or no direct access to or contact with the end users and thus the electronic survey proved highly effective in that environment. Overall, electronic surveys have proven to be a more successful and time-efficient way of collecting data compared to traditional methods as shown in this research paper. The high-quality data collected in this study will be valuable for future research and product development in the field of complementary medicine for pets. Methods and Outcomes: An online questionnaire template was developed using questionnaires from the previous studies and he decision was to use SurveyMonkey® as the mode of delivery to participants. Homeopet™ LLC employed an independent consultant to design and develop the front end for owner response input and the back end for data collection. Ms Jenny Doran Halcyon Days Ltd. worked with Dr Farrington and his team, some external individuals unfamiliar with the project (to ensure the public would understand the questionnaire fully), including staff at Homeopet familiar with the process, to test prototype versions of the SurveyMonkey® and tailor them to the projects requirements till the entire team came to a consensus acceptable to Homeopet™ in the time constraints available. The survey was then made available online with an invitation to participate added to the purchase process on the manufacturer’s website. Other online outlets were considered but were not open to the authors having access to their customer information even for verification purposes. This outlet area is being worked on for future surveys.

Data Privacy Practices of Private Higher Education Institutions in Malaysia: A Preliminary Study

Private higher education institutions as data users are subjected to the requirements of the Personal Data Protection Act 2010 (PDPA). These institutions process employee data as well as data of potential students, active students and alumni. They also deal with data of third parties such as vendors, visitors and contractors. Ten years after the coming into effect of the PDPA in 2013, the education sector has yet to develop their personal data protection code of practice as required by the Act. The General Code of Practice (CoP) of Personal Data Protection was introduced in December 2022 with the objective to provide guidelines to the Class of Data Users who have not prepared a Code of Practice and there is no data user forum to develop the relevant Code of Practice for the Class of Data Users. As the General CoP is legally binding, it is an offence punishable under the Act for any data user for failure to comply with any provision of this General CoP. As data users, private higher education institutions need to introduce certain mechanisms to adhere to the requirements such as privacy policy and procedure. This paper aims to compare the data privacy practices of private higher education institutions in Malaysia in order to determine to what extent the law has been complied with. Being a qualitative study, this paper applies content analysis technique. Data privacy policies of four private higher education institutions in Malaysia were examined to attain the objective. The four private higher education institutions are Universiti Tenaga Nasional (UNITEN), Universiti Teknologi PETRONAS (UTP), Taylor’s University and University of Nottingham Malaysia. The data privacy policies of the four institutions are accessible on the official website of the institutions. The study indicates that in the absence of a personal data protection code of practice for the education sector as a guideline, the data privacy practices of the institutions vary from one to another. While some of the privacy policies contain provisions which are general in nature which may lead to confusion to the data subjects, the data privacy policies show that the four institutions have, to a certain extent, complied with the requirements of the PDPA in general.

Creeping Road Traffic Surveillance in Latvia: Social and Legal Implications of Digital Policing Tools

This article critically analyses road traffic surveillance and its social and legal implications, with a focus on the use of digital tools in policing, namely: speed cameras, drones, and a police mobile application in Latvia. Specifically, the article explores: (1) the attributed role of these surveillance tools in terms of caring, preventive, and punitive functions and the potential for function creep and (2) the key challenges these tools pose to fundamental rights and data protection. Thus, it contributes to academic and public debate around the consequences of digital surveillance and embedding democratic governance in policing. The research is based on an exploratory case study that includes analysis of expert interviews, media coverage, the legal framework, and a focus group with traffic participants. We argue that, while the use of these surveillance tools is construed as an example of benevolent and caring surveillance aimed at improving road safety in a preventive manner, it is reliant upon a pronounced punitive dimension that in itself may not be conducive to behavioural change. At the same time, the increasing deployment of all of these tools may lead to function creep and raises challenges for fundamental rights and data protection. While efforts have been made to ensure legitimate use of these tools, not enough attention has been paid to their compliance with data protection requirements. Moreover, there is a need to improve the regulatory framework regarding police use of new surveillance tools, such as drones, which would determine the purposes of such uses and set an obligation to evaluate their effectiveness, impact, and proportionality in order to comply with fundamental rights law and ensure their trustworthy use.

Encrypted federated learning for secure decentralized collaboration in cancer image analysis

Artificial intelligence (AI) has a multitude of applications in cancer research and oncology. However, the training of AI systems is impeded by the limited availability of large datasets due to data protection requirements and other regulatory obstacles. Federated and swarm learning represent possible solutions to this problem by collaboratively training AI models while avoiding data transfer. However, in these decentralized methods, weight updates are still transferred to the aggregation server for merging the models. This leaves the possibility for a breach of data privacy, for example by model inversion or membership inference attacks by untrusted servers. Somewhat-homomorphically-encrypted federated learning (SHEFL) is a solution to this problem because only encrypted weights are transferred, and model updates are performed in the encrypted space. Here, we demonstrate the first successful implementation of SHEFL in a range of clinically relevant tasks in cancer image analysis on multicentric datasets in radiology and histopathology. We show that SHEFL enables the training of AI models which outperform locally trained models and perform on par with models which are centrally trained. In the future, SHEFL can enable multiple institutions to co-train AI models without forsaking data governance and without ever transmitting any decryptable data to untrusted servers.

A Study on Data Protection in Cloud Environment

Data protection in the online environment pertains to the safeguarding of sensitive or important data kept, analyzed, or sent in cloud-based systems. It entails assuring data confidentiality, integrity, and availability, as well as adhering to appropriate data protection requirements. In a nutshell, cloud data protection seeks to protect data against unauthorized access, deletion, or breaches while retaining its accuracy and accessible to authorized users. This is accomplished in the cloud environment using various security measures, encryption approaches, access controls, disaster recovery and backup processes, and constant monitoring and threat detection. The research significance of data protection in the cloud environment can be summarized as follows: Security and Privacy: Research in data protection in the cloud helps address the security and privacy concerns associated with storing and processing sensitive data in cloud-based systems. It explores and develops advanced security mechanisms, encryption techniques, and access controls to protect data from unauthorized access, data breaches, and privacy violations. Trust and Confidence: Research in data protection contributes to building trust and confidence in cloud computing. By developing robust security solutions and demonstrating their effectiveness, research helps alleviate concerns about data security and privacy, fostering greater adoption of cloud services by organizations and individuals. Compliance and Regulations: Cloud computing often involves compliance with data protection regulations and industry standards. Research in this area explores the legal and regulatory aspects of data protection in the cloud and helps organizations understand and comply with relevant requirements. Data Resilience and Recovery: Research in data protection focuses on ensuring data resilience and developing efficient data recovery mechanisms in the cloud. It explores backup and disaster recovery strategies, data replication techniques, and data loss prevention methods to minimize downtime, recover data promptly, and maintain business continuity in the event of system failures or disasters. By addressing these research areas, studies on data protection in the cloud environment contribute to enhancing security, privacy, compliance, and resilience in cloud computing. They provide valuable insights, practical solutions, and guidelines for organizations and service providers to protect data effectively and maintain the trust of users in cloud-based services. The weighted product method approach is commonly used to choose the best data protection in cloud environment. CCSS1, CCSS2, CCSS3, CCSS4, CCSS5 data visibility, data integrity, Maintains compliance, Data security, Data storage. From the result it is seen that CCSS2 got highest rank whereas CCSS5 got lowest rank According to the results, CCSS2 was ranked first.

Criminalization of failure to comply with personal data protection requirements

Subject of research: personal data as the subject of a socially dangerous act.
 Purpose of research: to justify the need to include in the Criminal Code of Russia (hereinafter referred to as the Criminal Code of the Russian Federation) a rule on liability for failure to comply with requirements for the protection of personal data.
 Methods and objects of research: in the preparation of this work, inductive and deductive methods of formal logic, the dialectical method of cognition, and the method of comparative analysis were used, incl. content analysis of current sources of Russian and foreign law, as well as a method of expert assessments on issues of the public danger of illegal acts in the field of circulation of personal data.
 Main results of research: it has been proven that the digital transformation of the economy has a significant impact on all relationships in modern society. Therefore, the value of information about a person increases significantly. It becomes a means for using various services, incl. ensuring the exchange of material and other values. Taking into account this circumstance, the protection of personal data must be ensured not only by civil and administrative, but also by criminal legislation. This requires the introduction of criminal liability for failure to comply with requirements for the protection of personal data.

Adherence to interdisciplinary tumor board recommendations as an expression of quality-assured patient care: results of a bicentric German analysis

PurposeInterdisciplinary tumor boards (ITBs) represent a central part of standard cancer care defining a guidelines-guided treatment plan adapted to the patient’s capabilities, comorbidities and wishes in a multi-professional team. The implementation rate of ITB recommendations can be monitored by structured adherence analyses. But (inter)national definitions how to measure the level of implementation are missing. Here, we present results of 4 years of ITB adherence analyses in a bicentric German Comprehensive Cancer Center (CCC).MethodsBetween 2018 and 2021, for at least 1 month, the implementation rate of recommendations of 8 different ITBs of 2 CCC sites was evaluated manually according to harmonized criteria between both sites regarding the degree of implementation of ITB’s recommendations.ResultsIn total, 1104 cases were analyzed (65% male, 35% female). Mean distance from patient’s home to the CCC was 57 km (range 0.8–560.6 km). For 949 cases (86%) with known follow-up, the adherence rate was 91.9% (95% CI 0.9; 0.935). In 8.1%, ITB decisions were not implemented due to medical reasons (45.4%), patient’s wish (35.1%) and unknown reasons (19.5%). Logistic regression revealed neither age (OR = 0.998, p = 0.90), nor gender (OR = 0.98, p = 0.92) or the distance from patient’s home to the CCC (OR = 1.001, p = 0.54) were significantly associated with ITB adherence.ConclusionITB adherences analyses can serve as a quality management tool to monitor the implementation rate of ITB recommendations and to stay in contact with practitioners, other hospitals and state cancer registries to share data and resources in accordance with data protection requirements for continuously improvement of quality management and patient care.

A Cloud-Edge Computing Method for Integrated Electricity-Gas System Dispatch

An integrated electric–gas system (IEGS) is the manifestation and development direction of a modern smart power system. This paper employs the cloud-edge computing method to research IEGS’s optimal dispatch to satisfy data protection requirements between power systems and natural gas systems and reduce data transmission pressure. Based on cloud-edge computing architecture, this paper constructs a cloud-edge computing method based on the Multi-agent Deep Deterministic Policy Gradient (MADDPG) algorithm to solve optimal dispatch problems. Then, this paper proposes an IEGS dispatch strategy based on cloud-edge computing, which conducts distributed computing independently at the edge of power and natural gas, and the cloud implements global dispatch based on boundary information and edge learning parameters. This method does not require the exchange of all information between the power system and natural gas system, effectively protecting data privacy. This paper takes the improved IEGS of the IEEE 9 node and Gas 8 node as an example to analyze. The equipment output of this dispatch method is within a reasonable range, and the cost is reduced by 0.21% to 1.03% compared with other methods, which verifies the effectiveness of the cloud-edge computing method in solving dispatch problems.

Reimagining Patient Data Access for Researchers

ObjectivesWidespread use of electronic health records (EHRs) now makes it feasible to expand beyond health insurance claims data to include full EHR data for health economics and outcomes research (HEOR) studies. We seek to develop ways to maximize researcher access to such data while strongly protecting patients’ privacy rights. MethodsWe analyzed alternative organizational structures and intellectual property rights assignments as they now exist and compared these with structures and intellectual property rights assignments that would maximize access to data for HEOR studies and minimize transactions costs. We analyzed data protection requirements and financial incentives at 3 levels: patient decision making, patients’ data aggregators, and final aggregation across patients’ data. ResultsCreating new HEOR data systems requires new organizations and funding, while also protecting patients’ data privacy rights. The Cures Act enables a new market for trusted third parties (TTPs) to aggregate patients’ data. New secondary data aggregators must combine individuals’ aggregated EHRs into usable HEOR databases. Maximal patient participation requires complete health insurance coverage of costs that healthcare providers charge for transmitting patients’ data to TTPs. The new secondary system to aggregate data from many TTPs into usable HEOR optimally has external funding. ConclusionsImportant steps remain uncompleted to achieve maximally available HEOR data while protecting patients’ privacy rights. HEOR information is a public good, so private incentives to support creation and operation of this new system remain incomplete. Public and private support can expand this system to optimally improve people’s health.