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Nowadays, the Internet of Things (IoT) is used in every domain, especially in the healthcare system it plays a very important role in our life and made our life easier by providing various facilities in every area. On the Internet of Medical Things (IoMT), IoT devices collect real-time data from patients and send it to the cloud through the Internet. These gathered data are extorted to centralized processing and computational power. Centralization can lead to a single point of failure, data modification, snooping, security, and privacy evasion. Blockchain can resolve such issues by providing decentralized computational power and better storage capacity for IoT data. Therefore, integrating IoT and blockchain technologies can be an intelligent way to implement a decentralized IoT-based smart healthcare system. We find that integration of the blockchain and IoT is persuasive and can cause remarkable transformations across the healthcare system. We discussed blockchain and its applicability in the healthcare industry. The paper explores blockchain's dimensions, making the innovative healthcare system more secure and stable. We provide a comparative analysis of well-known recent research on IoT-based smart healthcare system security using blockchain based on different parameters such as architecture, data integrity, medical information sharing, distributed electronic health records, patient encryption key, access control, hardware implementation, etc. The paper focuses on the current security issues in IoT-based smart healthcare systems, architectures, taxonomy, and research gap and their possible solutions we point out various research challenges that should be considered before the deployment of a blockchain network in an IoT setting. This paper will be helpful to new researchers to get an overview of IoT-based healthcare system security. [ABSTRACT FROM AUTHOR]

Interoperability plays a crucial role in facilitating seamless data sharing across system boundaries, necessitating collaborative efforts among multiple systems. To achieve this, the presence of a common reference model for data exchange and dedicated interfaces is essential. However, the current state of Health Information Systems (HIS) often falls short in providing effective design elements that enable smooth and continuous data exchange across diverse domains. To address this challenge, a comprehensive investigation of the technical, syntactic, semantic, and other important aspects of interoperability interfaces is necessary, both in theory and practice. This article aims to address the design challenges associated with interoperability interfaces in Electronic Medical Record (EMR) systems. We commence by establishing theoretical guidelines that serve as foundation for designing effective interfaces. These guidelines encompass key considerations for the usability of interoperability interfaces, such as importing and exporting data of EMRs. Building upon this theoretical framework, we evaluate the interoperability interfaces within OpenMRS, a widely used EMR system. By aligning the evaluations with the established theoretical guidelines, we propose a set of generic interoperability interfaces designed to enhance the seamless exchange of data across different domains. To assess their usability, we employ a predictive usability inspection, providing valuable insights into the practical aspects of these interfaces. Through this research, we aim to contribute to the improvement of interoperability interfaces in EMR systems, bridging the gap between theoretical guidelines and practical implementation. By addressing the design challenges, conducting evaluations, and proposing interoperability interfaces, we strive to enhance data exchange design and promote a more integrated and collaborative healthcare system. [ABSTRACT FROM AUTHOR]

Electronics-Health Care is one of the new ideas in the healthcare industry. For analyzing the patient's records, doctors need a centralized record of the patients, which gives useful and enormous information. There will be a threat of leaking of confidential e-health data, which will seriously endanger by modifying the health care data of medical and its individual entities. Protection of the confidential data of patients will be a primary constraint in the health care industry. There is a lot of progressiveness in the human services area as well as there is a lot of usage of the information gathered from various sensors and this information is stored in the cloud. As per the existing security algorithms, there is still some security breach and also it won't get satisfied with integrity and consistency while transferring the data from one vendor to others in the health care system. It also causes high spoofing of IP and side channel hackers. With the increase in the use of the internet, there is an increase in hacking also, especially in the health-care sector, e-commerce, military, and Education. Dealing with the huge volume of information in the electronics-healthcare area requires the processing of patient's information day by day and its memory allocation. Cloud is the best option to store these health records in a distributed manner rather than on a single server. So, whatever the information gathered from it will be encoded on block chain technology and an anonymous digital ring signature will be used to authorize the intended user and maintain the privacy of patient cloud-based data distributed Electronics health record system before sending the information to the cloud storage. In this paper, the protection of Personal data of the patient health data is enhanced with block chain and anonymous ring signatures in the e-healthcare cloud; thus making it suitable for real-time applications. [ABSTRACT FROM AUTHOR]

As healthcare data is extremely sensitive, it poses a risk of invading individuals' privacy if stored or exported without proper security measures. De-identification entails pseudonymization or anonymization of data, which are methods for temporarily or permanently removing an individual's identity. These methods are most suitable to keep user healthcare data private. Inference attacks are a commonly overlooked weakness of de-identification techniques. In this paper, I discuss a method for de-identifying Electronic Healthcare Records (EHR) using chained hashing to generate short-lived pseudonyms to reduce the impact of inference attacks, as well as a mechanism for re-identification based on information self-determination. It also removes the weaknesses of existing de-identification algorithms and resolve them by using appropriate real-time de-identification algorithm, Ephemeral Pseudonym Generation Algorithm (EPGA). [ABSTRACT FROM AUTHOR]

Unmeasured confounding undermines the validity of observational studies. Although randomized clinical trials (RCTs) are considered the "gold standard" of study types, we often observe divergent findings between RCTs and empirical settings. We present the "L-table", a simulation-based, prior knowledge (e.g., RCTs) guided approach that estimates the true effect adjusting for the potential influence of unmeasured confounders when using observational data. Using electronic health record data from Kaiser Permanente Southern California, we compare the effectiveness of coronary artery bypass grafting (CABG) and percutaneous coronary intervention (PCI) on endpoints at 1, 3, 5, and 10 years for patients with stable ischemic heart disease. We applied the L-table approach to the propensity score adjusted cohort to derive the omitted-confounder-adjusted estimated effects. After the L-table adjustment, CABG patients are 57.6% less likely to encounter major adverse cardiac and cerebrovascular event (MACCE) at 1 year (OR [95% CI] 0.424 [0.396, 0.517]), 56.4% less likely at 3 years (OR [95% CI] 0.436 [0.369, 0.527]), and 48.9% less likely at 5 years (OR [95% CI] 0.511 [0.451, 0.538]). CABG patients are also 49.5% less likely to die by the end of 10 years than PCI patients (OR [95% CI] 0.505 [0.446, 0.582]). We found the estimated true effects all shifted towards CABG as a more effective procedure that led to better health outcomes compared to PCI. Unlike existing sensitivity tools, the L-table approach explicitly lays out probable values and can therefore better support clinical decision-making. We recommend using L-table as a supplement to available techniques of sensitivity analysis. [ABSTRACT FROM AUTHOR]

Industry 4.0 has ushered in a new era in the manufacturing industry. Healthcare delivery, like manufacturing, is on the verge of a fundamental shift into the new era of smart and connected health care, termed Health Care 4.0. Sharing healthcare data is an important step in improving the healthcare system's intelligence and service quality. Healthcare data, which is a personal asset of the patient, should be owned and managed by the patient rather than being dispersed among several healthcare systems, preventing data exchange and jeopardizing patient privacy. Electronic Health Records (EHRs) assist individuals by allowing them to combine and manage their medical data. On the other hand, today's EHR systems fall short of providing patients with traceable, trustworthy, and secure ownership over their medical data, creating serious security risks. Furthermore, the most of present EHR techniques and systems are centralized, making it difficult to share medical data and increasing the danger of a single point of failure. Blockchain technology can enable dependable, transparent, and auditable computing in the healthcare industry by utilizing a decentralized network of peers and a public ledger. In this article, we propose Patient-Controlled Blockchain Enabled Electronic Health Records as a way for patients to have safe control over their data that is decentralized, immutable, transparent, traceable, and trustworthy. Decentralized Interplanetary file storage is used in the suggested technique. Two main performance criteria are used to evaluate the suggested solutions: cost and accuracy. [ABSTRACT FROM AUTHOR]