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This article addresses the privacy of medical and health data in the US. It analyzes the scope and requirements of federal and state laws in the US, and it discusses the weaknesses in the US protection of medical privacy. Then, this article explains how the weak US system of privacy protection was unable to handle many important privacy issues in the COVID-19 pandemic. Finally, the article concludes with some recommendations for action.

Healthcare data are arguably the most private of personal data. This very private information in the wrong hands can lead to identity theft, prescription fraud, insurance fraud, and an array of other crimes. Electronic-health systems such as My Health Record in Australia holds great promise in sharing medical data and improving healthcare quality. But, a key privacy issue in these systems is the misuse of healthcare data by “authorities.” The recent General Data Protection Regulation (GDPR) introduced in the EU aims to reduce personal-data misuse. But, there are no tools currently available to accurately reconcile a domestic E-health policy against the GDPR to identify discrepancies. Reconciling privacy policies is also non-trivial, because policies are often written in free text, making them subject to human interpretation. In this article, we propose a tool that allows the description of E-health privacy policies, represents them using formal constructs making the policies precise and explicit. Using this formal framework, our tool can automatically reconcile a domestic E-health policy against the GDPR to identify violations and omissions. We use our prototype to illustrate several critical flaws in Australia’s My Health Record policy, including a non-compliance with GDPR that allows healthcare providers to access medical records by default.

The obligation of physicians and other health professionals under Art. 240 § 1 of the Criminal Code instructs them to notify the law enforcement authority responsible for prosecuting crimes (in particular the Police or public prosecutor’s office) when prohibited acts are committed, attempted, or prepared. The list of such acts is enumerative, indicating the numbers of the relevant articles and paragraphs. On 13th July 2017 Art. 156 of the Criminal Code extended the list, adding grievous bodily harm as a prohibited act. Accordingly, this act introduced the legal obligation of denunciation, which outweighs medical privacy in such situations. As it can be difficult for a clinician to identify which injuries meet the criteria of grievous bodily harm, the authors of the paper have described in detail all of its forms with specific examples, since failure to comply with that obligation is punishable by up to three years of deprivation of liberty. Na lekarzach i innych pracownikach medycznych spoczywa obowiązek prawny wynikający z art. 240 § 1 Kodeksu karnego (k.k.), który nakazuje im zawiadomić organ powołany do ścigania przestępstw (tj. Policję lub prokuraturę) o dokonanym czynie zabronionym, jak również o jego karalnym przygotowywaniu lub usiłowaniu. Wykaz czynów podlegających takiej denuncjacji został podany enumeratywnie, ze wskazaniem numerów artykułów i paragrafów. Wyliczenie to zostało rozbudowane w wyniku nowelizacji k.k. dokonanej 13 lipca 2017 r. W jej wyniku do tego katalogu dodano art. 156 k.k., w którym spenalizowany jest ciężki uszczerbek na zdrowiu. Tym samym czyn ten został objęty prawnym obowiązkiem denuncjacji, który jest w takiej sytuacji ważniejszy niż tajemnica medyczna. Z uwagi na to, że dla lekarza klinicysty rozpoznanie, jakie obrażenia spełniają znamiona ciężkiego uszczerbku na zdrowiu, może być trudne, autorzy niniejszej pracy szczegółowo omówili wszystkie jego postaci z podaniem konkretnych przykładów, biorąc pod uwagę, że niewykonanie tej powinności jest zagrożone karą pobawienia wolności do lat 3.

In recent years, the Internet of Things (IoT) has gained increasing popularity due to the usage of Internet-enabled devices. However, Internet-enabled devices, also known as smart devices, share the information using an insecure channel, i.e., the Internet. Hence, the security and privacy of shared information remain the biggest concern. To ensure both security and privacy, many smart card based and biometric based schemes have been proposed for different Internet-based applications. Telecare Medical Information System (TMIS) is such an application which makes medical treatment easier by interacting with the patient and doctors. However, the transmission of the patient’s private information over an insecure channel is prone to several attacks. In order to protect the medical privacy of the patient and the reliability of the system, both the patient and medical server should be mutually authenticated. In this paper, we propose a three factor-based authentication scheme for health care system using IoT enabled devices (TFASH) that are secure and more efficient than other relevant schemes. We use Elliptic Curve Cryptography (ECC) for the scheme due to its smaller key size and high level of security. The session key security and the mutual authentication of the TFASH scheme have been proved using Real-Or-Random (ROR) model and Burrows–Abadi–Needham (BAN) logic. The simulation result of the proposed scheme shows that the scheme is safe under the OFMC and CLAtSe models. Moreover, compared to the existing schemes, the TFASH scheme provides better communicational and computational cost, which makes it suitable for practical use.

With the flourishing of ubiquitous healthcare and cloud computing technologies, medical primary diagnosis system, which forms a critical capability to link big data analysis technologies with medical knowledge, has shown great potential in improving the quality of healthcare services . However, it still faces many severe challenges on both users’ medical privacy and intellectual property of healthcare service providers, which deters the wide adoption of medical primary diagnosis system. In this paper, we propose an effi c ient and priv a cy-preserving m edical p rimary diagno s is framework (CAMPS). Within CAMPS framework, the precise diagnosis models are outsourced to the cloud server in an encrypted manner, and users can access accurate medical primary diagnosis service timely without divulging their medical data. Specifically, based on partially decryption and secure comparison techniques, a special fast secure two-party vector dominance scheme over ciphertext is proposed, with which CAMPS achieves privacy preservation of user’s query and the diagnosis result, as well as the confidentiality of diagnosis models in the outsourced cloud server. Through extensive analysis, we show that CAMPS can ensure that users’ medical data and healthcare service provider’s diagnosis model are kept confidential, and has significantly reduce computation and communication overhead . In addition, performance evaluations via implementing CAMPS demonstrate its effectiveness in term of the real environment.

Introduction. The development and application of medical robotics, medical robotic devices, automated technical systems in the field of health care are already quite successful and have great potential. Such large-scale technological changes inevitably actualize the social roles of law, that should properly settle, protect and guide the development of nascent social relations, which until recently occurred everywhere in a kind of regulatory vacuum. Material and methods. The methodological basis of the study included general scientific methods (dialectical, logical, systemic, historical, sociological, statistical) and private scientific methods of legal science (formal-legal, historical-legal and comparative-legal). The empirical basis of the study was Russian and foreign regulatory legal acts and law enforcement practice, as well as legal doctrine. Results. Based on the comparative legal study a legal definition of the medical robots and various options for their classification, among them a special one, including surgical robots, robots used in restorative medicine, rehabilitation of immobilized patients, nursing and care robots, have been developed. Cyborgs are biological organisms containing mechanical or electronic components are allocated to a special group. Legal mechanisms for ensuring security and cybersecurity in this area are highlighted. The necessity of more flexible legal regulation of personal data concerning the health of citizens and medical confidentiality under new technological conditions is justified. Discussion. Legal regulation of the medical robots should be of a staged nature. General norms of sectoral significance can be formulated at later stages. At the moment, it is more rational to direct efforts to determine the legal regime of certain types of created artificial intelligence systems in the healthcare sector. Conclusion. The legal concept of robotics in healthcare should take a significant place in a wide range of scientific studies of the development of new technologies for the benefit, not to the detriment, of a person.

Blockchain technologies have been benefiting many industries by being decentralized, secure and confidential. They offer great potential in pandemic impacted scenarios as well. Contact tracing helps to mitigate the transmission of disease by alerting people who may have been exposed so they can act on time to protect themselves. Contact tracing systems face some challenges related to issues of medical privacy, data security and transparency. Multiple researches show concern that contact tracing discourages people to seek medication because of the fear of loss of data, subsequent stigma, discrimination, or abuse. In this paper, we discuss how contact tracing can be improved using blockchain technology and could be able to solve these issues. The aim of our proposed system would be to reduce the impact of pandemic, to implement this merger of the blockchains and the Contact tracing app and to ensure user privacy and avoid data misuse by incorporating a symmetric key cryptographic mechanism. To tackle the scalability related issues of Blockchain this framework uses IPFS, a distributed file storage system also known as Interplanetary File System. This blockchain based solution system will enhance contact tracing by making it more stable, secure, performant, highly useable and above all effective in the fight against any pandemic.

CiteSpace refers to a kind of citation visual analysis software developed on the basis of scientometrics and data virtualization. To explore the hot spot of social risk and regulation of international artificial intelligent (AI) in medical treatment, this paper retrieves the paper in 2000–2019 by taking the paper core set of Web of Science as the retrieval database and inputting keywords and then reflects the structure, rules and distribution of science and technology knowledge of the retrieved information, through visual means via CiteSpace. By analyzing data from such aspects as the number of publications and citations, ranking of publishing journals, clustering analysis of co-cited literatures and co-occurrence analysis of keywords, this paper brings the following discoveries: there are few research results related to “AI + social risk and regulation+medical”, EU's leading status in the study of AI ethnics and law, and the scholars' focus in recent years: 1. Some new issues of DNA sequencing technology in terms of laws and ethnics; 2. Personal information privacy at the medical data collection end and AI application end and medical privacy safety; 3. Decision-making of medical robot; 4. The standard application of AI in medical field; 5. Standardization of AI medical device; 6. Nanometer safety. Among all the issues above, the ethnic reorganization of doctor-patient relationship of AI-aided medical treatment triggers extensive concerns.

Background: Based on the patients’ and relatives’ views on the level of preservation of privacy rights of individuals, we propose a way to reduce problems and disagreements about the competence of the provider and recipient of bad news. Methods: In the current cross-sectional study, the participants were recruited from the main northwest hospital of Iran. It was also conducted to study the scope of medical privacy and competence of bearers or receivers of bad news. After the literature review, two questionnaires were designed and administered. They contained items pertinent to the scope of medical privacy and competence of bearers and receivers of bad news. Each item of the original questionnaire was scored on a 5-point Likert scale. Results: The model quality and significance level were obtained using KMO and Bartlett tests. The results (patient’s attitudes questionnaire: KMO=0729 and P

The 19th Workshop on Privacy in the Electronic Society (WPES 2020) was held as a virtual conference on 9 November, 2020, in conjunction with the 27th ACM Conference on Computer and Communication Security (CCS 2020). The goal of WPES is to bring together privacy researchers and practitioners to discuss the privacy problems that arise in an interconnected society and solutions to those problems. The program for the workshop contains 12 full papers and 3 short papers selected from a total of 34 submissions. Specific topics covered in the program include but are not limited to: communication privacy, data anonymization, differential privacy, medical privacy, mobile privacy, privacy engineering, privacy policies, user perception of privacy, and Web privacy.

Background Various methods based on k-anonymity have been proposed for publishing medical data while preserving privacy. However, the k-anonymity property assumes that adversaries possess fixed background knowledge. Although differential privacy overcomes this limitation, it is specialized for aggregated results. Thus, it is difficult to obtain high-quality microdata. To address this issue, we propose a differentially private medical microdata release method featuring high utility. Methods We propose a method of anonymizing medical data under differential privacy. To improve data utility, especially by preserving informative attribute values, the proposed method adopts three data perturbation approaches: (1) generalization, (2) suppression, and (3) insertion. The proposed method produces an anonymized dataset that is nearly optimal with regard to utility, while preserving privacy. Results The proposed method achieves lower information loss than existing methods. Based on a real-world case study, we prove that the results of data analyses using the original dataset and those obtained using a dataset anonymized via the proposed method are considerably similar. Conclusions We propose a novel differentially private anonymization method that preserves informative values for the release of medical data. Through experiments, we show that the utility of medical data that has been anonymized via the proposed method is significantly better than that of existing methods.

With the rapid development of the mobile Internet and the increasing popularity of smart terminals, various mobile social applications are emerging. Medical data has become a valuable data asset and is being continuously explored and utilized, which has greatly promoted the improvement of the medical service level. However, publishing and using user data makes the user vulnerable to reasoning attacks. Due to the special nature of the medical field, medical data not only carries the health status of patients and medical process information but also involves individual sensitive information of a large number of patients. Allowing users to fully enjoy the advantages brought by social networks while ensuring security is an important issue that needs to be solved urgently in the era of big data. In this paper, we first provide an overview of social network data privacy risks and various types of attacks. Aiming at the privacy leakage of weighted social networks, we propose a privacy protection recommendation algorithm based on differential privacy. The algorithm utilizes the change of edge weight grouping, which greatly reduces the amount of calculation and satisfies the user's rapid response. It minimizes a privacy leak of user private data under data availability while supporting personalized rankings. Compared to the most advanced methods, this method protects users from reasoning attacks and reduces the distortion of ranking results caused by data confusion to ensure the accuracy of recommendations. Experiments on real-world datasets show that our framework can achieve more effective and lasting protection for user-sensitive data.

This chapter explores contemporary regulation of medical privacy in the United States and Europe and its challenges. The need for privacy is a fundamental human necessity. Privacy relates to human beings’ ability to maintain their dignity and avoid disclosure of information that might be deemed unpleasant. It is also associated with personal autonomy and informational self-determination. At the same time, however, some degree of data sharing is essential to the appropriate treatment of patients as well as to the proper functioning of society in general and the healthcare system in particular. Thus, privacy cannot be limitless. Hence, this chapter discusses regulatory strengths and shortcomings and highlights gaps in the law. It also suggests further safeguards that policy-makers should implement in order to protect patients and data subjects.

Legal and administrative documents are provided that include a form for consent to share medical information.

Objective Parents routinely access young children’s medical records, but medical societies strongly recommend confidential care during adolescence, and most medical centers restrict parental records access during the teen years. We sought to assess public opinion about adolescent medical privacy. Materials and Methods The Cornell National Social Survey (CNSS) is an annual nationwide public opinion survey. We added questions about a) whether parents should be able to see their 16-year-old child’s medical record, and b) whether teens would avoid discussing sensitive issues (sex, alcohol) with doctors if parents could see the record. Hypothesizing that highlighting the rationale for adolescent privacy would change opinions, we conducted an experiment by randomizing question order. Results Most respondents (83.0%) believed that an adolescent would be less likely to discuss sensitive issues with doctors with parental medical record access; responses did not differ by question order (P = .29). Most also believed that parents should have access to teens’ records, but support for parental access fell from 77% to 69% among those asked the teen withholding question first (P = .01). Conclusions Although medical societies recommend confidential care for adolescents, public opinion is largely in favor of parental access. A brief “nudge,” asking whether parental access might harm adolescent–doctor communication, increased acceptance of adolescent confidentiality, and could be part of a strategy to prepare parents for electronic patient portal policies that medical centers impose at the beginning of adolescence.

Objective Medical privacy policies, which are clear-cut for adults and young children, become ambiguous during adolescence. Yet medical organizations must establish unambiguous rules about patient and parental access to electronic patient portals. We conducted a national interview study to characterize the diversity in adolescent portal policies across a range of institutions and determine the factors influencing decisions about these policies. Methods Within a sampling framework that ensured diversity of geography and medical organization type, we used purposive and snowball sampling to identify key informants. Semi-structured interviews were conducted and analyzed with inductive thematic analysis, followed by a member check. Results We interviewed informants from 25 medical organizations. Policies established different degrees of adolescent access (from none to partial to complete), access ages (from 10 to 18 years), degrees of parental access, and types of information considered sensitive. Federal and state law did not dominate policy decisions. Other factors in the decision process were: technology capabilities; differing patient population needs; resources; community expectations; balance between information access and privacy; balance between promoting autonomy and promoting family shared decision-making; and tension between teen privacy and parental preferences. Some informants believed that clearer standards would simplify policy-making; others worried that standards could restrict high-quality polices. Conclusions In the absence of universally accepted standards, medical organizations typically undergo an arduous decision-making process to develop teen portal policies, weighing legal, economic, social, clinical, and technological factors. As a result, portal access policies are highly inconsistent across the United States and within individual states.

Traditional medical privacy data are at a serious risk of disclosure, and many related cases have occurred over the years. For example, personal medical privacy data can be easily leaked to insurance companies, which not only compromises the privacy of individuals, but also hinders the healthy development of the medical industry. With the continuous improvement of cloud computing and big data technologies, the Internet of Things technology has been rapidly developed. Radio frequency identification (RFID) is one of the core technologies of the Internet of Things. The application of the RFID system to the medical system can effectively solve this problem of medical privacy. RFID tags in the system can collect useful information and conduct data exchange and processing with a back-end server through the reader. The whole process of information interaction is mainly in the form of ciphertext. In the context of the Internet of Things, the paper presents a lightweight RFID medical privacy protection scheme. The scheme ensures security privacy of the collected data via secure authentication. The security analysis and evaluation of the scheme indicate that the protocol can effectively prevent the risk of medical privacy data being easily leaked.

Policy Points: Frequent data breaches in the US health care system undermine the privacy of millions of patients every year-a large number of which happen among business associates of the health care providers that continue to gain unprecedented access to patients' data as the US health care system becomes digitally integrated. Implementation of the HIPAA Omnibus Rules in 2013 has led to a significant decrease in the number of privacy breach incidents among business associates. Context Frequent data breaches in the US health care system undermine the privacy of millions of patients every year. A large number of such breaches happens among business associates of the health care providers that continue to gain unprecedented access to patients' data as the US health care system becomes digitally integrated. The Omnibus Rules of the Health Insurance Portability and Accountability Act (HIPAA), which were enacted in 2013, significantly increased the regulatory oversight and privacy protection requirements of business associates. The objective of this study is to empirically examine the effects of this shift in policy on the frequency of medical privacy breaches among business associates in the US health care system. The findings of this research shed light on how regulatory efforts can protect patients' privacy. Methods Using publicly available data on breach incidents between October 2009 and August 2017 as reported by the Office for Civil Rights (OCR), we conducted an interrupted time-series analysis and a difference-in-differences analysis to examine the immediate and long-term effects of implementation of HIPAA omnibus rules on the frequency of medical privacy breaches. Findings We show that implementation of the omnibus rules led to a significant reduction in the number of breaches among business associates and prevented 180 privacy breaches from happening, which could have affected nearly 18 million Americans. Conclusions Implementation of HIPAA omnibus rules may have been a successful federal policy in enhancing privacy protection efforts and reducing the number of breach incidents in the US health care system.

Multiple surveys show that patients want medical privacy; however, there are costs to maintaining privacy. There are also risks if information is not shared. A review of previous surveys found that most surveys asked questions about patient's privacy concerns and willingness to share their medical information. We found only one study that asked about sharing medical information for better care and no survey that asked patients about the risk, cost or comparison between medical privacy and privacy in other areas. To fill this gap, we designed a survey to: (1) compare medical privacy preferences to privacy preferences in other areas; (2) measure willingness to pay the cost of additional privacy measures; and (3) measure willingness to accept the risks of not sharing information.A total of 834 patients attending physician offices at 14 sites completed all or part of an anonymous questionnaire.Over 95% of patients were willing to share all their medical information with their treating physicians. There was no difference in willingness to share between primary care and specialty sites including psychiatry and an HIV clinic. In our survey, there was no difference in sharing preference between standard medical information and information with additional legal protections including genetic testing, drug/alcohol treatment and HIV results. Medical privacy was ranked lower than sharing social security and credit card numbers, but was deemed more private than other information including tax returns and handgun purchases. There was no statistical difference for any questions by site except for HIV/AIDS clinic patients ranking privacy of the medical record more important than reducing high medical costs and risk of medical errors (p .05). Most patients were willing to spend a modest amount of additional time for privacy, but few were willing to pay more for additional medical privacy. Most patients were unwilling to take on additional risks to keep medical information hidden.Patients were very willing to share medical information with their providers. They were able to see the importance of sharing medical information to provide the best possible care. They were unwilling to hide information from providers if there was increased medical risk. Patients were willing to spend additional time for privacy, but most were unwilling to spend extra money. Sixty-eight percent of patients favored reducing medical costs over privacy.

Hungary’s special approach to political and social questions is frequently analysed by the media. Taking a closer look at the details of the privacy regulations, we can also identify several unique features. For Hungary, the era of socialism ended with the proclamation of the new Republic of Hungary on 23rd October, 1989. The substantially renewed constitution was entered into force on the same day. The fundamental rights defined in the European Convention of Human Rights were included in it and, in addition, the right to the protection of personal data. The main characteristic of the legal system is that politicians understand the constitution so that it would always require passing a new law whenever they want a public authority to collect personal data for some purpose. By now, Hungary has several hundred laws and decrees in effect on the obligatory collection and transfer of personal data. The nature of such types of regulation ab ovo excludes the possibility of objection and challenging a regulation before the court. Turning our attention to healthcare, we see that medical authorities and researchers are authorized by the law to collect personal medical data without providing information and the right to object to data subjects. The author has been studying the changes in the medical privacy regulations since 2004. Here, he gives an account of the key characteristics of the Hungarian legislation and provides a comparison with the relevant European Union legislation in relation to medical data. When the EU General Data Protection Regulation came into force, the conflict between the two became obvious. This paper gives the reader an expert’s view of the Hungarian data protection policy, while attempting to pave the way to stimulate social debate concerning the necessity for better, and more privacy aware legislation.

As big data, medical digitalization, and wearable devices continue to evolve, these technologies are driving the advancement of clinical medicine, genomics, and wearable health while also posing a risk of privacy breaches. For the disclosure of medical privacy issues, some methods and systems combining differential privacy protection applied in the clinical, genomic and wearable fields have been summarized, analyzed and compared. Finally, through the investigation and research, the assumptions and prospects for future research hotspots are given.

Mobile technology is changing the way the patient is undergoing medical treatment. The patient is integrated to manage their health, smartphone, and tablet. The mobile device, such as a patient monitoring system, provides easy-to-doctor real-time patient information. It is easier to communicate with patients and doctors. Mobile health care offers several advantages; however, there are also disadvantages to using these mobile technologies. Necessary to solve privacy is one of the few problems. The patient will not pay more attention. It will focus on mobile medical privacy issues. Based on the mobile medical privacy protection laws, will show how to protect the patient of intelligence Privacy-Preserving Approach for Mobile Healthcare (PAMH). Based on the smartphone's application and access control mechanism, the solution is designed to allow patients to develop their privacy settings, the disclosure of confidential medical information. Various aspects of solution are to use the proposed method; it is defined by whether the patient's privacy policy is shown in the actual scenario. Low Molecular Weight Heparin (LMWH) has been extensively studied; it has become the preferred treatment for several indications, including pulmonary embolism. Effectiveness of their blood dialysis, but is believed to be similar to that of Unfractionated Heparin (UFH), there is a discussion that the risk of their safety is still renal disorder in a patient bio-enrichment. Compared to unfractionated heparin for Extracorporeal Circulation (ECC) anticoagulant, Sodium has been introduced as a viable diagnostic tool for assessing the Na + content of the tissue in kidney disease patients.

Recently the interest in secondary use of medical information has emerged. But the domestic legislation or guidelines, such as being able to say that already specialize in healthcare information, can be seen a 'national medical privacy guidelines'. However the guidelines have suggested that only a violation of privacy laws in the medical information, it does not defined clearly with respect to protected health information(PHI) for secondary use. In this paper, we learn the HIPAA(Health Insurance Portability and Accountability Act) Privacy Rule of the US legislation which provides a non-identifiable screen instructions for secondary utilization of medical information, domestic guidelines and other country's guidelines. comparing with the HIPAA, national medical privacy guidelines and the domestic studies, we propose a new domestic target non-identifying information suitable for the domestic field and present future research direction.

As life in a rapidly changing Internet age at home and abroad, large amounts of information are being used medical, financial, services, etc. Accordingly, especially hospitals, is an invasion of privacy caused by leakage and intrusion of personal information in the system in medical institutions, including clinics institutions. To protect the privacy & information protection of personal health medical information in medical institutions at home and abroad presented by national policies and de-identification processing technology standards in accordance with the legislation. By comparative analysis in existing domestic and foreign institutional privacy and de-identification technique, derive a advanced one of pseudonymization and anonymization techniques for destination data items that fell short in comparison to the domestic laws and regulations, etc. De-identification processing technology for personal health information is compared to a foreign country pharmaceutical situations. We propose a new de-identification techniques by reducing the risk of re-identification processing to enable the secondary use of domestic medical privacy.

At present, the medical management technology has many secure drawbacks, such as, the X-ray transparency leaks user privacy, access to view the medical privacy record is not strictly controlled, infusion confirmation is without technical authentication, patient wrist identity (ID) is easy to be forged, payment is not convenient and so on. This paper first analyzes the present situation of medical management technology and its security defects, and then discusses the possibility of applying quick response (QR) code to secure medical management and improve medical management security through utilizing visual secret sharing (VSS) technology and the convenience of QR code. Finally, aiming at overcome the above secure defects in the current medical management technology, several schemes based on QR code secure technology are designed or applied to improve the security of the above medical management applications.

Nowadays, genomic sequencing has become affordable for many people. Since more people let analyze their genome, more genome data gets collected. The good side of this is that analyses on this data become possible. However, this raises privacy concerns because the genomic data uniquely identify their owner, contain sensitive information about his/her risk for getting diseases, and even sensitive information about his/her family members. In this paper, we introduce a highly efficient privacy-preserving protocol for Similar Sequence Queries (SSQs), which can be used for finding genetically similar individuals in an outsourced genomic database aggregated from data of multiple institutions. Our SSQ protocol is based on the edit distance approximation by Asharov et al. (PETS'18), which we extend to the outsourcing scenario. We also improve their protocol by using more efficient building blocks and achieve a 5-6× run-time improvement compared to their work in the two-party scenario. Recently, Cheng et al. (ASIACCS'18) introduced protocols for outsourced SSQs that rely on homomorphic encryption. Our approach outperforms theirs by more than factor 20000× in terms of run-time in the outsourcing scenario.

Telemedicine is an effective way to solve the imbalance in the distribution of medical resources. However, since related medical privacy data needs to be transmitted over the Internet, it will be exposed to the attacker. Therefore, designing a corresponding authentication protocol to protect users’ privacy has practical significance. For the security problems existing in telemedicine systems, an improved telemedicine system authentication protocol is proposed. This authentication protocol has indistinguishability and forward security, it can effectively resist attacks such as retransmission, tracking, eavesdropping, man-in-the-middle and denial of service. The relevant security performance analysis proves that this protocol can have higher efficiency and security.

With the advent of information technology, we are now able to collect and analyze large sums of data. It is not uncommon now to hear in the mass media terms such as artificial intelligence, business analytic, data mining, neural networks and the like. This is somewhat of a new phenomenon because of the cost of computing is reasonable for performing complex calculations and the storage of large sums of data. In the medical industry informational technology is deployed in many ways, e.g. medical imaging, patient record keeping and biochemistry research. There are some that propose that this informational technology boom will be utopic and societies will be more efficient — there is a downside that is quite dystopic. This downside is an erosion of privacy and security of such personal medical information. In this essay the I will explore the privacy paradox and the positive and negative effects of this informational technology boom in the medical industry.

Background With the increasing application of electronic health records (EHRs) in the world, protecting private information in clinical text has drawn extensive attention from healthcare providers to researchers. De-identification, the process of identifying and removing protected health information (PHI) from clinical text, has been central to the discourse on medical privacy since 2006. While de-identification is becoming the global norm for handling medical records, there is a paucity of studies on its application on Chinese clinical text. Without efficient and effective privacy protection algorithms in place, the use of indispensable clinical information would be confined. Objectives We aimed to (i) describe the current process for PHI in China, (ii) propose a machine learning based approach to identify PHI in Chinese clinical text, and (iii) validate the effectiveness of the machine learning algorithm for de-identification in Chinese clinical text. Methods Based on 14,719 discharge summaries from regional health centers in Ya'an City, Sichuan province, China, we built a conditional random fields (CRF) model to identify PHI in clinical text, and then used the regular expressions to optimize the recognition results of the PHI categories with fewer samples. Results We constructed a Chinese clinical text corpus with PHI tags through substantial manual annotation, wherein the descriptive statistics of PHI manifested its wide range and diverse categories. The evaluation showed with a high F-measure of 0.9878 that our CRF-based model had a good performance for identifying PHI in Chinese clinical text. Conclusion The rapid adoption of EHR in the health sector has created an urgent need for tools that can parse patient specific information from Chinese clinical text. Our application of CRF algorithms for de-identification has shown the potential to meet this need by offering a highly accurate and flexible solution to analyzing Chinese clinical text.

The age of big data is coming. Many data processing and statistical analysis technologies of big data are developing now. They widely impact our live, for examples: society, science, medical industry, military, education, government and business, etc. By using statistical analysis technologies of big data, many valuable information are produced and those results can be used to predict the trend of the future. However, it also brings huge challenges for personal privacy. For protecting the privacy of personal medical data, how to use cryptographic technologies de-identify medical privacy data becomes very important. On the other hand, how to control the access privileges of privacy data for authorized persons are also needed to be solved. This paper bases on Diffie-Hellman protocol to design a privacy protection system for medical big data. It can protect patient privacy information and avoid revealing the medical data. Besides, it can assign access right to authorized doctors, such that the authorized doctors can access and share the patient privacy information. Finally, it can achieve the destination of protecting the privacy and confidentiality of medical big data.

The Health Insurance Portability and Accountability Act (HIPAA) passed by the US Congress establishes a number of privacy/security regulations for e-healthcare systems. These regulations support patients’ medical privacy and secure exchange of PHI (protected health information) among medical practitioners. Three existing HIPAA-based schemes have been studied but appear to be ineffective as patients’ PHI is stored in smartcards. Moreover, carrying a smartcard during a treatment session and accessing PHI from different locations results in restrictions. In addition, authentication of the smartcard presenter would not be possible if the PIN is compromised. In this context, we propose an MCS (medical center server) should be located at each hospital and accessed via the Internet for secure handling of patients’ PHI. All entities of the proposed e-health system register online with the MCS, and each entity negotiates a contributory registration key, where public-key certificates issued and maintained by CAs are used for authentication. Prior to a treatment session, a doctor negotiates a secret session key with MCS and uploads/retrieves patients’ PHI securely. The proposed scheme has five phases, which have been implemented in a secure manner for supporting HIPAA privacy/security regulations. Finally, the security aspects, computation and communication costs of the scheme are analyzed and compared with existing methods that display satisfactory performance.

A variety of security and privacy threats to RFID authentication protocols with embedded healthcare system have been widely studied. The representative vulnerabilities include eavesdropping, replay attacks, denial of service attacks, tracking, and traceability. Considering this RFID security issues, we analyzed the security threats and open problems related to these matters. In ubiquitous system with sensor node, we use small and limited resources and low memory. Then the application with these kinds of have lots of vulnerabilities and attacks such RFID protocol in healthcare system. Even though, concerns about the disclosure of personal medical privacy in e-healthcare system have already appeared. In this paper, we analyzed and compared practical threat on U-healthcare system.

We invented this system “Bed Site Health Care Video Phone System” aiming to increase process efficiency in medical care. This system includes three functions. First, patients can have instant direct contact with medical professional when they need help through a video call. In consideration to patients’ privacy, this device is designed to hide the camera lens unless activated through pressing the nursing call button. The second function is patients’ family and friends can have a remote video visit instead of an in-person visit. Third, it can detect record and analyze patients’ temperature, blood pressure, heart beat.

Introduction : The aim of this study is to evaluate the effectiveness and efficiency of privacy-preserving data cubes of electronic medical records (EMRs). An EMR data cube is a complex of EMR statistics that are summarized or aggregated by all possible combinations of attributes. Data cubes are widely utilized for efficient big data analysis and also have great potential for EMR analysis. For safe data analysis without privacy breaches, we must consider the privacy preservation characteristics of the EMR data cube. In this paper, we introduce a design for a privacy-preserving EMR data cube and the anonymization methods needed to achieve data privacy. We further focus on changes in efficiency and effectiveness that are caused by the anonymization process for privacy preservation. Thus, we experimentally evaluate various types of privacy-preserving EMR data cubes using several practical metrics and discuss the applicability of each anonymization method with consideration for the EMR analysis environment. Methods : We construct privacy-preserving EMR data cubes from anonymized EMR datasets. A real EMR dataset and demographic dataset are used for the evaluation. There are a large number of anonymization methods to preserve EMR privacy, and the methods are classified into three categories (i.e., global generalization, local generalization, and bucketization) by anonymization rules. According to this classification, three types of privacy-preserving EMR data cubes were constructed for the evaluation. We perform a comparative analysis by measuring the data size, cell overlap, and information loss of the EMR data cubes. Results : Global generalization considerably reduced the size of the EMR data cube and did not cause the data cube cells to overlap, but incurred a large amount of information loss. Local generalization maintained the data size and generated only moderate information loss, but there were cell overlaps that could decrease the search performance. Bucketization did not cause cells to overlap and generated little information loss; however, the method considerably inflated the size of the EMR data cubes. Conclusions : The utility of anonymized EMR data cubes varies widely according to the anonymization method, and the applicability of the anonymization method depends on the features of the EMR analysis environment. The findings help to adopt the optimal anonymization method considering the EMR analysis environment and goal of the EMR analysis.

Automated formalization of legal text is a time- and effort-consuming task, but human-based validation consumes even more of both. The exchange of healthcare data in compliance with the medical privacy law requires experts with deep familiarity of its intricate provisions for verification. The article presents a medical relational model (MRM) for the extraction of logical rules from medical law, required to design a medical decision support system (MDSS) that facilitates the process of exchanging data electronically with minimum human intervention. The division of medical law into small concept classes makes it easier to formalize the legal text of medical law into logical rules. These logical rules are then used to make a precise decision in compliance with the law, after evaluating requests from different entities for different purposes in MDSS. Our methodology is to analyze the legal text and release records in compliance with the medical law. For developing countries where medical laws are not as mature as HIPAA (Health Insurance Portability and Accountability Act) in the USA, the proposed methodology can be adapted to build their MDSS based on MRM.

Electronic medical records (EMRs) facilitate fast and accurate access to patient records, which could improve diagnosis and patient monitoring. Using a 12-year county-level panel, we find that a 10 percent increase in births that occur in hospitals with EMRs reduces neonatal mortality by 16 deaths per 100,000 live births. This is driven by a reduction of deaths from conditions requiring careful monitoring. We also find a strong decrease in mortality when we instrument for EMR adoption using variation in state medical privacy laws. Rough cost-effectiveness calculations suggest that EMRs are associated with a cost of $531,000 per baby’s life saved.

Subject recruitment for epidemiologic studies is associated with major challenges due to privacy laws now common in many countries. Privacy policies regarding recruitment methods vary tremendously across institutions, partly because of a paucity of information about what methods are acceptable to potential subjects. The authors report the utility of an opt-out method without prior physician notification for recruiting community-dwelling US women aged 65 years or older with incident breast cancer in 2003. Participants (n = 3,083) and possibly eligible nonparticipants (n = 2,664) were compared using characteristics derived from billing claims. Participation for persons with traceable contact information was 70% initially (2005-2006) and remained over 90% for 3 follow-up surveys (2006-2008). Older subjects and those living in New York State were less likely to participate, but participation did not differ on the basis of socioeconomic status, race/ethnicity, underlying health, or type of cancer treatment. Few privacy concerns were raised by potential subjects, and no complaints were lodged. Using opt-out methods without prior physician notification, a population-based cohort of older breast cancer subjects was successfully recruited. This strategy may be applicable to population-based studies of other diseases and is relevant to privacy boards making decisions about recruitment strategies acceptable to the public.

This comment on the case presented in ‘Cholera and Nothing More’ argues that the physicians at this public-health centre did not have an ordinary clinician's obligations to promote the health of the people who came to them for care, as they were instead set up to serve a laudable and urgent public-health goal, namely, controlling a cholera outbreak. It argues that, nonetheless, these physicians did have some limited moral duties to care for other diseases they encountered—some ancillary-care duties—arising from their voluntarily entering into a kind of intimate relationship with the patients they took in, one in which those patients effectively waive certain rights to bodily and medical privacy.

New HIV cases are increasing among women, especially women of color. Moreover, the rate of infection for incarcerated women is twice that of incarcerated men. With advances in medication therapy, HIV has become a chronic illness that can be successfully treated, provided the patient is able to achieve adherence with the prescribed antiretroviral medication regimen. Incarcerated women, however, frequently come from environments burdened with violence, substance and physical abuse, homelessness, child-care issues, and mental illness. Such burdens negatively affect the ability of these women to adhere to the medication plan. This study explored incarcerated HIV-infected women’s barriers to and facilitators of adherence to antiretroviral therapy (ART), the role of health care provider relationships in adherence, and the ways in which issues of medical privacy influence ability or desire to adhere while incarcerated. A secondary analysis of an existing set of qualitative interviews with HIV-infected female inmates was conducted.

This paper explores whether the Canadian legislative protections in place to safeguard medical privacy meet the expectations of Canadians. An overview of current governance systems designed to protect the privacy of personal health information at both the federal and provincial levels is first presented. This is followed by an empirical analysis of the results of a public opinion survey conducted to determine Canadian attitudes about medical privacy, particularly genetic privacy. The analysis highlights areas where legislation and public opinion converge and diverge.

Recently, a remote-sensing platform based on wireless interconnection of tiny ECG sensors called Telecardiology Sensor Networks (TSN) provided a promising approach to perform low-cost real-time cardiac patient monitoring at any time in community areas (such as elder nursing homes or hospitals). The contribution of this research is the design of a practical TSN hardware/software platform for a typical U.S. healthcare community scenario (such as large nursing homes with many elder patients) to perform real-time healthcare data collections. On the other hand, due to the radio broadcasting nature of MANET, a TSN has the risk of losing the privacy of patients' data. Medical privacy has been highly emphasized by U.S. Department of Health and Human Services. This research also designs a medical security scheme with low communication overhead to achieve confidential electrocardiogram data transmission in wireless medium.

This article profiles computer scientist Latanya Sweeney who runs the Data Privacy Laboratory at Carnegie Mellon University. Sweeney's job is to develop software that protects computer privacy and she urges engineers to design new technology with privacy in mind. Sweeney and her students work on issues of identity theft, medical privacy and camera surveillance. She thinks of her team as a digital detective agency.

Provider and payer groups have endorsed the goal of improving the integration of primary care and behavioral health across a variety of programs and settings. There is an interest in sharing patients' medical information, a goal that is permissible within HIPAA, but there are concerns about more restrictive state medical privacy laws. This article assesses whether a substantial number of state medical privacy laws are, or could be interpreted to be, more restrictive than HIPAA. Preliminary investigation found that in almost one third of the states (including large-population states such as Florida, Georgia, Massachusetts, New York, and Texas), primary care physicians (PCPs) may have difficulty accessing mental health treatment records without the patient's (or his/her guardian/conservator's) written consent. If a comprehensive legal analysis supports this conclusion, then those advocating integration of behavioral and primary care may need to consider seeking appropriate state legislative solutions.

The increasing use of electronic medical records (EMR) makes the medical data mining becomes a hot topic. Consequently, medical privacy invasion attracts people’s attention. Among these, we are particularly interested in the privacy preserving for association rule mining (ARM). In this paper, we improve the traditional reconstruction-based privacy preserving data mining (PPDM) and propose a new architecture for medical data publishing with privacy preserving, and we present a sanitization algorithm for the sensitive rules hiding. In this architecture, the sensitive rules are strictly controlled as well as the side effects are minimized. And finally we performed an experiment to evaluate the proposed architecture.

In this time of an aging population in the Western world and a concomitant need for cost reduction, there is an obvious need for innovative health care delivery. One of the consequences is that a growing number of telemedicine applications are emerging in different health care domains. Also in the area of speech-language (SL) disorders, particularly neurogenic disorders, telemedicine is rapidly gaining interest. In this paper, we place applications for neuro- genic SL disorders in a telemedicine taxonomy in order to establish common features along the dimensions of functionality, application, and technology, and their components. Thus, we aim at identifying common features in a wide variety of telemedicine applications and to establish common interests of stakeholders in health care for classified groups of telemedicine applications. This may facilitate decision-making with regard to expansion of innovative products, and give directions to measures needed for upscaling and structural embedding of feasible and effective SL telemedicine applications in health care. Common interests of stakeholders in health care, established using telemedicine taxonomy, is a key factor in decision-making with regard to which telemedicine applications should be given priority for genuine utilization. Priorities of health care institutions, patients, and reimbursement companies are also leading for research- ers aiming at solid scientific evidence for the beneficial effects of target applications. That is, although research results tend to indicate the potential of telemedicine in the area of SL pathol- ogy, the alleged benefits of most applications have not been confirmed according to the accepted standards for clinical outcome testing as yet. Methodologic obstacles and the lack of adequate speech materials and suitable outcome measures for efficacy and effectiveness testing partially account for this. From the perspective of scientific evidence, the benefits of asynchronous SL telemedicine applications concern data storage and data analyses. To facilitate implementation of telemedicine, there is a call for development of information and communication technology infrastructures that allow feasible applications which meet requirements with regard to licensure and medical privacy laws. For applications with evidence for beneficial effects, we are challenged

We argue that while presidential candidates have the right to medical privacy, the public nature and importance of the presidency generates a moral requirement that candidates waive those rights in certain circumstances. Specifically, candidates are required to disclose information about medical conditions that are likely to seriously undermine their ability to fulfill what we call the "core functions" of the office of the presidency. This requirement exists because (1) people have the right to be governed only with their consent, (2) people's consent is meaningful only when they have access to information necessary for making informed voting decisions, (3) such information is necessary for making informed voting decisions, and (4) there are no countervailing reasons sufficiently strong to override this right. We also investigate alternative mechanisms for legally encouraging or requiring disclosure. Protecting the public's right to this information is of particular importance because of the documented history of deception and secrecy regarding the health of presidents and presidential candidates.