Facilitating the Urgent Public Health Need to Improve Data Sharing With Tribal Epidemiology Centers.

Tribal epidemiology centers (TECs) are an essential and unique part of the public health system and an important part of federal efforts to improve the health status of American Indian and Alaska Native people. Pursuant to federal statute, TECs serve the 574 federally recognized tribes (hereinafter, "tribes") and their members across the United States, as well as American Indian and Alaska Native people in general. The COVID-19 pandemic has highlighted the need for timely, complete, and accurate public health data, particularly for American Indian and Alaska Native communities and others who may have been disproportionately impacted by COVID-19. This article reviews the history and importance of TECs and federal statutes governing TECs' ability to access and use protected health information for public health purposes. TECs and tribes often encounter difficulty receiving public health data from state and federal agencies despite their designation as "public health authorities" under the Health Insurance Portability and Accountability Act and associated regulations. Limited access to this information hinders the statutory mission of TECs as well as tribal monitoring of and response to public health threats such as SARS-CoV-2. Agency acknowledgment and compliance with current federal law regarding data sharing with TECs are essential to improve data access and the fragile public health of tribal communities.

Breast Cancer Treatment at Home During COVID Pandemic Using IoT, Cloud Computing and Machine Learning

It is crucial that Breast Cancer should be detected early. Breast cancer time series forecasting is a novel data - driven approach to breast cancer diagnosis. Instead of looking at static images of the medical records, it analyses the dynamics in the tumour's growth rate, especially in its early stages. It uses machine learning models to find patterns that are not readily observable in static images, but are predictive of later outcomes. During COVID-19 it is necessary to monitor patient from home and IOT devices can be used that give moment forecast to the client and doctor during their typical day by day routine. Various Machine learning models are reviewed for classification of Breast Cancer symptoms. It is observed that data visualization and feature engineering play a crucial role in the classification before applying any model on data set. For human protection during COVID-19 it is better to depend on IoT enabled wearable device for automatic detection and appointment. The IoT enabled devices can use power of cloud computing and machine learning models to complete the framework of getting treated at home. Security of the data is another aspect to be taken into consideration. Solutions are available for the whole process and their aggregation will result in generating the desired model. In this paper, model is proposed to diagnose breast cancer at home using IoT, Blockchain, Machine learning and Cloud Computing. © 2022 American Institute of Physics Inc.. All rights reserved.

Analyzing Security and Privacy Concerns of Contact Tracing Applications

The spread of COVD-19 has affected normal life like no other pandemic in the 21st century. This has seen the evolution and adoption of digital contact tracing applications, majority of which rely on google and apple exposure notification and can easily be downloaded for use in any smartphone. It is imperative to protect personal health information transmitted in these apps. Developers have been criticized for slacking in protecting personal health information and on being non-compliant to HIPAA. Using MobSF, we interact with these apps to detect security vulnerabilities and demonstrate whether they are complying with their privacy policies. Our analysis showed that contact tracing applications have poor security features and not safe.

A Web-based Blood Bank System for Managing Records of Donors and Receipts

The Online Blood Donation Management System, the purpose of which is to act as a bridge between a person who needs blood, a patient, and a blood donor. The design of an automatic blood system has become an integral part for saving the human lives, who need the blood under different situations. Since, there are various drawbacks of the pre-existing system like privacy issues for the donors, which are getting reflected directly on the interface. Thus, we have designed a robust system that will create a connection between different hospitals, NGOs, and blood banks to help the patient in any difficult situation. Thus, HIPPA model provides a backbone for security breaches The interface designed will be easy-to-use and easy to access and will be a fast, efficient, and reliable way to get lifesaving blood, totally free of charge. Apart from this the visualization of the data is present along with the one extra COVID module, which will help covid and normal patients for plasma donation. The main aim of the paper is to reduce the complications of finding a blood donor during panic situations and provide a high level of security for the donors. © 2022 IEEE.

Telehealth Practice Standards With Emphasis on the United States: What Telerehabilitation Providers Need to Know

Telehealth has taken the spotlight with the onset of the global COVID-19 pandemic, which rendered traditional, in-person health care visits potentially unsafe in the face of a highly communicable virus. Because many conditions can be adequately diagnosed and treated via telehealth, the use of this mechanism of health care delivery became desirable for telehealth providers and patients alike. Concurrently, a myriad of laws and regulations governing health care practice were relaxed in an attempt to make use of telehealth easier for telehealth providers and patients. Nonetheless, a patchwork of varying standards governing the practice of telehealth in the United States and across the globe is the norm, which makes practicing telehealth and telerehabilitation potentially confusing for the newly initiated. © 2022 Elsevier Inc. All rights reserved.

The Security of Blockchain-Based Medical Systems: Research Challenges and Opportunities

The current COVID-19 pandemic has, perhaps, expedited the move to electronic medical systems (e.g., telemedicine). However, in the digitalization of healthcare services, we have to ensure the security and privacy of (sensitive) healthcare data, often stored locally in the hospital's server or remotely within a trusted cloud server. There have been many attempts to design blockchain-based approaches to support security and privacy in medical systems, and this is the focus of this article where we systematically review the existing literature on blockchain-based medical systems. We then categorize the existing security solutions into three categories, namely, 1) decentralized authentication, 2) access control, and 3) audit, and discuss the privacy protection technologies in blockchain-based healthcare systems. Based on our analysis, we identify a number of challenges, including performance limitations and inflexible audit, as well as future research opportunities (e.g., the need for lightweight security schemes for blockchain-based medical systems).

A Policy-Driven Approach to Secure Extraction of COVID-19 Data From Research Papers.

The entire scientific and academic community has been mobilized to gain a better understanding of the COVID-19 disease and its impact on humanity. Most research related to COVID-19 needs to analyze large amounts of data in very little time. This urgency has made Big Data Analysis, and related questions around the privacy and security of the data, an extremely important part of research in the COVID-19 era. The White House OSTP has, for example, released a large dataset of papers related to COVID research from which the research community can extract knowledge and information. We show an example system with a machine learning-based knowledge extractor which draws out key medical information from COVID-19 related academic research papers. We represent this knowledge in a Knowledge Graph that uses the Unified Medical Language System (UMLS). However, publicly available studies rely on dataset that might have sensitive data. Extracting information from academic papers can potentially leak sensitive data, and protecting the security and privacy of this data is equally important. In this paper, we address the key challenges around the privacy and security of such information extraction and analysis systems. Policy regulations like HIPAA have updated the guidelines to access data, specifically, data related to COVID-19, securely. In the US, healthcare providers must also comply with the Office of Civil Rights (OCR) rules to protect data integrity in matters like plasma donation, media access to health care data, telehealth communications, etc. Privacy policies are typically short and unstructured HTML or PDF documents. We have created a framework to extract relevant knowledge from the health centers' policy documents and also represent these as a knowledge graph. Our framework helps to understand the extent to which individual provider policies comply with regulations and define access control policies that enforce the regulation rules on data in the knowledge graph extracted from COVID-related papers. Along with being compliant, privacy policies must also be transparent and easily understood by the clients. We analyze the relative readability of healthcare privacy policies and discuss the impact. In this paper, we develop a framework for access control decisions that uses policy compliance information to securely retrieve COVID data. We show how policy compliance information can be used to restrict access to COVID-19 data and information extracted from research papers.

Innovation Inspired by COVID: A Virtual Treatment Program for Patients With Mild Cognitive Impairment at Mayo Clinic.

Limited access to mental health and behavioral interventions is a public health issue that predated and is further worsened by coronavirus disease 2019 (COVID-19) social distancing restrictions. The Healthy Action to Benefit Independence and Thinking (HABIT) program is a cognitive rehabilitation and wellness program for patients with a diagnosis of mild cognitive impairment and their partners that involves groups of up to 32 people (16 dyads) at a time. Thus, the public health recommendation to avoid groups at the start of the COVID-19 pandemic immediately impacted our ability to offer this treatment protocol. This brief report provides patient and partner satisfaction data as well as clinical outcomes with a virtual adaptation of the HABIT program developed because of the COVID-19 pandemic. At the time of their participation, patients who attended in-person sessions had an average age of 74.4 years and those who attended virtual sessions had an average age of 75.4 years (P=.60). Both groups had an average of 16.3 years of education (P=.95). Approximately half of the patients in both groups were male (30 of 57 [53%]), most were White (54 of 57 [95%]) and were accompanied to the program by a spouse (50 of 57 [88%]). Overall, patient and partner satisfaction with the HABIT program remained high, ranging from a mean score of 5.8 to 6.6 on a rating scale of 1 to 7 for patients and partners, and clinical outcomes remained consistent with our face-to-face formatting when compared with pre-COVID pandemic sessions. The most notable changes across both formats were improvements in patient anxiety (Cohen's d=0.25 face-to-face; d=0.39 virtual), partner anxiety (d=0.37 face-to-face; d=0.34 virtual), and partner depression (d=0.37 face-to-face; d=0.35 virtual). This preliminary program evaluation suggests that transitioning the HABIT program to virtual formatting provides high-quality care similar to our in-person care models. Ongoing program evaluation is planned as we continue using virtual treatment for safety. Even after COVID-19 pandemic public health restrictions are lifted, these findings will have continued relevance to ongoing demand for telehealth.

Health Information Privacy Laws in the Digital Age: HIPAA Doesn't Apply.

The notion of health information privacy has evolved over time as the healthcare industry has embraced technology. Where once individuals were concerned about the privacy of their conversations and financial information, the digitization of health data has created new challenges for those responsible for ensuring that patient information remains secure and private. Coupled with the lack of updated, overarching legislation, a critical gap exists between advancements in technology, consumer informatics tools and privacy regulations. Almost twenty years after the HIPAA (Health Insurance Portability and Accountability Act) compliance date, the healthcare industry continues to seek solutions to privacy challenges absent formal contemporary law. Since HIPAA, a few attempts have been made to control specific aspects of health information including genetic information and use of technology however none were visionary enough to address issues seen in today's digital data focused healthcare environment. The proliferation of digital health data, trends in data use, increased use of telehealth applications due to COVID-19 pandemic and the consumer's participatory role in healthcare all create new challenges not covered by the existing legal framework. Modern efforts to address this dilemma have emerged in state and international law though the United States healthcare industry continues to operate under a law written two decades ago. As technology continues to advance at a rapid pace along with consumers playing a greater role in the management of their healthcare through digital health the privacy guidance provided by federal law must also shift to reflect the new reality.

Implementation of teledentistry for orthodontic practices.

Recent advances in technology, growing patient demand, and the need for social distancing due to Coronavirus Disease 2019 has expedited adoption of teledentistry in orthodontics as a means of consulting and monitoring a patient without an in-office visit. However, a lack of computer literacy and knowledge of software choices, and concerns regarding patient safety and potential infringement of regulations can make venturing into this new technology intimidating. In this article, various types of teledentistry systems for orthodontic practices, implementation guidelines, and important regulatory considerations on the use of teledentistry for orthodontic purposes are discussed. A thorough evaluation of the intended use of the software should precede commitment to a service. Selected service should be Health Insurance Portability and Accountability Act compliant at minimum and a Business Associate Agreement should be in place for protection of privacy. Ensuring the compatibility of the designated clinic computer with the system's requirements and installation of all safeguards must follow. Appointments should be documented in the same manner as in-office visits and teledentistry patients must be located within the clinician's statutory license boundary. Informed consent forms should include teledentistry or a supplemental teledentistry consent form should be used. Malpractice insurance covers everything usual and customary under the provider's license but the need for cyber liability insurance increases with teledentistry.

COVID-19 contact tracing apps: a stress test for privacy, the GDPR, and data protection regimes.

Digital surveillance has played a key role in containing the COVID-19 outbreak in China, Singapore, Israel, and South Korea. Google and Apple recently announced the intention to build interfaces to allow Bluetooth contact tracking using Android and iPhone devices. In this article, we look at the compatibility of the proposed Apple/Google Bluetooth exposure notification system with Western privacy and data protection regimes and principles, including the General Data Protection Regulation (GDPR). Somewhat counter-intuitively, the GDPR's expansive scope is not a hindrance, but rather an advantage in conditions of uncertainty such as a pandemic. Its principle-based approach offers a functional blueprint for system design that is compatible with fundamental rights. By contrast, narrower, sector-specific rules such as the US Health Insurance Portability and Accountability Act (HIPAA), and even the new California Consumer Privacy Act (CCPA), leave gaps that may prove difficult to bridge in the middle of an emergency.

Balancing health privacy, health information exchange, and research in the context of the COVID-19 pandemic.

The novel coronavirus disease 2019 infection poses serious challenges to the healthcare system that are being addressed through the creation of new unique and advanced systems of care with disjointed care processes (eg, telehealth screening, drive-through specimen collection, remote testing, telehealth management). However, our current regulations on the flows of information for clinical care and research are antiquated and often conflict at the state and federal levels. We discuss proposed changes to privacy regulations such as the Health Insurance Portability and Accountability Act designed to let health information seamlessly and frictionlessly flow among the health entities that need to collaborate on treatment of patients and, also, allow it to flow to researchers trying to understand how to limit its impacts.