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BackgroundThe security and privacy of health care information are crucial for maintaining the societal value of health care as a public good. However, governance over electronic health care data has proven inefficient, despite robust enforcement efforts. Both federal (HIPAA [Health Insurance Portability and Accountability Act]) and state regulations, along with the ombudsman rule, have not effectively reduced the frequency or impact of data breaches in the US health care system. While legal frameworks have bolstered data security, recent years have seen a concerning increase in breach incidents. This paper investigates common breach types and proposes best practices derived from the data as potential solutions. ObjectiveThe primary aim of this study is to analyze health care and hospital breach data, comparing it against HIPAA compliance levels across states (spatial analysis) and the impact of the Omnibus Rule over time (temporal analysis). The goal is to establish guidelines for best practices in handling sensitive information within hospitals and clinical environments. MethodsThe study used data from the Department of Health and Human Services on reported breaches, assessing the severity and impact of each breach type. We then analyzed secondary data to examine whether HIPAA’s storage and retention rule amendments have influenced security and privacy incidents across all 50 states. Finally, we conducted a qualitative analysis of textual data from vulnerability and breach reports to identify actionable best practices for health care settings. ResultsOur findings indicate that hacking or IT incidents have the most significant impact on the number of individuals affected, highlighting this as a primary breach category. The overall difference-in-differences trend reveals no significant reduction in breach rates (P=.50), despite state-level regulations exceeding HIPAA requirements and the introduction of the ombudsman rule. This persistence in breach trends implies that even strengthened protections and additional guidelines have not effectively curbed the rising number of affected individuals. Through qualitative analysis, we identified 15 unique values and associated best practices from industry standards. ConclusionsCombining quantitative and qualitative insights, we propose the “SecureSphere framework” to enhance data security in health care institutions. This framework presents key security values structured in concentric circles: core values at the center and peripheral values around them. The core values include employee management, policy, procedures, and IT management. Peripheral values encompass the remaining security attributes that support these core elements. This structured approach provides a comprehensive security strategy for protecting patient health information and is designed to help health care organizations develop sustainable practices for data security.

BackgroundIntegrating pervasive computing with blockchain’s ability to store privacy-protected mobile health (mHealth) data while providing Health Insurance Portability and Accountability Act (HIPAA) compliance is a challenge. Patients use a multitude of devices, apps, and services to collect and store mHealth data. We present the design of an internet of things (IoT)–based configurable blockchain with different mHealth apps on iOS and Android, which collect the same user’s data. We discuss the advantages of using such a blockchain architecture and demonstrate 2 things: the ease with which users can retain full control of their pervasive mHealth data and the ease with which HIPAA compliance can be accomplished by providers who choose to access user data. ObjectiveThe purpose of this paper is to design, evaluate, and test IoT-based mHealth data using wearable devices and an efficient, configurable blockchain, which has been designed and implemented from the first principles to store such data. The purpose of this paper is also to demonstrate the privacy-preserving and HIPAA-compliant nature of pervasive computing-based personalized health care systems that provide users with total control of their own data. MethodsThis paper followed the methodical design science approach adapted in information systems, wherein we evaluated prior designs, proposed enhancements with a blockchain design pattern published by the same authors, and used the design to support IoT transactions. We prototyped both the blockchain and IoT-based mHealth apps in different devices and tested all use cases that formed the design goals for such a system. Specifically, we validated the design goals for our system using the HIPAA checklist for businesses and proved the compliance of our architecture for mHealth data on pervasive computing devices. ResultsBlockchain-based personalized health care systems provide several advantages over traditional systems. They provide and support extreme privacy protection, provide the ability to share personalized data and delete data upon request, and support the ability to analyze such data. ConclusionsWe conclude that blockchains, specifically the consensus, hasher, storer, miner architecture presented in this paper, with configurable modules and software as a service model, provide many advantages for patients using pervasive devices that store mHealth data on the blockchain. Among them is the ability to store, retrieve, and modify ones generated health care data with a single private key across devices. These data are transparent, stored perennially, and provide patients with privacy and pseudoanonymity, in addition to very strong encryption for data access. Firms and device manufacturers would benefit from such an approach wherein they relinquish user data control while giving users the ability to select and offer their own mHealth data on data marketplaces. We show that such an architecture complies with the stringent requirements of HIPAA for patient data access.

Water is a very valuable natural resource. As the demand for water increases the presence of emerging contaminants in wastewater has become a growing concern. This is particularly true when one considers direct reuse of wastewater. Obtaining sufficient removal of emerging contaminants will require determining the level of removal for the various unit operations in the wastewater treatment process. Membrane bioreactors are attractive as they combine an activated sludge process with a membrane separation step. They are frequently used in a wastewater treatment process and can operate at higher solid loadings than conventional activated sludge processes. Determining the level of removal of emerging contaminants in the membrane bioreactor step is, therefore, of great interest. Removal of emerging contaminants could be by adsorption onto the biomass or membrane surface, biotransformation, size exclusion by the membrane, or volatilization. Given the fact that most emerging contaminants are low molecule weight non-volatile compounds, the latter two methods of removal are usually unimportant. However, biotransformation and adsorption onto the biomass are important mechanisms of removal. It will be important to determine if the microorganisms present at given treatment facility are able to remove ECs present in the wastewater.

Ultrafiltration membranes, that respond to an external magnetic field and local temperature have been developed. Surface-initiated activator-generated electron transfer (AGET) atom transfer radical polymerization (ATRP) has been used to graft poly(N-isopropylacrylamide) (PNIPAm) from the surface of 300 kDa regenerated cellulose membranes. The polymerization initiator was selectively attached to the entire membrane surface, only the outer membrane surface or only the inner pore surface. A superparamagnetic nanoparticle was attached to the end of the polymer chain. The DI water flux as well as the flux and rejection of bovine serum albumin were investigated in the absence and presence of a 20 and 1000 Hz oscillating magnetic field. In an oscillating magnetic field, the tethered superparamagnetic nanoparticles can cause movement of the PNIPAm chains or induce heating. A 20 Hz magnetic field maximizes movement of the chains. A 1000 Hz magnetic field leads to greater induced heating. PNIPAm displays a lower critical solution temperature at 32 °C. Heating leads to collapse of the PNIPAm chains above their Lower Critical Solution Temperature (LCST). This work highlights the versatility of selectively grafting polymer chains containing a superparamagnetic nanoparticle from specific membrane locations. Depending on the frequency of the oscillating external magnetic field, membrane properties may be tuned.

Magnetically responsive ultrafiltration membranes were prepared by grafting poly(2-hydroxyethyl methacrylate) chains from the outer surface of 100-kDa regenerated cellulose ultrafiltration membranes. Surface-initiated atom transfer radical polymerization was used to graft the polymer chains. Grafting from the internal pore surface was suppressed by using glycerol as a pore-filling solvent during initiator immobilization at varied densities. Glycerol suppresses the initiator attachment to the pore surface. Polymerization times of up to four hours were investigated. Superparamagnetic nanoparticles were covalently attached to the chain end. Membrane performance was determined using bovine serum albumin and dextran as model solutes. Increasing the grafted polymer chain density and length led to a decrease in the permeate flux and an increase in the apparent rejection coefficient. In an oscillating magnetic field, movement of the grafted polymer chains led to a decrease in the permeate flux, as well as an increase in the apparent rejection coefficient of the model solutes.

A simple, rapid and accurate method for the determination of monoethanolamine (MEA) in PHWR steam-water circuits has been developed. MEA is added in the feed water to provide protection against corrosion while hydrazine is added to scavenge dissolved oxygen. The quantitative determination of MEA in presence of hydrazine was accomplished using derivatization ion chromatography with conductometric detection in nonsuppressed mode. A Metrosep cation 1-2 analytical column and a Metrosep cartridge were used for cation separation. A mixture of 4 mM tartaric acid, 20% acetone and 0.05 mM HNO3 was used as eluent. Acetone in the mobile phase leads to the formation of different derivatives with MEA and hydrazine. The interferences due Na+ and NH4 + were eliminated by adopting a simple pretreatment procedure employing OnGuard-H cartridge. The limit of detection limit of MEA was 0.1 μg mL−1 and the relative standard deviation was 2% for the overall method. The recovery of MEA added was in the range 95%–102%. The method was applied to the determination of MEA in steam generator water samples.