Cloudy confidentiality: clinical and legal implications of cloud computing in health care.

J Am Acad Psychiatry Law

Department of Mental Health, Saint Elizabeths Hospital, Washington, DC, USA.

Published: April 2012

The Internet has grown into a world of its own, and its ethereal space now offers capabilities that could aid physicians in their duties in numerous ways. In recent years software functions have moved from the individual's local hardware to a central server that operates from a remote location. This centralization is called cloud computing. Privacy laws that speak to the protection of patient confidentiality are complex and often difficult to understand in the context of an ever-growing cloud-based technology. This article is a review of the legal background of protected health records, as well as cloud technology and physician applications. An attempt is made to integrate both concepts and examine Health Insurance Portability and Accountability Act (HIPAA) compliance for each of the examples discussed. The legal regulations that may inform care and standards of practice are reviewed, and the difficulties that arise in assessment and monitoring of the current situation are analyzed. For forensic psychiatrists who may be asked to provide expert opinions regarding malpractice situations pertaining to confidentiality standards, it is important to become acquainted with the new digital language from which these questions may arise.

Download full-text PDF

Source

Publication Analysis

Top Keywords

cloud computing
8
cloudy confidentiality
4
confidentiality clinical
4
clinical legal
4
legal implications
4
implications cloud
4
computing health
4
health care
4
care internet
4
internet grown
4

Similar Publications

Solu: a cloud platform for real-time genomic pathogen surveillance.

BMC Bioinformatics

January 2025

Solu Healthcare Oy, Kalevankatu 31 A 13, 00100, Helsinki, Finland.

Background: Genomic surveillance is extensively used for tracking public health outbreaks and healthcare-associated pathogens. Despite advancements in bioinformatics pipelines, there are still significant challenges in terms of infrastructure, expertise, and security when it comes to continuous surveillance. The existing pipelines often require the user to set up and manage their own infrastructure and are not designed for continuous surveillance that demands integration of new and regularly generated sequencing data with previous analyses.

View Article and Find Full Text PDF

In response to the demand for advanced tools in environmental monitoring and policy formulation, this work leverages modern software and big data technologies to enhance novel road transport emissions research. This is achieved by making data and analysis tools more widely available and customisable so users can tailor outputs to their requirements. Through the novel combination of vehicle emissions remote sensing and cloud computing methodologies, these developments aim to reduce the barriers to understanding real-driving emissions (RDE) across urban environments.

View Article and Find Full Text PDF

Most current research in cloud forensics is focused on tackling the challenges encountered by forensic investigators in identifying and recovering artifacts from cloud devices. These challenges arise from the diverse array of cloud service providers as each has its distinct rules, guidelines, and requirements. This research proposes an investigation technique for identifying and locating data remnants in two main stages: artefact collection and evidence identification.

View Article and Find Full Text PDF

Securing Cloud-Based Internet of Things: Challenges and Mitigations.

Sensors (Basel)

December 2024

Department of Computer Science & Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea.

The Internet of Things (IoT) has seen remarkable advancements in recent years, leading to a paradigm shift in the digital landscape. However, these technological strides have introduced new challenges, particularly in cybersecurity. IoT devices, inherently connected to the internet, are susceptible to various forms of attacks.

View Article and Find Full Text PDF

Objective: In recent years, wearable devices such as smartwatches and smart patches have revolutionized biosignal acquisition and analysis, particularly for monitoring electrocardiography (ECG). However, the limited power supply of these devices often precludes real-time data analysis on the patch itself.

Approach: This paper introduces a novel Python package, tinyHLS (High Level Synthesis), designed to address these challenges by converting Python-based AI models into platform-independent hardware description language (HDL) code accelerators.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!