healthcare technology

The Internet of Things (IoT) is a network of physical objects that can share electronic information when gathered together. They include sensors that have the ability to track information about the human body or industrial machines that transmit the production process data to the nearby sensors.

 

The IoT is all over and is used in smart homes and even retail. It also plays a crucial role in healthcare.

 

The Internet of Things (IoT) is changing healthcare in different ways, including improving the care patients get, better results from treatments, and reducing the costs of treatments for patients. Patients get to connect better with the healthcare providers, and their performance is also enhanced.

 

The main benefits it has brought about to the healthcare industry include:

 

• Real-time monitoring of patients remotely, which reduces the costs incurred during readmissions and doctor visits.
• Errors are much less likely to occur with IoT devices. The data plays an essential role in ensuring effective decision-making, and all the operations in the healthcare industry are functioning smoothly. This helps reduce the overall number of errors.
• The quality of treatment received is excellent since physicians make decisions from evidence-based information. Hence there’s complete transparency.
• Equipment and drugs are better managed. It has always been a significant challenge to manage drugs and equipment in healthcare. However, with devices being connected, the drugs and equipment are utilized and managed efficiently, which helps with cost reduction.
• Diagnosis is much faster and more accurate. A patient can be diagnosed more efficiently due to consistent remote monitoring. Real-time data is collected, and it helps with the diagnosis of a vast number of different diseases. They are diagnosed at an early stage before they worsen or even before the disease develops fully.

 

IoT devices are revolutionizing how healthcare is delivered and monitored. We guess that we still have only seen the tip of the iceberg. In the years to come, the question will not be if we are connected but how we will be connected and protect our privacy: digital tattoos, smartwatches, smart lenses, or smart pills being just some of the possibilities.

 

The Internet of Things and the multitude of connected devices it offers is on a path to disrupt how healthcare is carried out.

 

Discover how by reading the original article at https://digitalhealthcentral.com/2021/05/07/the-benefits-of-internet-of-things-in-healthcare/

 

Contact tracing apps are potentially useful tools for supporting national COVID-19 containment strategies. Various national apps with different technical design features have been commissioned and issued by governments worldwide.

Objective: Our goal was to develop and propose an item set that was suitable for describing and monitoring nationally issued COVID-19 contact tracing apps.

 

This item set could provide a framework for describing the key technical features of such apps and monitoring their use based on widely available information.

Methods: We used an open-source intelligence approach (OSINT) to access a multitude of publicly available sources and collect data and information regarding the development and use of contact tracing apps in different countries over several months (from June 2020 to January 2021). The collected documents were then iteratively analyzed via content analysis methods. During this process, an initial set of subject areas were refined into categories for evaluation (ie, coherent topics), which were then examined for individual features.

 

These features were paraphrased as items in the form of questions and applied to information materials from a sample of countries (ie, Brazil, China, Finland, France, Germany, Italy, Singapore, South Korea, Spain, and the United Kingdom [England and Wales]). This sample was purposefully selected; our intention was to include the apps of different countries from around the world and to propose a valid item set that can be relatively easily applied by using an OSINT approach.

Results: Our OSINT approach and subsequent analysis of the collected documents resulted in the definition of the following five main categories and associated subcategories:

 

(1) background information (open-source code, public information, and collaborators);

 

(2) purpose and workflow (secondary data use and warning process design);

 

(3) technical information (protocol, tracing technology, exposure notification system, and interoperability);

 

(4) privacy protection (the entity of trust and anonymity); and

 

(5) availability and use (release date and the number of downloads).

 

Based on this structure, a set of items that constituted the evaluation framework were specified. The application of these items to the 10 selected countries revealed differences, especially with regard to the centralization of the entity of trust and the overall transparency of the apps’ technical makeup.

Conclusions: We provide a set of criteria for monitoring and evaluating COVID-19 tracing apps that can be easily applied to publicly issued information. The application of these criteria might help governments to identify design features that promote the successful, widespread adoption of COVID-19 tracing apps among target populations and across national boundaries.

 

 read the study at https://mhealth.jmir.org/2021/3/e27232

 

 

Information technology has allowed much of our economy to automate processes. We have seen transformations of the airline, banking, brokerage, entertainment, lodging, music, printing, publishing, shipping and taxi industries through the availability of massive volumes of real-time price and service data. Across America, consumer-facing retail service continues to shift to a virtual environment.

 

Healthcare is the exception. Many health information technology (health IT) products initially focused on billing.

The misalignment between billing support and the sense that these tools do not materially automate clinician work to build in efficiencies or improve workflows adds to an overall frustration with the increasing amount of time providers spend at their screens.

 

Automation is hard because it tends to require interfaces of various types – both to other machines (Internet of Things) and to humans.

 

Often automation proposals involve solutions that focus on highly structured data. But, someone or something has to put energy (physician salary, for example) into organizing much of this information, assuming it is even knowable.

 

The underlying disease or patient behavior (e.g., smoking) is also often not knowable. And, automation relying on machine to machine interfaces regularly runs into a lack of application programming interfaces (APIs) supporting complex clinical data flows.

 

I posted this week old piece now and now when it was published as #NHITWeek is this week. A lot of posts this week deal with possibilities and problems with healthcare focussed automation. 

 

The original unedited piece can be read at https://www.himss.org/news/healthcare-automation-transforming-medicine