You are impacted by the things you see and read whether you like it or not. It can be hard to erase from your mind undesirable images or messages you receive and they can cause much angst, anger, doubt and grief.

Twitter has recently posted a set of instructions on how you can control what you see on twitter, the conversations you are a part of and the types of notifications you receive.

Take action and mute bad messages so they don't impact you negatively. There is a wealth of good information out there that will engage your mind both positively and critically without exposing you to harm from trolls who are out to manipulate you.

In this article written by Brian X. Chen from the New York Times he discusses some of the potential ways in which mobile apps that you download to your phone may be collecting and using your personal data in ways you did not know.

One of the key takeaways is that there are ways in which to protect yourself and tools that can help you figure out which apps are collecting your data and how to remove their ability to do so.

Don’t get me wrong, the information blocking regulations are important, but let’s not forget that the 21st Century Cures Act (Cures Act) and our implementing regulations (Cures Act Final Rule) had a few other impactful provisions. In particular, certain changes to the ONC Health IT Certification Program may seem like “more of the same” for health IT developers, but in reality they are really important and beneficial to clinicians, researchers, and the public alike.
Two new education resources are now available specifically geared toward these audiences to describe “what the rule says” and what those regulatory requirements “mean” from the perspective of those who interact with developers of certified health IT and use their products.

The post Not-So-Hidden Gems in the 21st Century Cures Act Final Rule: Get to Know the Conditions of Certification appeared first on Health IT Buzz.

In the third blog in our series on artificial intelligence (AI) and machine learning (ML)-driven predictive models (data analytics tool or software) in health care, we discussed some potential risks (sometimes referred to as model harms) related to these emerging technologies and how these risks could lead to adverse impacts or negative outcomes. Given these potential risks, some have questioned whether they can trust the use of these technologies in health care.

We are encouraged to see that some stakeholders are demonstrating that a predictive model is fair,

The post Back to the Future: What Predictive Decision Support Can Learn from DeLoreans and The Big Short appeared first on Health IT Buzz.

As you design, market, and distribute a mobile health (mHealth) app that your customers will use to collect, share, use, or maintain individuals’ health information, it is likely you have questions about what U.S. federal laws apply. You may also wonder which federal agencies oversee various aspects of mHealth — including how this varies by how individuals, their health plan, or health care providers will use the app.  Depending on who is expected to use an app and how they will get and use the app (e.g.,

The post Guiding Developers through Foundational Federal Laws Applicable to Mobile Health Technology appeared first on Health IT Buzz.