healthcare technology

A fundamental question about any (Clinical Decision Support System) CDS is just how good is it, i.e. does it get the right answer for generic and specific patients? If it doesn’t this may be the result of one or more issues such as flawed information having been used to build the system, flawed programming, or the patient being outside of an often undefined or ill defined population when for another population the CDS does actually provide the right answer

A common CDS disclaimer is that it is always up to the practitioner to second guess the CDS as necessary, or in other words, the CDS is not actually supposed to be relied upon. Depending on the complexity of the underlying theory and data, the practitioner may or may not in reality have the ability to do this, or they may not have a more rational basis for doing so than “I don’t think that is right”. Such a conclusion would put the practitioner outside of what might be considered a practice guideline. On the other hand if a CDS is easy to second guess, then it might not be very valuable in the first place.

In this context comes the recent controversy over the new cholesterol and statin on line “risk calculator”. As first reported in the New York Times, it was determined that an online risk calculator overestimated patient specific risk by an average of 100% (100 here is not a typo). If action were based on this erroneous calculator, statin therapy would be substantially over-prescribed. In this regard the Times cites a statement from the organizations that published the guidelines that will continue to be a CDS classic: patients and doctors should discuss treatment options rather than blindly follow a calculator. Or, in other words, it is not to be relied on.

Apparently the problem with the risk calculator is at least in part that the risk data on which it was based was decades old and therefore did not apply to the current US population which in at least some ways has actually gotten healthier. In addition the mathematical model used was one of linearly increasing risk which has not been demonstrated to be correct. Thus the flaws in the calculator were a result of the inappropriateness and lack of justification of the knowledge bases used to build it. Despite these fundamental issues, no plans to remove or revise the calculator were identified.

This risk calculator was not imbedded within an EHR, and it requires manual input of multiple patient parameters. And of course there are additional potentially relevant patient parameters that are not part of the calculation. However something like this certainly could be part of an EHR either by direct integration, or by pointing the EHR user to it and perhaps automatically using relevant patient information that might already be in the EHR. 

more at http://www.hitechanswers.net/lesson-clinical-decision-support/

Healthcare providers who access clinical decision support through mHealth platforms are finding a world of information at their fingertips – and they could be saving lives.

Digital technologies are changing the way medical information is gathered and exchanged.  Physicians of all ages and medical subspecialties from across the globe are utilizing tools to discuss potential diagnoses and obtain second opinions.

That’s the takeaway from researchers at the Scripps Research Translational Institute who took a closer look at online crowdsourced consult platforms.

Their conclusion is that these platforms, which include social media networks like SERMO, Medscape and HealthTap, are giving providers quick access to information that’s helping them reduce serious, costly and potentially deadly medical errors.

The study, focusing on an analysis of more than 37,000 active users on the MedScape Consult network between 2015 and 2017, appears in a recent issue of NPJ Digital Medicine.

The research points to the value of a mobile health resource for clinical decision support, giving providers a real-time portal for physician-to-physician engagement. Billed as a source for “the second to hundredth opinion in medicine,” these portals allow providers to gather best practices and apply them quickly, reducing the chances of a clinical error.

The study also points to the changing nature of clinical decision support.The study noted that providers can’t necessarily rely on informal face-to-face consults with colleagues – commonly known as curbside consults – because they’re “frequently inaccurate and incomplete.” Yet they can’t just call up a nearby specialist at a moment’s notice.

The study found that : "At a time when we’re turning to artificial intelligence to help improve diagnostic accuracy, there’s still plenty of room for tapping into human intelligence via such medical consulting platforms, Artificial intelligence has been advocated as the definitive pathway for reducing misdiagnosis, But the study's findings suggest the potential for collective human intelligence, which is algorithm-free and performed rapidly on a voluntary basis, to emerge as a competitive or complementary strategy."