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A Lesson in Clinical Decision Support

A Lesson in Clinical Decision Support | 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. 

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EHR, clinical decision support help identify autism earlier

EHR, clinical decision support help identify autism earlier | healthcare technology |

Researchers from the Regenstrief Institute and Indiana University have demonstrated the potential of an automated system to help primary care physicians screen for autism spectrum disorders (ASDs) more effectively and efficiently, according to an article published in Infants & Young Children.

The work of the research team centered on the implementation of the Child Health Improvement through Computer Automation (CHICA) system, an open source tool that comprises an EHR and aclinical decision support system (CDSS) for pediatric preventive care anddisease management.

“Autism isn’t like strep throat where you can do a quick throat swab and then have a diagnosis,” lead author Nerissa Bauer, MD, of the Regenstrief Institute and Indiana University School of Medicine said last Friday.

“Autism is a behavioral diagnosis and can look very different depending on the child. Some behaviors are subtle, especially early on. CHICA prompts parents to think about whether they have concerns about certain health risks, such as autism, which makes it easier for the doctor to focus on key issues during a hectic visit.”

According to Bauer et al., the purpose of the tool is to address limitations commonly present in primary care practices when it comes to screening children for ASD. “Limited visit time, low reimbursement, logistics of the clinic workflow, and lack of appropriate staff to implement these tools continue to be major barriers to implementing clinical guidelines in primary care practice,” the authors write.

The CHICA system works by producing a personalized 20-question prescreening form in either English or Spanish for the patient linked to the patient’s EMR and completed by the patient’s parents in the waiting at each visit and scanned back into the system. Then at the 24-month visit system scores these results and alerts the physician to intervene if sufficient concerns are raised.
Prior to the implementation of the CHICA system, only eight out of 5,128 children had an ASA ICD-9 billing code assigned to them. During the two-year study (Nov. 15, 2010–July 25, 2012), a total of 857 were deemed eligible for screening with two-thirds (567) having the autism screening instrument, called the Modified Checklist for Autism in Toddlers (M-CHAT), completed.  Of these, CHICA identified 171 (30%) as having concerning results, which led to 73 (43%) of these patients having their physicians receive and respond to an alert, and leading to the following decisions:

• 50 (68%)children were considered not to have an ASD;
• 13 (18%) were referred for a more comprehensive workup;
• 8 (11%) children were suspected of having an ASD, but not referred; and
• 2 (3%) were referred for an audiology evaluation.
Bauer et al. are optimistic that similar approaches to screening for chronic diseases have the potential to improve detection and ensure that proper intervention occurs sooner rather than later.
While the results are encouraging, the willingness of physicians to take the necessary steps in adapting their clinical workflows still remains an obstacle that needs to be overcome.
Mikaila Ludvik's curator insight, November 18, 2013 11:17 AM

Its interesting that studies are coming closer to finding a way to detect Austism earlier than we are able to currently.The sooner autism can be detected, then the sooner that child can get help, which is always a good thing. More research studies like this should be funded and should be happening.

Tech4MD's curator insight, December 27, 2013 2:39 PM

Yes, while the results are encouraging, the willingness of physicians to take the necessary steps in adapting their clinical workflows still remains an obstacle that needs to be overcome.

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