View source for Validating a guidelines based asthma decision support system: step one

== Introduction ==

This study used Global Initiatives for Asthma (GINA) guidelines incorporated within a Computerized Decision Support System to assess the accuracy of the CDSS compared with expert assessment for the diagnosis of the severity of asthma.

== Subjects ==

A convenience sample of 82 consecutive patients seen in an asthma clinic. Thirteen patients were excluded due to inaccurate documentation of asthma severity leaving a total of 69 patients.

== Methods ==

Categories were collapsed to include dichotomous groups of mild and severe. Mild asthma included mild intermittent asthma and mild persistent asthma.  Severe asthma consisted of moderate persistent and severe persistent asthma.  It was suggested these groupings would likely discriminate between those requiring subspecialty care.  Data entered into the CDSS included symptoms and a peak expiratory flow rate before and after albuterol.  Clinicians were given the same information and blinded to the CDSS results.

== Results ==

The accuracy of the CDSS was 91% for recognizing severe asthma with a sensitivity of 0.96, a specificity of 0.73, positive predictive value 0.93 and negative predictive value of 0.85.
Discussion ==

The CDSS was able to distinguish severe from mild asthma.  The authors point out that since this patients attended an asthma clinic, the findings may not be generalizable.  They also question the validity of using asthma clinicians as a gold standard.

== Comments ==

Most asthma guidelines use a variety of levels of severity and by dichotomizing this decision it may limit the usefulness of using this CDSS in diagnosing and following patients whose treatment may vary with severity.  Other guidelines due have a gradation of treatment based both on severity of symptoms and frequency of symptoms.  As mentioned, however, this may be a useful technique to discriminate those who need specialized care.

==Related References ==
<ref name="tamblyn, 2015">Tamblyn et al. Evaluating the impact of an integrated computer-based decision support with person-centered analytics for the management of asthma in primary care: a randomized controlled trial. J Am Med Inform Assoc. 2015: Feb.
http://jamia.oxfordjournals.org.ezproxyhost.library.tmc.edu/content/early/2015/02/09/jamia.ocu009</ref>



[[category: BMI-512-W-08]]
[[Category: Reviews]]