Study suggests analytics, screening tools and EHRs can aid autism treatment
New research is trying to determine if computer automation coupled with clinical decision support software can increase timely screening of autism spectrum disorder.
Autism spectrum disorder (ASD) represents a range of disabilities in speech, social interaction and intellect, and features repetitive movements or behaviors ranging from mild to severe. Although the prevalence of ASD has been increasing in recent decades, primary care physicians may not have a deep understanding of autism and may not routinely screen pediatric patients for its signs.
An article in the Journal JAMA Network.com describes research involving a clinical trial that took place in four primary care practices at Eskenazi Health System in Indianapolis. The trial compared ASD screening rates among 274 children in urban pediatric clinics of an inner-city county hospital with or without a screening module built into an existing clinical decision support system.
Therapies for ASD, in particular the use of applied behavioral analysis, have been shown to be effective. Applied behavioral analysis can result in significant increases in IQ with improved chances of mainstreaming the child in school.
However, the likelihood that a child will benefit from applied behavioral analysis decreases with age, but that’s not a given, because many children are diagnosed and then benefit at an older age. ASD can be diagnosed as early as 16 months, but the mean age in the United States is 4.5 years. That’s why the American Academy of Pediatrics recommends primary care physicians treating toddlers routinely screen for ASD at 18-month and 24-month appointments with doctors.
Several screening tools, some free, are available to primary care physicians. The most widely used screening tool is the 23-item Modified Checklist for Autisim in Toddlers with Follow-up, known as the 20-item M-CHAT-R/F. This instrument has a positive predictive value of 50 percent, can be administered in less than 10 minutes and is easily downloaded from the Internet.
An available computer-based clinical decision support system, called Child Health Improvement through Computer Automation (CHICA), has been shown to improve guideline-based care for a range of clinical purposes.
CHICA communicates with the electronic health record, so when a patient registers, CHICA analyzes the child’s EHR for demographic characteristics, morphometric characteristics, diagnoses and medications, and selects the highest priority yes or no question covering a range of primary care issues for the physician to ask the family.
The questions are displayed on a sheet of scannable paper or an electronic tablet that the family is given to complete in the waiting room. CHICA analyzes responses to physician questions and selects the six most important alerts or reminders for the clinician. These are turned into a “visit agenda” that can be printed on a scannable worksheet or displayed via the electronic health record for the physician.
The clinician responds to alerts and reminders by checking associated boxes in the EHR. These responses further store data that can be used for future decision support.
In total, the automated screening tools were shown to have an effect on the rate of routine ASD screening in general pediatric practice. Screening in the intervention clinics when from 0 percent to 68 percent within six months and reached 100 percent during the two years of the study, and physicians seemed to become accustomed to clinical decision support over time, results show.