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All in the Algorithm
Pediatric craniofacial surgeon Anand Kumar's heart goes out to newborns with Pierre Robin sequence, a congenital condition marked by a severely small mandible and a cleft soft palate, putting them at high risk of airway obstruction, as the tongue frequently falls to the back of the throat. Also, the typical small opening in the roof of the mouth may cause choking or regurgitation of liquids through the nose. Needless to say, the condition brings breathing and feeding difficulties too. These patients, stresses Kumar, need prompt multidisciplinary care.
For newborns in the Johns Hopkins Children’s Center’s neonatal intensive care unit (NICU), appropriate consultation most often happens immediately or soon after birth. However, some referrals from other hospitals without craniofacial specialists have been delayed due to miscommunication on either end. Often, the confusion is around who the patient with these anomalies should see: ENT, genetics, plastics, pulmonary?
To ensure appropriate and expeditious referrals in these cases, Kumar and colleagues led the development of a condition-specific algorithmic care model for craniofacial patients. When a referring hospital describes a newborn with a suspected small jaw and cleft palate, for instance, the NICU physician on call searches such signs and symptoms on the algorithm and sends one email that connects with all of the appropriate subspecialists.
“I like the algorithm because it touches on many specialties and is team based, not person based,” says Kumar. “Referring physicians from other hospitals like it too—they’re calling back with new patients because they felt we did a nice job the first time around getting their patient in and appropriately treated. They’re telling us algorithmic care is improving our outcomes and patient satisfaction.”
The other piece of that equation is the Johns Hopkins Cleft and Craniofacial Center, where team members diagnose, treat and study anomalies like Pierre Robin sequence. Relying on the latest technology, including low-dose CT scanners interfaced with 3-D cameras, they have enhanced their diagnostic capability to virtually plan surgical procedures and provide the most appropriate and safest care. Using a dental cone beam CT, for example, they’re able to produce precise 3-D images of a patient’s teeth, soft tissues, nerve paths and bone at lower radiation exposure compared to conventional CT.
“No dental cast models are needed; we’re going pure digital in scanning teeth,” says Kumar. “And the images are 99 percent accurate.”