Improving Outcomes in Pediatric Congenital Hypothyroidism Through an Electronic Dashboard: A Quality Improvement Initiative

Congenital hypothyroidism (CH) is a prevalent endocrine disorder that can lead to intellectual disability, psychomotor dysfunction, and impaired growth if not treated promptly. Early diagnosis and consistent monitoring are critical, especially during the first three years of life. We developed a PowerBI dashboard integrated with the electronic medical record (EMR) to track thyroid-stimulating hormone (TSH) levels, clinic visits, and upcoming appointments for patients aged 3 months to 3 years. It enables real-time identification of patients not meeting clinical targets, facilitating timely interventions. Prior to dashboard implementation, 75% of patients achieved two or more normal TSH values annually. One year post-implementation, this figure rose to 91%, and further refinements increased it to 93% the following year. The dashboard also improved clinic efficiency by streamlining communication and reducing manual data tracking. This quality improvement (QI) initiative shows the effectiveness of EMR-integrated dashboards in improving clinical outcomes and operational efficiency. The model is scalable and adaptable for other chronic pediatric conditions requiring regular follow-up and laboratory monitoring. Our findings support broader adoption of similar PowerBI dashboards in Endocrinology and other specialties focused on chronic disease management. Highlights Electronic dashboard implementation significantly improved clinical outcomes for pediatric patients with congenital hypothyroidism (CH) at Phoenix Children’s Hospital. TSH monitoring compliance increased from 75% to 93% over two years following dashboard deployment. The dashboard enabled real-time tracking of lab results, appointments, and patient demographics, streamlining care coordination. Quality improvement methodology using Plan-Do-Study-Act (PDSA) cycles facilitated iterative enhancements to the dashboard and clinical workflow. The project demonstrates a scalable model for other institutions to improve care for chronic pediatric conditions requiring frequent follow-up and lab monitoring.