Abstract
This brief highlights the major strategies, lessons learned, and outcomes from South Carolina’s experience during the quality demonstration funded by the Centers for Medicare & Medicaid Services (CMS) through the Children’s Health Insurance Program Reauthorization Act of 2009 (CHIPRA) from February 2010 to February 2016.
South Carolina’s Goals: Improve the quality of care for children by: 1) helping practices build quality improvement capacity by using quality measures, implementing the medical home model, and integrating physical and mental health services 2) Using electronic health records (EHRs) to calculate and report quality measures for practices in order to guide QI efforts
Insights Results
Overview of model
Using a learning collaborative, South Carolina provided 18 child-serving primary care practices with technical assistance to implement quality improvement (QI) activities, strengthen their medical home features and integrate physical and mental health
South Carolina developed a screening protocol that included 6 developmental and psychosocial screenings for well-child visit; the learning collaboratives provided trainings in screenings, guidance on accessing community resources and information on reimbursement procedures
Key takeaways/implications
After the learning collaborative, practices showed: 1) Improvements on 16 of 21 Child Core Set measures; 2) Increased adoption of mental health and developmental screenings; and 3) More consistent development of care plans for patients with behavioral health issues
Demonstration staff reported that practices consequently increased families’ access to care, provided oral health preventive services more regularly and improved adherence to national guidelines for asthma, obesity and ADD
Practices appreciated the flexibility to establish their own QI priorities and placed a high value on learning from other practices
Challenges: the State struggled to link EHR and administrative data to produce practice-level quality reports because of: 1) The diversity of EHR products used by practices; 2) The labor required to develop the infrastructure and functionality needed to transfer data from EHRs to the state; and 3) Data inconsistency and completeness
