Community Care of North Carolina (CCNC), the primary care case management program for NC Medicaid, found that it needed consistent, structured, and coded data from its community pharmacy partners in the Community Pharmacy Enhanced Services Network (CPESN) in order to support quality metrics. During the initial years of CPESN pharmacy partnerships, community pharmacy encounters with high-risk patients were either not documented, reported using free text, or, most commonly, were hand-entered into a portal which created a workflow burden on service providers. Under a High Impact Pilot grant from the Office of the National Coordinator for Health Information Technology, Lantana worked with CCNC and an initial pair of pharmacy management vendors to establish high-priority reporting requirements while easing the reporting burden on pharmacists.
Looking at the CCNC measures and the data available from the pharmacy systems, we designed a reporting specification for pharmacists based on nationally standardized data elements that would support key quality metrics—the electronic pharmacist care plan or ePhCP. Our strategy bridged the current generation of clinical data standards based on HL7’s Consolidated Clinical Document Architecture (C-CDA) with the emerging generation of Fast Healthcare Interoperability Resources (FHIR). While in pilot, the number of pharmacy system vendor implementers grew from 2 to 22.
- The number of pharmacist care plans submitted to CCNC increased by 350%
- All pharmacist care plans submitted were valid according to the national standard
- The structured data automated reporting of three measures for medication non-adherence within high-risk populations
- Pioneered dual CDA & FHIR development and implementation creating a template for industry migration
- Created the basis for electronic pharmacist care planning across the industry
- Predictable Pipeline for Health Information
Tools and Methods Used:
- Trifolia Workbench and Lantana Validator
- Two-way FHIR/CDA transform
- Data Element Maturity Model
- Data Analysis Methodology