TASI/PHIDC in collaboration with SAS, hosted workshops and capacity building sessions in SAS at the University of Hawaii and remotely. This included high level overviews and hands on activities using various software components and codes techniques. In, January 2019 TASI/PHIDC hosted the Hands-on Visualization Workshop where participants could use own data and work with SAS experts on best way to generate or modify visualization of data. November 2018 SAS Suite Demonstration including an overview of the SAS education analytics suite (EAS) and their new platform Viya which has integrations with other programming languages such as R and Python. In November 2018 SAS Health Sector Solutions including how SAS can be used for population health analysis & health outcomes and public health reporting & transparency. 


In 2017, TASI/PHIDC provided training to the Guam Community Health Centers (CHCs) and CNMI Commonwealth Healthcare Corporation (CHCC) in R, an open source statistical software, which can be used to build analytic capacity in the Pacific Region.  Building upon a data science framework, training sessions were held in-person and via distance learning.  The main focus of the training was to introduce the R programming language, learn methods for data cleansing and manipulation, conduct descriptive statistics and bivariate analysis and techniques for visualization.


In 2017, the CNMI and Guam Medicaid programs submitted a joint expression of interest to receive Technical Assistance (TA) for data analytics.  TASI/PHIDC provides support for the Medicaid Innovation Accelerator Program (IAP) for Data Analytics TA provided by the CMS Center for Medicaid and CHIP Services (CMCS) and the Center for Medicare & Medicaid Innovation (CMMI).  The objectives of the IAP Data Analytics TA are to improve the health and health care of Medicaid beneficiaries through improvements in data management and analytics.  The main areas of focus are on Medicaid managed care encounter data requirements for risk adjustment, risk adjustment models and quality measures.

For more information about the Medicaid IAP for Data Analytics TA Program, please visit: