The Child Nutrition Program Operations Study II (CN-OPS II) is a multiyear study that provides FNS with information on current state agency and school food authority policies, practices, and needs related to school nutrition service operations, financial management, meal counting, training and professional standards, food service equipment, and technology. 

The Study of Food Safety Needs of Adult Day Care Centers in the Child and Adult Care Food Program report identified and evaluated food safety knowledge gaps and education needs of adult day care center program operators. Overall, this study provides information on knowledge gaps related to food safety practices in adult day care centers and illuminates the best way for center staff to receive future food safety training and information support.

This study provides current information on adoption of scanning technology among small SNAP-authorized retailers to assess readiness for meeting the Farm Bill requirement, barriers and benefits to adopting scanning technologies, and costs for nonadopting retailers to comply with this requirement.

FNS conducted a study of the first two years of this demonstration to describe the implementation process and explore the effects on certification, participation, federal reimbursements, and state administrative costs. This report presents the findings from the first year of the demonstration evaluation, school year 2016–17.

The Evaluation of the School Meal Data Collection Process study describes and evaluates the methodologies and processes used by schools, school food authorities and state agencies to collect and report data on three FNS forms used for the federal school meal programs: the Report of School Program Operations (FNS-10), the SFA Verification Collection Report (FNS-742), and the State Agency Direct Certification Rate Data Element Report (FNS-834). In addition to describing the processes, the study identifies potential sources of error when completing the three forms and provides useful practices and recommendations for improving data collection processes.

This report describes the feasibility of a modeling approach to forecast tiering error rates based on prior data, in lieu of annual assessments of misclassified FDCHs. It presents estimates for forecasted rates and associated improper payments for FDCHs for each fiscal year (FY) from 2016 to 2020. Due to data limitations, the report concludes that building a reliable model is not possible with the currently available data and estimates produced by the models cannot be used for IPERIA reporting.