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P22 Application of Nutrition Education Informatics to Pennsylvania Food Stamp Nutrition Education Delivery Judy Gromis, MS, RD, Pennsylvania Nutrition Education Tracks, The Pennsylvania State University, 135 East Nittany Avenue, State College, PA 16801, [email protected]; Kimberly Bodes, MS, [email protected]; Denise Wall, MPH, RD, [email protected]; Barbara Lohse, PhD, RD, [email protected] Objective: To develop a web-based reporting system to collect data for process evaluation, federal reporting, and program management. Use of Theory or Research: Nutrition informatics– systematic collection and use of information for nutrition- related decision making– guided this project. Target Audience: Data are collected on Food Stamp Nu- trition Education (FSNE) participants, their nutrition ed- ucation experiences, and value of cost share contributed by local partners. Description: Recent federal mandates require state FSNE programs to report standard programming information. Lo- cal matching funds also must be verified and tracked to secure federal reimbursement. Pennsylvania FSNE data management tasks are substantial given the diversity of local partners who contribute cost share and the variety of nutrition education delivered to participants who span the life cycle from preschoolers to seniors. The Statewide Tech- nical and Administrative Reporting (STAR) system col- lects process evaluation data for federal reporting and pro- gram monitoring purposes, informs outcome evaluation and program planning, and identifies potential training and resource needs of local partners. Data collected on cost share contributions allow effective financial management at both the state and local levels. Evaluation: The STAR system was field tested with local partners in Philadelphia. Repeated quality assurance assess- ments were conducted until system accuracy and reliability were established. User feedback was obtained, and guided system changes to increase data entry efficiency. Statewide implementation followed. Conclusions and Implications: Informatics principles ap- plied to public health nutrition programs can provide state leaders and local partnering agencies with data necessary to meet funding agency reporting requirements, manage pro- grams effectively, and provide quality programming to the target audience. Funded by Food Stamp Nutrition Educa- tion, USDA. P23 Nutrition Classes for People with Limited Resources Noy Rathakette, PhD, Oregon State University Lane County Extension, 950 West 13th Avenue, Eugene, OR 97402 Objective: To deliver nutrition information in order to improve nutrition and health of parents with children, adults, including disable adults with limited resources. Use of Theory or Research: Need to focus on hands-on learning to be able to change behavior. Target Audience: Limited resources parents and disable people who lived in low income housing in Eugene- Springfield, Oregon. They also received some food from Extra Helping Program of Food for Lane County. Description: I taught nutrition in 8 low income housing sites. A series of four nutrition classes were offered in each housing site. I applied the curriculum from “Simple Good Eating” from the University of Minnesota. Evaluation: Participants did pre and post evaluations to see the change in their knowledge. I also visited them after 3-6 months to interview them about their food choices, cook- ing, and their nutrition. Conclusions and Implications: Participants learned better with hands-on activities which helped them visualize the concept of eating more fruits and vegetables; eating less fat, sugar and salt; and increasing more physical activities. Interesting activities kept them engaged in the topics. Cooking and eating together in each class helped them network and be more social. They supported each other in changing behaviors. This helped them continue their good practice even when I finished my classes. P24 Improving the Quality of NEERS5/CRS5 Databases Michelle L. Scott-Pierce, MBA, [email protected], Jamie S. Dollahite, PhD, RD, [email protected], Cornell University, 3M27 Martha Van Rensselaer Hall, Ithaca, NY 14853 Objective: To develop a method for quality improvement of data in Nutrition Education Evaluation and Reporting System 5 (NEERS5) County Reporting Software (CRS5). Use of Theory or Research: This method is based on Total Quality Management (TQM) involving both management and employees in continuous improvement of services. Target Audience: State and local EFNEP and FSNE man- agers. Description: The New York State program has output criteria for county programming that include defined cost/ participant, educator caseload, and graduation rate. To ensure TQM, routine training and support is provided to county staff to make certain output criteria are met and data are consistent and accurate. Quality assurance meth- ods include submission of CRS5 databases quarterly to state staff; Statistical Analysis Software is used to identify data missing or outside expected limits, as well as output data not meeting criteria. A feedback report is sent to county managers for correction and/or clarification. Managers re- spond within 2 weeks. Continued on page S53 S52 Poster Abstracts

P23: Nutrition Classes for People with Limited Resources

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P22 Application of Nutrition EducationInformatics to Pennsylvania Food StampNutrition Education DeliveryJudy Gromis, MS, RD, Pennsylvania Nutrition EducationTracks, The Pennsylvania State University, 135 EastNittany Avenue, State College, PA 16801,[email protected]; Kimberly Bodes, MS, [email protected];Denise Wall, MPH, RD, [email protected];Barbara Lohse, PhD, RD, [email protected]

Objective: To develop a web-based reporting system tocollect data for process evaluation, federal reporting, andprogram management.Use of Theory or Research: Nutrition informatics–systematic collection and use of information for nutrition-related decision making– guided this project.Target Audience: Data are collected on Food Stamp Nu-trition Education (FSNE) participants, their nutrition ed-ucation experiences, and value of cost share contributed bylocal partners.Description: Recent federal mandates require state FSNEprograms to report standard programming information. Lo-cal matching funds also must be verified and tracked tosecure federal reimbursement. Pennsylvania FSNE datamanagement tasks are substantial given the diversity oflocal partners who contribute cost share and the variety ofnutrition education delivered to participants who span thelife cycle from preschoolers to seniors. The Statewide Tech-nical and Administrative Reporting (STAR) system col-lects process evaluation data for federal reporting and pro-gram monitoring purposes, informs outcome evaluation andprogram planning, and identifies potential training andresource needs of local partners. Data collected on costshare contributions allow effective financial management atboth the state and local levels.Evaluation: The STAR system was field tested with localpartners in Philadelphia. Repeated quality assurance assess-ments were conducted until system accuracy and reliabilitywere established. User feedback was obtained, and guidedsystem changes to increase data entry efficiency. Statewideimplementation followed.Conclusions and Implications: Informatics principles ap-plied to public health nutrition programs can provide stateleaders and local partnering agencies with data necessary tomeet funding agency reporting requirements, manage pro-grams effectively, and provide quality programming to thetarget audience. Funded by Food Stamp Nutrition Educa-tion, USDA.

P23 Nutrition Classes for People withLimited ResourcesNoy Rathakette, PhD, Oregon State University LaneCounty Extension, 950 West 13th Avenue, Eugene, OR97402

Objective: To deliver nutrition information in order toimprove nutrition and health of parents with children,adults, including disable adults with limited resources.Use of Theory or Research: Need to focus on hands-onlearning to be able to change behavior.Target Audience: Limited resources parents and disablepeople who lived in low income housing in Eugene-Springfield, Oregon. They also received some food fromExtra Helping Program of Food for Lane County.Description: I taught nutrition in 8 low income housingsites. A series of four nutrition classes were offered in eachhousing site. I applied the curriculum from “Simple GoodEating” from the University of Minnesota.Evaluation: Participants did pre and post evaluations to seethe change in their knowledge. I also visited them after 3-6months to interview them about their food choices, cook-ing, and their nutrition.Conclusions and Implications: Participants learned betterwith hands-on activities which helped them visualize theconcept of eating more fruits and vegetables; eating less fat,sugar and salt; and increasing more physical activities.Interesting activities kept them engaged in the topics.Cooking and eating together in each class helped themnetwork and be more social. They supported each other inchanging behaviors. This helped them continue their goodpractice even when I finished my classes.

P24 Improving the Quality of NEERS5/CRS5DatabasesMichelle L. Scott-Pierce, MBA, [email protected],Jamie S. Dollahite, PhD, RD, [email protected], CornellUniversity, 3M27 Martha Van Rensselaer Hall, Ithaca,NY 14853

Objective: To develop a method for quality improvementof data in Nutrition Education Evaluation and ReportingSystem 5 (NEERS5) County Reporting Software (CRS5).Use of Theory or Research: This method is based on TotalQuality Management (TQM) involving both managementand employees in continuous improvement of services.Target Audience: State and local EFNEP and FSNE man-agers.Description: The New York State program has outputcriteria for county programming that include defined cost/participant, educator caseload, and graduation rate. Toensure TQM, routine training and support is provided tocounty staff to make certain output criteria are met anddata are consistent and accurate. Quality assurance meth-ods include submission of CRS5 databases quarterly to statestaff; Statistical Analysis Software is used to identify datamissing or outside expected limits, as well as output datanot meeting criteria. A feedback report is sent to countymanagers for correction and/or clarification. Managers re-spond within 2 weeks.

Continued on page S53

S52 Poster Abstracts