coordinated program research projects

1
Body Mass Index and Co-Morbidities Generate Revenue for Health Care Facilities Author(s): N. Matyas; Nutrition Services, Hazleton General Hospital, Hazleton, PA Learning Outcome: To identify the steps involved in documenting patient’s Body Mass Index and comorbidities to increase reimbursement dollars. Healthcare funding is changing in America. Administrators are looking for ways to add more money to the bottom line so they can redistribute those funds and create more services for the community. Dietitians can help improve reimbursement and generate revenue for healthcare facilities where every dollar counts. A team of nurses, dietitians and billing coders evaluated the coding and billing processes. They determined that documenting Body Mass Index (BMI) and corresponding co-morbidities could realize increased payment. The project evaluated the cost effectiveness of documenting BMI and co-morbidities to increase hospital reimbursements with an interdisciplinary team approach. Body mass index and co-morbidities provide a measurement as a reliable indicator of health status. BMI was included in the medical record either calculated by the dietitian or electronically. The physician was educated to provide a current or past history of malnutrition or morbid obesity. The coder then determined if additional monies can be realized by physician co-morbidity documentation. A BMI over 40 can be considered a complicating co-morbidity using the code V 85.4 for morbid obesity. A BMI under 19 can also generate revenue with documentation of malnutrition using the code V 85.0. Coding experts assisted physicians to ensure proper documentation. Dietitians can play an active role in collaborating with physicians, nursing, and coders to increase reimbursement and improve the bottom line for administrators. Funding Disclosure: None Determinant Factors of Food Consumption in Low Income Rural Communities Author(s): S. McWhinney, 1 A. McDonald, 1 C. Outley, 2 E. McKyer 3 ; 1 Agriculture, Nutrition & Human Ecology, Prairie View A&M University, Prairie View, TX, 2 Texas A&M University, College Station, TX, 3 Division of Health Education, Dept of Health & Kinesiology, Texas A&M University, College Station, TX Learning Outcome: Participants will be able to identify and understand some of the factors affecting food consumption practices of residents living in rural communities. Healthy food consumption remains one of the most important components in maintaining a healthy lifestyle. Segregation of communities due to low income or rural location can significantly affect the nutritional intake of residents. A total of one hundred low income parents with children in the fourth grade were selected from four adjoining rural communities to participate in this study. Participants were solicited via signage provided in both Spanish and English. Selection of final participants was conducted by purposive sampling. Twelve focus groups of four to twelve participants each were conducted to determine the factors influencing their food consumption practices. Focus group sessions were conducted in a neutral setting and lasted for approximately 120 minutes. The focus groups included one parent per family and consisted of males and females. Participants were African Americans and Hispanic Americans, and all were in the lower income category. Data collected from focus groups were transcribed and entered into Atlas Ti for analysis. Results indicated that decision on what to eat were based on a variety of factors including culture, family preferences, food cost, time, season, and familiarity with the food. Surprisingly, all the groups indicated that children in charge of making food decisions had a significant impact on what the family consumed. Findings indicate that low income rural families face many challenges in regard to thier nutritional intake. Funding Disclosure: Funding for this project was made possible by 1P20MD0002295 from the National Center on Minority Health and Health Disparities. Coordinated Program Research Projects Author(s): C. S. McCarroll, M. Penumetcha; Nutrition, Georgia State University, Atlanta, GA Learning Outcome: Participant will be able to identify a method to meet Coordinated Program Outcome CP 1.5. Need or purpose of project: This project fulfills the 2008 Eligibility Requirements and Accreditation Standards for Coordinated Programs (CP) for Outcome 1.5: ”Conduct research projects using appropriate research methods, ethical procedures and statistical analysis. Setting for use: CP students meet weekly with area dietetic interns for skills development sessions. Unique characteristics: The competency was completed during a series of four didactic sessions, in addition to time for completing the research project. Project steps included: Identifying nutrients/foods with sub-optimal intakes through a literature review Developing a food frequency questionnaire (FFQ) to capture the intakes of the suboptimal nutrients/foods Collecting data using both their FFQ and the gold standard FFQ Validating the FFQ using standard statistical methods Target characteristics of target audience: CP students and dietetic interns Evaluation: The students/interns presented their research at two different sessions and were evaluated by faculty and program directors. Objectives for the first student presentations were to describe: How and why they chose a particular nutrient/food to survey Components of the FFQ including types of foods, portion sizes, and demographic information Plans to implement the survey, including sample size and administration plans Objectives for the second presentation were to demonstrate ability to: Calculate descriptive data for the FFQ study and interpret results Calculate parameters of validation such as sensitivity, specificity, positive negative predictive value Calculate correlation coefficients and interpret findings Funding Disclosure: None Comparison of a Historical Food Frequency Questionnaire with a Three-Day Diet Record Author(s): L. S. Brown, 1 D. M. Wolongevicz, 1 S. M. Karl, 2 M. J. Pencina, 2 R. W. Kimokoti, 3 R. B. D’Agostino, 2 B. E. Millen 1 ; 1 Nutrition, Simmons College, Boston, MA, 2 Mathematics and Statistics, Boston University, Boston, MA, 3 Family Medicine, Boston University School of Medicine, Boston, MA Learning Outcome: The participant will learn about the existence of the USDA trends database for analyzing historical nutrient intake data and be able to determine if this tool could be useful for their own research. Background: In the mid-1980s, the Framingham Heart Study reintroduced methods to evaluate dietary exposures in the Framingham Offspring/Spouse (FOS) cohort. Several assessment tools were administered at exam 3 (1984-88) including a three-day food record and the Framingham food frequency questionnaire (FFQ). The aim of this validation study was to investigate the relative ability of a newly created historic FFQ database derived from the 1985 USDA Survey Nutrient Database for Trends Analysis to estimate nutrient profiles in this cohort. Methods: Nutrient profiles generated by the newly created historic FFQ database were compared with profiles created in the early 1990s for the exam 3 food records. Population means, Pearson correlations, and interquintile movement were calculated. Results: The FFQ demonstrated the ability to estimate population means of most nutrients within 10 to 20 percent and ranked subjects into comparable quintiles with severe misclassification being under 5 percent for all nutrients. Deattenuated energy adjusted correlations for men ranged from 0.24 for zinc to 0.65 for grams of alcohol with an overall mean correlation of 0.40. Energy adjusted correlations for women ranged from 0.20 for sodium to 0.67 for grams of alcohol with an overall mean correlation of 0.39. Conclusion: These results demonstrate that the newly created historic nutrient database for the exam 3 Framingham FFQ is a suitable tool for assessing the dietary intake of major nutrients within the Framingham cohort. This historic database may be used to study potential relationships between nutrient intake as measured by the FFQ and risk of disease development. Funding Disclosure: This work was supported by the National Heart, Lung and Blood Institute’s Framingham Heart Study (Contract No. N01-HC-25195). MONDAY, NOVEMBER 8 POSTER SESSION: SCIENCE/EDUCATION/MANAGEMENT/FOODSERVICE/CULINARY/RESEARCH Journal of the AMERICAN DIETETIC ASSOCIATION / A-77

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MONDAY, NOVEMBER 8

POSTER SESSION: SCIENCE/EDUCATION/MANAGEMENT/FOODSERVICE/CULINARY/RESEARCH

ody Mass Index and Co-Morbidities Generate Revenue forealth Care Facilities

uthor(s): N. Matyas; Nutrition Services, Hazleton Generalospital, Hazleton, PA

earning Outcome: To identify the steps involved in documentingatient’s Body Mass Index and comorbidities to increaseeimbursement dollars.

ealthcare funding is changing in America. Administrators areooking for ways to add more money to the bottom line so they canedistribute those funds and create more services for the community.ietitians can help improve reimbursement and generate revenue forealthcare facilities where every dollar counts. A team of nurses,ietitians and billing coders evaluated the coding and billingrocesses. They determined that documenting Body Mass IndexBMI) and corresponding co-morbidities could realize increasedayment.

he project evaluated the cost effectiveness of documenting BMI ando-morbidities to increase hospital reimbursements with annterdisciplinary team approach. Body mass index and co-morbiditiesrovide a measurement as a reliable indicator of health status. BMIas included in the medical record either calculated by the dietitianr electronically. The physician was educated to provide a current orast history of malnutrition or morbid obesity. The coder thenetermined if additional monies can be realized by physiciano-morbidity documentation. A BMI over 40 can be considered aomplicating co-morbidity using the code V 85.4 for morbid obesity.

BMI under 19 can also generate revenue with documentation ofalnutrition using the code V 85.0. Coding experts assisted

hysicians to ensure proper documentation.

ietitians can play an active role in collaborating with physicians,ursing, and coders to increase reimbursement and improve theottom line for administrators.

unding Disclosure: None

Funding Disclosure: None

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eterminant Factors of Food Consumption in Low Income Ruralommunities

uthor(s): S. McWhinney,1 A. McDonald,1 C. Outley,2 E. McKyer3;Agriculture, Nutrition & Human Ecology, Prairie View A&M University,rairie View, TX, 2Texas A&M University, College Station, TX, 3Divisionf Health Education, Dept of Health & Kinesiology, Texas A&Mniversity, College Station, TX

earning Outcome: Participants will be able to identify and understandome of the factors affecting food consumption practices of residents livingn rural communities.

ealthy food consumption remains one of the most important componentsn maintaining a healthy lifestyle. Segregation of communities due to lowncome or rural location can significantly affect the nutritional intake ofesidents. A total of one hundred low income parents with children in theourth grade were selected from four adjoining rural communities toarticipate in this study. Participants were solicited via signage providedn both Spanish and English. Selection of final participants was conductedy purposive sampling. Twelve focus groups of four to twelve participantsach were conducted to determine the factors influencing their foodonsumption practices. Focus group sessions were conducted in a neutraletting and lasted for approximately 120 minutes. The focus groupsncluded one parent per family and consisted of males and females.articipants were African Americans and Hispanic Americans, and allere in the lower income category. Data collected from focus groups were

ranscribed and entered into Atlas Ti for analysis. Results indicated thatecision on what to eat were based on a variety of factors includingulture, family preferences, food cost, time, season, and familiarity withhe food. Surprisingly, all the groups indicated that children in charge ofaking food decisions had a significant impact on what the family

onsumed. Findings indicate that low income rural families face manyhallenges in regard to thier nutritional intake.

unding Disclosure: Funding for this project was made possible byP20MD0002295 from the National Center on Minority Health and Healthisparities.

oordinated Program Research Projects

uthor(s): C. S. McCarroll, M. Penumetcha; Nutrition, Georgia Stateniversity, Atlanta, GA

earning Outcome: Participant will be able to identify a method to meetoordinated Program Outcome CP 1.5.

eed or purpose of project: This project fulfills the 2008 Eligibilityequirements and Accreditation Standards for Coordinated Programs (CP) forutcome 1.5: ”Conduct research projects using appropriate research methods,

thical procedures and statistical analysis.

etting for use: CP students meet weekly with area dietetic interns for skillsevelopment sessions.

nique characteristics: The competency was completed during a series of fouridactic sessions, in addition to time for completing the research project. Projectteps included:

dentifying nutrients/foods with sub-optimal intakes through a literature review

eveloping a food frequency questionnaire (FFQ) to capture the intakes of theuboptimal nutrients/foods

ollecting data using both their FFQ and the gold standard FFQ

alidating the FFQ using standard statistical methods

arget characteristics of target audience: CP students and dietetic interns

valuation: The students/interns presented their research at two differentessions and were evaluated by faculty and program directors. Objectives for therst student presentations were to describe:

ow and why they chose a particular nutrient/food to survey

omponents of the FFQ including types of foods, portion sizes, and demographicnformation

lans to implement the survey, including sample size and administration plans

bjectives for the second presentation were to demonstrate ability to:

alculate descriptive data for the FFQ study and interpret results

alculate parameters of validation such as sensitivity, specificity, positiveegative predictive value

alculate correlation coefficients and interpret findings

omparison of a Historical Food Frequency Questionnaire with ahree-Day Diet Record

uthor(s): L. S. Brown,1 D. M. Wolongevicz,1 S. M. Karl,2 M. J. Pencina,2

. W. Kimokoti,3 R. B. D’Agostino,2 B. E. Millen1; 1Nutrition, Simmons College,oston, MA, 2Mathematics and Statistics, Boston University, Boston, MA,

Family Medicine, Boston University School of Medicine, Boston, MA

earning Outcome: The participant will learn about the existence of theSDA trends database for analyzing historical nutrient intake data and be able

o determine if this tool could be useful for their own research.

ackground: In the mid-1980s, the Framingham Heart Study reintroducedethods to evaluate dietary exposures in the Framingham Offspring/Spouse

FOS) cohort. Several assessment tools were administered at exam 3 (1984-88)ncluding a three-day food record and the Framingham food frequencyuestionnaire (FFQ). The aim of this validation study was to investigate theelative ability of a newly created historic FFQ database derived from the 1985SDA Survey Nutrient Database for Trends Analysis to estimate nutrientrofiles in this cohort.

ethods: Nutrient profiles generated by the newly created historic FFQatabase were compared with profiles created in the early 1990s for the exam 3ood records. Population means, Pearson correlations, and interquintile

ovement were calculated.

esults: The FFQ demonstrated the ability to estimate population means ofost nutrients within 10 to 20 percent and ranked subjects into comparable

uintiles with severe misclassification being under 5 percent for all nutrients.eattenuated energy adjusted correlations for men ranged from 0.24 for zinc to.65 for grams of alcohol with an overall mean correlation of 0.40. Energydjusted correlations for women ranged from 0.20 for sodium to 0.67 for gramsf alcohol with an overall mean correlation of 0.39.

onclusion: These results demonstrate that the newly created historic nutrientatabase for the exam 3 Framingham FFQ is a suitable tool for assessing theietary intake of major nutrients within the Framingham cohort. This historicatabase may be used to study potential relationships between nutrient intakes measured by the FFQ and risk of disease development.

unding Disclosure: This work was supported by the National Heart, Lungnd Blood Institute’s Framingham Heart Study (Contract No. N01-HC-25195).

Journal of the AMERICAN DIETETIC ASSOCIATION / A-77