It is estimated that close to 143,000 Americans will be diagnosed with colorectal cancer (CRC) that about 51,000 Americans will die from CRC in 2013. This makes CRC the second leading cause of cancer deaths in the country, and the third most diagnosed. With early stage diagnosis, the outcome is favorable, and the survival rate is close to 90%. Yet, the predicted number of deaths is roughly 3.5 times more than anticipated were the disease detected early. A primary reason for the discrepancy is the lack of adherence to the screening guidelines set forth by the U.S. Preventive Services Task Force (USPSTF) which recommends screening for all patients between 50 and 75 years of age, using one of the three screening methods: Fecal Occult Blood Test, flexible sigmoidoscopy, or colonoscopy. Within the population at risk, only 58.6% adhere to the guidelines. The rate drops to 46.5% in the Hispanic population, who also suffer greater mortality compared to age and stage matched individuals. Innovative strategies are needed to address low screening rates in, in particular among Hispanics. The primary objective of this proposal is to develop, test and determine the feasibility of implementing a bilingual, culturally tailored and theory-based decision-support intervention targeting low literacy Hispanic populations, to facilitate high quality informed decision making at the point of care for patients, in order to increase the uptake of CRC screening. We apply new decision -theoretic methods relying on the concepts of non-additive integration, to help patients make better-informed decisions pertaining to CRC screening. Because of the ubiquitous and pervasive nature of informatics, an informatics-based decision aid system is an ideal vector for such an intervention. We propose to develop a web-based, open- source software delivered on touch screen computers which 1.) Provides culturally tailored and theory-based education on CRC and screening. 2) Provides an interactive, explicit preference clarification exercise incorporating key test attributes;3.) Computes the non-additive measures based on individual preferences, and provides decision-making guidelines for the patient and the treating physician;and 4.) Links the patient's decision directly into the EMR. We propose to recruit 140 Hispanic patients and 20 providers from two primary care clinics in order to pilot and test the usability of the software, the intervention, gather data on the feasibility o integrating it into clinical practice and to garner information about its potential effect on screening uptake, patient provider interaction and clinic processes. The central hypothesis of our research is that an intervention based on proper decision-making tools (e.g. based on recent research in decision theory), within a computing infrastructure will increase the awareness of the population at risk, especially Hispanics, will facilitate the decision-making process, will yield a higher rate of screening and general adherence to USPSTF guidelines for CRC, and will lead to higher early detection rates, and thus higher actual survival rates. This project will provide vital information for the development of an R01 grant to conduct a multi- site intervention to improve CRC screening rates among Hispanic patients across the US.

Public Health Relevance

The primary goal of this project is to develop a novel and highly innovative web-based intervention, to help patients make better informed decisions pertaining to colorectal cancer. We aim at improving the knowledge and understanding of the disease and its detection methods, in particular among the Hispanics, who remain largely under-screened.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21CA178506-01A1
Application #
8690320
Study Section
Special Emphasis Panel (ZCA1)
Program Officer
Chou, Wen-Ying
Project Start
2014-04-01
Project End
2016-03-31
Budget Start
2014-04-01
Budget End
2015-03-31
Support Year
1
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Texas Tech University
Department
Family Medicine
Type
Schools of Medicine
DUNS #
City
Lubbock
State
TX
Country
United States
Zip Code
79430