Article type
Year
Abstract
Background: Cancer disparities exist for American Indian and Alaska Natives (AI/ANs) with some tribes having the highest rates in the US. National efforts to improve access to healthcare may not affect AI/ANs. Current programs have limited resources for cancer prevention, screening and care. Little has been done to coordinate efforts in improving cancer control & prevention in these populations or identify and promote best practices.
Objectives: To identify current AI/AN best practices in cancer program databases and evaluate their relevance and evidence-base regarding cancer control & prevention.
Methods: Known databases for AI/AN cancer control & prevention interventions were search including Cochrane Library, Campbell Library, Research Tested Interventions and Programs (RTIPs) by National Cancer Institute (NCI), the Community Guide for Preventive services from the Centers for Disease Control & Prevention (CDC), and the University of New Mexico (UNM) Native Health Database.
Results: Few programs conducted evaluation necessary to establish them as effective. Identified programs existed for tobacco control interventions. Many programs listed AI/AN as target audiences but did not include over 3% of this population and did not conduct any analysis by race. Some materials and success stories are available through the CDC but insufficient evidence exists to recommend these programs.
Conclusions: A paucity of evidence-based interventions regarding AI/AN cancer control and prevention are available in current databases. Few funding sources are available to address these gaps. Funding to establish and maintain such a database is currently lacking. Health disparities in this population can not be adequately addressed without prioritizing and funding trials for AI/AN populations. Creating a promising practices database may be a significant step forward for AI/AN programs seeking to conduct such trials.
Objectives: To identify current AI/AN best practices in cancer program databases and evaluate their relevance and evidence-base regarding cancer control & prevention.
Methods: Known databases for AI/AN cancer control & prevention interventions were search including Cochrane Library, Campbell Library, Research Tested Interventions and Programs (RTIPs) by National Cancer Institute (NCI), the Community Guide for Preventive services from the Centers for Disease Control & Prevention (CDC), and the University of New Mexico (UNM) Native Health Database.
Results: Few programs conducted evaluation necessary to establish them as effective. Identified programs existed for tobacco control interventions. Many programs listed AI/AN as target audiences but did not include over 3% of this population and did not conduct any analysis by race. Some materials and success stories are available through the CDC but insufficient evidence exists to recommend these programs.
Conclusions: A paucity of evidence-based interventions regarding AI/AN cancer control and prevention are available in current databases. Few funding sources are available to address these gaps. Funding to establish and maintain such a database is currently lacking. Health disparities in this population can not be adequately addressed without prioritizing and funding trials for AI/AN populations. Creating a promising practices database may be a significant step forward for AI/AN programs seeking to conduct such trials.