IntroductionThis review summarizes the current literature for the prevalence and medical costs of noncommunicable chronic diseases among adult Medicaid beneficiaries to inform future program design.MethodsThe databases MEDLINE and CINAHL were searched in August 2016 using keywords, including Medicaid, health status, and healthcare cost, to identify original studies that were published during 2000–2016, examined Medicaid as an independent population group, examined prevalence or medical costs of chronic conditions, and included adults within the age group 18–64 years. The review and data extraction was conducted in Fall 2016–Spring 2017. Disease-related costs (costs specifically to treat the disease) and total costs (all-cause medical costs for a patient with the disease) are presented separately.ResultsAmong the 29 studies selected, prevalence estimates for enrollees aged 18–64 years were 8.8%–11.8% for heart disease, 17.2%–27.4% for hypertension, 16.8%–23.2% for hyperlipidemia, 7.5%–12.7% for diabetes, 9.5% for cancer, 7.8%–19.3% for asthma, 5.0%–22.3% for depression, and 55.7%–62.1% for one or more chronic conditions. Estimated annual per patient disease-related costs (2015 U.S. dollars) were $3,219–$4,674 for diabetes, $3,968–$6,491 for chronic obstructive pulmonary disease, and $989–$3,069 for asthma. Estimated hypertension-related costs were $687, but total costs per hypertensive beneficiary ranged much higher. Estimated total annual healthcare costs were $29,271–$51,937 per beneficiary with heart failure and $11,446–$20,585 per beneficiary with schizophrenia. Costs among beneficiaries with cancer were $29,384–$46,194 for the 6 months following diagnosis.ConclusionsThese findings could help inform the evaluation of interventions to prevent and manage noncommunicable chronic diseases and their potential to control costs among the vulnerable Medicaid population.

Micro-costing data collection tools often used in literature include standardized comprehensive templates, targeted questionnaires, activity logs, on-site administrative databases, and direct observation. These tools are not mutually exclusive and are often used in combination. Each tool has unique merits and limitations, and some may be more applicable than others under different circumstances. Proper application of micro-costing tools can produce quality cost estimates and enhance the usefulness of economic evaluations to inform resource allocation decisions. A common method to derive both fixed and variable costs of an intervention involves collecting data from the bottom up for each resource consumed (micro-costing). We scanned economic evaluation literature published in 2008-2018 and identified micro-costing data collection tools used. We categorized the identified tools and discuss their practical applications in an example study of health interventions, including their potential strengths and weaknesses. Sound economic evaluations of health interventions provide valuable information for justifying resource allocation decisions, planning for implementation, and enhancing the sustainability of the interventions. However, the quality of intervention cost estimates is seldom addressed in the literature. Reliable cost data forms the foundation of economic evaluations, and without reliable estimates, evaluation results, such as cost-effectiveness measures, could be misleading. In this project, we identified data collection tools often used to obtain reliable data for estimating costs of interventions that prevent and manage chronic conditions and considered practical applications to promote their use.

Objective: Significant delays in translating health care–related research into public health programs and medical practice mean that people may not get the best care when they need it. Regarding cardiovascular disease, translation delays can mean lives may be unnecessarily lost each year. To facilitate the translation of knowledge to action, we created a Best Practices Guide for Cardiovascular Disease Prevention Programs. Design: Using the Rapid Synthesis Translation Process and the Best Practices Framework as guiding frameworks, we collected and rated research evidence for hypertension control and cholesterol management strategies. After identifying best practices, we gathered information about programs that were implementing the practices and about resources useful for implementation. Research evidence and supplementary information were consolidated in an informational resource and published online. Web metrics were collected and analyzed to measure use and reach of the guide. Results: The Best Practices Guide was released in January 2018 and included background information and resources on 8 best practice strategies. It was published as an online resource, publicly accessible from the Centers for Disease Control and Prevention Web site in 2 different formats. Web metrics show that in the first year after publication, there were 25 589 Web page views and 2467 downloads. A query of partner use of the guide indicated that it was often shared in partners' own resources, newsletters, and online material. Conclusion: In following a systematic approach to creating the Best Practices Guide and documenting the steps taken in its development, we offer a replicable approach for translating research on health care practices into a resource to facilitate implementation. The success of this approach is attributed to 3 key factors: using a prescribed and documented approach to evidence translation, working closely with stakeholders throughout the process, and prioritizing the content design and accessibility of the final product.