Background: National administrative healthcare data may be used as a case-finding method for prevalence studies of chronic disease in the United States, but the completeness of ascertainment likely varies depending on the disease under study.
Methods: We used 3 case-finding sources (Medicare, Medicaid, and Veterans Administration data) to estimate the prevalence of amyotrophic lateral sclerosis (ALS) in the United States for 2002-2004, and applied the capture-recapture methodology to estimate the degree of under-ascertainment when relying solely on these sources for case identification.
Results: Case-finding completeness was 76% overall and did not vary by race, but was lower for males (77%) than for females (88%), and lower for patients under age 65 (66%) than patients over age 65 (79%). The uncorrected ALS prevalence ratio was 2.8/100,000 in 2002, 3.3/100,000 in 2003, and 3.7/100,000 in 2004. After correcting for under-ascertainment, the annual prevalence increased by approximately 1 per 100,000 to 3.7/100,000 in 2002 (95% CI 3.66-3.80), 4.4/100,000 in 2003 (95% CI 4.34-4.50), and 4.8/100,000 in 2004 (95% CI 4.76-4.91).
Conclusions: Federal healthcare claims databases ascertained are a very efficient method for identifying the majority of ALS-prevalent cases in the National ALS Registry, and may be enhanced by having patients self-register through the registry web portal.
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http://dx.doi.org/10.1159/000488798 | DOI Listing |
J Med Internet Res
January 2025
Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, Ann Arbor, MI, United States.
Background: Clinical decision support systems leveraging artificial intelligence (AI) are increasingly integrated into health care practices, including pharmacy medication verification. Communicating uncertainty in an AI prediction is viewed as an important mechanism for boosting human collaboration and trust. Yet, little is known about the effects on human cognition as a result of interacting with such types of AI advice.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Psychology, University of Bath, Bath, United Kingdom.
Background: Mental health problems in university students are associated with many negative outcomes, yet there is a gap between need and timely access to help. Single-session interventions (SSIs) are designed to be scalable and accessible, delivering core evidence-based intervention components within a one-off encounter.
Objective: COMET (Common Elements Toolbox) is an online self-help SSI that includes behavioral activation, cognitive restructuring, gratitude, and self-compassion.
JMIR Res Protoc
January 2025
University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States.
Background: Black adults in the United States experience disproportionately high rates of tobacco- and obesity-related diseases, driven in part by disparities in smoking cessation and physical activity. Smartphone-based interventions with financial incentives offer a scalable solution to address these health disparities.
Objective: This study aims to assess the feasibility and preliminary efficacy of a mobile health intervention that provides financial incentives for smoking cessation and physical activity among Black adults.
Vasc Biol
January 2025
K Landers, Psychology, University of Arkansas at Little Rock, Little Rock, United States.
Blood flow restriction exercise (BFRE) is a therapeutic approach traditionally used to facilitate muscular strength and hypertrophy. Emerging evidence has identified its benefits on other systems and metabolic processes. The emphasis of this study was to examine potential impact of BFRE on serum levels of tissue plasminogen activator (tPA).
View Article and Find Full Text PDFJ Med Internet Res
January 2025
NORC at the University of Chicago, Chicago, IL, United States.
Background: Poor health outcomes are well documented among patients with a non-English language preference (NELP). The use of interpreters can improve the quality of care for patients with NELP. Despite a growing and unmet need for interpretation services in the US health care system, rates of interpreter use in the care setting are consistently low.
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