Health Insurance Coverage
Since 2001, the National Center for Health Statistics (NCHS) National Health Interview Survey (NHIS) Early Release Program has furnished selected estimates of health and health care for the civilian noninstitutionalized U.S. population. A NCHS report released in May 2024 provides quarterly estimates of health insurance coverage disaggregated by age group and family income as a percentage of the federal poverty level (FPL) for the civilian noninstitutionalized U.S. population based on data from the July–September 2023 NHIS. Quarterly population estimates are presented of health insurance coverage disaggregated by age group, along with quarterly estimates of health insurance coverage for adults aged 18–64 disaggregated by race and ethnicity. Quarterly estimates of health insurance coverage for adults aged 18–64 are disaggregated by region. Quarterly estimates for October– December 2022 through July–September 2023 also are presented for comparison.
Epidemiology Of Parkinson Disease
Recent decades have shown that epidemiological understanding of Parkinson disease (PD) has evolved significantly. Major discoveries in genetics and large epidemiological investigations have enabled a better understanding of the genetic, behavioral, and environmental factors that play a role in the pathogenesis and progression of this disease. A review appearing in the June 2024 issue of the journal Current Neurology and Neuroscience Reports has an epidemiological update of PD with a particular focus on advances in the last five years of published literature. Included are an overview of PD pathophysiology, followed by a detailed discussion of the known distribution of disease and varied determinants of disease. Investigations of risk factors for PD are described and a critical summary of current knowledge, knowledge gaps, and both clinical and research implications is provided. Recent paradigm shifts in the conceptualization of PD as a biological entity will have an impact on research moving forward and will guide further work in this field.
HEALTH TECHNOLOGY CORNER
Predicting First Time Depression Onset In Pregnancy
Approximately 15% of individuals report depressive symptoms at some point in their pregnancy, with instances of major depression occurring among roughly 12% of pregnancies. A simple survey delivered during the first trimester through digital pregnancy support app MyHealthyPregnancy predicted which mothers went on to develop moderate to severe depression with a high level of accuracy. As reported in a study by University of Pittsburgh investigators published on May 22, 2024 in the Archives of Women’s Health, the approach is considered to be unique because it predicts who is likely to develop depression in the future. A conclusion from the study is that a relatively small amount of self-report data produced a highly predictive model of first time depression among pregnant individuals. The researchers analyzed data from 944 patients who used the app as part of a larger study and did not have a history of depression.
Accuracy Of Online Artificial Intelligence Models In Primary Care Settings
As patients increasingly turn to online resources for supplementary advice, the role of artificial intelligence (AI) in providing accurate and reliable information has emerged. A study described in the June 2024 issue of the American Journal of Preventive Medicine aimed to assess ChatGPT-4’s and Google Bard's capacity to deliver accurate recommendations in preventive medicine and primary care. After reaching a consensus, 28.6% of ChatGPT-4-generated answers were deemed accurate, 28.6% inaccurate, and 42.8% accurate with missing information. In comparison, 53.6% of Bard-generated answers were deemed accurate, 17.8% inaccurate, and 28.6% accurate with missing information. Responses to CDC and immunization-related questions showed notable inaccuracies (80%) in both models, while they also demonstrated potential in offering accurate information in preventive care. Additionally, they brought to light the critical need for regular updates, particularly in the rapidly evolving areas of medicine.