CDC public health datasets and access guide for tribes and tribal epidemiology centers

ph-datasets-tribestecs.pdfData Subject -- Lead CDC Center, Institute, or Office -- Data System or Dataset -- How To Access the Data

Vaccination Hesitation: Investigation Why Parents Decline Pediatric Influenza Vaccines in Juneau, Alaska

The influenza virus is responsible for hundreds of childhood deaths and costs the health care system millions of dollars each year (Hassan, Lewis, Davis, Gebremariam, and Dombkowski, 2009). The influenza vaccine is the most effective intervention for prevention of pediatric influenza, yet many parents decline this vaccine for their children. Studies completed in various geographic locations cite different factors influencing parents who decline pediatric vaccinations. Alaska has the second lowest rate of influenza vaccination in the country (Center for Disease Control [CDC], 2012). The purpose of this project was to understand the factors that influence parental decision to refuse influenza vaccination in Juneau, Alaska. A modified version of the Childhood Influenza Immunization Questionnaire, an instrument based on the Health Belief Model, was utilized to collect data from a convenience sample of parents at a private pediatric practice in Juneau, AK. Statistical analysis revealed the only significant influencing factor on parents’ decisions on whether to vaccinate against influenza was their perception of vaccine risk (p < .001). Information obtained from this study will be used to educate local providers in the community with the goal of enabling said providers to overcome resistance to vaccination hesitancy based on parent perceptions

Health, United States, 2015 : in brief

Health, United States, 2015: In Brief is provided as a companion to the full report. This short report contains summary information on the health of the American people, including mortality and life expectancy, morbidity and risk factors such as cigarette smoking and overweight and obesity, health insurance coverage, access to and utilization of health care, and health expenditures. The At a Glance table and Highlights summarize some of these key indicators at the national level and are followed by 27 figures from Health, United States, 2015, that focus on these topics in addition to this year's Special Feature on racial and ethnic health disparities.CS260383hus15_inbrief.pdf2016736

Health, United States, 2015 : with special feature on racial and ethnic health disparities

Health, United States, 2015 is the 39th report on the health status of the nation and is submitted by the Secretary of the Department of Health and Human Services to the President and the Congress of the United States in compliance with Section 308 of the Public Health Service Act. This report was compiled by the Centers for Disease Control and Prevention's (CDC) National Center for Health Statistics (NCHS).Suggested citation: National Center for Health Statistics. Health, United States, 2015: With Special Feature on Racial and Ethnic Health Disparities. Hyattsville, MD. 2016.hus15.pdf2016736

2023 EIS Conference

Welcome or welcome back. Four years have passed since our last in-person conference of CDC\u2019s Epidemic Intelligence Service (EIS). The COVID-19 pandemic has been hard on everyone and especially for our public health workforce. The EIS classes of 2018, 2019, and 2020 were remarkable for having completed EIS during the pandemic and while transitioning to virtual training. Thank you to our officers for your service under the most challenging of circumstances. And thank you to our EIS alumni, supervisors, and partners for your service and continued support of the EIS program. We are thankful you are back with us at the EIS conference.The conference is a core element of EIS training. It is an opportunity for EIS officers to refine their scientific communication skills, gain experience responding to questions about their work, and share their stories. For all of us, the conference is an opportunity to learn from their analyses, investigations, and practice of consequential epidemiology.Publication date from document properties.https://www.cdc.gov/eis/downloads/eis-conference-2023-508.pd

Prev Chronic Dis

IntroductionMonitoring and understanding population health requires conducting health-related surveys and surveillance. The objective of our study was to assess whether data from self-administered surveys could be collected electronically from patients in urban, primary-care, safety-net clinics and subsequently linked and compared with the same patients\u2019 electronic health records (EHRs).MethodsData from self-administered surveys were collected electronically from a convenience sample of 527 patients at 2 Chicago health centers from September through November, 2014. Survey data were linked to EHRs.ResultsA total of 251 (47.6%) patients who completed the survey consented to having their responses linked to their EHRs. Consenting participants were older, more likely to report fair or poor health, and took longer to complete the survey than those who did not consent. For 8 of 18 categorical variables, overall percentage of agreement between survey data and EHR data exceeded 80% (sex, race/ethnicity, pneumococcal vaccination, self-reported body mass index [BMI], diabetes, high blood pressure, medication for high blood pressure, and hyperlipidemia), and of these, the level of agreement was good or excellent (\u3ba 650.64) except for pneumococcal vaccination (\u3ba = 0.40) and hyperlipidemia (\u3ba = 0.47). Of 7 continuous variables, agreement was substantial for age and weight (concordance coefficients 650.95); however, with the exception of calculated survey BMI and EHR\u2013BMI (concordance coefficient = 0.88), all other continuous variables had poor agreement.ConclusionsSelf-administered and web-based surveys can be completed in urban, primary-care, safety-net clinics and linked to EHRs. Linking survey and EHR data can enhance public health surveillance by validating self-reported data, completing gaps in patient data, and extending sample sizes obtained through current methods. This approach will require promoting and sustaining patient involvement.29346063PMC577430

Rift Valley fever outbreak--Kenya, November 2006-January 2007.

In mid-December 2006, several unexplained fatalities associated with fever and generalized bleeding were reported to the Kenya Ministry of Health (KMOH) from Garissa District in North Eastern Province (NEP). By December 20, a total of 11 deaths had been reported. Of serum samples collected from the first 19 patients, Rift Valley fever (RVF) virus RNA or immunoglobulin M (IgM) antibodies against RVF virus were found in samples from 10 patients; all serum specimens were negative for yellow fever, Ebola, Crimean-Congo hemorrhagic fever, and dengue viruses. The outbreak was confirmed by isolation of RVF virus from six of the specimens. Humans can be infected with RVF virus from bites of mosquitoes or other arthropod vectors that have fed on animals infected with RVF virus, or through contact with viremic animals, particularly livestock. Reports of livestock deaths and unexplained animal abortions in NEP provided further evidence of an RVF outbreak. On December 20, an investigation was launched by KMOH, the Kenya Field Epidemiology and Laboratory Training Program (FELTP), the Kenya Medical Research Institute (KEMRI), the Walter Reed Project of the U.S. Army Medical Research Unit, CDC-Kenya's Global Disease Detection Center, and other partners, including the World Health Organization (WHO) and Médecins Sans Frontières (MSF). This report describes the findings from that initial investigation and the control measures taken in response to the RVF outbreak, which spread to multiple additional provinces and districts, resulting in 404 cases with 118 deaths as of January 25, 2007

Alaska health profile 2001

Each year, the Centers for Disease Control and Prevention (CDC) publishes a State Health Profilefor each state and the District of Columbia. This publication series uses selected \u201chealth statusindicators\u201d to describe the health status of the United States on a state-by-state basis. Thisinformation is presented through user-friendly graphics and narrative interpretation. The series alsohighlights selected demographic information, prevention and control efforts aimed at specific health conditions, and CDC funding for and partnership agreements with all 50 states and the District of Columbia

Pediatr Infect Dis J

Background:Alaska Native infants from the Yukon-Kuskokwim Delta (YKD) experienced respiratory syncytial virus (RSV) hospitalization rates 5 times higher and an RSV season twice as long as the general US infant population. We describe trends in hospitalization rates and seasonality during 18 years of continuous RSV surveillance in this population and explore contributions of climate and sociodemographic factors.Methods:We abstracted clinical and RSV test information from computerized medical records at YKD Regional Hospital and Alaska Native Medical Center from 1994 to 2012 to determine hospitalization rates and RSV season timing. Descriptive village and weather data were acquired through the US Census and Alaska Climate Research Center, University of Alaska, Fairbanks, respectively.Results:During 1994\u20132012, YKD infant RSV hospitalization rates declined nearly 3-fold, from 177 to 65 per 1000 infants/yr. RSV season onset shifted later, from mid October to late December, contributing to a significantly decreased season duration, from 30 to 11 weeks. In a multivariate analysis, children from villages with more crowded households and lacking plumbed water had higher rates of RSV hospitalizations (relative rate, 1.17; P = 0.0005 and relative rate, 1.45; P = 0.0003). No association of temperature or dew point was found with the timing or severity of RSV season.Conclusions:Although the RSV hospitalization rate decreased 3-fold, YKD infants still experience a hospitalization rate 3-fold higher than the general US infant population. Overcrowding and lack of plumbed water were associated with RSV hospitalization. Dramatic changes occurred in RSV seasonality, not explained by changes in climate.20152019-12-26T00:00:00ZCC999999/ImCDC/Intramural CDC HHS/United States26065863PMC6931377876

Evaluating Preventative Care and Post-Hospitalization Primary Care Follow-Up in Adults with Intellectual and/or Developmental Disabilities

Post-Hospitalization Primary Care Follow-Up Abstract Title: Characteristics that are associated with primary care follow-up and discharge summary receipt post-hospitalization in adults with intellectual and/or developmental disabilities. Background: Transition from an inpatient to an outpatient setting is a high risk time for patients. Studies in the general population find that poor post-hospitalization primary care follow-up results in higher rates of readmissions – a widely used indicator of healthcare quality. There is no research that evaluates post-hospitalization primary care follow-up or discharge summary receipt in the IDD population. Objective: To explore the demographic, socioeconomic, and clinical characteristics that are associated with whether an adult with IDD will achieve timely post-hospitalization primary care follow-up. Methods: A cross-sectional study evaluating 788 hospitalizations of adults with IDD from January 1, 2012 to December 31, 2016 and their primary care follow-up at an IDD-specific multi-specialty outpatient facility. Applicable inpatient admissions were identified using Medicare Quality and Resource Use Reports and linked to the outpatient facilities’ electronic medical records in order to capture demographic, socioeconomic, clinical, and follow-up variables on each subject. Results: A total of 788 hospital admissions completed by 341 unique individuals were identified. This population had a high rate of primary care follow-up (94.8%), and hospitalization discharge summary receipt (83.5%) within 30 days. Multivariate regression analysis, which controlled for demographics, living situation, level of intellectual disability, hospital, and principal hospital diagnosis, identified that living in non-group home settings was associated with a lower likelihood of timely primary care follow-up and discharge summary receipt when compared to adults with IDD who live in group homes. This analysis also detected that age over 40 was associated with a lower likelihood or primary care follow-up within 7 days (aOR: 0.2, 95% CI: 0.1-0.8) and non-Caucasian race to be associated with a higher likelihood of primary care follow-up within 14 days (aOR: 2.3, 95% CI: 1.0-5.3). Conclusion: The major variable that predicted timely primary care follow-up and discharge summary receipt was living in a group home. This is most likely due to state-mandated audits of group home policies and procedures. Nevertheless, primary care follow-up for the population evaluated in this study was much better than the general Medicare population. Primary care providers and hospital discharge teams should be cognizant of the challenges and barriers that adults with IDD who live in non-group home settings face. Further research should continue to evaluate the success that group homes have had in post-hospitalization primary care follow-up and communicate their success to other state regulatory groups