| 7121 |
Centers for Disease Control and Prevention |
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CDC - Preventing Chronic Disease: Volume 9, 2012: 11_0311 |
The objective of this study was to identify the number of people with diabetes from a diabetes DataLink developed as part of the SUPREME-DM (SUrveillance, PREvention, and ManagEment of Diabetes Mellitus) project, a consortium of 11 integrated health systems that use comprehensive EHR data for research. |
| diabetes identification | 0.765247 |
| Kaiser Permanente Hawaii | 0.550204 |
| data | 0.799193 |
| multiple health systems | 0.577056 |
| diabetes DataLink | 0.791154 |
| diabetes mellitus | 0.751003 |
| EHR data | 0.609631 |
| Henry Ford Health | 0.611646 |
| health administrative data | 0.554313 |
| accurate diabetes registries | 0.719193 |
| laboratory test results | 0.603154 |
| diabetes cases | 0.68164 |
| possible diabetes | 0.655968 |
| care management studies | 0.542253 |
| diabetes prevalence | 0.690503 |
| health care delivery | 0.575476 |
| SUPREME-DM DataLink criteria | 0.545175 |
| Kaiser Permanente Colorado | 0.613122 |
| gestational diabetes | 0.741736 |
| diabetes registries | 0.736427 |
| laboratory results data | 0.541177 |
| incident diabetes | 0.737534 |
| comparative effectiveness research | 0.654371 |
| complete EHR data | 0.549935 |
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| administrative data | 0.64788 |
| Kaiser Permanente regions | 0.559555 |
| diabetes database | 0.645217 |
| health care systems | 0.635698 |
| diabetes incidence | 0.682673 |
| health systems | 0.670621 |
| true diabetes incidence | 0.679103 |
| Diabetes Care | 0.645917 |
| diabetes case status | 0.695494 |
| diabetes duration | 0.683337 |
| integrated health systems | 0.653062 |
| health | 0.743001 |
| diabetes surveillance | 0.650956 |
| diabetes diagnosis | 0.717072 |
| incident cases | 0.699994 |
| diabetes researchers | 0.664847 |
| comprehensive EHR data | 0.609401 |
| multisite diabetes registries | 0.721459 |
| SUPREME-DM DataLink | 0.73137 |
| Geisinger Health | 0.541014 |
| health plan | 0.542056 |
| diabetes | 0.905873 |
| adult diabetes prevalence | 0.672867 |
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| 7999 |
Centers for Disease Control and Prevention |
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South Africa - FELTP Graduates Are Ready to Serve Public Health in South Africa |
CDC partners in South Africa with government and parastatal agencies, private institutions, universities and non-governmental organizations to improve the country’s public health foundation, to prevent transmission of HIV, to provide care and treatment for those who are already infected with HIV, and to strengthen laboratory capacity.
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| typhoid fever | 0.565286 |
| Laboratory Training Program | 0.642786 |
| multidrug-resistant hospital-acquired infections | 0.63682 |
| Communicable Diseases | 0.568359 |
| Sub-Saharan Africa | 0.585447 |
| data gathering | 0.572414 |
| South Africa Field | 0.666202 |
| National Health Laboratory | 0.64806 |
| Seymour Williams | 0.574151 |
| North West | 0.688392 |
| surveillance data | 0.566084 |
| graduate Thejane Motladiile | 0.617089 |
| SA-FELTP residents | 0.584345 |
| Gauteng province | 0.569271 |
| North West Provincial | 0.619784 |
| SA-FELTP graduates | 0.640915 |
| Southern African Journal | 0.615652 |
| Western Cape provinces | 0.618197 |
| SA-FELTP work | 0.570924 |
| nosocomial outbreaks | 0.587838 |
| new MPH diploma | 0.611626 |
| Resident Advisor | 0.570084 |
| South Africa | 0.840127 |
| well-functioning public health | 0.666203 |
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| public health awareness | 0.681702 |
| MDR Acinetobacter baumannii | 0.618824 |
| hospital-acquired infections | 0.643063 |
| public health policy | 0.678924 |
| public health priorities | 0.661294 |
| multi-pathogen diarrheal disease | 0.624686 |
| important work | 0.568469 |
| Limpopo province | 0.572865 |
| important health messages | 0.63699 |
| regional public health | 0.65191 |
| synthesis skills | 0.571735 |
| national departments | 0.566806 |
| public health professionals | 0.650388 |
| public health | 0.904961 |
| National Institute | 0.570315 |
| multi-drug resistant TB | 0.630761 |
| critical data | 0.575659 |
| North West province | 0.621628 |
| hospital’s ICU | 0.564097 |
| n’t respect boundaries | 0.636631 |
| non-federal site | 0.566538 |
| infection control procedures | 0.613671 |
| Free State province | 0.624464 |
| CDC South Africa | 0.652492 |
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Centers for Disease Control and Prevention |
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Integración de un diseño multimodal a la Encuesta Nacional Telefónica de Marcación Aleatoria |
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| múltiples métodos | 0.902521 |
| Salud Pública | 0.773353 |
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Centers for Disease Control and Prevention |
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Ionizing Radiation and Diagnostic Exams - Health Communication |
Gateway to Health Communication and Social Marketing Practice - Radiation: Ionizing Radiation and Diagnostic Exams |
| abdominal pains | 0.303353 |
| large number | 0.303387 |
| diagnostic exams | 0.612018 |
| PET scans | 0.299379 |
| radiation experts | 0.439376 |
| diagnostic examinations | 0.313324 |
| Medical Imaging | 0.38357 |
| mental retardation | 0.311805 |
| diagnostic scan uses | 0.381939 |
| children | 0.257902 |
| medical condition | 0.298832 |
| large amounts | 0.308633 |
| diagnostic tests | 0.310735 |
| Lauren | 0.263485 |
| benefit | 0.233585 |
| fluoroscopy exams | 0.333829 |
| tests | 0.321831 |
| older age | 0.301614 |
| skin burns | 0.301312 |
| ionizing radiation | 0.720967 |
| medical tests | 0.304098 |
| fetus | 0.243534 |
| CT scans | 0.316144 |
| parents | 0.252245 |
| benefits | 0.233872 |
|
| radiation increases | 0.457743 |
| harm | 0.243207 |
| medically necessary imaging | 0.371699 |
| high levels | 0.302893 |
| possible concussion | 0.309191 |
| radiation exposure | 0.470887 |
| CT/CAT scans | 0.299438 |
| correct diagnosis | 0.295349 |
| medical x-rays | 0.324829 |
| old football player | 0.379248 |
| adverse health effects | 0.399046 |
| small increase | 0.29807 |
| diagnostic ionizing radiation | 0.620639 |
| recent football game | 0.37844 |
| CT scan | 0.388284 |
| James | 0.306685 |
| beneficial uses | 0.316143 |
| younger age | 0.303734 |
| greater opportunity | 0.30391 |
| exposures | 0.249511 |
| medical test | 0.301558 |
| radiation | 0.917366 |
| higher lifetime risk | 0.390118 |
| future pregnancies | 0.3028 |
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Centers for Disease Control and Prevention |
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Oregon: Using PRAMS Data for Legislation to Support Breastfeeding in the Workplace - PRAMS - Reproductive Health |
Oregon: Using PRAMS Data for Legislation to Support Breastfeeding in the Workplace, Pregnancy Risk Assessment Monitoring System |
| American Academy | 0.326924 |
| Ron Wyden | 0.297664 |
| Patient Protection | 0.30249 |
| Human Services | 0.435761 |
| Breast Milk | 0.3177 |
| U.S. Department | 0.427488 |
| building managers | 0.311255 |
| Family Physicians | 0.331723 |
| American College | 0.330675 |
| state legislature | 0.307445 |
| Oregon’s U.S. | 0.327055 |
| state employees | 0.303301 |
| Oregon law | 0.3278 |
| private area | 0.296134 |
| study group | 0.507592 |
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| Oregon House | 0.332978 |
| Oregon PRAMS data | 0.949675 |
| health organizations | 0.333926 |
| Affordable Care Act | 0.465653 |
| public restroom | 0.300644 |
| Surgeon General | 0.449979 |
| Division staff study | 0.485235 |
| Oregon women | 0.372691 |
| 30-minute break period | 0.470999 |
| Oregon Bureau | 0.319047 |
| breastfeeding | 0.469692 |
| large employers | 0.307169 |
| breastmilk.1 Oregon PRAMS | 0.651217 |
| Oregon Public Health | 0.514071 |
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| 11320 |
Centers for Disease Control and Prevention |
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Organization Assessment Tools |
This page provides tools and resources for researching and evaluating health literacy practice. |
| Public Health | 0.508141 |
| usable health information | 0.560751 |
| develop materials | 0.513186 |
| Literacy Universal Precautions | 0.703116 |
| HHS Office | 0.468457 |
| Index Score Sheet | 0.505015 |
| Group Health Research | 0.547014 |
| Health Literate Organizations | 0.558089 |
| Health Information Technology | 0.560749 |
| HHS AHRQ National | 0.539696 |
| Achieving Organizational Change | 0.50407 |
| health care research | 0.548172 |
| health literacy skills | 0.642049 |
| Universal Precautions Toolkit | 0.610984 |
| Health Centers | 0.510955 |
| Federal Plain Language | 0.516394 |
| Minority Health | 0.498427 |
| Federal usability information | 0.512931 |
| AHRQ Health Literacy | 0.753337 |
| Disease Control | 0.507141 |
| multiple stakeholders | 0.462881 |
| Health Technology Assessment | 0.551646 |
| address its health | 0.52245 |
| Unity Point Health | 0.553031 |
|
| Healthcare Facility Literacy-Friendly | 0.518192 |
| current situation | 0.463838 |
| Healthcare Research | 0.624138 |
| NIH National Library | 0.570253 |
| General Assessment Tools | 0.527238 |
| Medicine Evidence-based Practice | 0.499767 |
| health literacy issues | 0.732673 |
| Health Literacy Environment | 0.655657 |
| Mass Media News | 0.497318 |
| honest assessment | 0.477976 |
| Emergency Risk Communication | 0.501291 |
| Develop Materials section | 0.511261 |
| Health Literacy Universal | 0.729734 |
| Plain Language Action | 0.51623 |
| health literacy | 0.939868 |
| plain language | 0.550249 |
| Emergency Risk Messaging | 0.496698 |
| Limited Literacy | 0.541553 |
| Linguistically Appropriate Services | 0.506534 |
| National Culturally | 0.461563 |
| training opportunities | 0.460365 |
| Information Network | 0.476231 |
| Health Literacy Assessment | 0.671265 |
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Centers for Disease Control and Prevention |
Html |
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When Do You Step In and Assist? Personal ProtectiveEquipment (PPE) | Ebola Hemorrhagic Fever | CDC |
null |
| hand signals | 0.558795 |
| certain steps | 0.615541 |
| healthcare provider | 0.966209 |
| doffing process | 0.805886 |
| unnecessary errors | 0.605804 |
| red flag words | 0.992464 |
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| physical contact | 0.63181 |
| doffing assistant | 0.867653 |
| equipment | 0.263469 |
| assistance | 0.509497 |
| proper protocols | 0.589828 |
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Centers for Disease Control and Prevention |
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2009-10 State, Regional, and National Influenza Vaccination Report II |
FluVaxView 2009-10 State, Regional, and National Vaccination Report II - CDC |
| Microsoft PowerPoint file | 0.346591 |
| Early Vaccination Coverage | 0.457406 |
| influenza vaccination coverage | 0.498149 |
| Population Early Season | 0.493784 |
| Microsoft Word file | 0.347432 |
| Vaccination Trends | 0.441 |
| Women Vaccination Coverage | 0.52868 |
| Single Season Report | 0.379374 |
| Season Vaccination Coverage | 0.786328 |
| vaccination coverage | 0.965024 |
| Influenza Season Vaccination | 0.528269 |
| General Population Coverage | 0.475544 |
| hhs region | 0.349546 |
| Key Findings | 0.40274 |
| General Population | 0.791489 |
| 2011-12 Report | 0.361344 |
| National Immunization Survey-Flu | 0.347983 |
| Microsoft Excel file | 0.346305 |
| Live Birth Data | 0.34618 |
| Tweet Share Compartir | 0.350603 |
| Population Vaccination Coverage | 0.662003 |
| page options Skip | 0.355241 |
| different file formats | 0.34748 |
| Pregnant Women Vaccination | 0.526533 |
| Apple Quicktime file | 0.346665 |
|
| Season General Population | 0.580203 |
| General Population Vaccination | 0.665396 |
| (Flu) | 0.35602 |
| Behavioral Risk Factor | 0.346546 |
| Adobe PDF file | 0.34627 |
| 2012-13 Report | 0.361431 |
| Early Season Vaccination | 0.615584 |
| 2016-17 Trend Report | 0.400813 |
| Search Form Controls | 0.399308 |
| Health Care Personnel | 0.598433 |
| 2016-17 Key Findings | 0.35096 |
| 2016-17 Report | 0.362522 |
| NIS-Flu Influenza Data | 0.457541 |
| Local Areas | 0.388433 |
| General Population Place | 0.47699 |
| General Population NHIS | 0.475003 |
| level influenza vaccination | 0.461112 |
| Search Controls | 0.353702 |
| Mid-Season Flu Vaccination | 0.487798 |
| 2013-14 Report | 0.382475 |
| Vaccination Coverage Dashboard | 0.55595 |
| Download Report Data | 0.367552 |
| report | 0.443332 |
| Flu Vaccination Coverage | 0.562035 |
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Centers for Disease Control and Prevention |
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WHO Region of the Americas (AMR) 2011-2012 |
Overview of the CDC Influenza Division International Program WHO Region of the Americas (AMR), its objectives and goals, and contains downloadable annual reports on supported countries. |
| Global Disease Detection | 0.695255 |
| Global Influenza Surveillance | 0.823888 |
| severe influenza | 0.699996 |
| real-time RT-PCR | 0.674756 |
| Influenza Surveillance Specialist | 0.767544 |
| Post influenza pandemic | 0.753719 |
| Disease Control | 0.807309 |
| El Salvador | 0.735814 |
| Nationwide Enhanced SARI | 0.701617 |
| CDC Influenza Division | 0.743846 |
| PAHO Nationwide Enhanced | 0.821401 |
| pandemic influenza preparedness | 0.755881 |
| PAHO | 0.856885 |
| virologic surveillance systems | 0.662492 |
| World Health Organization | 0.845958 |
| seasonal influenza | 0.700613 |
| risk communication | 0.676348 |
| PAHO training materials | 0.744217 |
| public health emergencies | 0.694479 |
| sari surveillance | 0.890565 |
| PAHO Region | 0.7182 |
| Influenza Division | 0.821065 |
| influenza surveillance | 0.859134 |
| American Health Organization | 0.942806 |
| International Health Regulations | 0.716964 |
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| influenza | 0.952769 |
| national SARI surveillance | 0.692958 |
| U.S. Centers | 0.80934 |
| novel influenza | 0.753618 |
| National Influenza Centers | 0.810572 |
| Pan American Health | 0.943415 |
| Costa Rica | 0.66778 |
| pandemic influenza | 0.86855 |
| sentinel surveillance activities | 0.657147 |
| technical assistance | 0.70598 |
| technical cooperation | 0.655863 |
| public health | 0.800746 |
| health care | 0.706186 |
| PAHO missions | 0.702366 |
| novel influenza strains | 0.753425 |
| sentinel surveillance | 0.676417 |
| quality sentinel surveillance | 0.660658 |
| influenza data analysis | 0.714951 |
| influenza cooperative agreements | 0.770712 |
| SARI Surveillance Protocol | 0.762543 |
| local influenza labs | 0.733509 |
| novel influenza vaccines | 0.732966 |
| 2009 influenza pandemic | 0.750526 |
| Dominican Republic | 0.729436 |
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Centers for Disease Control and Prevention |
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CDC Recommends All Nursing Homes Implement Core Elements to Improve Antibiotic Use |
CDC public health news, press releases, government public health news, medical and disease news, story ideas, photos. |
| health risk | 0.366292 |
| large health systems | 0.407605 |
| antibiotic-resistant infections | 0.455353 |
| new action | 0.362289 |
| new strategies | 0.360434 |
| nursing home residents | 0.448337 |
| Disease Control | 0.370175 |
| antibiotic stewardship activities | 0.735702 |
| CMS deputy administrator | 0.407009 |
| frequently prescribed medications | 0.425635 |
| Antibiotic Resistance Solutions | 0.571384 |
| nursing home leadership | 0.439233 |
| CDC’s recommendation | 0.404052 |
| practical ways | 0.3635 |
| CDC Director Tom | 0.451073 |
| C. difficile infections | 0.432147 |
| step-wise manner | 0.360575 |
| antibiotic stewardship program | 0.744265 |
| companion checklist | 0.360313 |
| nursing staff | 0.381382 |
| acute care hospitals | 0.425295 |
| CDC medical epidemiologist | 0.437051 |
| New recommendations | 0.369096 |
| antibiotics | 0.453911 |
| important protections | 0.362723 |
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| nursing homes | 0.893532 |
| year.1 Antibiotics | 0.417295 |
| antibiotic stewardship efforts | 0.605627 |
| long-term care | 0.438808 |
| long-term care settings | 0.408837 |
| Combating Antibiotic-resistant Bacteria | 0.416668 |
| wrong drug | 0.365029 |
| Core Elements | 0.612227 |
| antibiotic resistance | 0.578902 |
| antibiotic use protocols | 0.516017 |
| home antibiotic stewardship | 0.632499 |
| new resource | 0.372047 |
| core element | 0.360905 |
| Nursing Homes expand | 0.469812 |
| long-term care facilities | 0.411486 |
| nursing home | 0.54321 |
| antibiotic stewardship | 0.920196 |
| antibiotic prescribing practices | 0.626429 |
| adverse events | 0.368761 |
| Indian Health Service | 0.407701 |
| antibiotic monitoring | 0.518374 |
| Drug expertise | 0.362637 |
| CDC’s Core | 0.388883 |
| National Action Plan | 0.40216 |
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