| 1137 |
Centers for Disease Control and Prevention |
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Expanding Primary Care Capacity to Treat Hepatitis C VirusInfection Through an Evidence-Based Care Model - Arizona and Utah,2012-2014 |
Kiren Mitruka, MD1, Karla Thornton, MD2, Susanne Cusick3, Christina Orme3, Ann Moore4, Richard A. Manch, MD4, Terry Box, MD3, Christie Carroll2, Deborah Holtzman, PhD1, John W. Ward, MD1 (Author affiliations at end of text). |
| primary care providers | 0.369506 |
| treatment | 0.267371 |
| Project ECHO | 0.713995 |
| chronic HCV infection | 0.356934 |
| HCV infection | 0.941631 |
|
| primary care | 0.826029 |
| teleECHO clinics | 0.280125 |
| rural settings | 0.209845 |
| primary care clinicians | 0.745976 |
|
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Centers for Disease Control and Prevention |
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Mumps | CDC Features |
Mumps vaccine is the best way to protect your child against mumps, a contagious disease that can cause serious complications. |
| college | 0.233111 |
| health insurance | 0.380947 |
| best way | 0.430966 |
| insurance provider | 0.296669 |
| program | 0.233109 |
| children | 0.321615 |
| long-lasting problems | 0.305609 |
| highly vaccinated U.S. | 0.418681 |
| swollen jaw | 0.313968 |
| long-term health problems | 0.398518 |
| rubella | 0.25424 |
| diseases | 0.239648 |
| puffy cheeks | 0.319614 |
| effects | 0.237217 |
| viral encephalitis | 0.316183 |
| mumps vaccine | 0.821166 |
| rare cases | 0.298914 |
| high vaccination coverage | 0.392112 |
| mumps | 0.987273 |
| child | 0.39332 |
| doses | 0.250447 |
| mumps outbreaks | 0.701938 |
| vaccines | 0.313758 |
| fever | 0.238637 |
| cause | 0.224854 |
|
| sudden deafness | 0.314551 |
| immunization records | 0.323964 |
| MMRV vaccine | 0.420166 |
| trade school | 0.301263 |
| muscle aches | 0.315344 |
| combination vaccine | 0.517956 |
| healthcare professionals | 0.298044 |
| eligible children | 0.304683 |
| higher risk | 0.295749 |
| health insurance plans | 0.374364 |
| salivary glands | 0.319639 |
| mumps cases | 0.572791 |
| Talk | 0.241521 |
| varicella | 0.223804 |
| doctor | 0.253158 |
| rash | 0.223153 |
| MMR vaccine. Learn | 0.435683 |
| state VFC coordinator | 0.377972 |
| close-contact settings | 0.30226 |
| international travelers | 0.299874 |
| appetite | 0.222208 |
| measles | 0.252434 |
| MMR vaccine | 0.678751 |
| contagious disease | 0.421704 |
|
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| 4596 |
Centers for Disease Control and Prevention |
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Photograph of lobster tank (700W x 933H) |
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| 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 |
|
| 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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| 7415 |
Centers for Disease Control and Prevention |
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Emergency and Environmental Health Services: Improving the Practice of Environmental Health |
NCEH provides leadership to promote health & quality of life by preventing or controlling those diseases or disabilities resulting from interaction between people and the environment. Site has information/education resources on a broad range of topics, including asthma, birth defects, radiation, sanitation, lead in blood, and more. |
| cruise ship industry | 0.582846 |
| Health Services advances | 0.641406 |
| Technical expertise | 0.446088 |
| Surveillance data | 0.439076 |
| sanitation inspections | 0.470169 |
| chemical warfare agents | 0.997802 |
| environmental health programs | 0.604549 |
| Monitors gastrointestinal illnesses | 0.569315 |
| highest risk children | 0.552676 |
| Safe Water | 0.442415 |
| foodborne illnesses | 0.455429 |
| National Center | 0.461629 |
| cruise ship | 0.604093 |
| construction inspections | 0.436695 |
| Vessel Sanitation Program | 0.588778 |
| U.S. disposal facility | 0.573039 |
| emergency preparedness | 0.461868 |
| chemical weapons elimination | 0.853621 |
| safe disposal | 0.459915 |
| Blue Grass | 0.43691 |
| response efforts | 0.453888 |
| practice-based research | 0.447491 |
| limited resources | 0.439847 |
| lead exposure | 0.448234 |
| Poisoning Prevention Program | 0.614092 |
|
| highly hazardous chemicals | 0.559811 |
| environmental public health | 0.680933 |
| Control Communicable Diseases | 0.541855 |
| Environmental Health/Division | 0.486092 |
| United States | 0.461337 |
| prevents childhood | 0.459838 |
| program’s resources | 0.460408 |
| Weapons Elimination team | 0.58017 |
| health departments | 0.473101 |
| funded program | 0.477027 |
| U.S. Army | 0.445945 |
| public health | 0.796779 |
| Lead surveillance | 0.464119 |
| recreational water | 0.437027 |
| cruise ships | 0.465012 |
| nonstockpile chemical warfare | 0.614546 |
| environmental health practitioners | 0.602843 |
| Healthy community design | 0.582912 |
| public health practices | 0.588732 |
| Public Health Service | 0.583703 |
| childhood lead poisoning | 0.86423 |
| independent oversight | 0.446432 |
| lead poisoning prevention | 0.852702 |
| technical guidance | 0.458386 |
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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.
|
| 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 |
|
| 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 |
null |
| múltiples métodos | 0.902521 |
| Salud Pública | 0.773353 |
|
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Centers for Disease Control and Prevention |
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2014 Ebola Outbreak in West Africa - Outbreak Distribution Map |
null |
| World Health Organization | 0.386427 |
| Ebola virus transmission | 0.551441 |
| Sierra Leone | 0.215804 |
| countries | 0.250096 |
| large proportion | 0.203997 |
| public health authorities | 0.71591 |
| Ebola cases | 0.275819 |
|
| country classification | 0.532038 |
| widespread transmission | 0.983761 |
| incubation periods | 0.204118 |
| international air travel | 0.358638 |
| control measures | 0.865347 |
| new cases | 0.205876 |
| active surveillance | 0.216651 |
|
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The Immunization Baby Book (4:16) |
For parents there's no greater joy then watching your child grow up happy and healthy. That's why most parents choose the safe, proven protection of vaccines. |
| National Center | 0.51992 |
| baby book | 0.522184 |
| Immunization | 0.441879 |
| vaccines babies | 0.579397 |
| greater joy | 0.547986 |
| childhood diseases | 0.517617 |
| protection | 0.345664 |
| visit https://www.cdc.gov/vaccines/parents | 0.524881 |
| feedback | 0.342894 |
| preparedness topics | 0.794775 |
| variety | 0.394424 |
|
| children | 0.392653 |
| safety | 0.394208 |
| Respiratory Diseases | 0.51405 |
| safe | 0.345741 |
| different audiences | 0.779248 |
| public health professionals | 0.976221 |
| CDC-TV videos | 0.679996 |
| comment | 0.34489 |
| information | 0.342774 |
| power | 0.343494 |
| age | 0.343218 |
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Association Between User-Generated Commuting Data andPopulation-Representative Active Commuting Surveillance Data - FourCities, 2014-2015 | MMWR |
The Morbidity and Mortality Weekly Report (MMWR) Series is prepared by the Centers for Disease Control and Prevention (CDC). |
| transportation officials | 0.494218 |
| active transportation programs | 0.560702 |
| U.S. cities | 0.523482 |
| higher block group | 0.497114 |
| GPS-based commuting data | 0.495315 |
| rank block groups | 0.496131 |
| number | 0.487534 |
| population density | 0.593834 |
| GPS-tracked data sources | 0.50622 |
| active transportation data | 0.667143 |
| non-work active transportation | 0.499146 |
| active transportation | 0.953258 |
| public health surveillance | 0.572828 |
| ACS samples | 0.500699 |
| block group estimates | 0.500222 |
| User-generated GPS data | 0.504512 |
| block group level | 0.504577 |
| user-generated active transportation | 0.65995 |
| block groups | 0.795709 |
| population-representative active transportation | 0.513961 |
| general U.S. population | 0.482884 |
| census block groups | 0.517093 |
| population-representative commuting data | 0.495192 |
| public health practice | 0.479923 |
| ACS active commuters | 0.800198 |
|
| ACS commuter variables | 0.502229 |
| application users | 0.509091 |
| GPS-tracked active commuters | 0.547925 |
| traditional active transportation | 0.559652 |
| active transportation surveillance | 0.640386 |
| GPS-tracked commuters | 0.628709 |
| GPS-tracked commuting data | 0.497135 |
| ACS cycles | 0.495666 |
| GPS-tracked active transportation | 0.52346 |
| general population | 0.493775 |
| higher population density | 0.476658 |
| block group | 0.770412 |
| user-generated data | 0.482316 |
| public health | 0.609312 |
| block group population | 0.548516 |
| data collection | 0.506339 |
| in-person data collection | 0.480745 |
| physical activity | 0.51674 |
| Census block group | 0.508739 |
| San Francisco | 0.579883 |
| user-generated GPS-tracked | 0.502146 |
| ACS respondents | 0.484546 |
| transportation surveillance systems | 0.500767 |
| public health priority | 0.477993 |
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