| 1303 |
Centers for Disease Control and Prevention |
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Do you know someone with sickle cell disease? | CDC Features |
Find out how teachers and others can help children with this sickle cell disease. |
| red blood cells | 0.721483 |
| health education | 0.382002 |
| Healthy red blood | 0.474289 |
| CDC | 0.335739 |
| sickle cells | 0.449671 |
| Birth Defects | 0.380896 |
| health problem | 0.387822 |
| lifelong disabilities | 0.383234 |
| sickle cell disease | 0.864855 |
| Disease Control | 0.3862 |
| children | 0.352683 |
| new booklet | 0.412524 |
| school staff | 0.479156 |
| blood flow | 0.398413 |
| Statistical Brief | 0.383971 |
| National Center | 0.381729 |
| school personnel | 0.39614 |
| classroom setting | 0.391535 |
| small blood vessels | 0.610064 |
| daily life | 0.39324 |
| hospital stays | 0.383786 |
| acute chest syndrome | 0.457332 |
| condition | 0.332985 |
| health problems | 0.395429 |
| education outcomes | 0.391484 |
|
| Developmental Disabilities | 0.37779 |
| United States | 0.384615 |
| constant shortage | 0.391982 |
| students | 0.398824 |
| red blood cell | 0.481107 |
| C-shaped farm tool | 0.463443 |
| major public health | 0.451531 |
| U.S. Hospitals | 0.38044 |
| teachers | 0.368627 |
| KB | 0.343294 |
| Blood Disorders | 0.389959 |
| health care | 0.385539 |
| Healthcare Research | 0.37916 |
| Cell Disease Patients | 0.460322 |
| pain | 0.32866 |
| blood disorder | 0.395049 |
| Utilization Project | 0.384777 |
| people | 0.341147 |
| stroke | 0.33019 |
| SCD | 0.987235 |
| average life expectancy | 0.45252 |
| financial cost | 0.381829 |
| information | 0.328328 |
| ways SCD | 0.727543 |
|
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| 5614 |
Centers for Disease Control and Prevention |
Html |
en |
Kerosene - NIOSH Pocket Guide to Chemical Hazards |
null |
| MPEG | 0.378858 |
| search | 0.263099 |
| PDF | 0.261307 |
| PPT | 0.446092 |
|
| DOC | 0.368812 |
| information | 0.262482 |
| different file formats | 0.938484 |
| page | 0.276773 |
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| 6807 |
Centers for Disease Control and Prevention |
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Summary of Notifiable Diseases --- May 13, 2011 |
Persons using assistive technology might not be able to fully access information in this file. For assistance, please send e-mail to: mmwrq@cdc.gov. |
| CDC | 0.535106 |
| data | 0.58573 |
| surveillance information systems | 0.461334 |
| disease reporting | 0.421229 |
| nationally notifiable diseases | 0.528874 |
| public health authorities | 0.439023 |
| seasonal influenza viruses | 0.461051 |
| Notifiable disease reports | 0.458593 |
| CDC programs | 0.428809 |
| notifiable conditions | 0.416316 |
| public health surveillance | 0.631571 |
| state health departments | 0.517705 |
| national public health | 0.438312 |
| additional information | 0.409915 |
| infectious notifiable diseases | 0.454317 |
| seasonal influenza virus | 0.42261 |
| seasonal influenza | 0.528472 |
| public health emergencies | 0.410715 |
| ethnicity data | 0.415303 |
| surveillance case definitions | 0.426315 |
| health surveillance data | 0.443152 |
| hantavirus pulmonary syndrome | 0.421832 |
| health surveillance case | 0.424403 |
| 2009 pandemic | 0.440149 |
|
| reportable disease lists | 0.42086 |
| reported event | 0.412339 |
| notifiable disease cases | 0.49751 |
| influenza-associated pediatric mortality | 0.481416 |
| notifiable infectious disease | 0.452175 |
| nationally notifiable disease | 0.454457 |
| United States | 0.965663 |
| novel influenza | 0.513298 |
| health surveillance information | 0.41876 |
| notifiable diseases | 0.805035 |
| different CDC programs | 0.428141 |
| notifiable infectious diseases | 0.86565 |
| National Notifiable Diseases | 0.58456 |
| pandemic influenza | 0.444033 |
| reportable disease list | 0.427369 |
| State Reportable Conditions | 0.408046 |
| seasonal influenza infection | 0.421524 |
| public health | 0.803725 |
| cases | 0.647882 |
| Notifiable Diseases Surveillance | 0.60129 |
| Electronic Disease Surveillance | 0.411859 |
| certain notifiable diseases | 0.442428 |
| Health Surveillance Program | 0.41737 |
| potential PHEIC | 0.407865 |
|
CLICK HERE |
| 9537 |
Centers for Disease Control and Prevention |
Html |
en |
Preventing Chronic Disease | PCD Recognizes Outstanding Student Research: Patel et al on Emergency Medical Services Capacity for Prehospital Stroke Care in North Carolina - CDC |
This week, Preventing Chronic Disease (PCD) publishes the winning submission in the journal’s third annual Student Research Paper Contest, “Emergency Medical Services Capacity for Prehospital Stroke Care in North Carolina,” by Mehul D. Patel and colleagues. |
| North Carolina | 0.992246 |
| public health researchers | 0.78079 |
| Dr Wayne Rosamond | 0.604495 |
| stroke signs | 0.580922 |
| student papers | 0.562802 |
| PCD editorial board | 0.614117 |
| Preventing Chronic Disease | 0.580521 |
| health outcomes | 0.853519 |
| Health Promotion | 0.544457 |
| Disease Control | 0.565625 |
| stroke care capacity | 0.683435 |
| Global Public Health | 0.695123 |
| public health systems | 0.783291 |
| prehospital stroke screening | 0.665485 |
| stroke mortality | 0.657767 |
| surveillance data | 0.519639 |
| PCD Student Research | 0.625877 |
| EMS stroke care | 0.699834 |
| EMS systems | 0.598234 |
| event outcomes | 0.557504 |
| health outcome data | 0.656501 |
| Mail Stop F-68 | 0.568326 |
| Prehospital Stroke Care | 0.71091 |
| external data sources | 0.602288 |
| Research Paper Contest | 0.776832 |
|
| data highlights | 0.517664 |
| Deputy Associate Director | 0.568543 |
| Chronic Disease | 0.665478 |
| Mr Patel | 0.645118 |
| Medical Services Capacity | 0.645607 |
| patient outcomes | 0.547643 |
| EMS education | 0.540088 |
| emergency medical services | 0.797515 |
| public health professionals | 0.696534 |
| public awareness | 0.529434 |
| stroke care | 0.733042 |
| service protocols | 0.564047 |
| epidemiology student | 0.524581 |
| public health | 0.974639 |
| health care | 0.561268 |
| PCD’s effort | 0.564507 |
| public health programs | 0.652911 |
| annual Student Research | 0.626425 |
| proxy outcome measures | 0.573927 |
| Mehul D. Patel | 0.673202 |
| Chronic Disease Prevention | 0.584559 |
| EMS capacity | 0.558434 |
| Student Research Paper | 0.774786 |
| Samuel F. Posner | 0.571891 |
|
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| 9810 |
Centers for Disease Control and Prevention |
Html |
en |
Hantavirus - U.S. HPS Cases, by State of Exposure |
null |
| States | 0.38185 |
| MPEG | 0.441083 |
| USA | 0.370785 |
| PDF | 0.370014 |
| PPT | 0.488895 |
|
| Total Cases | 0.696395 |
| presumed exposure | 0.846838 |
| DOC | 0.434539 |
| unknown exposure | 0.798909 |
| different file formats | 0.92522 |
|
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| 12086 |
Centers for Disease Control and Prevention |
Html |
en |
HAN Archive - 00372|Health Alert Network (HAN) | Enhanced Airport Entry Screening |
Health Alert Network (HAN). Provided by the Centers for Disease Control and Prevention (CDC). |
| Ebola epidemic | 0.446534 |
| CDC Health Alert | 0.526065 |
| enhanced entry screening | 0.704908 |
| CDC | 0.606964 |
| United States | 0.890511 |
| Guinea | 0.550956 |
| Sierra Leone | 0.966744 |
| active post-arrival monitoring | 0.837228 |
| public health authorities | 0.683888 |
| Ebola cases | 0.601027 |
| U.S. airports | 0.376059 |
| HAN Advisory | 0.37878 |
| international partners | 0.375098 |
| muscle pain | 0.369465 |
| technical support | 0.372913 |
| post-arrival monitoring measures | 0.426768 |
| Disease Control | 0.379285 |
| Mali | 0.68962 |
| risk level | 0.371766 |
| New York JFK | 0.566712 |
| twice-daily temperature | 0.454462 |
| air travelers | 0.430137 |
| local health departments | 0.550062 |
| Ebola exposure assessments | 0.632501 |
|
| World Health Organization | 0.456363 |
| current epidemic | 0.376701 |
| global emergency response | 0.438559 |
| recent days. | 0.371205 |
| U.S. government agencies | 0.436679 |
| body fluids | 0.368995 |
| public health officials | 0.45072 |
| people | 0.378497 |
| travelers | 0.576562 |
| local public health | 0.550478 |
| Liberia | 0.494246 |
| final destination | 0.37189 |
| enhanced screening | 0.378381 |
| Atlanta Hartsfield-Jackson | 0.377306 |
| entry screening activities | 0.557139 |
| symptom checks | 0.449527 |
| West Africa | 0.443686 |
| possibility such persons | 0.368907 |
| additional precautions | 0.376313 |
| high risk | 0.372992 |
| PM ET | 0.382205 |
| Ebola | 0.696499 |
| Mali. CDC | 0.436414 |
|
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| 13172 |
Centers for Disease Control and Prevention |
Html |
en |
Using Electronic Clinical Quality Measure Reporting forPublic Health Surveillance |
Dawn Heisey-Grove, MPH1, Hilary K. Wall, MPH2, Amy Helwig, MD3, Janet S. Wright, MD2 (Author affiliations at end of text). |
| certified EHR technology | 0.554543 |
| incentive program cqms | 0.626196 |
| data | 0.591651 |
| health care provider | 0.645952 |
| patient health information | 0.503025 |
| health care agencies | 0.512322 |
| public health improvement | 0.503069 |
| incentive program | 0.788117 |
| Hearts CQMs | 0.495137 |
| original EHR | 0.505315 |
| public health surveillance | 0.508383 |
| health care providers | 0.899072 |
| blood pressure values | 0.507271 |
| blood pressure | 0.928557 |
| population health | 0.497858 |
| health care services | 0.5369 |
| National Quality Forum | 0.528158 |
| patients | 0.532772 |
| individual health care | 0.511558 |
| blood pressure control | 0.873096 |
| eligible health care | 0.626476 |
| primary care provider | 0.512732 |
| Federal public health | 0.497364 |
| electronic health record | 0.516651 |
| population-level quality data | 0.493412 |
|
| sensitive health information | 0.509029 |
| Health Information Technology | 0.603569 |
| electronic CQM data | 0.580447 |
| EHR data | 0.575059 |
| certified EHR | 0.578393 |
| optional CQMs | 0.493811 |
| health care practice | 0.524757 |
| EHR Incentive Program | 0.648705 |
| public health concern | 0.554679 |
| key public health | 0.506981 |
| incentive program CQM | 0.597833 |
| EHR systems | 0.556222 |
| health care | 0.952534 |
| public health | 0.664053 |
| health care systems | 0.524296 |
| clinical performance | 0.493837 |
| additional CQMs | 0.495543 |
| greater EHR | 0.531266 |
| health data | 0.506687 |
| health insurance plan | 0.495265 |
| local public health | 0.498407 |
| local health information | 0.499357 |
| EHR implementation | 0.507311 |
| Medicare EHR Incentive | 0.645437 |
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| 14249 |
Centers for Disease Control and Prevention |
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Increase in Reported Prevalence of Microcephaly in InfantsBorn to Women Living in Areas with Confirmed Zika VirusTransmission During the First Trimester of Pregnancy - Brazil, 2015| MMWR |
The Morbidity and Mortality Weekly Report (MMWR) Series is prepared by the Centers for Disease Control and Prevention (CDC). |
| overall microcephaly birth | 0.410435 |
| Zika virus | 0.922437 |
| widespread transmission | 0.24613 |
| average estimated pregnancy | 0.248485 |
| average head circumference | 0.245885 |
| pregnant women | 0.331313 |
| Brazil | 0.323497 |
| Northeast region states | 0.251841 |
| Aedes mosquitoes | 0.273152 |
| Zika virus RNA | 0.297732 |
| infants | 0.262918 |
| annual mean number | 0.246996 |
| Pernambuco | 0.263737 |
| Brazil Ministry | 0.25444 |
| pregnancy | 0.279228 |
| ad hoc | 0.41646 |
| Zika virus disease | 0.491629 |
| General Coordination | 0.245868 |
| mean number | 0.257308 |
| highest prevalence rates | 0.252209 |
| transcription–polymerase chain reaction | 0.27525 |
| public health practice | 0.247846 |
| live births | 0.320492 |
| Northeast region | 0.279395 |
|
| Zika virus transmission | 0.740338 |
| laboratory-confirmed Zika virus | 0.438017 |
| case definition | 0.284174 |
| rash illness | 0.365145 |
| American Health Organization | 0.308669 |
| earlier Zika virus | 0.281301 |
| maternal Zika virus | 0.282082 |
| critical Zika virus | 0.281405 |
| head circumference | 0.385456 |
| febrile rash illness | 0.364 |
| laboratory confirmation | 0.261979 |
| Rio Grande | 0.255853 |
| microcephaly cases | 0.452157 |
| microcephaly birth prevalence | 0.473006 |
| annual reported number | 0.286548 |
| hoc microcephaly surveillance | 0.63923 |
| Zika virus infection | 0.482005 |
| Pan American Health | 0.272707 |
| ad hoc surveillance | 0.253959 |
| states | 0.360593 |
| ParaÃba | 0.249888 |
| public health | 0.265165 |
| real time | 0.260665 |
| RT-PCR–confirmed Zika virus | 0.283413 |
|
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| 15292 |
Centers for Disease Control and Prevention |
Html |
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Recent Influenza Vaccination Trends across Influenza Seasons |
Summary: Recent Influenza Vaccination Trends across Influenza Seasons - CDC |
| National Immunization Survey | 0.596799 |
| recent influenza vaccination | 0.984395 |
| click Table | 0.38332 |
| NHFS | 0.229826 |
| influenza vaccination coverage | 0.808251 |
| H1N1 Flu Survey | 0.588709 |
| 2010-2011 seasons | 0.451107 |
| Estimates | 0.258954 |
| sections | 0.242253 |
|
| influenza seasons | 0.738076 |
| Surveillance | 0.245413 |
| Influenza Vaccination Trends | 0.809661 |
| KB | 0.258011 |
| NIS | 0.273464 |
| information | 0.226085 |
| page | 0.239631 |
| Behavioral Risk Factor | 0.613048 |
| navigation links | 0.383616 |
|
CLICK HERE |
| 15795 |
Centers for Disease Control and Prevention |
Html |
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Improving Adjuvant Hormone Therapy Use in Medicaid ManagedCare-Insured Women, New York State, 2012-2014 |
Preventing Chronic Disease (PCD) is a peer-reviewed electronic journal established by the National Center for Chronic Disease Prevention and Health Promotion. PCD provides an open exchange of information and knowledge among researchers, practitioners, policy makers, and others who strive to improve the health of the public through chronic disease prevention. |
| NYS Medicaid-insured women | 0.607714 |
| primary breast cancer | 0.616239 |
| data | 0.638951 |
| web-based data exchange | 0.59299 |
| health plans | 0.647104 |
| York State Department | 0.644782 |
| median outreach completion | 0.621436 |
| NYS Medicaid data | 0.607538 |
| AHT | 0.864336 |
| New York City | 0.597829 |
| Medicaid data | 0.617446 |
| AHT prescription | 0.67973 |
| AHT outcomes | 0.65404 |
| NYS Medicaid pharmacy | 0.592669 |
| AHT use postintervention | 0.65318 |
| AHT prescriptions | 0.733583 |
| Cancer Registry data | 0.635125 |
| York State Medicaid | 0.591813 |
| New York State | 0.789398 |
| plan care managers | 0.685712 |
| adjuvant hormone therapy | 0.768375 |
| breast cancer care | 0.592689 |
| HR-positive breast cancer | 0.715725 |
| data exchange platform | 0.592987 |
| AHT status | 0.721649 |
|
| randomized clinical trials | 0.599685 |
| NYS Cancer Registry | 0.596477 |
| women | 0.850689 |
| early breast cancer | 0.599979 |
| guideline-concordant AHT care | 0.693223 |
| NYS Medicaid | 0.628118 |
| outreach completion date | 0.643771 |
| breast cancer diagnosis | 0.618774 |
| lowest AHT adherence | 0.674906 |
| breast cancer surgery | 0.683555 |
| AHT adherent group | 0.766173 |
| noncontacted group | 0.647769 |
| quality improvement pilot | 0.597499 |
| New York | 0.81898 |
| Clin Oncol | 0.604593 |
| receptor–positive breast cancer | 0.631213 |
| breast cancer | 0.984814 |
| hormone therapy status | 0.604134 |
| AHT possession ratio | 0.72225 |
| health plan care | 0.691857 |
| AHT adherence rates | 0.679889 |
| Medicaid pharmacy data | 0.622814 |
| hormone receptor–positive breast | 0.618614 |
| et al | 0.604634 |
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