Cause of Fetal Death: Data from the Fetal Death Report, 2014

October 31, 2016

Questions for Donna L. Hoyert, Ph.D., Health Scientist and Lead Author on “Cause of Fetal Death: Data from the Fetal Death Report, 2014

Q: Why did you conduct this study?

DH: We wanted to provide background regarding what information has become available recently through vital statistics data on the cause of fetal death. The National Vital Statistics System is an example of intergovernmental sharing of public health data, and in the United States, State laws require the reporting of fetal deaths, and Federal law mandates national collection and publication of the data. There is much we can learn from the statistics in this study.


Q: Why focus on fetal deaths of 20 weeks gestation or more in your report – versus fetal deaths of any and all gestation?

DH: Because the States typically require reporting of these events, we focused on fetal deaths of 20 weeks gestation or more. These spontaneous intrauterine deaths are sometimes referred to as stillbirths. While there are a few states that report fetal deaths at all gestation periods, consistent national data is found at 20 weeks or more.


Q: What are the most common selected causes of fetal death?

DH: There are five most common selected causes of fetal death, one of which is listed as an unspecified cause. Placenta, cord, and membrane complications is another one. There are also congenital malformations, maternal complications, and maternal conditions unrelated to pregnancy.


Q: What variations by maternal demographics, if any, did you observe in the fetal death data you examined?

DH: The same five causes of fetal death were among the most common selected causes for many maternal characteristics. The characteristics of delivery weight and gestation period were different, and for these two, diabetes mellitus emerged, and maternal complications dropped below the top five selected causes for fetuses with longer gestation and heavier delivery weights.


Q: What do you think is the most significant finding in your new study?

DH: Probably that the variations observed across maternal and fetal characteristics are consistent with those documented in other research. This represents an important expansion of what is available from vital statistics on fetal death.


QuickStats: Cigarette Smoking Status Among Current Adult E-cigarette Users by Age Group — National Health Interview Survey, United States, 2015

October 28, 2016

In 2015, 3.5% of U.S. adults were current e-cigarette users.

Among adult e-cigarette users overall, 58.8% also were current cigarette smokers, 29.8% were former cigarette smokers, and 11.4% had never been cigarette smokers.

Among current e-cigarette users aged 45 years or older, 98.7% were either current or former cigarette smokers, and 1.3% had never been cigarette smokers. In contrast, among current e-cigarette users aged 18–24 years, 40% had never been cigarette smokers.

Source: https://www.cdc.gov/mmwr/volumes/65/wr/mm6542a7.htm


Q & A from Lead Author of “State Variation in Electronic Sharing of Information in Physician Offices: United States, 2015”

October 28, 2016
Eric Jamoom, Research Scientist Officer

Eric Jamoom, Research Scientist Officer

Questions for Eric Jamoom, Research Scientist Officer at the Collaborating Center for Questionnaire Design and Evaluation Research and Lead Author on “State Variation in Electronic Sharing of Information in Physician Offices: United States, 2015.”

Q: What findings in the report surprised you and why?

EJ: In this data brief, we are capturing for the first time four elements for measuring the electronic sharing of health information. Specifically, we now have insight into the number of office-based physicians that electronically sent, received, integrated and searched for patient health information from other providers.

Coupled with the recent release of a September 2, 2016 MMWR Quickstat that provided estimates on the number of physicians having electronic access to patient health information at the point of care, information is now available about the state of electronic information sharing by office-based physicians in the United States.


Q: How many office-based physicians electronically sent, received, integrated or searched for patient health information from other providers in 2015?

EJ: In 2015, roughly one-third of physicians indicated they either electronically sent, received, integrated, or searched patient health information in 2015.

Specifically, 38.2% of physicians had electronically sent patient health information to other providers, 38.3% of physicians had electronically received patient health information from other providers, 31.1% of physicians had electronically integrated patient health information from other providers, and 34.0% of physicians had electronically searched for patient health information from other providers.


Q: Which states did you find that electronically sent patient health information to other providers that were higher and lower than the national average?

EJ: In 2015, the percentage of physicians that sent patient health information to other providers ranged from 19.4% in Idaho to 56.3% in Arizona. Arizona was significantly greater than the national percentage, while three states – Idaho, New Jersey, and Connecticut – were significantly less than the national percentage.


Q: Can you explain what you found from state variation among physicians who had electronically searched for information from other providers?

EJ: In 2015, 34% of physicians had electronically searched for patient health information from other providers, ranging from 15.1% in the District of Columbia to 61.2% in Oregon. Five states, which include Texas, Oklahoma, Missouri, Mississippi, and Pennsylvania, as well as the District of Columbia were significantly less than the national percentage. Whereas, 10 states were significantly greater than the national percentage: Alaska, Oregon, Washington, Colorado, Wisconsin, Ohio, North Carolina, Virginia, Maryland, and Delaware.


Q: Do you have trend data that goes further back than 2015 on this topic?

EJ: These data represent new information previously not available before on electronic information sharing of patient health information. Therefore, the information contained in this report represents a baseline for which future data can be used for trend data on these four elements of electronic information sharing among office-based physicians.


Q: Why did you decide to study state variation in electronic sharing of information in physician offices?

EJ: The Health Information Technology for Economic and Clinical Health Act provided financial incentives to eligible providers to demonstrate the meaningful use of a certified electronic health record (EHR) system, which also includes capacity to share patient health information.

In 2015, a federal plan was published to enhance the nation’s health IT infrastructure to support sending, receiving, integrating, and searching for patient health information electronically. The 2015 data from the National Electronic Health Records Survey provides national and state based estimates about physician EHR adoption and use.

 


Health Care Access and Utilization Among Adults Aged 18–64, by Poverty Level: United States, 2013–2015

October 28, 2016
Brian Ward, Health Statistician

Brian Ward, Health Statistician

Michael Martinez, Health Statistician

Michael Martinez, Health Statistician

Questions for Michael Martinez and Brian Ward, Health Statisticians and Lead Authors on “Health Care Access and Utilization Among Adults Aged 18–64, by Poverty Level: United States, 2013–2015.”

Q: What findings in the report surprised you and why?

MM BW: We found it noteworthy that even though all adults aged 18-64 among all poverty level subgroups had decreases in the uninsured population from 2013 through 2015, only poor and near-poor adults had increases in the percentage that had a usual place to go for medical care and had seen or talked to a health professional in the past 12 months.


Q: How has the number of uninsured adults aged 18-64 by poverty level changed from 2013 to 2015?

MM BW: In 2013, 10.9 million poor, 13.2 million near-poor, and 15.2 million not-poor U.S. adults aged 18-64 were uninsured; in 2015, 6.6 million poor, 8.2 million near-poor, and 10.3 million not-poor U.S. adults aged 18-64 were uninsured.  There were 4.3 million fewer poor,  5 million fewer near-poor, and 4.9 million fewer near-poor uninsured adults aged 18-64 from 2013 through 2015.


Q: What did you find out from the percentage of adults aged 18-64 among all poverty level subgroups who did not obtain needed medical care due to cost?

MM BW: We observed that percentage of adults aged 18-64 who did not obtain needed medical care due to cost  decreased for all poverty level subgroups from 2013 through 2015, but the largest percentage point decreases were among poor adults, 4.2  percentage point decrease, and near-poor adults, 3.6 percentage point decrease, respectively.


Q: How do you determine federal poverty level?

MM BW: Federal poverty level was determined through a series of questions on the National Health Interview Survey (NHIS) to obtain family income. Federal poverty level was then determined by dividing the total family income by the U.S. Census Bureau’s poverty threshold specific to a family’s size and age of members in that family. This ratio is multiplied by 100, and family poverty level was determined based on where a family fell relative to certain thresholds. Adults were considered poor if their family poverty level fell below 100% of the threshold. Adults were determined to be near-poor if their family poverty level fell at or above 100% but less than 200%. And adults were considered not-poor if their family poverty level fell at or above 200%.


Q: What can you conclude from this report?

MM BW: We concluded from this report that despite improvements in health insurance coverage and health care access from 2013 through 2015 for poor and near-poor adults aged 18-64, they were still less likely than not-poor adults to have a usual place to go for medical care and to have seen or talked to a health professional in the past 12 months.


State Variation in Electronic Sharing of Information in Physician Offices: United States, 2015

October 27, 2016

The Health Information Technology for Economic and Clinical Health Act (HITECH) provides financial incentives to eligible providers using a certified electronic health record (EHR) system.

In 2015, 77.9% of office-based physicians had a certified EHR system, up from 74.1% in 2014. A federal plan to enhance the nation’s health information technology infrastructure was published in 2015 to support information sharing.

A new NCHS report uses the 2015 National Electronic Health Records Survey to describe the extent to which physicians can electronically send, receive, integrate, and search for patient health information.

Findings:

  • In 2015, the percentage of physicians who had electronically sent patient health information ranged from 19.4% in Idaho to 56.3% in Arizona.
  • In 2015, the percentage of physicians who had electronically received patient health information ranged from 23.6% in Louisiana
    and Mississippi to 65.5% in Wisconsin.
  • In 2015, the percentage of physicians who had electronically integrated patient health information from other providers ranged from 18.4% in Alaska to 49.3% in Delaware.
  • In 2015, the percentage of physicians who had electronically searched for patient health information ranged from 15.1% in the
    District of Columbia to 61.2% in Oregon.

Injury Mortality: United States, 1999–2014

October 21, 2016

NCHS has released new data visualization that depicts injury mortality in the United States from 1999 through 2014.

This storyboard allows the user to select subcategories of injury deaths based on intent and mechanism of injury.

Numbers and rates are provided for the subcategory selected by the user.

The storyboard includes six dashboards. Deaths can be grouped or separated by mechanism of injury, intent of injury, and selected demographics (sex, age group, race and Hispanic origin).

Drop-down boxes across the top of the dashboard control the display of the entire visualization. The dashboards feature:

Rates: Line charts displaying trends for injury death rates. Both fixed and dynamic scale line charts are provided. The fixed scale line chart allows the user to see changes in rates relative to a predefined y-axis, while the dynamic scale line chart adjusts to maximize the visualization of the trend for the options selected. A dialog box on the left of the dashboard allows the user to select among several options for the range of y-axis values used in the fixed scale line chart.

Numbers of deaths: A table describes numbers of injury deaths for selections made at the top of the visualization.


QuickStats: Gestational Weight Gain Among Women with Full-Term, Singleton Births, Compared with Recommendations — 48 States and the District of Columbia, 2015

October 14, 2016

Gestational weight gain was within the recommended range for 32% of women giving birth to full-term, singleton infants in 2015, with 48% gaining more weight and 21% less weight than recommended.

Approximately 44% of women who were underweight before pregnancy gained within the recommendations, compared with 39% of women who were normal weight, 26% of women who were overweight, and 24% of women with obesity before pregnancy.

Weight gain above the recommendations was highest among women who were overweight (61%) or had obesity (55%) before pregnancy.

SOURCE: https://www.cdc.gov/mmwr/volumes/65/wr/mm6540a10.htm