Patient Health Information Shared Electronically by Office-based Physicians: United States, 2015

August 15, 2018

Questions for Brian Ward, Health Statistician and Lead Author of “Patient Health Information Shared Electronically by Office-based Physicians: United States, 2015

Q: Why did you decide to focus on office-based physicians who electronically share patient health information (PHI) in the United States?

BW: While previous research has looked at the extent to which office-based physicians electronically shared PHI, it has not provided details as to the types of PHI that are electronically sent, received, integrated, and searched for. Therefore, we decided to expand upon this previous research by describing the types of PHI that are shared electronically.


Q: How did you collect data for this report?

BW: Data from this report were from the 2015 National Electronic Health Records Survey (NEHRS). NEHRS is a nationally representative mixed-mode survey of office-based physicians, and asks about their adoption and use of electronic health records (EHRs). The different modes (or manners) NEHRS uses to collect data are via web, mail, and telephone.


Q: What were some of the most observed types of PHI electronically shared in physician offices?

BW: Among office-based physicians who sent PHI electronically, the most commonly observed types of PHI sent were referrals (67.9%), laboratory results (67.2%), and medication lists (65.1%). Among physicians who received PHI electronically, the most commonly observed types of PHI received were laboratory results (78.8%), imaging reports (60.8%), and medication lists (54.4%).

For physicians who integrated PHI electronically, the most commonly observed types of PHI integrated were laboratory results (73.2%), imaging reports (49.8%), and hospital discharge summaries (48.7%).

Finally, a large majority of physicians who searched for PHI electronically did so for medication lists (90.2%), medication allergy lists (88.2%), and hospital discharge summaries (80.4%).


Q: Do you have trend data that is older than 2015 or is this the first this data has been published?

BW: Older NEHRS data are available, dating back to 2008 (when it was a supplement to the National Ambulatory Medical Care Survey); however, these older data are not compatible with the measures examined in this report.


Q: What is the take home message in this report?

BW: These are the first national estimates of PHI type according to the aspects of interoperability among physicians with EHR systems, and these estimates can be used as a benchmark for future studies. Combined with measures of electronic sharing of PHI by physicians, information on the specific type of PHI shared electronically among office-based physicians will assist in tracking progress outlined in the federal plan for achieving interoperability.

Advertisements

High-deductible Health Plan Enrollment Among Adults Aged 18-64 With Employment-based Insurance Coverage

August 9, 2018

Questions for Robin Cohen, Ph.D. and Lead Author of “High-deductible Health Plan Enrollment Among Adults Aged 18-64 With Employment-based Insurance Coverage

Q: What made you decide to put together a report about high and low deductible health plans for adults with employment-based coverage?

RC: We decided to produce an analysis focusing on high-deductible health plans (HDHPs) after observing how enrollment in HDHPs has increased over the past decade. In addition, HDHP enrollment growth has been faster among those with employment-based coverage than among those with directly-purchased coverage, so it also made sense to highlight employment-based insurance plans in this study. This report examines differences in the demographic characteristics for those with employment-based coverage by plan type.    


Q: Was there a finding in your new report that really surprised you?

RC: It was the dramatic increase in high-deductible health plan (HDHP) enrollment in recent years that really surprised us. We hadn’t expected to see such a large jump, which was most notable among those with a health savings account (HSA). The percentage of adults aged 18 to 64 enrolled in an HDHP with an HSA more than quadrupled in the past decade from 4.2% to 18.9%.


Q: What differences or similarities did you see between or among various demographic groups in this analysis?

RC: Both the differences among age groups and the lack of variance by sex in this study’s findings are notable. Among adults aged 18 to 64 with employment-based coverage, there were no differences in the type of health insurance plan by sex. Enrollment in a high-deductible health plan with a health savings account was higher among adults aged 30 to 44 than those aged 18 to 29 and 45 to 64.


Q: What is the significance of having a health savings account and not having one when you have a high-deductible health insurance plan?

RC: A health savings account (HSA) allows pretax income to be saved to help pay for the higher costs associated with a high-deductible health plan (HDHP). However, this report did not examine the association of having an HDHP — coupled with an HSA — on service use and financial burden for medical care.

 

Q: Is it a choice for Americans to have a health savings account? Can anyone have one?

 

RC: A health savings account (HSA) must be coupled with a high-deductible health plan (HDHP), but not everyone enrolled in an HDHP has an HSA. High-deductible health plans with HSAs are offered to individuals both by employers and in the direct-purchase health insurance market.

Q: What would you say is the take-home message of this report?

 

RC: I think the real take-home message in this Data Brief is the role that education and income play in health insurance coverage with these types of high-deductible health plans (HDHPs). More highly educated and affluent adults were more likely to enroll in an HDHP with a health savings account (HSA) and less likely to enroll in a traditional plan or an HDHP without an HSA — than their less educated and less affluent counterparts. The National Health Interview Survey will continue to monitor different types of private health insurance, and the survey can be used to examine further differences according to plan type.

Q: Do you have trend data on high-deductible health plans going back further than 2007?

RC: No, we don’t have earlier than 2007 trend data on high-deductible health plans (HDHPs). The National Health Interview Survey began to collect data on enrollment in HDHPs starting in 2007.


QuickStats: Age-Adjusted Death Rates from Lung Cancer by Race/Ethnicity — National Vital Statistics System, United States, 2001–2016

August 6, 2018

During 2001–2016, the lung cancer death rates for the total population declined from 55.3 to 38.3 as well as for each racial/ethnic group shown.

During 2001–2016, the death rate for the non-Hispanic black population decreased from 63.3 to 41.2, for the non-Hispanic white population from 57.7 to 41.5, and for the Hispanic population from 23.9 to 16.6.

Throughout this period, the Hispanic population had the lowest death rate.

SOURCE: CDC/National Center for Health Statistics, National Vital Statistics System, 2001–2016, Mortality. CDC Wonder online database. https://wonder.cdc.gov/ucd-icd10.html.

https://www.cdc.gov/mmwr/volumes/67/wr/mm6730a8.htm?


QuickStats: Percentage of Residential Care Community Residents with an Advance Directive by Census Division — National Study of Long-Term Care Providers, 2016

July 23, 2018

In 2016, 77.9% of residents in residential care communities had an advance directive documented in their files.

By Census division, the highest percentage (87.8%) of residents who had an advance directive were located in the Mountain division, followed by residents in East North Central (83.7%), New England (80.0%), West North Central (78.9%), Pacific (77.6%), South Atlantic (77.4%), East South Central (76.4%), Middle Atlantic (68.8%), and West South Central (64.9%).

Source: National Center for Health Statistics, National Study of Long-Term Care Providers, 2016. https://www.cdc.gov/nchs/nsltcp/index.htm.

https://www.cdc.gov/mmwr/volumes/67/wr/mm6728a7.htm


Adoption-related Behaviors Among Women Aged 18–44 in the United States: 2011–2015

July 19, 2018

Questions for Lead Author Chinagozi Ugwu, Statistician and Author of “Adoption-related Behaviors Among Women Aged 18–44 in the United States: 2011–2015

Q: Why did you decide to focus on adoption-related behaviors in the United States?

CU: Adoption is one way people build their families, and this report provides some basic statistics on adoption in the United States. The National Survey of Family Growth (NSFG) is one of few sources of nationally representative data on adoption and adoption seeking among adult women in the U.S.


Q: How did the findings vary by age groups?

CU: This report documented some differences by age groups in adoption-related behaviors. Women in the oldest age category (35-44 years) were more likely to be seeking to adopt than women of younger ages, and were also more likely to have ever adopted.

Approximately 1.5% of women aged 35-44 in 2011-2015 were currently seeking to adopt, followed by 1.4% of women aged 25-34 and 0.6% of women aged 18-24. The percentage of women who had ever adopted a child increased with increasing age (0.1%, aged 18–24; 0.5%, aged 25–34; 1.3%, aged 35–44).


Q: Were there any major changes in adoption-related behaviors from previous years?

CU: In this report, we did not study trends in these adoption-related behaviors.  We focused more on providing a snapshot of the demographic characteristics of U.S. adult women who had engaged in these three adoption-related behaviors: ever considered adoption, currently seeking to adopt, and ever adopted a child.


Q: Do you have data for adoption-related behavior data on women older than age 44?

CU: The NSFG data used for this report reflect survey years when the age range extended only to age 44.  Beginning in 2015, the NSFG expanded its age range to 15-49, so future analyses can include adults 18-49.  The public use files for 2015-2017, which will reflect the expanded age range of 15-49 are expected to be released later this year.


Q: What is the take home message in this report?

CU: While the percentages of adult women aged 18-44 with adoption-related experience are relatively low, this report documents key variations by demographic characteristics, including age and current fertility problems. More women with fertility problems than those without had ever considered adopting or were currently seeking to adopt a child. Higher percentages of women in the oldest age (35-44 years) category were currently seeking to adopt or had ever adopted, than women in the youngest age (18-24 years) category.


Accidental Drowning Deaths in the U.S., 2010-2016

July 18, 2018

drowning

Source: National Vital Statistics System, CDC WONDER 2010-2016


Trends in Liver Cancer Mortality Among Adults Aged 25 and Over in the United States, 2000-2016

July 17, 2018

Jiaquan Xu, M.D., NCHS Epidemiologist

Questions for Lead Author Jiaquan Xu, M.D., Epidemiologist, and Author of “Trends in Liver Cancer Mortality Among Adults Aged 25 and Over in the United States, 2000-2016

Q: What made you decide to focus on liver cancer deaths for this study?

JX: It was the dramatic rise in the death rate for liver cancer that caused me to want to look more deeply into various aspects of this marked change and produce this new report. I also wanted to offer state-by-state data for liver cancer mortality, so that the U.S. Public Health Community might have information that will help them in their important work throughout America. While we have seen decreases in death rates from many major causes — such as heart disease, cancer (all cancer combined), and stroke recently – liver cancer deaths stand out far away from the decreasing trends of these causes of death. To elaborate, the age-adjusted death rates for all cancer combined, have declined since 1990. Also, for the top six cancer death causes in 2016 (lung cancer, colorectal cancer, pancreatic cancer, breast cancer, prostate cancer, and liver cancer), the age-adjusted death rates decreased for four of them (lung, colorectal, breast, and prostate) and increased for two (liver cancer and pancreatic cancer) — with the liver cancer death rate increasing much faster than the pancreatic cancer death rate, since 2000.


Q: Was there a finding in your new report that you hadn’t expected and that really surprised you?

JX:  There actually are quite a few interesting results in this new analysis that surprised me. While there are some reports out there that show the increase of liver cancer mortality, we also know that the liver cancer death rate demonstrates a trend of continued rate increase during the period from 2000 through 2016 – which is the time span this report analyzed. The surprise is that the liver cancer death rate for men is between 2 and 2.5 times the rate for women aged 25 and over, during the period of 2000–2016. Within the four race/ethnic groups analyzed, the only decrease trend in liver cancer mortality observed, is for the non-Hispanic Asian or Pacific Islander (API) group. The rate increased for non-Hispanic white, non-Hispanic black, and Hispanic persons. Also the liver cancer death rates varied quite a bit by state, which is another surprising finding.


Q: What made you decide to focus on the age group of adults 25 years old and older?

JX: I had a number of reasons to focus on the liver cancer death rate for adults aged 25 and over. More than 99% of all deaths with liver cancer reported on the death certificate are for adults 25 years of age and over. It made sense to focus this analysis on the majority age group that dies from this cancer cause. We also know that age is a leading risk factor for the development of many types of cancer. Aging increases cancer risk. This is exactly what we see here in this new report. And the liver cancer death rate for older age groups is significantly higher than the rate for younger age groups throughout the period examined in this analysis.


Q: What differences or similarities did you see between or among various demographic groups in this analysis?

JX:  The differences among demographic groups is also what I found most surprising in this report. The liver cancer death rate for men aged 25 and over is between 2 and 2.5 times the rate for women. The liver cancer death rate varies by race/ethnic groups. The Non-Hispanic Asian or Pacific Islander (API) group have the highest liver cancer death rate among the four race/ethnic groups analyzed during 2000–2014. The rate for Hispanic adults surpassed the rate for non-Hispanic API and became the highest in 2016. The liver cancer death rate for non-Hispanic white adults was the lowest among the race/ethnic groups throughout the period (2000–2016).


Q: Why do you think there is such a vast difference among the states in death rates from liver cancer?

JX: The mortality data we analyzed does not provide any evidence itself to show the reason or reasons that could contribute to the variation of liver cancer death rates by state. In general, the majority of the liver cancer in the United States is often attributed to some potential risk factors such as metabolic disorders (including obesity, diabetes, and nonalcoholic fatty liver disease), chronic Hepatitis C (HCV) infection, excessive consumption of alcohol, smoking, and chronic Hepatitis B (HBV) infection. If the number of people affected by those potential risk factors is different from one state to another, the liver cancer incidence rate and death rate would vary.


Q: What do you think is the reason for the growing increase in deaths from liver cancer in the United States?

JX: The mortality data we analyzed does not provide any evidence itself to show the reason or reasons that could contribute to the rising of the liver cancer death rate in this country. Some risk factors might contribute to the increase in liver cancer incidence rate and death rate. For example, some attribute the baby boomer generation’s higher hepatitis C virus infection rate than other adult age groups. Some have identified an increase in the obesity rate as another reason. Unfortunately, we can’t answer this question with our data, though it is an important question.


Q: What would you say is the take-home message of this report?

JX: I think the real take-home message of this Data Brief is what it can offer to the Public Health Community to learn about liver cancer mortality variance among different groups. The report shows that liver cancer mortality varies by sex, age, race/ethnic groups, and by state. Although the overall liver cancer death rate increased from 2000 to 2016, the rate for non-Hispanic Asian or Pacific Islander (API) decreased. The rate for adults aged 45–54 has decreased since 2012.