About this dataset

Context

The dataset tabulates the Medical Lake population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Medical Lake. The dataset can be utilized to understand the population distribution of Medical Lake by age. For example, using this dataset, we can identify the largest age group in Medical Lake.

Key observations

The largest age group in Medical Lake, WA was for the group of age 30 to 34 years years with a population of 580 (11.77%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Medical Lake, WA was the 85 years and over years with a population of 24 (0.49%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Medical Lake is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Medical Lake total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Medical Lake Population by Age. You can refer the same here

Note: CoP, WHO Global Code of Practice on the International Recruitment of Health Personnel; US IMGs, citizens of the US who graduated from non-US medical schools; non-US IMGs, foreign nationals who graduated from non-US medical schools.Data sources: Educational Commission for Foreign Medical Graduates [27–30].Numbers and percentages of US and non-US citizens who graduated from international medical schools in the National Residency Match Program after the 2010 launch of the CoP.

Abstract (en): This study comprises the second round of the physician survey component of the Community Tracking Study (CTS) sponsored by the Robert Wood Johnson Foundation. The CTS is a national study designed to track changes in the American health care system and the effects of the changes on care delivery and on individuals. Central to the design of the CTS is its community focus. Sixty sites (51 metropolitan areas and 9 nonmetropolitan areas) were randomly selected to form the core of the CTS and to be representative of the nation as a whole. As in the first round of the physician survey (COMMUNITY TRACKING STUDY PHYSICIAN SURVEY, 1996-1997: UNITED STATES), the second round was administered to physicians in the 60 CTS sites and to a supplemental national sample of physicians. The survey instrument collected information on physician supply and specialty distribution, practice arrangements and physician ownership of practices, physician time allocation, sources of practice revenue, level and determinants of physician compensation, provision of charity care, career satisfaction, physicians' perceptions of their ability to deliver care, views on care management strategies, and various other aspects of physicians' practice of medicine. In addition, primary care physicians (PCPs) were asked to recommend courses of action in response to some vignettes of clinical presentations for which there was no prescribed method of treatment. Dataset 3, the Site and County Crosswalk Data File, identifies the counties that constitute each CTS site. Dataset 4, the Physician Survey Summary File, contains site-level estimates and standard errors of the estimates for selected physician characteristics, e.g., the percentage of physicians who were foreign medical school graduates, the mean age of physicians, and the mean percentage of patient care practice revenue from Medicaid. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Checked for undocumented or out-of-range codes.. Physicians practicing in the 48 states of the contiguous United States who provided direct patient care for at least 20 hours per week and were not federal employees, specialists in fields in which the primary focus was not direct patient care, or graduates of foreign medical schools who were only temporarily licensed to practice in the United States. Residents, interns, and fellows were excluded. The CTS sites were selected using stratified sampling with probability proportional to population size. The supplemental sample, which was selected using stratified random sampling, was included in the survey in order to increase the precision of national estimates. The sample frame was developed by combining lists of physicians from the American Medical Association and the American Osteopathic Association. For both the site and supplemental samples, the sampling design involved randomly selecting physicians who were part of the Round 1 survey and physicians who were not covered by Round 1. Thus, about 58 percent of the Round 2 respondents also participated in Round 1. PCPs were oversampled in the site sample. 2009-02-02 Stata setups produced by ICPSR were added to the collection.2004-02-24 The user guide for the restricted-use version of the main data file has been revised. As noted on the "What's New" page in the guide, there are minor changes to the text related to the recommended SUDAAN parameters.2002-03-01 The user guides for the public- and restricted-use versions of the main data file have been revised. A discussion was added about how to pool data from Round 1 and Round 2 in order to increase sample size. In addition, the data definition statements have been enhanced. Funding insitution(s): Robert Wood Johnson Foundation (29275). computer-assisted telephone interview (CATI) For additional information about this study see the Web site of the Center for Studying Health System Change.

About this dataset

Context

The dataset tabulates the population of Medical Lake by race. It includes the population of Medical Lake across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Medical Lake across relevant racial categories.

Key observations

The percent distribution of Medical Lake population by race (across all racial categories recognized by the U.S. Census Bureau): 88.25% are white, 4.28% are Black or African American, 0.08% are American Indian and Alaska Native, 0.16% are Asian, 0.08% are Native Hawaiian and other Pacific Islander, 6.72% are some other race and 0.43% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Medical Lake
• Population: The population of the racial category (excluding ethnicity) in the Medical Lake is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Medical Lake total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Medical Lake Population by Race & Ethnicity. You can refer the same here

Note: Post-CoP recruits, physicians in first through third residency years as of December 2013; Pre-CoP recruits, licensed and resident physicians beyond their third year of residency training as of December 2013; Semi-retired physicians, physicians working less than 20 hours a week; SSA-IMG, international medical graduate who completed medical school in the SSA region; Annual pre-CoP recruitment growth = 2002–2010 percent increase divided by 7.5; Annual post-CoP recruitment growth rate = 2010–2013 percent increase divided by 3.5.a Baseline data sources: Hagopian et al. [4]; Tankwanchi [37]; Redi-Medi Data Interactive Medical Database System [51].Sub-Saharan African (SSA) immigrant physicians appearing in the American Medical Association (AMA) Physician Masterfile before and after the launch of the WHO Global Code on the International Recruitment of Health Personnel (CoP).

This dataset tracks annual american indian student percentage from 2009 to 2023 for Legacy Of Dr Josie R Johnson Montes vs. Minnesota and Legacy Of Dr Josie R Johnson Montes School District

This dataset tracks annual american indian student percentage from 2019 to 2020 for Dr. Sammy Lee Medical And Health Science Magnet Elementary School vs. California and Los Angeles Unified School District

BackgroundHealth literacy experts and the American Medical Association have developed recommended communication techniques for healthcare providers given that effective communication has been shown to greatly improve health outcomes. The purpose of this study was to determine the number and types of communication techniques routinely used by Maryland physicians.MethodsIn 2010, a 30-item survey was mailed to a random sample of 1,472 Maryland family physicians and pediatricians, with 294 surveys being returned and usable. The survey contained questions about provider and practice characteristics, and 17 items related to communication techniques, including seven basic communication techniques. Physicians’ use of recommended communication techniques was analyzed using descriptive statistics, analysis of variance, and ordinary least squares regression.ResultsFamily physicians routinely used an average of 6.6 of the 17 total techniques and 3.3 of the seven basic techniques, whereas pediatricians routinely used 6.4 and 3.2 techniques, respectively. The use of simple language was the only technique that nearly all physicians routinely utilized (Family physicians, 91%; Pediatricians, 93%). Physicians who had taken a communications course used significantly more techniques than those who had not. Physicians with a low percentage of patients on Medicaid were significantly less likely to use the recommended communication techniques compared to those providers who had high proportion of their patient population on Medicaid.ConclusionsOverall, the use of recommended communication techniques was low. Additionally, many physicians were unsure of the effectiveness of several of the recommended techniques, which could suggest that physicians are unaware of valuable skills that could enhance their communication. The findings of this study suggest that communications training should be given a higher priority in the medical training process in the United States.

Medical Service Study Areas (MSSAs)As defined by California's Office of Statewide Health Planning and Development (OSHPD) in 2013, "MSSAs are sub-city and sub-county geographical units used to organize and display population, demographic and physician data" (Source). Each census tract in CA is assigned to a given MSSA. The most recent MSSA dataset (2014) was used. Spatial data are available via OSHPD at the California Open Data Portal. This information may be useful in studying health equity.Definitions:Race/Ethnicity: Race/ethnicity is categorized as: All races/ethnicities, Non-Hispanic (NH) White, NH Black, Asian/Pacific Islander, or Hispanic. "All races" includes all of the above, as well as other and unknown race/ethnicity and American Indian/Alaska Native. The latter two groups are not reported separately due to small numbers for many cancer sites.Racial/Ethnic Composition: Distribution of residents' race/ethnicity (e.g., % Hispanic, % non-Hispanic White, % non-Hispanic Black, % non-Hispanic Asian/Pacific Islander). (Source: US Census, 2010.)Rural: Percent of residents who reside in blocks that are designated as rural. (Source: US Census, 2010.)Foreign Born: Percent of residents who were born outside the United States. (Source: American Community Survey, 2008-2012.)Socioeconomic Status (Neighborhood Level): A composite measure of seven indicator variables created by principal component analysis; indicators include: education, blue-collar job, unemployment, household income, poverty, rent, and house value. Quintiles based on state distribution, with quintile 1 being the lowest SES and 5 being the highest. (Source: American Community Survey, 2008-2012.)Spatial extent: CaliforniaSpatial Unit: MSSACreated: n/aUpdated: n/aSource: California Health MapsContact Email: gbacr@ucsf.eduSource Link: https://www.californiahealthmaps.org/?areatype=mssa&address=&sex=Both&site=AllSite&race=&year=05yr&overlays=none&choropleth=Obesity

This dataset tracks annual american indian student percentage from 2011 to 2023 for High School For Medical Professions vs. New York and New York City Geographic District #18 School District

This dataset tracks annual american indian student percentage from 1990 to 2010 for Medical Lake Elementary School vs. Washington and Medical Lake School District

This dataset tracks annual american indian student percentage from 2011 to 2023 for Bronx High School For Medical Science vs. New York and New York City Geographic District # 9 School District

This dataset tracks annual american indian student percentage from 2013 to 2014 for Academy Of Medical Arts At Carson High School vs. California and Los Angeles Unified School District

This dataset tracks annual american indian student percentage from 2021 to 2022 for Meridian Medical Arts Charter vs. Idaho and Joint School District No. 2

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Medical Lake by race. It includes the distribution of the Non-Hispanic population of Medical Lake across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Medical Lake across relevant racial categories.

Key observations

Of the Non-Hispanic population in Medical Lake, the largest racial group is White alone with a population of 4,343 (92.96% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the Medical Lake
• Population: The population of the racial category (for Non-Hispanic) in the Medical Lake is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Medical Lake total Non-Hispanic population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Medical Lake Population by Race & Ethnicity. You can refer the same here

This dataset tracks annual american indian student percentage from 1994 to 2023 for Cactus Medical Health And Technology Magnet Academy vs. California and Palmdale Elementary School District

This dataset tracks annual american indian student percentage from 2010 to 2011 for University Heights School Of Medical Arts vs. Arkansas and Nettleton School District

In May 2022, the most widespread outbreak of sustained transmission of mpox outside of countries historically affected countries in Western and Central Africa occurred. We aimed to examine the personal and clinical experiences of international healthcare workers (HCWs) during this public health emergency. We conducted an international cross-sectional survey study between August and October 2022, examining the experiences and perceptions of HCWs clinically involved in the 2022 mpox response. Respondents were recruited via an international network of sexual health and HIV clinicians responding to mpox and promoted through clinical associations and social media. Survey domains included: clinical workload; preparedness; training and support at work; psychological well-being and vaccination. 725 multi-national healthcare workers across 41 countries were included in the analysis. 91% were physicians specialised in Sexual Health or Infectious Diseases; with 34% (n = 247) of all respondents involved in mpox policy. A substantial proportion of respondents (n = 296, 41%) reported working longer hours during the mpox outbreak, with no concomitant removal of other clinical responsibilities. 30% (n = 218) of respondents reported that they had never heard of mpox before the outbreak and over 25% of the respondents reported that they had misdiagnosed someone initially. This culminated in a high prevalence of moral distress at thirty percent. Less than 9% of HCWs in the region of the Caribbean, Central America and South America had been offered a vaccine as compared to almost one-third in the other regions. Where offered, there were high levels of uptake across all regions. The findings highlight a critical need for addressing the profound gaps in HCW knowledge about re-emerging diseases with pandemic potential. Strengthening the resilience of global health systems and prioritising internationally coordinated approaches to global vaccine deployment is imperative.

Baseline characteristics of respondents and non-respondents in the ALTERNATIVE survey cohort.

Summary scores of the patient-reported outcomes and health literacy.