Comprehensive dataset of 268,061 Nurse practitioners in United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Nurse Practitioners play a vital role in contributing to the UN's Sustainable Development Goals, and Universal Health Coverage, especially the management of chronic noncommunicable diseases. Artificial intelligence tools such as ChatGPT are becoming promising resources for healthcare professionals. This study aimed to explore the capability of ChatGPT as a Nurse Practitioner by validating the performance of ChatGPT-3.5 and GPT-4 in the American Association of Nurse Practitioners (AANP) practice examinations. Questions from exams for five Nurse Practitioner disciplines were used to evaluate the accuracy and consistency of the responses in two phases. In the first phase, the accuracy rates and concordance of answers between the two versions with the five exam sets, totaling 535 questions were analyzed. In the second phase, the consistency of ChatGPT-4 performance in six retests, each involving five random questions from each set. ChatGPT-3.5 achieved an overall accuracy rate of 80.6%, while ChatGPT-4 achieved 90.7%. ChatGPT-3.5 and ChatGPT-4 showed strong consistency within all sets, while ChatGPT-4 performed better than ChatGPT-3.5. In the retests, ChatGPT-4 provided exactly the same answers as generated initially, including the incorrect ones. In conclusion, ChatGPT demonstrated excellent performance in AANP practice exams, with high levels of accuracy and consistency. This suggests that ChatGPT may support nurse practitioners in making clinical decisions and improving efficiency. Further studies could explore ways to integrate artificial intelligence tools with nurse practitioner practice to enhance the advanced practice nursing workforce.

United States - Employed full time: Wage and salary workers: Nurse practitioners occupations: 16 years and over: Women was 193.00000 Thous. of Persons in January of 2024, according to the United States Federal Reserve. Historically, United States - Employed full time: Wage and salary workers: Nurse practitioners occupations: 16 years and over: Women reached a record high of 194.00000 in January of 2022 and a record low of 65.00000 in January of 2012. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Employed full time: Wage and salary workers: Nurse practitioners occupations: 16 years and over: Women - last updated from the United States Federal Reserve on June of 2025.

Graph and download economic data for Employed full time: Wage and salary workers: Nurse practitioners occupations: 16 years and over (LEU0257870000A) from 2011 to 2024 about nursing, occupation, full-time, salaries, workers, 16 years +, wages, employment, and USA.

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for adult health nurse practitioner in the U.S.

BackgroundGrowing physician maldistribution and population demographic shifts have contributed to large geographic variation in healthcare access and the emergence of advanced practice providers as contributors to the healthcare workforce. Current estimates of geographic accessibility of physicians and advanced practice providers rely on outdated “provider per capita” estimates that have shortcomings.PurposeTo apply state of the art methods to estimate spatial accessibility of physician and non-physician clinician groups and to examine factors associated with higher accessibility.MethodsWe used a combination of provider location, medical claims, and U.S. Census data to perform a national study of health provider accessibility. The National Plan and Provider Enumeration System was used along with Medicare claims to identify providers actively caring for patients in 2014 including: primary care physicians (i.e., internal medicine and family medicine), specialists, nurse practitioners, and chiropractors. For each U.S. ZIP code tabulation area, we estimated provider accessibility using the Variable-distance Enhanced 2 step Floating Catchment Area method and performed a Getis-Ord Gi* analysis for each provider group. Generalized linear models were used to examine associations between population characteristics and provider accessibility.ResultsNational spatial patterns of the provider groups differed considerably. Accessibility of internal medicine most resembled specialists with high accessibility in urban locales, whereas relative higher accessibility of family medicine physicians was concentrated in the upper Midwest. In our adjusted analyses independent factors associated with higher accessibility were very similar between internal medicine physicians and specialists–presence of a medical school in the county was associated with approximately 70% higher accessibility and higher accessibility was associated with urban locales. Nurse practitioners were similar to family medicine physicians with both having higher accessibility in rural locales.ConclusionsThe Variable-distance Enhanced 2 step Floating Catchment Area method is a viable approach to measure spatial accessibility at the national scale.

Success.ai’s Healthcare Industry Leads Data and B2B Contact Data for US Healthcare Professionals offers an extensive and verified database tailored to connect businesses with key executives and administrators in the healthcare industry across the United States. With over 170M verified profiles, including work emails and direct phone numbers, this dataset enables precise targeting of decision-makers in hospitals, clinics, and healthcare organizations.

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The dataset is a collection of legal fact sheets on drug checking equipment and Fentanyl Test Strips adapted from the Network for Public Health Law for the states in the Appalachian American region. Fact sheets were created for the Appalachian American Alliance of Nurse Practitioners. State specific information on where to obtain Fentanyl Test Strips and other drug checking equipment is also included.

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for gerontologicaladult health nurse practitioner in the U.S.

To estimate county of residence of Filipinx healthcare workers who died of COVID-19, we retrieved data from the Kanlungan website during the month of December 2020.22 In deciding who to include on the website, the AF3IRM team that established the Kanlungan website set two standards in data collection. First, the team found at least one source explicitly stating that the fallen healthcare worker was of Philippine ancestry; this was mostly media articles or obituaries sharing the life stories of the deceased. In a few cases, the confirmation came directly from the deceased healthcare worker's family member who submitted a tribute. Second, the team required a minimum of two sources to identify and announce fallen healthcare workers. We retrieved 86 US tributes from Kanlungan, but only 81 of them had information on county of residence. In total, 45 US counties with at least one reported tribute to a Filipinx healthcare worker who died of COVID-19 were identified for analysis and will hereafter be referred to as “Kanlungan counties.” Mortality data by county, race, and ethnicity came from the National Center for Health Statistics (NCHS).24 Updated weekly, this dataset is based on vital statistics data for use in conducting public health surveillance in near real time to provide provisional mortality estimates based on data received and processed by a specified cutoff date, before data are finalized and publicly released.25 We used the data released on December 30, 2020, which included provisional COVID-19 death counts from February 1, 2020 to December 26, 2020—during the height of the pandemic and prior to COVID-19 vaccines being available—for counties with at least 100 total COVID-19 deaths. During this time period, 501 counties (15.9% of the total 3,142 counties in all 50 states and Washington DC)26 met this criterion. Data on COVID-19 deaths were available for six major racial/ethnic groups: Non-Hispanic White, Non-Hispanic Black, Non-Hispanic Native Hawaiian or Other Pacific Islander, Non-Hispanic American Indian or Alaska Native, Non-Hispanic Asian (hereafter referred to as Asian American), and Hispanic. People with more than one race, and those with unknown race were included in the “Other” category. NCHS suppressed county-level data by race and ethnicity if death counts are less than 10. In total, 133 US counties reported COVID-19 mortality data for Asian Americans. These data were used to calculate the percentage of all COVID-19 decedents in the county who were Asian American. We used data from the 2018 American Community Survey (ACS) five-year estimates, downloaded from the Integrated Public Use Microdata Series (IPUMS) to create county-level population demographic variables.27 IPUMS is publicly available, and the database integrates samples using ACS data from 2000 to the present using a high degree of precision.27 We applied survey weights to calculate the following variables at the county-level: median age among Asian Americans, average income to poverty ratio among Asian Americans, the percentage of the county population that is Filipinx, and the percentage of healthcare workers in the county who are Filipinx. Healthcare workers encompassed all healthcare practitioners, technical occupations, and healthcare service occupations, including nurse practitioners, physicians, surgeons, dentists, physical therapists, home health aides, personal care aides, and other medical technicians and healthcare support workers. County-level data were available for 107 out of the 133 counties (80.5%) that had NCHS data on the distribution of COVID-19 deaths among Asian Americans, and 96 counties (72.2%) with Asian American healthcare workforce data. The ACS 2018 five-year estimates were also the source of county-level percentage of the Asian American population (alone or in combination) who are Filipinx.8 In addition, the ACS provided county-level population counts26 to calculate population density (people per 1,000 people per square mile), estimated by dividing the total population by the county area, then dividing by 1,000 people. The county area was calculated in ArcGIS 10.7.1 using the county boundary shapefile and projected to Albers equal area conic (for counties in the US contiguous states), Hawai’i Albers Equal Area Conic (for Hawai’i counties), and Alaska Albers Equal Area Conic (for Alaska counties).20

United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Nurse practitioners occupations: 16 years and over: Women was 2117.00000 $ in January of 2024, according to the United States Federal Reserve. Historically, United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Nurse practitioners occupations: 16 years and over: Women reached a record high of 2117.00000 in January of 2024 and a record low of 1432.00000 in January of 2011. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Nurse practitioners occupations: 16 years and over: Women - last updated from the United States Federal Reserve on July of 2025.

Graph and download economic data for Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Nurse practitioners occupations: 16 years and over (LEU0257870300A) from 2011 to 2024 about nursing, second quartile, occupation, full-time, salaries, workers, earnings, 16 years +, wages, median, employment, and USA.

AbstractBackground Moral injury is an emerging explanation of burnout and suicidality, but remains poorly quantified in at-risk practitioners. We hypothesized that COVID-19 pandemic-related moral injury differs between frontline clinicians, genders, age, and country of practice. Methods We conducted an online cross-sectional survey of international physicians, nurses, nurse practitioners, paramedics and respiratory therapists between April and June 2020. We included the adapted version of the Expressions of Moral Injury Scale (EMIS). The primary outcome was differences in moral injury scores between clinician roles. Results Three hundred and two clinicians participated, including physicians (61% [n=184]), nurses (28% [n=85]), and nurse practitioners (5% [n=14]). The median age was 39 (IQR 32-76), females comprised 54% of the respondents, and the majority resided in Canada (n =183 [61%]) or the United States (US; n = 106 [35%]). Emergency medicine (88% [n=265]), and intensive care (6% [n=17]) were the main specialties responding. Median moral injury scores across multiple domains were higher for nurses compared to physicians, as well as for younger, and female respondents. Moral injury scores were also significantly higher for respondents from the United States, the United Kingdom and Australia, compared to Canada. Conclusions Our research suggests that during COVID-19, measures of moral injury differ across roles, gender and place of work. Future research is warranted to better understand the impact of moral injury on clinicians’ psychological well-being during the COVID-19 pandemic. MethodsThis dataset was collected through the Qualtrics online survey application.

This data package contains information about Abeyance, Dispersal and GP Practice Codes for Prescribing Cost Centres and Relevant Health Trusts. It comprises of datasets on Hospital Compare by General Practitioners and Long Term Care Hospitals by General Information and Provider data. It also includes datasets on Nurse Prescribers, Pharmacy Headquarters and Private Controlled Drug Prescribers in England as well as Medical Center Location of US Hospital.

Processes of care by the type of primary care practice identified through SNA.

Graph and download economic data for Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Nurse practitioners occupations: 16 years and over: Men (LEU0257870400A) from 2011 to 2011 about nursing, second quartile, occupation, full-time, males, salaries, workers, earnings, 16 years +, wages, median, employment, and USA.

Respondent descriptions.

Blinder-Oaxaca linear decomposition results for rural/urban disparities in obstetrician-gynecologist and nurse practitioner/physician assistant visits among women age 18 to 44.