Appendix C

Data Sources, Definitions, and Methods

This appendix describes the two main sources of data used to produce the tables and figures for Chapter 3 on the nursing workforce and provides definitions of key variables. To assist researchers interested in replicating the descriptive results presented in the chapter, step-by-step procedures are provided that identify how variables were defined and data analyzed.

U.S. CENSUS BUREAU, AMERICAN COMMUNITY SURVEY (ACS)

The ACS, an annual nationwide survey designed to supplement the decennial census, began reporting data in 2001. The survey is based on the decennial census long form and produces population and housing information every year instead of every 10 years. Annual estimates of demographic, social, economic, and housing characteristics are available for geographic areas with a population of 65,000 or more. This includes all states, the District of Columbia, all congressional districts, approximately 800 counties, and 500 metropolitan and micropolitan statistical areas. Multiyear estimates are available for smaller geographic areas. During the demonstration stage (2000 to 2004), the U.S. Census Bureau carried out large-scale, nationwide surveys and produced reports for the nation, the states, and large geographic areas. The full implementation stage began in January 2005, with an annual housing unit (HU) sample of approximately 3 million addresses throughout the United States and 36,000 addresses in Puerto Rico. And in 2006, approximately 20,000 group quarters were added to the ACS so that the data fully describe the characteristics of the population residing in geographic areas.

The ACS Public Use Microdata Sample (PUMS) files show the full range of population and housing unit responses collected on individual ACS question-

naires for a subsample of ACS housing units and group quarters persons. PUMS files covering a 5-year period, such as 2011–2015, contain data on approximately 5 percent of the U.S. population.

The survey is fielded annually and achieves a response rate exceeding 90 percent. The race/ethnicity questions are asked nearly identically in the National Sample Survey of Registered Nurses (NSSRN), with respondents first asked about Hispanic origin and then about race. Data were weighted using sampling weights provided by the Census Bureau. Registered nurses (RNs) and nurse practitioners (NPs) are reported as working on a full-time equivalent (FTE) basis, which was estimated by counting a 40-hour workweek as 1.0 FTE.

The ACS surveyed approximately 12,000 RNs in each year from 2001 to 2004, and more than 30,000 RNs in each year starting in 2005 (when the sample was enlarged).

Population data used to adjust estimates of advanced practice registered nurses (APRNs) were obtained from the ACS.

Projections of the NP workforce come from Auerbach, D., P. Buerhaus, and D. Staiger. 2020. Implications of the rapid growth of the nurse practitioner workforce. Health Affairs 39(2):273–279. doi: 10.1377/hlthaff.2019.00686. These projections used data from the ACS.

The ACS can be accessed from the Census Bureau: About PUMs. https://www.census.gov/programs-surveys/acs/technical-documentation/pums/about.html (accessed April 13, 2021).

Definition of an FTE Employed RN or APRN: Using the ACS, a 1.0 FTE = 40 hours, reported as usual weekly hours.

Replicating Results: So that others can replicate the results shown in tables and figures in Chapter 3, the following provides the procedures used to analyze data and, in this illustrative example, develop the information shown in Table C-1.

TABLE C-1 Demographic Characteristics of Full-Time Equivalent (FTE) Registered Nurses (RNs), 2001–2018

Step-by-step procedures for generating the data shown in Table C-1. (Note: Names of variables as they appear in the ACS are depicted in italic.)

1. Download ACS data for 2018 (https://usa.ipums.org/usa-action/samples) (accessed July 24, 2021).
2. Select RNs only, occ = 3255 to 3258. See https://usa.ipums.org/usa/volii/occ2018.shtml (accessed July 24, 2021).
3. Construct FTEs
   1. Keep RNs who are working (empstat = 1).
   2. Construct FTEs as the ratio of usual hours worked (uhrswork, top-coded at 60 hours) to 40.

4. Use survey weights: variable is perwt.
5. U.S. population taken from the U.S. Census Bureau.
6. Gender: variable “sex” coded male = 1, female = 2.
7. Define race/ethnicity
   1. The ACS variable “race” is coded in the following categories:
      1. White
      2. Black/African American
      3. American Indian or Alaska Native
      4. Chinese
      5. Japanese
      6. Other Asian or Pacific Islander
      7. Other race, not elsewhere classified
      8. Two major races
      9. Three or more major races
   2. The ACS variable “hispan” denotes various categories of Hispanic ethnicity.
   3. Coding is as follows:
      1. Any nonzero value of “hispan” à Hispanic
      2. Hispan = 0 AND Black/African American à Black/African American
      3. Hispan = 0 AND (Chinese, Japanese, or OtherAsian or Pacific Islander) à Asian
      4. Hispan = 0 AND White à White
      5. All others = Other
8. Define educational attainment
   1. Use variable educd.
      1. Associate’s degree: (educd ≥0 & educd <101)
      2. Bachelor’s degree (educd = 101)
      3. Graduate (educd >101)
9. Define employment setting
   1. Prior to 2003, hospital employed if = ind1990 = 831.
   2. 2003 and later, hospital employed if ind >8189 and ind <8193.
   3. All other are considered non-hospital employed.
10. The variable indicating age is age.

2008 AND 2018 NATIONAL SAMPLE SURVEY OF REGISTERED NURSES (NSSRN)

The second major source of data for constructing the tables and figures describing the RN and APRN workforce was the 2008 and 2018 NSSRNs. According to excerpts from the Health Resources and Services Administration, the NSSRN is the longest-running survey of RNs in the United States. Since its inaugural assessment in 1977, the NSSRN has provided educators, health

workforce leaders, and policy makers with key details and developments of the nursing workforce supply. The survey assesses the number of RNs in the United States and contains questions regarding RNs’ educational background, employment setting, job position, salary, geographic distribution, social and demographic characteristics, job satisfaction, and other information. The NSSRN was fielded every 4 years from 1977 to 2008 and again in 2018, with most questions pertaining to the RNs’ status as of December 31, 2017.

Considered the cornerstone of nursing workforce data, this comprehensive exploration provides a dynamic status of the RN population by revealing their demographics, educational attainment, licenses and certifications, and employment characteristics. These continued data collections have supported evaluations of government RN workforce programs, assisting in critical decision making affecting the U.S. health care system. Highlighting the intricacies of the current status of the RN workforce is essential for developing strategies that address present-day health care challenges and evolving nursing workforce needs. Following the 2008 survey, the NSSRN questionnaire underwent a complete content review, and large improvements were made based on changes in the U.S. health care landscape and best practices in survey methodology. The latest survey also aims to reduce redundancy in the collection of data and lower the response burden on participants.

The 2018 NSSRN comprises questions derived from both the National Sample Survey of Nurse Practitioners (NSSNP) and the NSSRN for one concise survey capturing a broader RN workforce and is the first production implementation that provides data for both RNs and NPs at the state and national levels. In collaboration with the U.S. Census Bureau, the National Center for Health Workforce Analysis administered the 10th NSSRN data collection in 2018. From April 2018 to October 2018, a total of 50,273 RNs completed the survey via a web instrument or paper questionnaire with an unweighted response rate of 50.1 percent (49.1 percent weighted). This instrument gathered data from participants with active RN licenses from all U.S. states, providing a comprehensive look at the RN workforce. The 2018 NSSRN heavily oversampled NPs and obtained a roughly 50 percent response rate for RNs and NPs, with a final sample of 28,489 RNs excluding NPs and 21,784 NPs.

Data from the 2008 and 2018 NSSRNs were used to produce tables and figures describing characteristics of both RNs and the APRN workforce, particularly NPs.

Definition of Employed APRNs Using the 2008 and 2018 NSSRNs: The following procedures were used to define employed APRNs:

1. The respondent to the NSSRN was identified as being educationally prepared as either a nurse practitioner (NP), clinical nurse specialist (CNS), certified nurse midwife (CNM), or certified nurse anesthetist (CNA);

2. The respondent was identified as employed in nursing and active in providing patient care in his/her primary nursing position.

For cases in which a respondent reported being active in providing patient care but who was identified as being educationally prepared in more than one APRN role (e.g., as both an NP and a CNS), the following methods were used to assign the type of APRN employment (i.e., employed as an NP versus employed as a CNS):

For the 2008 NSSRN, if the respondent reported an APRN job title, the observation was coded to match that job title. For example, if the respondent was identified as having been prepared as both an NP and a CNS, employed in nursing, and active in providing patient care in his/her primary nursing position but reported a job title of NP, the observation was coded “employed as NP.”

The 2018 NSSRN did not ask individuals to report a job title; however, the survey did ask explicitly whether the individual was employed as an NP. As a result, individuals who were identified as being educationally prepared in more than one APRN role but reported employment as an NP were coded “employed as NP.” If the reported job title could not be used to assign APRN employment type (2008 NSSRN) or the respondent did not report being employed as an NP (2018 NSSRN), variables describing the patient population most often cared for and the reported clinical specialty area were examined. For example, if the respondent was identified as being prepared as both a CNM and an NP, employed in nursing, and active in providing patient care in his/her primary nursing position but reported caring primarily for a geriatric patient population, the respondent was coded “employed as NP.” Similarly, if the respondent was identified as being prepared as both a CNM and a CNS, employed in nursing, and active in providing patient care in his/her primary nursing position but reported a clinical specialty of labor and delivery, the individual was coded “employed as CNM.”

If the reported primary patient population or clinical specialty could not be used to determine the type of APRN employment, data were examined to determine whether the respondent was required by an employer to be state-licensed (2008) or nationally certified (2018) in one role but not the other. In such cases APRN employment was assigned to the role in which the respondent reported employer-required licensure or certification.

In the 2018 NSSRN, all sample cases were assigned to an APRN employment type using this approach. In the 2008 NSSRN, a total of 30 sample observations (out of 2,381) were excluded from the analysis of APRN employment because an individual’s APRN employment type could not be determined. These 30 cases represented an estimated 2,727 employed nurses active in providing patient care in their primary nursing position.

Replicating Results: To assist individuals interested in replicating results shown in tables and figures in Chapter 3, the following provides the procedures used to

generate the data included in Table C-2, which are representative of the descriptive analyses conducted of RNs and APRNs.

TABLE C-2 Number of Registered Nurses by Employment Settings, Average Annual Earnings, and Age, 2018

SOURCE: Calculations based on the 2018 National Sample Survey of Registered Nurses.

Step-by-step procedures to replicate the results for Table C-2 are shown below. Note that the variable names are the original variable names given in the 2018 NSSRN public use file.

1. Download the 2018 NSSRN public use data.
2. Define RNs as non-APRNs using the variable APN_COMBOS_PUF and respondents with value = 0.
3. Define an FTE as the ratio of hours worked (variable = HRS_YR) to 2000. FTEs = HRS_YR/2000.
4. Use the variable RKRNWGTA as the survey weight for all respondents.
5. Define RNs over age 50 using the variable AGE_PUF.
6. Tabulate employment settings using the variable PN_EMPSET_ COMB_PUF, only for respondents who are an RN (step 2) and working at least 0.75 FTE (step 3), for both those under and over age 50 (step 5), employing survey weights (step 4), and for each value of PN_EMPSET_COMB_PUF, summarizing earnings using the variable PN_EARN_PUF.

In the case of Table C-3, which focuses on NP employment, the data shown in the table also were obtained from the 2018 NSSRN. Step-by-step procedures to replicate the results are shown below. Note that the variable names are the original variable names given in the 2018 NSSRN public use file.

TABLE C-3 Nurse Practitioner Employment Settings, 2018

SOURCE: Calculations from data in the 2018 National Sample Survey of Registered Nurses.

Employed NPs active in providing patient care were identified using the variables “NP_EMPL_17” and “PN_PATCARE”; for both variables, sample cases with a recorded value of “1.” In Table C-3, the values of “PN_HOSPSET,” “PN_INPSET_PUF,” “PN_CLINSET_PUF,” and “PN_OTHSET” were used to calculate estimated employment by work setting; within each broad group, specified settings with small sample sizes were recoded and combined with cases originally reported as “other setting.” For example, in the broad group of “other setting,” the small number of cases reported for “outpatient dialysis centers” and “call center/telenursing center” were recoded and combined with cases originally reported as “other setting.” The variables “PN_EARN_PUF” and “EMP_STAT” were used to calculate median full-time annual earnings from the principal nursing position, by employment setting.