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Health Care Workforce Needs in Wyoming: Update 2017


Table of Contents | Findings | Chapter 1 | Chapter 2 | Chapter 3 | Chapter 4 | Chapter 5 | Chapter 6 | Chapter 7 | PDF

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Published June 2017

Chapter 1: Introduction

by: Tom Gallagher, Research & Planning Manager

Viable communities provide for public safety, ensure the inter-generational transfer of knowledge through schools and cultural activities, and – very importantly – provide health care for their citizens. This publication examines demand and supply issues for the health care industry in Wyoming. It represents an update to the publication Health Care Workforce Needs in Wyoming: Advancing the Study, published in the fall of 2011.

Following a decade of research on the nursing profession in Wyoming, Advancing the Study introduced several research innovations, but still left knowledge gaps. Health Care Workforce Needs in Wyoming: Update 2017 continues the tradition of research innovation. This new publication introduces measures of hours worked, links postsecondary graduation awards to license attainment and employment, and introduces measures of workplace safety. As a result, Update provides a better understanding of the extent to which the health care workforce in the state is fully used, provides information on the workforce supply system, and offers an opportunity to identify areas where workplace safety interventions may prove promising, thereby enhancing labor supply.

The most recently available quarterly Unemployment Insurance payroll reveals a decline in employment and wages for six consecutive quarters ending with third quarter 2016 (2016Q3) – one quarter longer than the coal bed methane decline from 2009Q1 to 2010Q1. The available data indicates that contraction persists through 2017Q1. However, even through times of economic downturn, Wyoming’s health care sector has continued to grow.

As noted by Faler (in press), between 2009 and 2015, gross domestic product (GDP) – the value of all goods and services produced – for health care & social assistance (NAICS1 sector 62) grew by 17.3% in the U.S., while total GDP grew by 15.3% (in real 2009 dollars). Total health expenditures nationally represented 7.1% of GDP in 2015. Understanding these national trends and the regional configuration of the health care delivery system is important because spending on health care often takes place outside the community in which one lives. The faster national than state growth in NAICS sector 62 is an indication of strong national competition for health care labor.

Health care spending in Wyoming represents a smaller share of total consumption than at the national level. Its importance as a stabilizing factor in local economies prone to rapid economic expansion and contraction is a characteristic somewhat unique to Wyoming. Employment in the health care & social assistance sector in Wyoming has seen slow steady growth (see Chapter 2). However, because Wyoming’s economy is prone to rapid expansion and contraction (compared to most other states), the slow steady growth of health care can appear to be large or small depending on the context provided by the balance of Wyoming’s economy. Between 2009 and 2015, Wyoming’s gross state product (GSP) in health care grew by 4.0%, about one-fourth of the national growth rate. During Wyoming’s expansion in 2009, spending on health care made up 3.7% of GSP. On the other hand, it rose to 4.0% of GSP in 2015. Total GSP declined by 3.1% between the two time periods. The economic value of health care is determined by its slow steady growth in the context of rapid expansion and contraction in the balance of Wyoming’s economy.

The health care delivery system is more than the sum of purchases at local clinics, regional hospitals, or at the retail end of the pharmaceutical supply chain. As this publication makes clear, the system of formal education – as well as the role of the federal government in financing education and supporting the purchase of health care services – must be kept in mind. The total cost of providing health care substantially exceeds the total spending on the production and consumption of health care expressed by GDP and GSP.
The drivers of health care spending are, to a significant degree, financed by the federal budget for Medicare and Medicaid, programs with cost of living adjustments. Therefore, local employment in health care has an economic stabilizing effect (at least in the short run) when other Wyoming job losers and employers reduce overall spending. In terms of relative size, health care spending in Wyoming represents a smaller share of total consumption than it does in the U.S. as a whole. On the other hand, it is important in stabilizing local economies.

Demographics are another key driver in health care consumption and are covered extensively in Chapter 2. Age and gender are important factors associated with household composition and migration. They are associated with health care spending, certain types of health care services, access to employer provided benefits, and access to federal program resources. Health care spending increases as the population ages, even as income declines.

At the national level, the household Consumer Expenditure Survey reveals that spending on health care in households headed by persons ages 45-54 had post-tax incomes of $79,845 in 2015 and spent a mean average of $3,215 on health care. At the same time, households headed by those in the 55-64 age group had mean pre-tax incomes of $63,984 and spent $3,436 on health care, or $221 more than the younger cohort with higher incomes. Even though these are national estimates of earnings and spending, they clearly indicate that income is not the only factor in health care spending. Given the aging of Wyoming’s population, the pattern of increased spending on health care as one ages even though income is lower, is a reason for the state to anticipate sustained spending on health care (U.S. Bureau of Labor Statistics, 2016).

Industries differ in the extent to which the labor pipeline passes through postsecondary education in Wyoming and in the extent to which industries rely on importing labor from other parts of the country. As shown in Chapter 2, one in five employed workers in Wyoming during 2015 were nonresidents. On the other hand, in health care & social assistance, only one in 10 workers was a nonresident. Given the high proportion of employment requiring postsecondary education compared to most other industries, more attention needs to be paid to higher education as a supply factor in health care than in many other industries. However, the ratio of resident-to-nonresident workers with all types of educational attainment in this industry varies widely across periods of rapid expansion and contraction. Moreover, postsecondary education in Wyoming is not always the source of labor supply. The year 2015 represents a period of contraction and lesser reliance on nonresidents.

Retention of Nurses in Wyoming, published by Research & Planning 2008, was based on administrative and survey data collected in 2007 during the peak of the coal bed methane boom. At that time, a majority of nurses working in the state were nonresidents (Harris, et al., 2008, p. 42).

Nativity is important in several ways, among them are social acceptance in the workplace and a propensity toward out-migration during periods of economic decline or coincidental with retirement. The absence of economic opportunity and the attraction of family in other states leads to population impermanence among health care workers (Harris, et al., 2008, pp. 42-44).

Retention concluded that “… at mid-decade almost all new workers in Wyoming came from other states or were natives of Wyoming returning to the state … . Industries driving the in-migration of workers are higher-wage and are dominated by males (mining, construction, wholesale trade). As the families of these workers migrate to the state, spouses who are nurses come to represent a key share of the overall supply…” ( Harris, et al., 2008, p. 44). Understanding labor supply issues in health care requires understanding market issues that are not intrinsic to health care itself. Wyoming’s economy drives a unique demographic.

Only two in five residents of Wyoming were born here (see ACS reference). Other states like Colorado have similar ratios of native born to residents. However, Colorado is a center of sustained population in-migration, while Wyoming is currently experiencing net out-migration. In Wyoming, periods of rapid employment growth followed by rapid decline characterize the labor supply system and result in a state comprised of non-natives. It also means that the role of formal education in the supply chain for labor is more or less important depending upon the business cycle. Chapter 3 of this publication characterizes the role of formal education in the supply of health care workers. Longitudinal tracking of graduates from Wyoming’s postsecondary institutions from the earliest cohort available (2006/07 graduates) reveals that eight years after graduation, only 43.6% could be found working in Wyoming. This health care workforce loss rate in Wyoming is slightly higher than that found in previous studies of young adults leaving Wyoming (Jones, 2005; Harris, et. al, 2008, p. 17; and Glover, 2012).

When Advancing the Study was published in 2011, R&P knew a great deal about where the supply of labor in Wyoming originated. Data sharing agreements with state research offices affiliated with U.S. Department of Labor in other states enabled R&P to determine which workers in Wyoming were residents and which were nonresidents. On the other hand, very little was known about the educational attainment of the health care workforce and what role education played in labor supply.

Is holding a certified nursing assistant (CNA) award part of the track to obtaining a postsecondary award in an advanced licensed health care occupation? Is CNA status a predictor of continued employment in a health care industry? Chapter 4 offers a baseline model for what CNA status can tell us about developing a career pipeline for work in the health care industry. The premise of Chapter 4 is that understanding the baseline workforce-education model in the development of the credentialed occupations is a necessary first step in implementing policies that improve the labor supply.

Chapter 5 presents counts of persons working in licensed health care occupations across time and by age. The distribution of age is important to determining the extent to which worker replacement need (e.g. for reasons relating to retirement or death) should be an immediate consideration in workforce development regardless of anticipated growth. Hours worked for selected occupations in rural and urban settings provide an indication of how the two settings manage different staffing levels at different levels of full-time equivalency. Adding employees in some settings may be preceded by increasing work schedules. A changing population base of patients may not have the same effect on employment opportunities in both rural and urban settings.

The health care delivery system is concentrated in urban settings, where the advanced skills of health care workers can be efficiently integrated into specialized services. Chapter 6 examines health care employment-to-population ratios for sub-state regions in Wyoming, its metropolitan statistical areas (MSA), and adjacent MSAs in adjacent states. The author uses the ratio of health care jobs to population within the U.S. as a whole to establish an appropriate standard of service, then applies those ratios to geographic areas within Wyoming and among neighboring MSAs. Applying a national standard of health care jobs to population lays an empirical foundation for determining the adequacy of local service. Mapping the availability of services illustrates the competitive nature of the health care delivery system.

Finally, reducing the incidence of workplace injury may enhance the supply and productivity of the health care workforce. In Chapter 7, analysts produced a record of workplace safety incidents by combining Workers’ Compensation claims records for workers employed in licensed health care occupations. Combining the information in this chapter with other chapters provides a comprehensive perspective on compensation and working conditions for each health care occupation. This chapter benefited substantially from comments provided by Wyoming’s State Occupational Epidemiologist.

Most of the data linkages used to develop this report have never before been carried out outside of Wyoming. There are no precedents for the evaluation of this work and several of the chapters represent unique efforts. We welcome comments on how to improve our research approach.

Data, Information, and Analysis: Two Dimensional Data in a Multi-Dimensional World

Update uses a range of statistical tools to organize data about the health care workforce. At the firm and industry levels, Update uses the North American Industrial Classification System (NAICS), the system State Unemployment Insurance (UI)2 agencies uses to classify almost all firms, jobs, and payrolls for purposes of administering the UI program, the foundation of the state-federal employment statistical system.

Health care & social assistance (NAICS sector 62) represents firms whose primary function is health care. Industry level data are frequently produced and more current than occupational data. In addition, health care occupations may be found in a variety of industrial sectors especially, but not limited to, educational services (NAICS sector 61) and public administration (NAICS 92). Each chapter of this publication specifies how it uses industry specific (NAICS 62 only) or cross-sector statistics.

Most issues in the labor market are complex, multidimensional, and changing. Rarely is one data source or unit of measure adequate to the question. Workforce supply chains reach from the domain of education into the domain of workforce, and often back again, spanning what could arguably be described as two different languages. Compelling, empirically-based narratives linking these two domains across time are rare.

Much of what we know about the labor market comes from national household surveys conducted by the Census Bureau or surveys of employers by the Bureau of Labor Statistics (BLS). The advantage of these sources is that the results can be compared between states and over time. However, as sample survey estimates programs, the amount of detail is often sparse and the level of error large. These limitations are especially problematic for small, dynamic state economies such as Wyoming’s.

Where federal data is cited in Update, the original data sources are often state agency administrative records. State UI payrolls, for example, are the single largest component of gross domestic product. Demographic data in Census products are often drawn from state vital statistics and school enrollment reports (in addition to Internal Revenue Service records). In large part, statistical use of administrative data at its core originates in state administrative records.

There is no established, single, integrated, locally relevant system of data about current and future supply and demand issues in health care (or any other domain). To obtain answers, it is necessary to build such a system. And if cost is a consideration, the elements to build the system must be readily available at low cost. Since data elements for the system come from different sources, they must have compatible characteristics facilitating comparison and potential linkage into a single data set. Thus, many of the data elements in this report were initially collected to administer different human resource programs. The challenge is to transform these different data elements into labor supply and demand information.

R&P uses data sharing agreements conforming to federal and state statutes with postsecondary institutions and health care licensing boards to obtain labor supply data elements. R&P’s staff link these records to UI employer payroll files to determine whether or not postsecondary awards are meeting employer needs for workers. For example, the linkage is made between the graduation award, licenses, and UI wage earnings records. The common linkage element is the social security number. However, each person can have several awards, licenses, and wage records (jobs) at any point in time and across time. One of the goals in this analysis is to simplify data presentation to conform to everyday usage concepts. However, people are multidimensional in their behavior and often no single dimension is more relevant than another in addressing a particular research question. The dynamic of workforce interaction with education and the market over time, results in complexity, a fact that cannot be dismissed as simply inconvenient.

The most frequently used concepts in labor market analysis are those of industry and occupation. An industry represents the economics of production. Firms having similar production functions are grouped together in industrial sectors. An occupation is defined as a set of tasks and activities performed by workers or required by jobs. Table 1.1 presents a cross tabulation of health care occupations across all industrial sectors in Wyoming.

Table 1.1 represents estimates of jobs worked (rather than persons working) from a sample survey of firms as part of the BLS Occupational Employment Statistics (OES) – state cooperative statistical program. The OES program uses the Standard Occupational Classification (SOC) system to group jobs into common occupational categories. Update uses the SOC to classify jobs, persons working, and health care licenses.

As a sample survey, OES estimates are subject to estimation error. Licensing files may contain errors associated with data entry, intentional misrepresentation, processing, and maintenance. Therefore comparisons across chapters will encounter differences because the unit of measure may change even though the system of coding, e.g. the SOC, remains the same.

All of the classification systems in used in Update are hierarchical, and comprised of mutually exclusive and exhaustive categories (see Figure 1.1). Mutual exclusivity means that each firm, license, or job can fit into only one category within the same classification system. A system is said to be exhaustive if all of the data subject to classification fits into one category. Hierarchical classification systems have general categories containing greater quantities comprised of similar but differentiated subsets. Health care & social assistance (NAICS 62), for example, includes ambulatory care (NAICS 621), hospitals (NAICS 622), and nursing & residential care (NAICS 623), as well as other subsets of firms.

Acknowledgements

Research & Planning would like to thank the state licensing boards with which it has data sharing agreements, without whom this research would not have been possible. These boards include, but are not limited to, the Board of Registration in Podiatry, Board of Speech Pathology & Audiology, Board of Hearing Aid Specialists, Board of Dental Examiners, Wyoming Board of Funeral Service Practitioners, Wyoming State Board of Nursing, Board of Examiners in Optometry, Wyoming Board of Physical Therapy, State Board of Psychology, Board of Chiropractic Examiners, Wyoming Board of Radiologic Technologist Examiners, Wyoming State Board of Respiratory Care, Nursing Home Administrators, State Board of Medicine, Mental Health Licensing Board, and Board of Occupational Therapy.

References

Faler, K. (In press). Wyoming’s gross state product: 2009-2015.

Glover, G. (2012, March). A decade later: Tracking Wyoming’s youth into the labor force. Wyoming Labor Force Trends, 49(3). Retrieved May 24, 2017, from http://doe.state.wy.us/LMI/trends/0312/a1.htm

Harris, M., et al. (2008, August). Retention of Nurses in Wyoming. Retrieved May 23, 2017, from http://doe.state.wy.us/LMI/nursing_retention_08.pdf

Jones, S. (2005, June). Labor retention: Out-migration of youth. Wyoming Labor Force Trends, 42(6). Retrieved May 24, 2017, from http://doe.state.wy.us/LMI/0605/a1.htm

U.S. Bureau of Labor Statistics (2016, August). Table 1300: Age of reference person: Annual expenditure means, shares, standard errors, and coefficients of variation. Consumer Expenditure Survey, 2015. Retrieved May 23, 2017, from https://www.bls.gov/cex/2015/combined/age.pdf

U.S. Census Bureau. (2016). Table 1: State of Residence by State of Birth. 2015 American Community Survey. Retrieved May 24, 2017, from http://census.gov/acs

1North American Industry Classification System.

2In Wyoming, this is the Department of Workforce Services.


© 2017 Wyoming Department of Workforce Services