Performing Department
Agr Economics
Non Technical Summary
Over a twelve year period (2005-2016), 199 hospitals have closed in the United States, of which 94 were located in rural zip codes. These rural hospitals were either the largest employer or one of the largest employers in the community. In addition, rural hospitals tend to provide relatively higher than average wages and benefits. Communities strive to keep these hospitals open to maintain a critical healthcare option for its residents as well as an important employer to the community.When a hospital closes it is important to understand those who are most likely impacted by the closure.The long-term goal of this 3-year integrated project is to improve our understanding of the role of healthcare and a healthy workforce as determinants of local economic development in rural communities. Specifically, our working hypothesis is that while healthcare itself is an important driver of local economic growth in rural communities, it is also a significant factor in both firm and residential location decisions. Through this research we will better understand how a change in the number and type of healthcare businesses impacts changes in employment and wages of both healthcare and non-healthcare related industries in rural communities across the United States.We propose the following integrated project objectives accomplished through an exploration of big data that has been largely underutilized for rural economic development purposes:Objective 1. Measure the role of healthcare as determinants of local economic development in rural communitiesObjective 2: Estimate the role a healthy workforce plays in firm location and retention decisions.Objective 3: Explore regional differences in the relationship between the healthcare industry and rural economic development.We will examine these issues using the U.S. Census Longitudinal Business Dataset and the Annual Services Survey among others available at the University of Kentucky Federal Statistical Research Data Center.We hypothesize that if there is a significant relationship between the healthcare industry and non-healthcare related industries then there are opportunities for these industries to work collaboratively to improve economic opportunities in rural communities. Expected long-term outcomes from this project would include the ability to attract and retain industry, higher wages, a healthier workforce, and population in-migration. By focusing our Extension efforts in two different regions in the US (Kentucky and Nevada), we can provide educational materials and best practices to promote this collaborative behavior based on the region's specific conditions.
Animal Health Component
0%
Research Effort Categories
Basic
(N/A)
Applied
100%
Developmental
(N/A)
Goals / Objectives
The long-term goal of this integrated project is to improve our understanding of the role of healthcare and a healthy workforce as determinants of local economic development in rural communities.Objective 1. Measure the impact of healthcare and workforce as determinants of local economic development in rural communitiesResearch ObjectivesR1A. Understand the factors (including healthcare) that economic development professionals perceive as important in attracting and retaining industry.R1B. Describe the hospital market in rural communities measuring changes in the number and ownership of hospitals from 1987-2015.R1C. Describe changes in non-hospital healthcare employment and wages in rural communities over time controlling for hospital closures, openings, or changes in the level of coverage.R1D. Measure changes in obstetric care when a hospital closes and estimate the impact on changes in residential population.R1E. Describe changes in employment and wages for other industries when a hospital closes, opens, or remains the same. In addition, determine the role healthcare (either hospital or other health-related establishments) plays in firm location decisions.Extension ObjectivesE1A. Strengthen the relationship between the healthcare industry and local economic development professionals through the development of advisory boards and coalitions.E1B. Create educational materials and trainings for both the healthcare and economic development audience including educational webinars, economic impact analyses, templates for news articles, press releases, videos, press releases, etc.Objective 2: Estimate the role a healthy workforce plays in firm location and retention decisions.Research ObjectivesR2. Identify indicators of a healthy workforce that firms and economic development professionals use to market a healthy and productive workforce. Estimate the influence of a healthy workforce as an amenity for industry attraction.Extension ObjectivesE2A. Identify and/or create health promotion and education programs through Cooperative Extension and health departments designed to address those factors identified in R2.E2B. Identify affordable and effective workplace wellness programs for a local employer or a group of local employers to implement to improve the health of the workforce.Objective 3: Explore regional differences in the relationship between the healthcare industry and rural economic development. Research ObjectivesR3A. Test the regional differences in the relationship between healthcare and rural economic development. Kentucky and Nevada represent varying industry, resident, and geographic differences.R3B. Conduct two case studies in both Kentucky and Nevada by exploring places where the relationship between the healthcare and non-healthcare sector has been notably strong as well as in a place where no relationship currently exists.Extension ObjectivesE3. Using the tools developed in E2A and E2B, work with the communities identified through R3B to strengthen the relationship between the healthcare industry, non-healthcare sectors, and economic development.
Project Methods
Objective R1AWe will create a survey for economic development professionals that builds on previous work by the PIs. This survey includes an extensive list of amenities that a firm might consider when relocating. This simple survey will be disseminated to KAED's membership list through an online Qualtrics platform.Objective R1B. Describe the hospital market in rural communities, measuring changes in the number and ownership of hospitals, for the years 1987-2015.The project will use data only available in a secure Federal Statistical Research Data Center (RDC) at the University of Kentucky. We will access the Longitudinal Business Database, the Integrated Longitudinal Business Database, the Service Annual Survey and the Census of Service Industries to address all remaining objectives. These data will be merged with secondary data from numerous publicly available sources to perform the statistical analysis to control for county-level factors affecting hospital and healthcare markets. The sources include:American Community Survey from the Census BureauOccupational Employment Statistics from the Bureau of Labor StatisticsMedicare Fee-For-Service Provider Utilization and Payment Data: Physician and Other Supplier Public Use File from the Center for Medicare and MedicaidNational Center for Health Statistics county-level health statisticsCounty Health Indicators, Robert Wood Johnson FoundationHospital Data. We will extract data from the LBD for each hospital establishment. The LBD includes information on the number of employees and total payroll. Indicators in the file allow us to identify if a hospital is a standalone unit or part of a multi-establishment firm. From the legal form of organization variable we would know if the hospital was for-profit or non-profit. From the LBD we will identify hospitals which enter and exit the community. We also tabulate the change in employment for a hospital over time to see expansion and contraction of the hospital. We will tabulate the number of ownership changes.We will collect data including hospital location and the legal ownership type (non-profit or for-profit). We will include hospitals that are non-Federal, general medical and surgical hospitals with at least one employee. We will measure changes in size by number of employees and wages. Finally, we will count the number of hospitals entering, exiting and continuing in a market overtime. We explicitly are interested in identifying markets where, after a hospital exit, no hospitals existed in the community as well as a hospital entrance where the hospital is now the sole hospital in the community.We also want to compile a group of counties or HSAs where there is no hospital or has continuous presence of one hospital. This group will be used as a comparison group when doing difference-in-difference regression models.We will also compare this community to the next closest one with a hospital and see if that community had an increase in hospital employment.Objective R1CWe will summarize healthcare employment data from the establishment-level data in the LBD for the county and/or HSA. In addition, we will use employment and occupation data at the 3-digit NAICS industry-level (NAICS 621 through 622) and 3-digit SOC (Standard Occupational Classification) codes (SOC 29-1 through 31-9) from the Bureau of Labor Statistics. We will link these data to the hospital data compiled in objective R1b. From this dataset, we will run a difference-in- difference (DiD) regression model. We will look at short and long run effects of hospital exit and entrants. The short run will be one calendar year prior and post hospital event. The long run will be five years prior and post event. With a five year window we will also be able to include data from the CSI and be able to include revenue sources. For the DiD regression, we define the "treated" group as communities where the hospital event occurred. A "comparison" group will be communities where no hospital event took place five years prior or post the event of interest.Objective R1DFor working age and child-bearing age employees various aspects of healthcare may be part of the decision to live in a location. We will look at the access to obstetric care in the local hospital as a measure. These data are available at the establishment level for the Census of Service Industries. Each hospital reports the revenue by primary diagnosis by ICD-9 and ICD-10 codes. From this we can observe changes in the revenue from pregnancy and childbirth. These data are available every five years ending in 2 and 7. Using the model developed in R1C, our dependent variable will be obstetric revenues before and after a hospital closure. In addition, we will explore changes in population with changes in obstetric care to determine if the loss of obstetric care is correlated with a loss in residential population.Objective R1EWe hypothesize that the presence of a hospital might impact the presence of other non-health related establishments and wages. We will evaluate this by observing changes in firm size, wages, ownership, revenue, and employment at the 2-digit industry level before and after an exit or entrance of a hospital. For the industry data we will compile establishment-level data from the LBD. We will summarize the observations to the 2-digit (and 3-digit if appropriate) industry level for the years 1987-2015. We will also use publicly available data from the American Community Survey and the Economic Census data to collect data reflecting characteristics of the community. From this dataset, we will again run a difference-in- difference (DiD) regression model. We will conduct this analysis to test for both short and long run effects of hospital exit and entrants. In addition, we will estimate the importance of healthcare as a contributing factor to firm location decisions. We will estimate a double hurdle model to estimate the probability of non-participation, the probability of zero firms, as well as the probability of a county attracting at least one or more firms based on the presence of community characteristics including a hospital, healthcare employment as well as other local factors including tax rates, workforce characteristics, broadband access, etc.Objective R2We will include measures of a healthy workforce that firms might consider when deciding to relocate or exit a market. We expect to include health characteristics related to obesity, physical activity, drug use, and tobacco use. We will access the County Health Indicators database to collect data at the county level that best reflect the characteristics revealed as important through the survey. Those factors will then be included in the double hurdle model discussed in objective R1E.Objective R3The last research objective will involve case studies of four different communities across Kentucky and Nevada. We will identify these locations based on existing knowledge of the working relationships between the healthcare and economic development partners. Each case study must have exactly one hospital and at least one paid economic development professionals. Through these case studies we hope to identify the nature of the existing relationship between the hospital and traditional industry, the role of the hospital in the local economy, the health of the workforce, the ways in which the economic development professional markets the community, and the success in attracting new firms or retaining existing firms. We anticipate selecting one community where the relationships between healthcare and industry are strong and one where there are only weak ties, if any at all. The purpose of these case studies is to highlight best practices for building a collaborative relationship, to identify successful marketing strategies, and to highlight success stories that can disseminated nationwide.