Linking Emotional Labor, Public Service Motivation, and Job Satisfaction: Social Workers in Health Care Settings.

This study examines the determinants of emotional laborers'--social workers in health care organizations--job satisfaction and their public service motivation in using a structural equation model and provides empirical evidence regarding what contributes to job satisfaction or burnout in these workers. Among several latent variables, this study confirmed that false face significantly decreases the job satisfaction of social worker and is positively associated with burnout. In addition, commitment to public interest increases social workers' job satisfaction significantly. This study has implications for the management of emotional labor. By educating emotional laborers to reappraise situations to increase their job satisfaction and avoid burnout, reappraisal training and education are expected to result in increases in positive emotions and decreases in negative emotions, and to improve employees' performance in their organizations.

Efficiency disparities among community hospitals in Tennessee: do size, location, ownership, and network matter?

This study examined the impact of ownership, size, location, and network on the relative technical efficiency of community hospitals in Tennessee for the 2002-2006 period, by applying data envelopment analysis (DEA) to measure technical efficiency (decomposed into scale efficiency and pure technical efficiency). Data envelopment analysis results indicate that medium-size hospitals (126-250 beds) are more efficient than their counterparts. Interestingly, public hospitals are significantly more efficient than private and nonprofit hospitals in Tennessee, and rural hospitals are more efficient than urban hospitals. This is the first study to investigate whether hospital networks with other health care providers affect hospital efficiency. Results indicate that community hospitals with networks are more efficient than non-network hospitals. From a management and policy perspective, this study suggests that public policies should induce hospitals to downsize or upsize into optional size, and private hospitals and nonprofit hospitals should change their organizational objectives from profit-driven to quality-driven.

Determinants of hospital choice of rural hospital patients: the impact of networks, service scopes, and market competition.

Among 10,384 rural Colorado female patients who received MDC 14 (obstetric services) from 2000 to 2003, 6,615 (63.7%) were admitted to their local rural hospitals; 1,654 (15.9%) were admitted to other rural hospitals; and 2,115 (20.4%) traveled to urban hospitals for inpatient services. This study is to examine how network participation, service scopes, and market competition influences rural women's choice of hospital for their obstetric care. A conditional logistic regression analysis was used. The network participation (p < 0.01), the number of services offered (p < 0.05), and the hospital market competition had a positive and significant relationship with patients' choice to receive obstetric care. That is, rural patients prefer to receive care from a hospital that participates in a network, that provides more number of services, and that has a greater market share (i.e., a lower level of market competition) in their locality. Rural hospitals could actively increase their competitiveness and market share by increasing the number of health care services provided and seeking to network with other hospitals.

Hospital choice by rural medicare beneficiaries: does hospital ownership matter?--a Colorado case.

About 45 percent of rural patients in Colorado bypassed their local rural hospitals during the 1990s. The effect of this phenomenon is a reduction in occupancy rates and a decrease in the competitiveness of rural hospitals, thereby ultimately causing rural hospitals to close and adversely affecting the communities that they were designed to serve. This study tests whether hospital ownership affects hospital choice by patients after controlling for institutional and individual dimensions. A conditional logistic regression is used to analyze Colorado Inpatient Discharge Data (CIDD) on 85,529 patients in addition to hospital data. Rural Medicare beneficiaries are influenced to choose a particular hospital by a combination of hospital characteristics (the number of beds, the number of services, accreditation, ownership type, and distance from patient residence) and patient characteristics (medical condition, age, gender, race, and total charge for services). Increasing rural hospitals' survivability, collaborating with other rural hospitals, expanding the number of available services, making strategic alliance with other providers are possible strategies that may help ward off encroachment by urban competitors.