Determinants of Job Satisfaction and Turnover Intent in Home Health Workers

Abstract

Based on the job demands–resources (JD-R) model, this study explored the impact of job demands (physical injury and racial/ethnic discrimination) and resources (self-confidence in job performance and recognition by supervisor/organization/society) on home health workers’ employee outcomes (job satisfaction and turnover intent). Using data from the National Home Health Aide Survey (N = 3,354), multivariate models of job satisfaction and turnover intent were explored. In both models, the negative impact of demands (physical injury and racial/ethnic discrimination) and the positive impact of resources (self-confidence in job performance and recognition by supervisor and organization) were observed. The overall findings suggest that physical injury and discrimination should be prioritized in prevention and intervention efforts to improve home health workers’ safety and well-being. Attention also needs to be paid to ways to bolster work-related efficacy and to promote an organizational culture of appreciation and respect.

Keywords

home health workers job satisfaction turnover intent physical injury racial/ethnic discrimination

Introduction

According to the U.S. Bureau of Labor Statistics (2012), there are more than 2.2 million home health workers who provide personal assistance services for the frail older adults and individuals with disability. By enabling those with functional challenges to live independently in their homes and communities, home health workers have made a substantial contribution to reducing institutionalization, lowering health care expenditures, and improving the quality of life for both older adults and their families (Benjamin & Matthias, 2004; Bercovitz et al., 2011; Delp, Wallace, Geiger-Brown, & Muntaner, 2010; Yamada, 2002). With the aging of the population and the desire for aging in place (Pastalan, 2013), home health workers are in high demand and are projected to be one of the fastest growing direct care occupations in the near future (Paraprofessional Healthcare Institute [PHI], 2011; U.S. Bureau of Labor Statistics, 2012). However, the home health workforce has been persistently challenged by poor wages, low social status, heavy workloads, and high turnover rates (Delp et al., 2010; Institute of Medicine [IOM], 2008; PHI, 2011; Sauter et al., 2002; Yamada, 2002).

Responding to the urgent need for recruitment and retention of home health workers, the present study has used data from a national sample of home health workers to examine factors associated with employee well-being. Conceptualizing job satisfaction and turnover intent as indicators of employee well-being, the overall framework of the study was based on the job demands–resources (JD-R) model (Demerouti, Bakker, Nachreiner, & Schaufeli, 2001). Originally introduced to explain burnout and work disengagement, the JD-R model includes job demands and resources as major components. Job demands refer to various types of job-related strains that pose burden on workers and deplete their energy. On the other hand, job resources represent factors that help workers alleviate the negative consequences of their job demands. The JD-R model has been widely used in explaining employee well-being in various occupational settings including industry, education, and health and human services (e.g., Bakker, Demerouti, Taris, Schaufeli, & Schreurs, 2003; Delp et al., 2010; Hakanen, Bakker, & Demerouti, 2005; Knudsen, Ducharme, & Roman, 2009; Korunka, Kubicek, Schaufeli, & Hoonakker, 2009).

Job Demands in the Home Health Workforce

Physical overexertion and fatigue, unfavorable work environment, work–family conflict, and emotionally demanding interpersonal interactions have been quite often noted as sources of job demands in home health workers (Bakker et al., 2003; Delp et al., 2010; Mittal, Rosen, & Leana, 2009). Moving beyond the literature, the current investigation focused on the experience of physical injury and racial/ethnic discrimination. In working with older adults with disabilities, home health workers are often faced with physically demanding tasks such as lifting and transferring clients and heavy housekeeping work (Butler, Brennan-Ing, Wardamasky, & Ashley, 2014). Indeed, the home health care sector has been identified as a high-risk industry (IOM, 2008; U.S. Bureau of Labor Statistics, 2012). According to a recent study (McCaughey et al., 2012), more than 1 in 10 home health workers had at least one job-related injury (e.g., back injury, strains, and pulled muscles) in the past 12 months. In accordance with the nationwide effort to ensure a safe environment for all working people (Sauter et al., 2002), further attention needs to be paid to exploring on-the-job physical injury in home health workers.

Considering that direct care work is provided in interpersonal contexts, another type of job demand that deserves further attention is racial/ethnic discrimination. The experience of being treated unfairly or discriminated against is quite often reported in the general U.S. population (Jang, Chiriboga, & Small, 2008; Williams & Mohammed, 2009) and by various workforce members (Ensher, Grant-Vallone, & Donaldson, 2001), regardless of their racial/ethnic orientation. For home health workers, the sources of discrimination could be multiple, including clients and their families as well as agencies and organizations (Berdes & Eckert, 2007). In a study of more than 600 direct care workers in long-term care organizations (Ejaz, Noelker, Menne, & Bagaka’s, 2008), participants reported that they had heard racial/ethnic remarks more often from their residents/clients than from other staff, with an average rate of 3.23 times from the former and 1.60 times from the latter. However, only the racist remarks from the staff were found to have a significant impact on job satisfaction. Although Ejaz and colleagues (2008) conceptualized racial/ethnic discrimination as a negative aspect of social support, the present study considered it as a major job demand along with physical injury.

Job Resources in the Home Health Workforce

Self-confidence in job performance is a personal-level resource that may protect workers from job demands and improves employee outcomes (Morris, 2009). Home health workers with such confidence can not only effectively handle job demands but also enjoy a sense of autonomy, taking pride in their role and contribution (Butler et al., 2014). As a broader level resource, social support is widely known to have a positive impact on employee well-being in many human service work settings (Bogo, Paterson, Tufford, & King, 2011; Smith & Shields, 2013; Strand & Dore, 2009). One example of social support is the recognition of the work that employees do. Studies show that recognition and respect from supervisors, organizations, and the general public play an important role in determining employees’ morale and well-being (Ashley, Butler, & Fishwick, 2010; Benjamin & Matthias, 2004; Morgan, Dill, & Kalleberg, 2013); this is particularly true for home health workers, whose profession has been socially devalued and underappreciated (Butler et al., 2014; Woodhead, Northrop, & Edelstein, 2014). By being recognized by a supervisor, organization, and/or society for the work they do, home health workers may be intrinsically rewarded and stay motivated (Morgan et al., 2013). In the present study, we considered various levels of job resources, including not only resources at the personal level (self-confidence in job performance) but also the interpersonal, organizational, and societal levels (recognition from supervisor/organization/society).

Based on the JD-R model (Demerouti et al., 2001), the present study was designed to explore the impact of the selected job demands (physical injury and racial/ethnic discrimination) and resources (self-confidence in job performance and recognition by supervisor/organization/society) in predicting employee outcomes (job satisfaction and turnover intent). We hypothesized that the presence of job demands and lack of resources would be linked to diminished job satisfaction and increased turnover intent. The assessment also took into consideration other variables previously known to be associated with job stress and employee well-being such as sociodemographic characteristics (age, gender, marital status, education, household income, and race/ethnicity) and work conditions (years as a home health worker, current work hour, formal training, agency ownership, and agency chain affiliation). Previous studies report that an early career stage, unstable work hours, lack of training, and affiliation with agencies that are for-profit and part of a chain are closely linked to home health workers’ job dissatisfaction and turnover intent (Delp et al., 2010; Faul, Schapmire, D’Ambrosio, Feaster, & Farley, 2009; McCaughey et al., 2012).

Method

Data Set

Data were drawn from the 2007 National Home Health Aide Survey (NHHAS), the first nationally representative sample survey of home health aides. As a supplement to the 2007 National Home and Hospice Care Survey (NHHCS), home health workers who were employed by the sampled agencies and provided assistance in activities in daily living—including eating, toileting, bathing, dressing, or transferring—were invited to participate in the NHHAS. Interviews were conducted in English using computer-assisted telephone interview technology. Details of the survey design and sampling procedures are available elsewhere (Bercovitz et al., 2011). A total of 3,377 individuals participated in the survey, with an 80% aide-level response rate. After removal of 23 individuals who had more than 20% of data missing in the variables included in the present analysis, the final sample was 3,354.

Measures

Sociodemographic characteristics

Sociodemographic information included age (in years), gender (0 = male, 1 = female), marital status (0 = married, 1 = unmarried), educational attainment (0 = >12 years, 1 = ≤12 years), annual household income (0 = <US$20,000, 1 = US$20,000 to <US$40,000, 2 = US$40,000 to <US$60,000, 3 = US$60,000 or more), and race/ethnicity (0 = non-Hispanic White, 1 = non-White).

Work conditions

Job-related variables included years as a home health worker (0 = <2 years, 1 = 2-5 years, 2 = 6-10 years, 3 = >10 years), current weekly work hour (0 = <20 hr, 1 = 20-30 hr, 2 = 31-40 hr, 4 = >40 hr), initial formal training (0 = no, 1 = yes), agency ownership (0 = non-profit, 1 = for-profit), and agency affiliation (0 = non-chain, 1 = chain).

Demands

In terms of on-the-job physical demands, the incidence of injury since starting the position or during the past 12 months was surveyed using a list, including (a) back injuries, (b) other strains or pulled muscles, (c) animal bites, (d) black eyes or other types of bruising, and (e) other work-related injuries. Participants were asked to report whether they had experienced each injury, in a yes/no format. A binary variable (0 = no injury, 1 = experience of any injury) was used in the analysis.

In terms of emotional demands, participants were asked whether they had been discriminated against on-the-job because of their race or ethnic origin. A binary response (0 = no, 1 = yes) was used. In addition, the questionnaire included information on the source of discrimination: whether the experience was from clients, clients’ family members or friends, agency management, or other sources.

Resources

Self-confidence in job performance and recognition by a supervisor/organization/society were considered. Participants were asked to rate how much they agreed with the statement, “I am confident in my ability to do my job,” on a 4-point scale (1 = strongly disagree, 2 = somewhat disagree, 3 = somewhat agree, 4 = strongly agree). The amount that participants think that their supervisor/organization/society values or appreciates the work they do was rated on a 3-point scale for each (1 = not at all, 2 = somewhat, 3 = very much).

Outcomes

In terms of job satisfaction, participants were asked to rate how satisfied they were with their job, on a 4-point response scale (1 = extremely dissatisfied, 2 = somewhat dissatisfied, 3 = somewhat satisfied, 4 = extremely satisfied). Turnover intent was also measured with a single item, asking how likely participants were to leave the job at their current agency during the next year. The original 3-point response (0 = not at all likely, 1 = somewhat likely, 2 = very likely) was re-coded as a dichotomous variable (0 = no turnover intent, 1 = presence of turnover intent) by combining the latter two categories.

Analytic Strategies

Descriptive and bivariate analyses were conducted to understand the characteristics of the sample and the underlying associations among study variables. To explore determinants of job satisfaction and turnover intent, separate regression analyses were conducted. A linear model was used for job satisfaction and a logistic model for turnover intent. Based on the JD-R model (Demerouti et al., 2001), the sets of variables included sociodemographic characteristics, work conditions, demands, and resources. Analyses were performed using Stata 13.

Results

Descriptive Characteristics

Table 1 summarizes the major characteristics of the sample and the study variables. The overall description is in accordance with the national profile of home health workers generated from the 2000 U.S. Census (Montgomery, Holley, Deichert, & Kosloski, 2005). Age ranged from 20 to 65 years, with an average of 45.6 years (SD = 11.6). Reflecting the nature of the workforce, an overwhelming majority (96.9%) was female. Due to its lack of variance, gender was excluded in further analyses. Forty-four percent of the participants were unmarried; about 64% had received a high school education or less; and more than 66% had an annual household income of less than US$40,000. About 33% were non-Whites, with 21.6% being non-Hispanic Blacks, 3.7% being Hispanics, and 7.8% being others. More than half (53%) had been working as a home health worker for more than 10 years. A majority (82.3%) reported 20 to 40 weekly work hours. About 85% reported that they had received formal training to become a home health worker. Thirty-one percent of the participants were working at for-profit agencies, and about 23% at agencies affiliated with a chain.

Table 1.

Descriptive Characteristics of Home Health Workers (N = 3,354).

Variable	M ± SD (minimum-maximum) or %
Sociodemographic characteristics
Age	45.6 ± 11.6 (20-65)
Gender (female)^a	96.9
Marital status (unmarried)	44.0
Education (≤high school)	63.3
Household income
<US$20,000	18.9
US$20,000 to <US$40,000	47.6
US$40,000 to <US$60,000	21.6
US$60,000 or more	11.8
Race/ethnicity (non-White)	32.8
Work conditions
Years as a home health worker
<2 years	8.3
2-5 years	19.6
6-10 years	19.2
>10 years	53.0
Current work hours
<20 hr	11.3
20-30 hr	19.2
31-40 hr	63.1
>40 hr	6.5
Training (yes)	84.8
Agency ownership (for-profit)	30.9
Agency affiliation (chain)	23.1
Demands
Physical injury	16.6
Perceived discrimination	10.8
Resources
Self-confidence in job performance	3.67 ± 0.66 (1-4)
Recognition by supervisor	2.79 ± 0.45 (1-3)
Recognition by organization	2.69 ± 0.51 (1-3)
Recognition by society	2.57 ± 0.56 (1-3)
Outcomes
Job satisfaction	3.51 ± 0.65 (1-4)
Turnover intent	25.3

Variable excluded in multivariate analyses because of a lack of variance.

About 17% of the participants had at least one on-the-job physical injury. In a subgroup analysis of those with an injury experience (n = 555), back injury was the most frequently reported (45.9%), followed by other strains or pulled muscles (38.4%). The rate of experiencing racial/ethnic discrimination was 10.8%. Among those with discriminatory experiences, 82.3% reported the source as being agency management, 80.4% clients, and 55% clients’ family members and friends. It was notable that 22.6% of the sample had experienced either physical injury or discrimination, and 2.4% had experienced both.

Self-confidence in job performance averaged 3.67 (SD = 0.66). The scores for recognition by supervisor/organization/society were all geared toward the positive side, with means of 2.79 (SD = 0.45), 2.69 (SD = 0.51), and 2.57(SD = 0.56), respectively. Job satisfaction scores were also quite high, with a mean of 3.51 (SD = 0.65); however, about a quarter of the participants indicated a turnover intent.

Predictive models of job satisfaction and turnover intent

Prior to analyzing the multivariate models, we examined bivariate correlations among the study variables. All variables were found to be correlated in the expected direction, and no concern about collinearity was identified. The highest coefficient was found in the relationship between recognition by supervisor and recognition by organization (r = .49, p < .001). Job satisfaction and turnover intent were inversely correlated (r = −.42, p < .001).

Table 2 summarizes the results of the multivariate analyses. In the linear model of job satisfaction, a lower level of satisfaction was predicted by younger age, higher education, lower income, and racial/ethnic minority status. Among the work condition variables, fewer weekly work hours and affiliation with for-profit agencies were found to pose a significant risk to job satisfaction. Both of the demand-related variables (physical injury and perceived discrimination) significantly reduced job satisfaction. Also, self-confidence in job performance and recognition by a supervisor or organization emerged as significant promoters of job satisfaction. Recognition by society was positively associated with job satisfaction on a bivariate level (r = .13, p < .001); however, it was no longer significant in the multivariate model. The total amount of variance explained by the estimated model was 27% (F = 74.4, p < .001). The interactions between the demand and resource variables were also explored; however, none of the interaction terms reached statistical significance.

Table 2.

Regression Models of Job Satisfaction and Turnover Intent.

Predictor	Job satisfaction		Turnover intent
Predictor	β	t	OR	95% CI
Sociodemographic characteristics
Age	.07	4.02***	0.99**	[0.98, 0.99]
Marital status (unmarried)	−.01	−0.54	1.25*	[1.04, 1.50]
Education (≤high school)	.05	3.25**	0.63***	[0.53, 0.74]
Household income	.05	2.39*	0.98	[0.89, 1.08]
Race/ethnicity (non-White)	−.08	−4.30***	1.64***	[1.38, 1.94]
Work conditions
Years as a home health aide	−.01	−0.95	0.88**	[0.80, 0.96]
Current work hours	.07	4.03***	0.65***	[0.58, 0.72]
Training (yes)	.01	0.40	0.97	[0.77, 1.22]
Agency ownership (for-profit)	−.08	−4.22***	1.25*	[1.02, 1.52]
Agency affiliation (chain)	−.02	−0.85	1.35**	[1.09, 1.66]
Demands
Physical injury	−.10	−5.73***	1.77***	[1.42, 2.20]
Perceived discrimination	−.11	−6.16***	1.71***	[1.33, 2.21]
Resources
Self-confidence in job performance	.11	6.65***	0.86*	[0.75, 0.98]
Recognition by supervisor	.19	10.4***	0.52***	[0.42, 0.64]
Recognition by organization	.30	16.4***	0.47***	[0.39, 0.57]
Recognition by society	.01	0.35	0.94	[0.80, 1.09]
Summary statistics	R² = .27		−2 log likelihood = 3,133.4
Summary statistics	F = 74.4***		χ²/df = 475.7***/16

Note. β = standardized regression coefficient; OR = odds ratio; CI = confidence internal.

p < .05. **p < .01. ***p < .001.

In the logistic model of turnover intent, a higher likelihood was observed among those of younger age, unmarried status, higher education, and racial/ethnic minority status. Among the work condition variables, a shorter career in home health workforce, fewer weekly work hours, and affiliation with agencies that were for-profit and part of a chain significantly increased the odds of having turnover intent. The experience of physical injury and racial/ethnic discrimination increased turnover intent by 1.77 times and 1.71 times, respectively. A substantial contribution by the resource variables was also observed; those who reported higher levels of self-confidence in job performance and recognition by supervisor and organization were less likely to have turnover intent. As was observed for job satisfaction, recognition by society became non-significant in the multivariate model, and no significant interaction effect was found.

Discussion

Responding to the growing needs for home health care and the persistent challenges experienced by its workforce (Delp et al., 2010; IOM, 2008; PHI, 2011; Sauter et al., 2002), the present study examined factors associated with job satisfaction and turnover intent in a national sample of home health workers. Basing our analysis on the JD-R model (Demerouti et al., 2001), we chose to focus on the role of job demands (physical injury and perceived discrimination) and resources (self-confidence in job performance and recognition by supervisor/organization/society). Our findings supported the proposed hypotheses by demonstrating a negative impact of job demands and the benefit of resource; these findings have implications for services and policies for home health workforce development.

The descriptive characteristics of the sample reflected the previously reported profile of home health workers in the United States, with a vast majority being women with a disadvantaged background (Montgomery et al., 2005; PHI, 2011; Yamada, 2002). Home health services have been considered a “minority” industry, and the home health workforce includes a substantially higher proportion of non-White members than does the national workforce in general (Montgomery et al., 2005). It is reported that 53% of the national direct care workforce is composed of people of color and 23% of foreign-born immigrants (PHI, 2011). However, the NHHAS sample only included 33% non-Whites. The fact that the NHHAS survey was offered only in English may indicate a systematic exclusion of non-White workers, particularly those with limited English proficiency. Considering the U.S. Census report from 2005 that more than a quarter of home health workers spoke a language other than English at home (Montgomery et al., 2005), the inherent selectiveness of the NHHAS sample calls for caution in making interpretations and generalizations from the survey’s findings.

In multivariate models, workers with advanced age, lower educational attainment, and non-minority status were found to have favorable employee outcomes (higher levels of job satisfaction and absence of turnover intent). The age difference in employee outcomes has been reported in the literature, with older workers being more likely than younger workers to remain in and be satisfied with their current positions (Butler et al., 2014; Faul et al., 2009). It is notable that those with a higher level of education were more dissatisfied with their job and had a higher intention of leaving it. We speculate that discordance between educational attainment and social status may be an underlying reason for this finding. A higher risk of job dissatisfaction and turnover intent was also observed among racial/ethnic minorities.

Both job dissatisfaction and turnover intent were observed among individuals who had fewer work hours and who were affiliated with for-profit agencies. A shorter career in the home health workforce and affiliation with an agency with a chain membership were associated only with turnover intent. These findings are in line with the literature demonstrating the vulnerability of direct care workers with unstable work hours, at an early career stage, and with employment by agencies that are for-profit and part of a chain (Delp et al., 2010; Faul et al., 2009; McCaughey et al., 2012).

Directly supporting the proposed hypotheses, we found a negative impact of physical injury and racial discrimination. Exposure to physical hazards and psychological stress are a central consideration in the work safety model postulated by the National Institute for Occupational Safety and Health (NIOSH; Sauter et al., 2002), and our findings confirm the value of considering both of these types of job demand. The rate of experiencing discrimination was substantially higher among non-Whites (24.0%) than that among their White counterparts (4.4%). Considering the exclusion of non-English-speaking home health workers from the NHHAS, the reported rate of discrimination could be an underestimate. It was quite striking that a quarter of the sample was exposed to physical injury or discrimination, or both, on the job. Thus, our overall findings suggest that physical injury and discrimination should be prioritized in prevention and intervention efforts to improve home health workers’ safety and well-being.

Our findings concerning the role of resources can serve as an important guideline for such intervention strategies. Three out of the four variables considered in the proposed model emerged as significant predictors of employee outcomes, after controlling for the background and demand variables. Given the benefits of self-confidence in job performance, ways to bolster home health workers’ work-related efficacy need to be sought. One such way may be the provision of employee training. Although training in itself was not a significant factor in our model, the literature shows that the perceived helpfulness of training has a positive impact on employee outcomes (McCaughey et al., 2012). Efforts should be made to improve the quality of training for home health workers, which can build not only their job-related skills but also their self-confidence in their job performance. Our observation that employee outcomes were substantially improved by the recognition that home health workers had received from their supervisors and organizations highlights the critical role of the workforce environment. Home health workers seem to be intrinsically rewarded by supervisory and organizational relationships that are supportive and appreciative (Butler et al., 2014; Woodhead et al., 2014).

Some limitations of the present study should be noted. First, as mentioned earlier, the underrepresentation of non-Whites, particularly those with limited English proficiency, limits the generalizability of the findings and invites further research with more representative samples of home health workers. Second, the cross-sectional nature of the data limits our ability to draw causal inferences among the study variables. Although turnover intent is an important proxy, actual turnover needs to be included in the longitudinal assessment. Also job satisfaction needs to be measured with a multidimensional scale with a validated psychometric quality. It should also be noted that participants’ responses, especially to the questions on job status and relationships with their current employers, might have been biased toward socially desirable directions.

Despite these limitations, the present study contributes to improving our understanding of home health workers, considering both physical and psychological job demands as well as multidimensional aspects of job resources. Our study findings suggest that three approaches are possible to improve home health workers’ well-being. The first comprises prevention and intervention efforts related to physical injury and discrimination. Given the higher rate of discriminatory experience in non-Whites, special attention needs to be paid to minority workers. In a stress reduction intervention with Black female workers, Mays (1995) showed that discussions on race and gender discrimination in the workplace were effective in alleviating their work-related stress. The second consists of providing quality training to bolster home health worker’s work-related efficacy and confidence. This type of person-directed intervention is known to reduce work stress and burnout in the short term; however, the long-term benefit would be maximized when the approach is combined with organization-directed interventions (Awa, Plaumann, & Walter, 2010; Westermann, Kozak, Harling, & Nienhaus, 2014; Woodhead et al., 2014). Such effort may include supervisor training to improve support provided to employees and promotion of an organizational culture that is based on mutual respect and appreciation. Multidimensional efforts to address job demands and strengthen resources will enhance home health workers’ job satisfaction and retention.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

Yuri Jang is an associate professor in the School of Social Work and a faculty research associate at the Population Research Center, The University of Texas at Austin. Her research focuses on positive adaptation in aging, health disparities, and minority health and service utilization.

Ahyoung A. Lee is a doctoral candidate in the School of Social Work at the University of Texas at Austin. Her research focuses on workforce development and retention in long-term care, occupational stress and well-being, and integrated health care.

Michelle Zadrozny, LMSW is the Director of Workforce Development at Helping the Aging, Needy, and Disabled (H.A.N.D.). She has been providing management consulting services to organizations in both nonprofit and private sector since 2006, focusing on developing and implementing new initiatives to further organizational development and employee wellness.

Sung-Heui Bae received her PhD in Health Policy and Administration from University of North Carolina at Chapel Hill in 2008. She is a health services researcher and an Assistant Professor at the School of Nursing at the University of Texas at Austin. Her program of research has focused on health policy, nurse staffing, CMS reimbursement policy, and survey research method.

Miyong T. Kim received her PhD in Nursing Research with a minor in Psychology from the University of Arizona in 1995. She is Professor and Associate Vice President for Community Health Engagement at the University of Texas at Austin. Dr. Kim’s areas of research expertise include community-based participatory research, comparative epidemiology, measurement science, and program evaluation.

Nathan C. Marti received his PhD in Psychology with a specialization in statistics from the University of Texas at Austin in 2001. He was affiliated at the Statistical and Mathematical Consulting Services at UT Austin before developing his private consulting practice, Abacist Analytics. His projects have focused primarily on health-related outcomes.

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