How ‘healthy’ are healthcare organizations? Exploring employee healthcare utilization rates among Dutch healthcare organizations

Abstract

Occupational health and safety research rarely makes use of data on employee healthcare utilization to gain insight into the physical and mental health of healthcare staff. This paper aims to fill this gap by examining the prevalence of two relevant types of healthcare utilization among staff working in healthcare organizations: physical therapy and mental healthcare utilization. The paper furthermore explores what role employee and organizational characteristics play in explaining differences in healthcare utilization between organizations. A Dutch healthcare insurance company provided healthcare utilization records for a sample of 417 organizations employing 136,804 healthcare workers in the Netherlands. The results showed that there are large differences between and within healthcare industries when it comes to employee healthcare utilization. Multivariate regression analyses revealed that employee characteristics such as age and gender distributions, and healthcare industry, explain some of the variance between healthcare organizations. Nevertheless, the results of the analyses showed that for all healthcare utilization indicators there is still a large amount of unexplained variance. Further research into the subject of organizational differences in employee healthcare utilization is needed, as finding possibilities to influence employee health and subsequent healthcare utilization is beneficial to employees, employers and society as a whole.

Keywords

healthcare costs healthcare insurance healthcare use mental healthcare occupational health physical therapy worker health

Introduction

Healthcare workers are exposed to a complex variety of physical and psychosocial risks every day. The current research on occupational health and safety includes many different outcomes to examine the extent to which the healthcare work environment impacts employee physical and mental health. In most cases, studies rely on self-reports to collect data regarding employee health status.¹ Given the susceptibility to measurement errors associated with subjective measures (i.e. self-report bias),² it is often suggested to use self-reports in conjunction with more objective measures based on archival data. Examples of archival data used as a proxy for employee health include sickness absence data, performance measures, accidents, injuries and death records.³ One source of archival data that is widely used in economic and epidemiological research,⁴ but is rarely included in the field of occupational health and safety research is healthcare utilization. Healthcare utilization data can be understood and interpreted as a set of proxies that indirectly describe the health status of an individual, because individuals in better health would be expected to consume less healthcare services than those in worse health.⁵

In current research, healthcare utilization data are mostly examined by looking at specific groups such as ethnic minorities, age groups or people with certain diseases such as diabetes or cancer. There is very little research examining utilization of health services by looking at specific occupational groups or organizations and there are, as far as we know, no studies examining healthcare utilization among employees working in healthcare organizations. This is surprising, because according to an U.S. healthcare industry study conducted by the Healthcare business of Thomas Reuters, hospital workers consume more medical services and accrue higher healthcare costs than the workforce at large.⁶ This study also found that health risks for hospital employees were 8.6% higher than the general employee population. A hospital or health system with 16,000 employees would be able to save an estimated 1.5 million annually in medical costs for each 1% reduction in health risk. As the rise of healthcare costs is becoming an important issue to combat all around the world, more research into the patterns of healthcare utilization among specific groups, such as healthcare workers, is therefore needed.

With this study, we aim to shed more light on the healthcare utilization of employees working in healthcare organizations. Given the variation in type of care delivery and subsequent work demands within the healthcare sector,⁷ we furthermore distinguish between different healthcare industries. The study makes use of specific insurance claim data from the Netherlands. We specifically focus on the utilization of two types of healthcare services: physical therapy and mental healthcare, which serve as proxies for musculoskeletal disorders and mental health problems. We made this choice because according to the EU-OSHA, the most common health threats posed by the work environment in European countries are musculoskeletal and mental health problems.⁸ In the UK for instance, around 80% of the new work-related conditions in 2015 were musculoskeletal disorders or stress, depression or anxiety.⁹ Moreover, a study by Goetzel et al.¹⁰ showed that health problems such as musculoskeletal disorders, depression and anxiety are among the top-20 list of health conditions requiring attention due to their high costs faced by employers and society. Research from the Netherlands for instance shows that musculoskeletal disorders and psychosocial disease are responsible for 83% of the cost of work-related ill health.¹¹

By examining physical therapy utilization and mental healthcare utilization, we provide insight into the prevalence of two of the most common health threats in healthcare organizations. Moreover, we are interested in examining what role employee and organizational characteristics play in employee healthcare utilization, as this could provide us with possible explanations of utilization patterns among healthcare organizations. These findings can subsequently serve as input in the formation of policies to improve healthcare worker health and reduce employee healthcare costs. The main goal of the study is thus twofold: (1) to describe the physical therapy and mental healthcare utilization of employees working in Dutch healthcare organizations, and (2) to examine what role employee and organizational characteristics play in explaining differences in healthcare utilization between healthcare organizations.

Methods

Data collection and sample

The study population comprises healthcare organizations in the four biggest healthcare industries in the Netherlands: hospitals, nursing homes and home care, mental healthcare and disability care. The Dutch healthcare system is primarily public and funded by means of taxes. Employers pay a fixed percentage of their employee’s income to the tax administration. In addition, employees also pay a fixed percentage of their income to the government. The remaining part of the healthcare funding is the monthly premium that each person pays to their healthcare insurance provider. In the Netherlands, it is mandatory to take out standard health insurance.

For this research, we used healthcare utilization records from the year 2015 to examine differences in physical therapy and mental healthcare utilization among employees working in healthcare organizations. These data were made available by a national healthcare insurance provider (IZZ), which is focused on providing healthcare insurance specifically for Dutch healthcare workers. We selected the healthcare utilization data from healthcare organizations with an IZZ insurance participation rate of 10%, meaning that at least 10% percent of the employees working within the organization have this specific IZZ healthcare insurance. This cut-off point generated an acceptable number of healthcare organizations included in the sample to perform multiple linear regression analyses and is representative of the population of healthcare organizations in the Netherlands.

Our selection resulted in a sample of 417 organizations (employing 136,804 IZZ insured workers) from a total population of 2285 registered healthcare organizations (our sample thus represents 18,2% of the Dutch population). The average IZZ insurance participation rate in these organizations was 24.6% and ranged between 10.1% and 69.2% per organization. This corresponds with a mean of 328 IZZ insured employees per organization (25 employees per organization for the smallest organization to 2798 employees for the largest organization). Table 1 presents the distribution of organizations in our sample compared to the distribution in the population. The results show that hospitals and mental healthcare facilities are overrepresented in our sample and nursing homes are underrepresented. There are several reasons for this. First, the distribution of IZZ insured employees is traditionally higher among hospitals and mental healthcare facilities. Second, in general, nursing homes and home care organizations are smaller in size. Many very small organizations (<25 employees) do not have an agreement with insurance companies to provide an employer contribution to the insurance premium of their employees. This makes the participation rate of IZZ insured employees relatively low in this sector.

Table 1.

Healthcare organizations included in the study compared to the population of healthcare organizations in The Netherlands.

	Included in study sample	Population in the Netherlands	Sample percentage of population (%)
Healthcare industry
Hospitals^a	100	139	71.9
Nursing homes and home care	155	1900	8.2
Mental healthcare	79	89	88.8
Disability care	83	157	52.9
Total	417	2285	18.2

Note: N = 417 organizations.

Including specialized hospitals and rehabilitation clinics.

Measures

Healthcare utilization

In view of the privacy of individual employees, the 2015 healthcare utilization data were provided by IZZ at the aggregated organizational level. We used three different indicators of healthcare utilization for each type of healthcare service: user rate, treatments per user and costs per 100 employees. The user rate is the percentage of employees within the organization that visited a physical therapist (for physical therapy utilization) or a mental healthcare provider such as a psychologist, therapist or psychiatrist (for mental healthcare utilization) during the past year. The treatment per user indicator represents the average number of physical therapy or mental healthcare treatments per user within the organization. The healthcare costs indicator describes the average costs of healthcare utilization in euros per 100 employees within the organization.

As healthcare utilization varies with age and gender,^12,13 the following employee characteristics were included in the analyses:

Employee age

The average employee age in years within the organization.

Employee gender

The percentage of female employees working within the organization.

The following organizational characteristics were available and included in the analyses:

Healthcare industry

The specific healthcare industry the organization belongs to (based on the type of patients and the type of healthcare provided). As the amount of physical and mental strain accompanying the work in these industries differs considerably,¹⁴ we expect the healthcare industry to be important for employee healthcare utilization. We included three dummy variables with the hospital industry as the reference category: nursing homes and home care, mental healthcare and disability care.

Organizational size

The total number of employees working within the organization.

Urbanization

The urbanization rate of the geographical area the organization is located in.

IZZ participation rate

The percentage of employees within the organization that have an IZZ healthcare insurance (our sample within the organization).

Results

Tables 2 and 3 include means, standard deviations, ranges and correlations for the variables in this study. The results show that almost one-third (32.8%) of the employees working in a healthcare organization visited a physical therapist in 2015. This percentage is lower for mental healthcare utilization: 5.7% of the employees visited a therapist, psychologist or psychiatrist. When we look at the treatments per user and costs indicators, we see that the average number of treatments per user and the costs per 100 employees are also lower for mental healthcare utilization (mean treatments = 3.4 and mean costs = €13,429) than for physical therapy utilization (mean treatments = 13.4 and mean costs = €5106). Finally, the range statistics show that there are large differences between organizations when it comes to healthcare utilization, both in utilization of services (users and treatments) and costs.

Table 2.

Descriptive statistics of study variables.

	Mean	SD	Range (min.–max.)
Healthcare utilization
Physical therapy utilization (user rate)	32.83%	6.94%	15.38–65.52%
Physical therapy utilization (treatments per user)	13.38	3.23	3.25–35.75
Physical therapy costs (per 100 employees)	€13429.68	€4619.12	€1647.88–€36435.45
Mental healthcare utilization (user rate)	5.68%	2.79%	0.00–17.86%
Mental healthcare utilization (treatments per user)	3.43	5.24	0.00–99.67
Mental healthcare costs (per 100 employees)	€5106.16	€8903.62	€0.00–€138923.51
Employee characteristics
Employee age (average age within org.)	48.44	2.22	38.99–55.36
Employee gender (% females within org.)	0.78	0.10	0.32–1.00
Organizational characteristics
Healthcare industry (hospital = ref. cat.)
Nursing homes and home care	0.37	0.48	0.00–1.00
Mental healthcare	0.19	0.39	0.00–1.00
Disability care	0.20	0.40	0.00–1.00
Organizational size (number of employees)	1312.57	1331.22	47–12.904
Urbanization rate	3.64	1.10	1.00–5.00
IZZ participation rate	24.58%	11.99	10.05–69.23%

Note: N = 417 organizations.

Table 3.

Correlations between study variables.

	1.	2.	3.	4.	5.	6.	7.	8.	9.	10.	11.	12.	13.	14.
Dependent variables
1. Physical therapy utilization (user rate)	1
2. Physical therapy utilization (treatments per user)	0.16**	1
3. Physical therapy costs (per 100 employees)	0.69**	0.77**	1
4. Mental healthcare utilization (user rate)	0.08	−0.05	0.00	1
5. Mental healthcare utilization (treatments per user)	0.02	0.09	0.09	0.05	1
6. Mental healthcare costs (per 100 employees)	0.00	0.01	0.01	0.19**	0.83**	1
Employee characteristics
7. Employee age (average age within org.)	0.24**	0.20**	0.30**	−0.21**	0.04	−0.06	1
8. Employee gender (% females within org.)	0.33**	0.12*	0.28**	−0.01	0.05	−0.06	0.06	1
Organizational characteristics
Healthcare industry (hospitals = ref.cat.)
9. Nursing homes and home care industry	0.38**	0.17**	0.37**	0.09	0.08	−0.00	0.349**	0.54**	1
10. Mental healthcare industry	−0.17**	−0.16**	−0.22**	−0.01	−0.03	0.06	−0.015	−0.55**	−0.37**	1
11. Disability care industry	0.10*	0.06	0.09	0.12*	−0.05	0.02	−0.246**	−0.09	−0.38**	−0.24**	1
12. Organizational size (number of employees)	−0.15**	−0.01	−0.11*	−0.07	−0.02	−0.06	−.132**	−0.06	−0.15**	−0.10*	0.02	1
13. Urbanization rate	−0.19**	−0.0	−0.18**	0.02	−0.11*	−0.02	0.025	−0.19**	−0.17**	0.12*	−0.11*	0.12*	1
14. IZZ participation rate	−0.17**	−0.06	−0.14**	−0.16**	−0.06	−0.02	−0.066	−0.16**	−0.42**	0.31**	−0.12*	0.03	0.06	1

Note: N = 417 organizations.

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

To shed some light on the large differences in healthcare utilization between organizations, we broke down the indicators and produced scatterplots for each healthcare industry (see Table 4 and Figure 1). The results show that two types of differences in healthcare utilization are visible in the data: differences between healthcare industries and differences between organizations within the same healthcare industry.

Table 4.

Differences in healthcare utilization between healthcare industries.

	Physical therapy utilization			Mental healthcare utilization
	User rate	Treatments per user	Costs	User rate	Treatments per user	Costs
	Mean (SD)	Mean (SD)	Mean (SD)	Mean (SD)	Mean (SD)	Mean (SD)
Hospitals	28.29%^ab (5.35)	12.81^a (3.9)	€10995.13^ab (€2977.61)	4.69^ab (1.53)	3.23 (1.62)	€4032.76 (€4569.01)
Nursing homes and home care	36.26%^ac (6.89)	14.11^ab (3.24)	€15616.64^ac (€4984.74)	6.00%^a (3.06)	3.97 (8.13)	€5091.32 (€12085.59)
Mental healthcare	30.35%^cd (5.69)	12.31^bc (2.00)	€11356.64^cd (€2664.78)	5.62% (2.49)	3.15 (3.00)	€6129.65 (€8860.13)
Disability care	34.23%^bd (5.89)	13.75^c (3.81)	€14251.91^bd (€4798.49)	6.33%^b (3.38)	2.89 (1.52)	€5452.94 (€5044.70)
Total healthcare sector	32.83% (6.94)	13.38 (3.23)	€13429.68 (€4619.12)	5.68% (2.79)	3.43 (5.24)	€5106.16 (€8903.62)

Note: N = 417 organizations (100 hospitals, 155 nursing homes, 79 mental healthcare facilities, 83 disability care organizations).

The mean difference between groups with the same superscript letter is statistically significant at the p < .05 level.

Figure 1.

Scatterplot of differences in healthcare utilization between healthcare organizations.

A one-way between-groups analysis of variance (ANOVA) was conducted to explore the impact of healthcare industry on the physical therapy and mental healthcare utilization indicators. Table 4 shows group means for each healthcare industry. The ANOVA output revealed that there was a statistically significant difference (at the p > .05 level) in physical therapy utilization (user rate [F (3, 413) = 40.27, p < .05]; treatments per user [F (3, 413) = 7.21, p < .05]; and costs [F (3, 413) = 33.32, p < .05]) and mental healthcare utilization (user rate [F (3, 413) = 6.58, p < .05]). Given the fact that significant differences were established, it was necessary to further find out which groups were significantly different from which other groups. This was done by use of a post hoc test (Tukey HSD). The results of the post hoc test presented in Table 4 show an interesting difference between hospitals and mental healthcare on the one hand, and nursing homes and disability care on the other hand. Nursing homes and disability care homes have a significant higher mean in physical therapy user rate and physical therapy costs compared to hospitals and mental healthcare facilities. Furthermore, the mean physical therapy treatments indicator also differed significantly between the nursing homes industry on the one side and the hospitals and mental care industry on the other side. From the mental healthcare utilization indicators, only the user rate appeared to significantly differ between industries. Again, the nursing homes and disability care homes scored significantly higher on mean mental healthcare utilization rate compared to the hospital industry.

Figure 1 shows the scatterplots of physical therapy and mental healthcare utilization user rates within each of the four healthcare industries. The plots identify a scattered, non-linear pattern indicating there is no relationship between physical therapy utilization and mental healthcare utilization (see also correlations in Table 3). Moreover, the plots show that within each industry, there are large differences between individual healthcare organizations. As can be seen in the plots in Figure 1, the variation in healthcare utilization is especially large in the long-term care settings (nursing homes and disability care).

In order to find leverage points for reducing employee healthcare utilization, the second goal of this paper was to examine what role employee and organizational characteristics play in explaining differences in healthcare utilization between healthcare organizations. We used multiple linear regression analyses to test the relationship between employee characteristics within the organization (average age and gender), organizational characteristics (industry, size and urbanization) and the three healthcare utilization indicators.

The results presented in Table 5 show that employee age and gender have a positive relationship with all three physical therapy utilization variables, indicating that organizations with a higher average employee age and a higher percentage of female employees score higher on physical therapy user rate (age: β = .17; p < .01; gender: β = .32; p < .01), treatments per user (age: β = .20; p < .01) and costs per 100 employees (age: β = .23; p < .01; gender: β = .13; p < .05). This result is consistent with generally higher use of healthcare services among the elderly and women.^12,13 The second models with the organizational characteristics show that healthcare industry has a significant effect on physical therapy utilization. In line with the results presented in Table 4 and Figure 1, we found that nursing homes and disability care homes have a significant higher physical therapy user rate (nursing homes: β = .39; p < .01; disability care: β = .35; p < .01) and costs (nursing homes: β = .33; p < .01; disability care: β = .29; p < .01) compared to organizations in the hospital sector. Organizations providing mental healthcare have a significant higher user rate than those in the hospital industry (β = .19; p < .01). Organizational size and urbanization rate were not significantly related to any of the three physical therapy utilization indicators. The second model shows that the included employee and organizational characteristics together explain 28% of the variation in physical therapy user rate, 8% in physical therapy treatments per user and 25% in physical therapy costs. Although employee age and gender account for the largest share in explained variance, there is thus still a large part of variance unexplained.

Table 5.

Multiple linear regression analysis with physical therapy utilization indicators as dependent variables.

	Physical therapy user rate		Physical therapy treatments per user		Physical therapy costs per 100 employees
	β (SE)
	Model 1	Model 2	Model 1	Model 2	Model 1	Model 2
Constant (B)	−17.58* (7.16)	−8.82 (7.99)	−3.25 (3.53)	−.88 (4.21)	−23251.22** (4777.81)	−13599.43** (5428.22)
Employee characteristics
Employee age	.22** (0.14)	.17** (.14)	.20** (.07)	.20** (.08)	.27** (94.38)	.23** (97.15)
Employee gender	.32** (3.25)	.23** (4.05)	.11* (1.60)	.02 (2.13)	.26** (2165.01)	.13* (2750.39)
Organizational characteristics
Healthcare industry (hospitals = ref. cat.)
Nursing homes and home care		.39** (.88)		.12 (.46)		.33** (594.91)
Mental healthcare		.19** (1.01)		−.07 (.54)		.06 (689.62)
Disability care		.35** (.91)		.13* (.48)		.29** (616.82)
Organizational size		−.03 (.00)		.03 (.00)		−.01 (.16)
Urbanization rate		−.06 (.28)		−.04 (0.15)		−.08 (187.72)
R ²	.16	.28	.05	.08	.15	.25
Change in R²		.13**		.03*		.10**
F for change in R²		14.76**		2.61*		11.28**

Note: N = 417 organizations.

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

The analyses for mental healthcare utilization in Table 6 did not show any significant relationship between employee characteristics, organizational characteristics and mental healthcare costs. For mental healthcare treatments per user we found one positive significant effect of urbanization rate (β = .11; p < .05). This means that healthcare organizations located in more urbanized geographical areas have a higher average number of mental health treatments per user among their employees than healthcare organizations located in rural areas. This is in line with the general finding that mental health problems are more prevalent in cities than on the countryside.¹⁵ For the mental healthcare user rate indicator the results show that employee age has a significant negative effect (β = −.28; p < .01), indicating that healthcare organizations with a younger workforce have a higher mental healthcare user rate. Finally, we found that, similar to the results for physical therapy utilization, healthcare industry matters. Nursing homes and disability care homes have a higher percentage of mental healthcare users among their employees than hospitals (nursing homes: β = .37; p < .01; disability care: β = .21; p < .01). Employee gender, organizational size and urbanization rate did not have a significant relationship with mental healthcare user rate. Contrary to physical therapy user rate, we found that the explained variance between organizations for mental healthcare user rate is mostly accounted for by the organizational characteristics. Nevertheless, the results show there is still a large part of variance between organizations within the discerned sectors unexplained in our mental healthcare utilization indicators.

Table 6.

Multiple linear regression analysis with mental healthcare utilization indicators as dependent variables.

	Mental healthcare user rate		Mental healthcare treatments per user		Mental healthcare costs per 100 employees
	β (SE)
	Model 1	Model 2	Model 1	Model 2	Model 1	Model 2
Constant (B)	18.31 (3.06)	23.59 (3.55)	−3.09 (5.86)	2.55 (7.06)	20814.09* (9951.37)	28095.51* (11997.30)
Employee characteristics
Employee age	−.21** (.06)	−.28** (.06)	.04 (.12)	.02 (.13)	−.06 (196.59)	−.09 (214.71)
Employee gender	.01 (1.39)	−.10 (1.80)	.05 (2.67)	.00 (3.58)	−.06 (4509.36)	−.08 (6078.84)
Organizational characteristics
Healthcare industry (hospitals = ref. cat.)
Nursing homes and home care		.37** (.39)		.03 (.77)		.10 (1314.85)
Mental healthcare		.10 (.45)		−.01 (.90)		.05 (1524.18)
Disability care		.21** (.40)		−.05 (.80)		.04 (1363.29)
Organizational size		−.07 (.00)		.00 (.00)		−.05 (.34)
Urbanization rate		.09 (.12)		.11* (.24)		−.02 (414.90)
R ²	.04	.11	.01	.02	.01	.02
Change in R²		.08**		.01		.01
F for change in R²		7.49**		1.11		.87

Note: N = 417 organizations.

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

Discussion and conclusions

Discussion

The main aim of this study was to describe the physical therapy and mental healthcare utilization of employees working in Dutch healthcare organizations, and to examine what role employee and organizational characteristics play in explaining differences in healthcare utilization between healthcare organizations. The results showed that, in the Netherlands, on average 32.8% of staff employed by a healthcare organization visit a physical therapist and 5.7% visit a mental healthcare provider every year. Compared to the Dutch population average of individuals between 20 and 65 years old, physical therapy utilization is higher among staff working in healthcare organizations (Dutch population average is 23.6%). On the other hand, the mental healthcare utilization average of the Dutch population (8.9%) is slightly lower.¹⁶ These percentages will probably vary across countries, as healthcare utilization varies according to characteristics of the healthcare system and socio-economic status.^17,18

Our exploratory analyses also showed that there are large differences between healthcare industries when it comes to employee healthcare utilization. Especially interesting is the difference between hospitals and mental care facilities on the one side and nursing homes and disability care organizations on the other side. Both physical therapy and mental healthcare utilization is significantly higher among nursing homes, home healthcare organizations and disability care homes compared to hospitals. One explanation for this could be that the level of physical and mental workload is higher in long-term care settings.¹⁹ Employees in nursing homes are, for example exposed to a greater amount of heavy handling and work under high time pressure more often than their counterparts in hospitals.^21,22 Furthermore, employees working in hospitals generally have a higher educated population¹⁹ and a lower experience of physical load,²⁰ which could explain the lower healthcare utilization within the hospital industry. The differences in qualification level of nurses between hospitals and nursing homes could also potentially play a role. A study by Simon et al.¹⁴ for instance showed that nursing aides are slightly more at risk of disability than registered nurses. However, there are very few studies investigating employee health in healthcare organizations other than hospitals. Research in mental health facilities and long-term care organizations such as nursing homes or disability care homes are relatively scarce.⁷ Given the increasing demands in long-term care, it is important to have a better understanding of employee health, safety and healthcare utilization in these types of healthcare industries. To shed more light on the unexplained variation in healthcare utilization between healthcare industries, it would be interesting to include information on educational level, healthcare profession and work demands as these socio-economic factors differ between healthcare settings. Unfortunately, it was not possible to add information about profession or educational level of individual healthcare professionals to our healthcare utilization dataset due to privacy legislation. Moreover, at the moment the data are not available at the organizational level. In the future it would be interesting to study differences between healthcare industries by examining a smaller sample of organizations and link their healthcare utilization rates to information on type of profession at the organizational level.

Another relevant conclusion from our research concerns the large differences in healthcare utilization between similar healthcare organizations within the same healthcare industry. Multivariate regression analyses showed that for physical therapy the employee characteristics (average age and gender) explained some variance between organizations. Organizational size and urbanization rate were not significantly related to our physical therapy utilization indicators. Urbanization rate was only negatively related to mental healthcare treatments per user. For mental healthcare user rate we found that the specific healthcare industry makes up the largest part of the explained variance. Nevertheless, the results of the analyses showed that for all healthcare utilization indicators there is still a large amount of unexplained variance. This suggests there are other factors contributing to the differences between healthcare organizations. Future research should examine this more in-depth and consider other variables that might help explain these differences. Obviously, employee characteristics concerning lifestyle such as such as smoking, physical inactivity and eating behaviours should be incorporated. However, other organizational characteristics such as psychosocial work factors may also play a role in this (e.g. see literature^5,23–25). Factors such as leadership and organizational climate have proven to be related to worker health, and can vary significantly between organizations that provide the same type of care. A study by Aiken et al.²⁶ has for instance shown that the odds of nurses being burned out were lower by 24% in hospitals with better work environments relative to hospitals with poor work environments (i.e. poor staff development, leadership and collegial relationships). Stone and Gershon²⁷ found that intensive care units of hospitals with a better organizational climate had lower rates of musculoskeletal injuries than the ones with lower organizational climate scores. The results of these studies indicate that employees’ perceptions of their work environment could be an interesting factor to examine in relation to healthcare utilization. More research on the relationship between various employee and organizational variables and healthcare utilization is needed to discover why similar organizations differ greatly in worker physical and mental health. An increased understanding of the factors underlying these differences is important because it provides information to policymakers and stakeholders on how to reduce employee mental and physical ill-health and subsequent adverse outcomes for the healthcare industry and, in the end, society as a whole. We therefore urge researchers in the field of healthcare management to further examine the healthcare utilization rates of healthcare organizations in different industries, and investigate their relationship with other organizational factors.

Strengths and limitations of the study

The strength of this exploratory study is that few researchers have considered exploring the healthcare utilization patterns of employees, and few researchers have focused on these patterns within healthcare organizations. Our sample consisting of 417 organizations presents almost one-fifth of the entire population of Dutch healthcare organizations. As the healthcare industry is continuously growing and rising healthcare costs are becoming an important issue all around the world, learning more about possible ways to prevent ill health and accompanying costs in this sector is crucial.

As with every research, this study also has its limitations. First, our research exclusively focuses on physical therapy and mental healthcare. Although these two types of healthcare are occupationally relevant, people with musculoskeletal disorders or mental health problems might also make use of other types of healthcare, such as hospital care or alternative medicine (both are not included in our measure). We should keep this in mind when interpreting the results as proxies for physical and mental health problems. A second limitation concerns the limited number of independent variables that were available for this research. To really gain insight into the employee and organizational characteristics that explain the organizational variance in employee healthcare utilization, more extensive explanatory analyses are needed. Finally, although our sample has a considerable size, the nursing homes industry is underrepresented compared to the other industries. Moreover, it is uncertain whether the IZZ insured employees within each organization adequately represent the entire staff. Therefore, sampling bias might have influenced the external validity of our results.²⁸

Implications for practice

Understanding the healthcare utilization patterns of healthcare employees is important because these data can serve as proxies for healthcare workers’ mental and physical health.⁵ Our results show that there are large differences in the physical and mental health status of employees working in different healthcare industries and between employees working in different organizations within the same industry. This implies organization- and industry-specific characteristics play a role in the health of healthcare employees. This opens up possibilities for healthcare organizations to influence employee health and subsequent healthcare utilization, which Is beneficial to employees, employers and society. Besides the direct economic burden of illness on society, our results are also interesting for employers as our findings about within-industry differences in employee health might also point to differences in health-related productivity losses,¹⁰ and eventually differences in quality of care between healthcare organizations. Gaining more insight into the healthcare utilization rates of healthcare organizations and monitoring these rates can therefore be an interesting way to keep tabs of employee health and subsequent outcomes.

Conclusions

The results of this study revealed that there are large organizational differences in healthcare utilization across healthcare industries and between organizations in the same healthcare industry. Differences in employee- or organizational characteristics such as age, gender, organizational size, or urbanization rate could not fully explain the variance between organizations. These findings highlight the need for research into other organizational factors that help explain the utilization differences between healthcare organizations and industries. More insight into the healthcare utilization rates of organizations will provide new ways of monitoring healthcare workers’ health and minimizing the costs and burden of ill health.

Footnotes

Acknowledgements

I would like to thank Bram Steijn and Lars Tummers for their comments on earlier versions of this article. This work is part of a PhD project on the physical and psychological health and safety of employees working in health care organizations.

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) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Stichting IZZ () provided a grant for this PhD project.

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