Burnout and health status differences among primary healthcare professionals in Portugal

In Portugal, the primary healthcare system has a relevant role in the overall health system as it works as a gatekeeper for hospital care. An international comparison of the importance of primary health care in Europe was presented by Kringos et al. [42]. They showed that Portugal as Belgium, Denmark, Finland, Spain and UK have a relatively strong primary care.

Portugal mainland comprises five Regional Health Authorities: North (NOR), Central (CEN), Lisbon and Tagus Valley (LTV), Alentejo (ALE), and Algarve (ALG) (as shown in Figure 1 in Appendix). Each of these Regional Health Authorities is responsible for running several Groups of Primary Care Centers, which in turn include several primary health care units [43, 44].

These primary health care units may have different organization formats. In our work, we identify the so-called family health units (USF) and the traditional primary health care units (UCSP). The former can be classified in models A and B, based on the way they are organized and on the type of incentives paid to professionals. USF units have some level of autonomy and participative management. Professionals in USF-B receive a monetary incentive for performance, in particular, GPs, whereas in USF-A payments are only salaries.

On the other hand, UCSP have well established vertical hierarchies and very low level of autonomy. Other primary health care units include USP (public health unit), UCC (continued care unit), and URAP (shared assistance resources unit) [44, 45].

It is noteworthy that the access by users to primary healthcare services may be different across regions. These differences have been described in a previous work by Ferreira et al. [46]. For instance, in Lisbon and Tagus Valley region is more likely to find people who are not enrolled in a GP which makes access to medical appointments very difficult.

Data was gathered from an online questionnaire to health professionals, which includes GP, nurses, technicians and other health care professionals. The survey was applied to all 19,563 healthcare professionals in all 1,212 primary healthcare units in Portugal mainland, between January and April 2018. The questionnaire was answered in a private access e-platform (LimeSurvey), using a password system to ensure anonymity, non-duplication and answers only from the target population.

The questionnaire was approved by the Portuguese Authority for Individual Data Protection. It included three main groups of questions: (i) sociodemographic and labour characteristics, (ii) job satisfaction, and (iii) burnout.

Sociodemographic data included gender, age, education level and family status. Labour characteristics encompassed professional category, regular working hours, experience in coordinating, managerial or leadership functions, and how long the professionals have been working in the unit and in the profession. The questionnaire was designed to evaluate professionals’ satisfaction with their job and workplace.

Measurement of job satisfaction was based on the questionnaire ‘Hospital Employee Judgment System’ [47] and developed and validated to the Portuguese context by the Centre for Health Studies and Research of the University of Coimbra, Portugal [48]. The instrument measures the dimensions 'quality of the workplace', 'quality of services provided' and 'continuous quality improvement'. An overall level of satisfaction regarding the unit where individuals work was computed by weighted average based on those dimensions.

Professionals' burnout was measured by the Portuguese validated version of the Copenhagen Burnout Inventory (CBI) [21] that encompasses three scales of burnout: personal, work-related, and patient-related [49, 50]. According to CBI authors, personal burnout measures professional's perception of psychological fatigue and exhaustion. Work-related burnout refers to the extent to which a professional attaches his/her perception of physical and emotional fatigue and exhaustion to his/her work. And patient-related burnout measures how much s/he attributes his/her perceived feelings of physical and emotional fatigue and exhaustion to the work with patients. The overall burnout indicator is obtained by computing a simple average between those three dimensions of burnout.

Two equations were estimated, one for SAH and the other for burnout as follows:

where β and δ correspond to a vector of the estimated coefficients for the independent variables, ε_i and μ_i is the residual term, and i represents an individual.

The set of independent variables in SAH-model could have included the burnout indicator and the Burnout-model could also have included SAH variable [46, 51]. However, this modelling specification raises the problem of endogeneity, resulting in biased and inconsistent coefficient estimates.

This means that there are unobservable variables which are correlated with both dependent and independent variables, such as lifestyle, family and personal life, spirituality, and genetic characteristics. Another possibility to explain endogeneity is by reverse causality, when the dependent variable has a causal effect on the independent variable, e.g. in the SAH-model, SAH may also determine burnout level.

One way to overcome the endogeneity problem would be to use instrumental variables. However, the variables available in our questionnaire are very limited, and so the use of instrumental variables is not an analytical option. Another possible alternative was to estimate simultaneous equations. However, burnout level and health status do not occur simultaneously. Also, the direction of the causality between health and burnout is not yet well established in the literature [49‐51].

The main hypothesis to be tested by this research paper is whether professionals' well-being, measured by SAH and burnout, is influenced by 'place', which includes the type of healthcare unit, level of urbanization and administrative region. Since it was not our purpose to establish a causal relationship between health and burnout, and the estimated models are not trivial (both models are expressed in different forms of regression), we estimated two single equations for each well-being variable, one for SAH and another for burnout.

We began by presenting some descriptive statistics about the sample of primary healthcare professionals. Next, we estimated the SAH-model and the Burnout-model. Based on the nature of the dependent variable, an ordered probit model was estimated for self-assessed health, and a tobit model was estimated for burnout level. Estimations were performed for all the primary healthcare professionals, and for GPs and nurses separately. These estimations were not worth reporting for the technicians because of the relatively small sample for these professionals and the consequent absence of statistical significance of most results.

The models were estimated for two specifications, a reduced and a full model. The 'reduced model' included only independent variables related to ‘place’, that is, type of healthcare unit, urbanization density where the unit is located, and health administrative region. The 'full model' considered all independent variables described above and the potential relation between SAH and burnout levels for the set of all professionals. For this purpose, we have included the burnout indicator in SAH-model and the SAH variable in the Burnout-model. These estimations, as explained above, may be subject to endogeneity, so they may be taken here as a sensitivity analysis. The results are presented in the Appendix.

All estimations were done using the econometric software package STATA 15.

The descriptive statistics concerning independent variables are displayed in Table 3.

The average number of completed years of education is 16.5, and so it may be said that on average professionals have college education, as it would be expected. We also evidenced that burnout indicator was normally distributed.

The values of the burnout indicator were, on average, different between GPs and nurses. While nurses reported an overall burnout equal to 37.2, GPs reported a higher value equal to 46.8. On the other hand, nurses reported more often lower levels of health (SAH) than GPs. For instance, 28.1% of nurses reported self-assessed health between very poor and reasonable levels, while 25.5% of GPs reported the same levels. It is worth to highlight that the average age of nurses was 43.5 and of GPs was 48.9 years old. Besides only 11% of nurses and 35% of GPs were men.

The results obtained in the reduced model are presented in Tables 6 (in the Appendix). At first glance, these results showed that burnout is a phenomenon emerging both at unit (both types of USF) and regional levels (especially in Central and Alentejo regions), while good (or poor) health tends to be locally observed at unit type. The level of urbanization seems not to have a relationship neither with health nor with burnout.

The well-being of professionals has fundamental importance to guarantee that health systems can pursue their main goal of improving people’s health. The current analysis aimed to determine individual drivers for well-being, measured by self-assessed health and by burnout, to verify whether there are ‘place’ determinants of well-being and whether there are differences between GPs and nurses.

The main results show that, firstly, nurses generally report slightly worse health than GPs, though suffering lower levels of burnout; secondly, 'place' effects are more significant in GPs than in nurses.

Concerning self-assessed health (SAH), we found that GPs tended to report higher health status in USF-B and in UCSP units; on the other hand, in Algarve we evidenced higher scores. This region has pleasant climate and living conditions, which may contribute to a better reported SAH. Moreover, despite seasonal demographic fluctuations, these do not affect the demand for primary care of the national health service. The worst SAH was reported in Alentejo, where there is the highest suicide rate, and the lowest demographic density. These features may explain the no 'urbanization effect'. For nurses, in general, no significant 'place' effects were found in SAH.

Concerning burnout, results showed that GPs give higher scores in USF-A and USF-B. In addition, burnout levels were higher in all regions when compared to Algarve, and the most intense levels of burnout are found in North and Lisbon and Tagus Valley. These results did not support previous evidence from Maroco et al. [39] who found that burnout syndrome among physicians was uniform across Portugal mainland regions. However, their sample [39] included physicians from different health care settings while our sample includes only primary healthcare physicians. Also, the burnout measurement scale was different. This may be a reason for the existing disparity of the results.

We also found that for GPs, 'urbanization effect' tended to decrease burnout intensity. This is different from what was seen by Saijo et al. [34], but identical to Lavanchy et al. [35]. The majority of the cities in Portugal have a medium-small size and provide a set of services and social environment, which are useful for personal and family life without heavy levels of pollution, traffic or crime. In general, the quality of life in Portuguese cities is good and people rather live and/or work in urban areas than in rural ones or outskirts/semi-urban.

We found 'place effects' for nurses in UCSP, where burnout levels tend to be low. Nurses in the Northern region suffer higher levels of burnout. This result is partially identical to the one found by the previous work [39] where it was identified higher burnout levels in the North and Centre of Portugal.

There was a tendency for nurses and GPs to suffer higher burnout in the Northern region and for GPs in Lisbon and Tagus Valley. This tendency may be related to the measures and policies followed by Regional Health Authorities. Good governance and organization measures may lead to the development of work quality. Additionally, weak leadership traits, poor staff management, and resource inadequacy of some of the Groups of Primary Care Centers do not boost work satisfaction. Therefore, these weak organizational and leadership attributes trigger burnout.

The case of GPs in Lisbon and Tagus Valley, where they tended to present higher levels of burnout, was also expected. In this region, the number of people not enrolled in a GP list is very large, due to the demographic pressure not timely addressed by the authorities, and by the consequent higher demand for consultations. Another fact that may explain this result comes from the tension arising from the lower levels of patient satisfaction in Lisbon and Tagus Valley [46], mainly caused by the difficult access to healthcare services [46].

Finally, in USF-B, GPs tended to report lower health status and higher levels of burnout, but this was not the case for nurses. One possible explanation for this result is related to the type of organization and contracting mechanisms of these units, characterized by some level of autonomy, participative management and pay for performance incentives to GPs. It may be the case that the pressure from this type of organization is causing chronic stress, anxiety, depression, and burnout feelings.

Concerning the individual drivers of well-being, our analysis showed that there are common determinants of SAH and burnout level between GPs and nurses. In the case of SAH, we found that being older is correlated with lower levels of health, as expected from the conceptual model of health demand [52] while being professionally more satisfied and reporting sufficient income to face family needs contribute to better health status.

In the case of burnout, the common determinants of lower burnout intensity between GPs and nurses included being older, with children, with a sufficient household income, and being more satisfied with the job. Among the socioeconomic factors, age tended to have a significant relationship with burnout. As found in most studies, younger individuals tended to experience stronger symptoms of burnout [25, 26, 38, 53]. Although this relationship may not be linear and so, higher levels of burnout in older ages may be found by other researchers [54].

Concerning the role of the sufficiency of the income for family needs, our findings suggest that higher income tended to be related with better health status and with lower burnout levels, both for GPs and nurses [26]. Several authors have identified a relationship between better payment or income earned and higher job satisfaction, which in turn decreases burnout level [54‐56]. Despite this general view, Picquendar et al. [53] did not find such relation between payment and burnout syndrome and Linzer et al. [57] concluded that the relevant factor for physicians was rather the relationship with patients than the monetary compensation. The income variable used in our work, in fact, measures better the family well-being concern than the absolute value of income or the implicit relationship with job satisfaction. In a family-based society, our results are expected to be found.

Concerning job satisfaction, and as expected from previous work [25, 26, 58‐61], we found that higher levels of satisfaction were correlated with better health status and lower burnout. In fact, job satisfaction contributes to the mitigation of the set of burnout dimensions, including lower emotional exhaustion and depersonalization. Simultaneously, job satisfaction is a consequence of good human resource policy (good leadership and communication), high levels of morale, good resources, as well as favourable attitudes towards the functioning and continuous quality improvement of the unit. These job satisfaction features contribute to a sense of personal and professional accomplishment.

The proportion of men and women in primary health care is unequal and the majority of professionals are women, about 90% of nurses and 65% of GPs. However, it can be noticed from other statistics [62‐64] that the percentage of males in leader positions is higher that the percentage of males in the working place.

We found that nurses reported a slightly worst health than GPs, but these tended to suffer from higher levels of burnout, unlikely previous findings [38]. Male gender was correlated with better health, among nurses, and lower burnout intensity, among GPs. So, being male seems to be protective of lower health and from higher burnout. Our result is not coincident to the one discussed before [25], where it was stated that in Southern European countries, male GPs tended to have a higher level of burnout. The existing ratio between nurses and physicians may explain our finding. On the other hand, as the share of male leaders (about 23.8% of the sample) is larger than the share of males in workplace (about 19% of the sample) there is some male style of leadership which favours the smaller share of males in the workplace. This may be observed in the assessment professionals do about the human resources policy and the coordination of the health in the sample unit [46, 63]. On average, males tend to be more satisfied with these specific aspects of the workplace than females. These differences may contribute to the differences found between genders. Finally, concerning self-assessed health, women tend to report worst health than men. But under the control of risk factors and socioeconomic factors, men and women may have identical health. In fact, this comparison may not be so clear [65, 66].

Well-being is measured by self-reported variables, which may yield to a self-reported bias [63]. However, due to the very large sample used, there is a trade-off between positive and negative biases, which may result in a strong mitigation of this bias.

Another limitation of our work is the possible bias of respondents’ decision not to fill the questionnaires. However, 46.4% response rate yields a large sample size of 9,094 professionals, a significant sample of all primary healthcare professionals of mainland Portugal. On the other hand, analysing the sociodemographic characteristics we confirmed that the obtained sample is representative of the workforce employed in the primary health care in mainland Portugal. Therefore, we tend to minimize this possible constraint.

The major strength of this analysis is the expansion of understanding of the relationship between well-being and ‘place’, defined by the type of health unit, the urbanization and the region. We not only contribute to the discussion on the relationship between well-being and the level of urbanization, but we also add knowledge about the relationship between well-being and the type of primary health care units and the Portuguese regions. The second major strength is the use of data from a very large sample of primary health care professionals. Finally, this analysis also includes simultaneously two important concepts related with well-being of professionals, which is not very common in the literature.

The analysis presented here provides a set of policy recommendations, which may contribute to the final aim of improving the workforce and, indirectly, the quality of the health care provided. Several measures at the health care unit and regional level should be considered to reduce GPs work stress and consequent burnout. Improving job satisfaction contributes not only to the reduction of burnout, but also to the improvement of the health of professionals. Job satisfaction is improved with a better communication and leadership from the top organization structures, also enhanced with morale in the workplace, and better resources to provide care. Other measures on health resources organization such as less bureaucracy to be attended, more time to provide personalised care, supportive supervision and coordination, enhancement of teamwork, mechanisms to hold professionals accountable for their actions, and non-pecuniary incentives may be considered to improve job satisfaction. Among the several factors that influence health status and burnout levels, income has a clear far-reaching effect, and so it may be considered in medium run policies by the Ministry of Health.