Despite the growing recognition of the need to retain trained providers and improve the quality of care they provide, there is no comprehensive analysis of the burden of provider burnout in low and middle-income countries (LMICs). In addition to the paucity of such syntheses, current data are cross-sectional without an evaluation of potential change over time and most studies have not characterized institutional (e.g., institutional management, quality, or supervision), individual, socioeconomic, or geopolitical factors that could potentially contribute to provider burnout. To address this gap, we conducted a systematic review to describe the prevalence of and factors associated with outpatient provider burnout in LMICs. These findings may help managers and policymakers develop and implement effective interventions to prevent burnout and improve work productivity, efficiency, quality and retention.

Identifying and characterizing burnout is important as it can have a negative impact on providers and patient care. Studies from predominantly high-income countries have shown that provider burnout is associated with adverse events including medical errors, unexplained work absenteeism, reduction in quality of care 24 , 25 , higher number of negative rapport-building statements (physician or patient offers a statement ‘characterized as criticism or disagreement’) 26 , job dissatisfaction 27 , and poor patient satisfaction 28 , 29 . A large study of 11,530 health professionals in Spain and Latin America showed that higher emotional exhaustion was associated with higher absenteeism, intention to exit the profession, and low quality of personal and family life 30 .

Burnout, as described by Freudenberg 13 and expanded by Maslach, is comprised of three dimensions: emotional exhaustion (‘emotionally overextended and exhausted by […] work’), depersonalization (‘unfeeling and impersonal response towards recipients of one’s care or service’), and low personal achievement (‘feelings of competence and successful achievement […] with people’), and results in negative work experiences 14 – 16 . There are a number of surveys used to assess burnout 17 , 18 ; however, the Maslach Burnout Inventory (MBI) has emerged as perhaps the most widely used survey to assess burnout across a wide variety of work and cultural settings 19 . Studies using the MBI in the United States, Canada, and mostly high-income countries in Europe have found that up to half of outpatient providers report high levels of emotional exhaustion, depersonalization, and a sense of low personal achievement 20 – 22 ). These findings are supported by a systematic review which documented high levels of burnout in both outpatient and inpatient providers in high-income countries 23 . In these studies, high burnout was associated with feeling undervalued and unsupported, having too much paperwork, and the existence of long waits for specialists and tests, among other factors 20 – 22 .

Primary health care (PHC) includes provision of services for the prevention, treatment, management, rehabilitation, and palliation of disease, and is integral to achieving global health security, universal health coverage and the Sustainable Development Goals 1 – 7 . A robust PHC system requires an adequate number of trained and motivated health care providers 6 , 8 , 9 . Alarmingly, the World Health Organization (WHO) has estimated that the global shortage of providers will increase by 80% to 12.9 million over the next 20 years and has called for the development of an expanded, high-quality workforce 10 . Given the projected shortages, there is great interest in strategies to retain existing providers and improve provider efficiency and productivity. Further, a positive work environment will reduce workforce turnover, and improve quality of life and care. The reasons for lower efficiency and productivity are unclear, and may be linked to extrinsic motivational factors including financial and non-financial, organizational, and environmental incentives 11 or to incompletely described intrinsic motivational factors such as achievement, recognition, responsibility, and growth 12 , which may be negatively impacted by provider burnout.

We collected information on the study location and design, participant demographics, cadre, and duration in practice. For burnout, we collected information on the type of burnout inventory used, and estimates of overall burnout and its subcomponents (depersonalization, emotional exhaustion, and level of personal achievement).

The titles and abstracts were reviewed independently by two authors. Research articles written in English were included if the study was based in an LMIC and explicitly investigated burnout and not solely work-related depression, anxiety, or stress, in outpatient healthcare workers. Articles were excluded if they were conference abstracts, case reports, case series, simulations, review articles, editorials, commentaries, perspectives, personal narratives, or qualitative studies; if the full-length article was not available; if the study had fewer than 50 subjects; or if the study focused on trainees (for example, students, residents, or fellows), inpatient providers, or on veterinary care providers. Discrepancies between the authors in abstracting data were resolved by discussion or through consultation with other authors. The detailed selection strategy is outlined in Supplementary File 3 .

We performed a systematic literature search to identify articles on burnout among outpatient health care providers in LMICs. The review protocol was not registered on an online portal. We focused on outpatient care settings as this is where the majority of primary health care services are provided. Our initial search was based on articles published in EMBASE (from 1947), MEDLINE (from 1966), and Commonwealth Agricultural Bureau (CAB) Abstracts (from 1973) up to December 1, 2014. We developed a broad search strategy for each key term: ‘burnout’, ‘healthcare providers’, and ‘LMICs’, through a combination of text words, words in the abstract or title, and Medical Subject Headings (MeSH). For burnout, we included “motivation” and “achievement”. For healthcare providers, we included “physician”, “nurse”, and “community health worker”; and for LMICs, we included “developing countries”, “resource constrained”, and “resource poor”. We used the World Bank system to classify countries as low or middle-income based on gross national income per capita 31 . The search terms were combined using ‘AND’ to identify articles that included all three concepts, as outlined in the S1 Supplementary Material . The search was updated using the same methodology to include articles from December 1, 2014 through January 23, 2016.

Consistent with trends observed for emotional exhaustion and depersonalization, higher personal achievement was associated with lower time pressure, lower stress, and higher availability of resources and intrinsic job satisfaction 32 , 37 , 39 , 41 . For example, among nurses in South Africa, higher personal achievement was significantly associated with lower time pressure 37 , and among AIDS care volunteers in South Africa, lower personal achievement was associated with higher rating of ‘lack of support’ (p=0.03), ‘professional uncertainty’ (p=0.008), and overwhelming nature of their patients’ disease (p=0.04). One study showed that higher emotional exhaustion was associated with increased likelihood of quitting the job (odds ratio 3.46 [2.00–5.99], p<0.001) while higher personal achievement lowered that risk (odds ratio 3.05 [1.67–5.56], p<0.001) 42 .

Variables associated with depersonalization were evaluated in 12 studies. As seen with emotional exhaustion, higher levels of depersonalization were associated with excessive time pressure and lack of support 32 , 37 , 41 . Amongst pharmacists in Turkey with excessive time pressure, the median depersonalization score was higher compared to those with low time pressure (4 versus 1, p=0.004) 41 . Similar findings were seen among nurses providing HIV care in South Africa 37 . Among AIDS care volunteers in South Africa, higher depersonalization was seen among those who perceived a ‘lack of support’ (p=0.025) 32 . In other studies, higher depersonalization was seen among men compared with women and was associated with higher rates of recent absenteeism (odds ratio 3.0 [1.2–7.8], p=0.02) 33 , 36 . Lower rates of depersonalization were associated with overall higher intrinsic and extrinsic job satisfaction among community health workers in China 39 .

Twelve studies in our analysis reported on factors associated with specific dimensions of burnout. Higher rates of e motional exhaustion were associated with higher time pressure of workload and excessive workload 37 , 41 . In Turkey, among pharmacists who reported having “excessive” time pressure, the mean emotional exhaustion score was higher (19.2 ± 5.9) compared to those with low time pressure (10.7 ± 5.6, p<0.001) 41 . Higher emotional exhaustion scores were also seen in pharmacists who had less work experience (10 years or less [17.6 ± 5.7]) compared to those who had worked longer in the field (30 years or more [13.8 ± 6.9]; p=0.007) 41 . In community health workers in China, emotional exhaustion was associated with lower intrinsic and extrinsic job satisfaction ( Table 3 ) 39 . Intrinsic satisfaction evaluates job-related tasks (e.g. professional development opportunities) while extrinsic satisfaction evaluates aspects external to the job (e.g. wages, benefits and bonuses) 39 . In general, inverse associations were seen with emotional exhaustion and perceived organizational support, leadership, and staff relationships.

$ High risk of burnout: (high emotional exhaustion + high depersonalization + high professional realization) OR (high emotional exhaustion + low depersonalization + low professional realization) OR (low emotional exhaustion + high depersonalization + low professional realization); moderate risk of burnout: high emotional exhaustion OR high depersonalization OR low professional realization; low risk of burnout: (low emotional exhaustion + low depersonalization + high professional realization)

Seven studies investigated variables associated with overall burnout ( Table 3 ). Among HIV healthcare providers in Zambia, Kruse and colleagues 50 observed that the 36–45 year age group had a higher relative risk (1.5 [1.1–1.9], at 95% confidence interval) of burnout compared with those 45 years or older. In Serbia, Jocic and colleagues 51 found that burnout was more common among older community pharmacists (51–60 years) compared with their younger colleagues. In addition, Kruse and colleagues 50 showed that females (relative risk 2.0 [1.1–2.7]), providers who worked other jobs (relative risk 1.4 [1.1–1.6]) and providers who knew a co-worker who had quit work (relative risk 1.6 [1.2–2.0]) reported higher levels of burnout. Among rural health workers in Iran, provider burnout was associated with longer work experience, high job stress (70.1% in those with burnout versus 37.7% in those without burnout; p=0.001), and having a higher General Health Questionnaire score, a measure of higher psychological distress 40 .

Four studies used non-MBI tools to measure burnout among providers. A study based in Serbia used a self-assessment test (15 questions assessed on a Freudenberg scale) and reported that 44.4% of community pharmacists had high levels of burnout 51 . A study based in Zambia used a single question to assess burnout and reported that 27.8% of HIV healthcare providers had burnout that was severe or not improving with time 50 . In Uganda, Muliira and colleagues 48 used the Professional Quality of Life Scale, which classifies provider burnout levels into three categories: high, average, and low, and reported that 89.3% and 10.1% of female midwives had average and high levels of burnout, respectively, while 82.6% and 10.8% of male midwives had average and high levels of burnout, respectively. Pandey and colleagues used a modified Copenhagen Burnout Inventory (scale 1–7, with higher scores reflecting higher burnout) 17 and showed that accredited social health activists (ASHA) in India had a mean burnout score of 4.0 ± 1.4 49 . Further, one study in South Africa used a modified version of MBI, in which the emotional exhaustion domain was excluded. Using this modified version, Akintola and colleagues reported a high level of depersonalization and personal achievement among AIDS care volunteers 32 .

Personal Achievement was reported in 16 studies, and the average score ranged from 3.9 43 to 39.6 33 . The lowest prevalence of ‘moderate or high’ personal achievement (score ≤29) was seen among primary health care providers (25.1%) in Lebanon 42 , whereas the highest (99.3%) was seen among nurses in South Africa 37 .

Depersonalization was reported in 16 studies. Similar to emotional exhaustion, a high level was reported, with the average score ranging from 0.7 38 to 17.8 37 . The lowest prevalence of ‘moderate or high’ depersonalization (score ≥6) was seen among rural health workers in Iran (13.3%) 40 and the highest among nurses in South Africa (98.0%) 37 . Nine studies reported the proportion of people with different levels of depersonalization; of these, six studies showed moderate to high levels of depersonalization in more than one-third of healthcare providers.

Emotional Exhaustion was evaluated in 15 studies, and the average score ranged from 2.3 38 to 31.3 37 . The lowest prevalence of moderate or high emotional exhaustion (score ≥14) was seen among rural health workers in Iran (27.4%) 40 and the highest was among nurses in South Africa (99.6%) 37 . Eight studies reported the proportion of people with different levels of emotional exhaustion; of these, six studies showed moderate to high levels of emotional exhaustion were reported in more than one-third of healthcare providers studied.

The MBI is the most widely used inventory to assess burnout, and consists of 22 questions across three dimensions: emotional exhaustion (nine questions), depersonalization (five questions), and personal achievement (eight questions). Each question is scored on a scale from 0 (never) to 6 (everyday). The points from each dimension are added to provide a total score for that dimension. The score for each dimension can be categorized as low, moderate, or high: emotional exhaustion (low ≤ 13; moderate 14 to 26; high ≥ 27); depersonalization (low ≤ 5; moderate 6 to 9; high ≥ 10); and personal achievement (high ≤ 33; moderate 34 to 39; low ≥ 40) 22 . Higher scores on emotional exhaustion and depersonalization, and a lower score on personal achievement, are associated with higher provider burnout. The development, reliability, and validity of the MBI have been previously described 15 . Of the 20 studies, 15 used the MBI 33 – 47 , one 32 used a modified version of MBI, and four 48 – 51 used other assessment tools ( Table 2 ).

Across the reported studies, the mean age of healthcare providers ranged from 26.4 years to 47.4 years ( Table 1 ). Studies included a range of provider types including HIV service providers (3 studies), PHC and general practitioners (five studies) and community-based workers (six studies). Cadres included physicians, nurses and midwives, dentists, pharmacists, community health workers and health volunteers. The range of education varied based on cadre, with lower rates among community health workers and volunteers compared to providers with a formal degree. For example, among AIDS volunteers in South Africa, 93.7% had completed secondary or high school education while only 2.4% had ‘higher education’ 32 , whereas among HIV caregivers in Brazil, 52.9% of volunteers had a university level education 33 .

Our initial search (on December 1, 2014) generated 5,412 articles (2,046 from EMBASE, 847 from CAB Abstracts, and 2,519 from MEDLINE), of which 735 were duplicates. Using eligibility criteria described above, 11 articles were included in final data extraction and analysis ( Supplementary File 3 ). We updated the search on January 23, 2016; we identified 770 articles (total of 6,182 articles when combined with search on December 1, 2014) and identified 9 additional articles that met our eligibility criteria ( S2 Supplementary Material ). The 20 studies included in the final analysis spanned all global regions, and focused on various providers including physicians, pharmacists, nurses, community health workers, and midwives. Only two studies were based in low income countries while the rest were based in middle-income countries.

Discussion

In this systematic literature review, we observed that burnout is prevalent across a range of frontline PHC service delivery providers including physicians, nurses, pharmacists, and community health workers in various outpatient health care settings including HIV care clinics in a number of LMICs. To our knowledge, this is the first systematic review to describe provider burnout in LMICs, and provides insight into factors that could influence worker productivity, efficiency, quality, and retention through their influence on burnout. The level of burnout across each MBI dimension is comparable to rates observed among outpatient general internists in the US, family doctors in Canada, and family doctors across 12 countries in Europe20–22. These studies, which include several high-income countries, found rates of high emotional exhaustion (range 43.0% to 48.1%), high depersonalization (32.7% to 46.3%), and low personal achievement (20.3% to 47.9%).

We were able to identify several consistent factors associated with different dimensions of burnout. Possibly modifiable factors included levels of organizational support, time pressure and workload, as well as the availability of accessible opportunities for professional growth, though the association of these factors with burnout is likely to depend on the cadre in question, their training level, degree of autonomy, and relationship with communities and patients. The roles and responsibilities of different cadres of health workers depends on the study, and therefore should be interpreted carefully. These results are generally supported by the other studies that showed positive association with longer work hours and inverse association with job satisfaction34,35,48,49. Absence of supportive supervision (managers helping health workers to do their job better) appears to also be related to the presence of burnout. Supportive supervision can provide health care workers with opportunities for new skills development as well as improving effectiveness and efficiency of their care delivery. While higher disease burden of patients is less amenable to simple solutions, service delivery changes such as multidisciplinary teams may provide approaches to reducing provider burnout. These reported findings were generally similar to findings seen in high-income countries20,22.

Additionally, there were also factors which were not modifiable through workplace interventions including age, gender, and level of education, which is also similar to results seen in high-income countries20,22. Further research is required to understand why burnout is higher among these groups in order to ensure that effective support and coping strategies are provided for health care workers.

Improving PHC will be critical for achieving universal health coverage and the Sustainable Development Goals by 2030. In LMICs, this will require an available, accessible, and acceptable workforce that can deliver efficient, high-quality patient care52. While increasing the number of providers in some regions is clearly necessary, health systems will also have to focus on ways to retain existing staff by reducing burnout, providing a supportive environment, creating opportunities for personal achievement and growth, reducing stress and maintaining motivation. Interventions focused on improving interpersonal relationships, supportive work environments, supportive supervision including mentorship, coaching incentives and training on self-awareness and mindfulness, may help to reduce burnout, however evidence from LMICs is often lacking and the generalizability of many of these interventions done in high income settings is not certain53–59. For example, a pre-post study of 84 mental health professionals in the United States found that a one-day retreat and training focused on increasing knowledge of and strategies to prevent burnout was associated at six weeks with significant decreases in emotional exhaustion and depersonalization55. While larger studies on effectiveness of interventions are generally lacking, a few ongoing studies in high-income countries on interventions to reduce burnout and improve patient outcomes may shed light on promising approaches, although these are generally limited to specific cadres or settings55,60. Further, provider depression may be a cause or consequence of provider burnout, and studies will be required to explore if they are separate or linked constructs.

Our paper has a number of important limitations. We included articles from three widely used electronic databases, and different cadres of health care providers across LMICs from many regions. However, we did not include articles that were not in English or articles that were published outside of the three search engines, including in non-peer reviewed literature. Further, we did not evaluate the quality of the studies. Only 15 of the 20 included studies used the MBI, and among them, differences in study population and design precluded analyses across different cadres of health providers.

We included a wide variety of primary care providers ranging in training from physicians to community health workers and volunteer caregivers. Because of high prevalence of HIV in some of the countries, we included providers of HIV services as they are a significant source of critical first contact care for people living with HIV/AIDS. The comparability of findings across these widely different health workers who operate within the primary health care sector in LMICs may not be complete. Finally, the quality of evidence available in the included studies was often low. Many studies relied on non-validated measures or used thresholds for defining burnout which were established for high-income countries but applied to LMIC. More work is needed to ensure high-quality measurement and the use of contextually appropriate diagnosis criteria. Additionally, further studies should ensure higher response rates among responders, describe the characteristics of non-responders, and clarify the level of anonymity responders have while participating in studies. Further, as many studies are cross-sectional, it will be challenging to generalize these findings to different contexts and situations. However, despite these limitations, we were able to observe consistent trends in burnout across these different health providers and in different countries.

Our understanding of factors related to high rates of burnout and low provider motivation in LMICs is still in its infancy. This review is based on 20 cross-sectional studies of diverse health providers in different countries. To better describe burnout and reduce its impact on provider retention and quality, further research should focus on more comprehensive investigation of the i) burden of provider burnout from diverse health care providers at different levels in the health care system, ii) demographic, socioeconomic, institutional, and geopolitical factors that influence or mitigate provider burnout, iii) longitudinal changes in burnout in response to extrinsic (i.e. monetary or training) and intrinsic motivational factors, iv) association between burnout, depression, lack of motivation, and other psychological stressors, and v) interventions likely to reduce the burden of burnout. These studies can guide health and policy makers on strategies to improve provider efficiency, productivity, quality, and possibly retention in the workforce.