Health Worker Absenteeism in Selected Health Facilities in Enugu State: Do Internal and External Supervision Matter?

Background: Absenteeism is widespread in Nigerian health facilities and is a major barrier to achievement of effective Universal Health Coverage. We have examined the role of internal (by managerial staff within facilities) and external (by managers at a higher level) supervision arrangements on health worker absenteeism. Specifically, we sought to determine whether these forms of supervision have any role to play in reducing health worker absenteeism in health facilities in Enugu State Nigeria.Methods: We conducted interviews with 412 health workers in urban and rural areas of Enugu State, in South-Eastern Nigeria. We used binary logistic regression to estimate the role of different types of supervision on health worker absenteeism in selected health facilities in Enugu State.Results: Internal supervision arrangements significantly reduce health worker absenteeism (odds ratio = 0.516, p = 0.03). In contrast, existing external supervision arrangements were associated with a small but significant increase in absenteeism (OR = 1.02, 0.043). Those reporting a better financial situation were more likely to report being absent (OR = 1.36, p < 0.01) but there was no association with age and marital status of respondents. Our findings also pointed to the potential for alternative forms of supervision, provided in a supportive rather than punitive way, for example by community groups monitoring the activities of health workers but trying to understand what support these workers may need, within or beyond the work environment.Conclusion: The existing system of external supervision of absenteeism in health facilities in Nigeria is not working but alternatives that take a more holistic approach to the lived experiences of health workers might offer an alternative.

The impact of health worker absenteeism on patient health care seeking behavior, testing and treatment: A longitudinal analysis in Uganda

Introduction Absenteeism of frontline health workers in public sector facilities is widespread in low-income countries. There is little quantitative evidence on how health worker absenteeism influences patient treatment seeking behavior, though low public sector utilization and heavy reliance on the informal sector are well documented in low-income settings. Methods Using a unique panel dataset covering health facilities and households over a 10-month period in Uganda, we investigate the extent to which health worker absenteeism (defined as zero health workers present at a health facility) impacts patient care seeking behavior, testing, and treatment. Results We find high rates of health worker absenteeism at public sector health facilities, with most of the absenteeism occurring at lower level public health clinics. On average, no health worker was present in 42% of all days monitored in lowest level public health clinics, whereas this number was less than 5% in high level public hospitals and private facilities. In our preferred empirical model with household fixed effects, we find that health worker absenteeism reduces the odds that a patient seeks care in the public sector (OR = 0.65, 95% CI = 0.44–0.95) and receives malaria testing (OR = 0.73, 95% CI = 0.53–0.99) and increases the odds of paying out-of-pocket for treatment (OR = 1.41, 95% CI = 1.10–1.80). The estimated differences in care-seeking are larger for children under-five than for the overall study population. Conclusions The impact of health worker absenteeism on the quality of care received as well as the financial burden faced by households in sub-Saharan Africa is substantial.

Adaptive staffing can mitigate essential worker disease and absenteeism in an emerging epidemic

Essential worker absenteeism has been a pressing problem in the COVID-19 pandemic. Nearly 20% of US hospitals experienced staff shortages, exhausting replacement pools and at times requiring COVID-positive healthcare workers to remain at work. To our knowledge there are no data-informed models examining how different staffing strategies affect epidemic dynamics on a network in the context of rising worker absenteeism. Here we develop a susceptible–infected–quarantined-recovered adaptive network model using pair approximations to gauge the effects of worker replacement versus redistribution of work among remaining healthy workers in the early epidemic phase. Parameterized with hospital data, the model exhibits a time-varying trade-off: Worker replacement minimizes peak prevalence in the early phase, while redistribution minimizes final outbreak size. Any “ideal” strategy requires balancing the need to maintain a baseline number of workers against the desire to decrease total number infected. We show that one adaptive strategy—switching from replacement to redistribution at epidemic peak—decreases disease burden by 9.7% and nearly doubles the final fraction of healthy workers compared to pure replacement.

Current Data Gaps in Modeling Essential Worker Absenteeism Due to COVID-19

With the uncertain physical and mental health implications of COVID-19 infection, companies have taken a myriad of actions that aim to reduce the risk of employees contracting the virus, with most grounded in reducing or eliminating in-person interactions. Our preliminary analysis indicates that while there is some data to support modelling absenteeism, there are gaps in the available evidence, requiring the use of assumptions that limit precision and efficacy for decision support. Improved data on time-to-recovery after hospitalization, absenteeism due to family or other household member illness, and mental health’s impact on returning to work will support the development of more robust absenteeism models and analytical approaches.

Projected geographic disparities in healthcare worker absenteeism from COVID-19 school closures and the economic feasibility of child care subsidies: a simulation study

ABSTRACTBackgroundSchool closures have been enacted as a measure of mitigation during the ongoing COVID-19 pandemic. It has been shown that school closures could cause absenteeism amongst healthcare workers with dependent children, but there remains a need for spatially granular analyses of the relationship between school closures and healthcare worker absenteeism to inform local community preparedness.MethodsWe provide national- and county-level simulations of school closures and unmet child care needs across the United States. We develop individual simulations using county-level demographic and occupational data, and model school closure effectiveness with age-structured compartmental models. We perform multivariate quasi-Poisson ecological regressions to find associations between unmet child care needs and COVID-19 vulnerability factors.ResultsAt the national level, we estimate the projected rate of unmet child care needs for healthcare worker households to range from 7.5% to 8.6%, and the effectiveness of school closures to range from 3.2% (R0 = 4) to 7.2% (R0 = 2) reduction in fewer ICU beds at peak demand. At the county-level, we find substantial variations of projected unmet child care needs and school closure effects, ranging from 1.9% to 18.3% of healthcare worker households and 5.7% to 8.8% reduction in fewer ICU beds at peak demand (R0 = 2). We find significant positive associations between estimated levels of unmet child care needs and diabetes prevalence, county rurality, and race (p < 0.05). We estimate costs of absenteeism and child care and observe from our models that an estimated 71.1% to 98.8% of counties would find it less expensive to provide child care to all healthcare workers with children than to bear the costs of healthcare worker absenteeism during school closures.ConclusionsSchool closures are projected to reduce peak ICU bed demand, but could disrupt healthcare systems through absenteeism, especially in counties that are already particularly vulnerable to COVID-19. Child care subsidies could help circumvent the ostensible tradeoff between school closures and healthcare worker absenteeism.