Association of nurse understaffing and limited nursing work experience with in-hospital mortality among patients: A longitudinal register-based study

BACKGROUND

Although nurse understaffing and limited nursing work experience may affect hospital patients' risk of mortality, relatively little longitudinal patient-level evidence on these associations is available. Hospital administrative data could provide important information about the level of staffing, nurses' work experience and patient mortality over time.

OBJECTIVE

To examine whether daily exposure to nurse understaffing and limited nursing work experience is associated with patient mortality, using patient-level data with different exposure time windows and accounting for several patient-related characteristics.

METHODS

This longitudinal register-based study combined administrative data on patients (clinical database Auria) and employees (Titania® shift-scheduling) from one hospital district in Finland in 2013-2019, covering a total of 254,446 hospital stays in 40 units. We quantified nurse understaffing as the number of days with low nursing hours in relation to target hours (<90 % of the annual unit median), and limited work experience as the number of days with a low proportion of nurses with >3 years of in-hospital experience, and those aged over 25 (<90 % of the annual unit median). We used two survival model designs to analyze the associations between nurse understaffing and limited nursing work experience and the in-hospital mortality of the patients: we considered these exposures during the first days in hospital and as a cumulative proportion of days with suboptimal staffing during the first 30 days.

RESULTS

In total, 1.5 % (N = 3937) of the hospital stays ended in death. A 20 % increase in the proportion of days with nurse understaffing was associated with an increased, 1.05-fold mortality risk at the patient level (95 % confidence interval, 1.01-1.10). The cumulative proportion of days with limited nursing work experience, or the combination of nurse understaffing and limited work experience were not associated with increased risk of death among all patients. However, both indicators of limited nursing work experience were associated with an increased mortality risk among patients with comorbidities (HR 1.05, 95 % CI 1.02-1.08 and HR 1.05, 95 % CI 1.00-1.10, respectively).

CONCLUSIONS

Nurse understaffing was associated with a slight, but a potentially critical increase in patient in-hospital mortality. Limited nursing work experience was associated with increased in-hospital mortality in a subgroup of patients with comorbidities. Increased use of administrative data on planned and realized working hours could be a routine tool for reducing avoidable in-hospital mortality.

Nurse Staffing Level, Length of Work Experience, and Risk of Health Care-Associated Infections Among Hospital Patients: A Prospective Record Linkage Study

BACKGROUND

Nurse understaffing may have several adverse consequences for patients in hospitals, such as health care-associated infections (HAIs), but there is little longitudinal evidence available on staffing levels and HAIs with consideration of incubation times to confirm this. Using daily longitudinal data, we analyzed temporal associations between nurse understaffing and limited work experience, and the risk of HAIs.

METHODS

The study was based on administrative data of 40 units and 261,067 inpatient periods for a hospital district in Finland in 2013-2019. Survival analyses with moving time windows were used to examine the association of nurse understaffing and limited work experience with the risk of an HAI 2 days after exposure, adjusting for individual risk factors. We reported hazard ratios (HRs) with 95% CIs.

RESULTS

Neither nurse understaffing nor limited work experience were associated with the overall risk of HAIs. The results were inconsistent across staffing measures and types of HAIs, and many of the associations were weak. Regarding specific HAI types, 1-day exposure to low proportion of nurses with >3 years of in-hospital experience and low proportion of nurses more than 25 years old were associated with increased risk of bloodstream infections (HR=1.30; 95% CI: 1.04-1.62 and HR=1.40; 95% CI: 1.07-1.83). Two-day exposure to low nursing hours relative to target hours was associated with an increased risk of surgical-site infections (HR=2.64, 95% CI: 1.66-4.20).

CONCLUSIONS

Data from time-varying analyses suggest that nursing staff shortages and limited work experience do not always increase the risk of HAI among patients.

Work unit level personnel working hours and the patients' length of in-hospital stay-An administrative data approach

Administrative data accumulating daily from hospitals would provide new possibilities to assess work shifts and patient care. We aimed to investigate associations of work unit level average work shift length and length of patient in-hospital stay, and to examine the role of nurse-patient-ratio, year, night work, age, work units and working hours at the work units for these estimations. The data for this study were based on combined administrative day-to-day patient and pay-roll based objective working hour data of employees of one hospital district in Finland for 2013-2019. Three patient measures were calculated: the overall length of in-hospital stay, the length of in-hospital stay before a medical procedure and the length of in-hospital stay after a medical procedure. A Generalized Linear Mixed Model (GLMM) with multivariate normal random effects was used with Penalized Quasi-Likelihood for relative risk ratios (RR) with 95% confidence intervals (CI). The results showed that compared to <8 hours work shifts, 8-10 hours work shifts were associated with an increased likelihood of overall length of in-hospital stay (RR 1.16, 95%CI 1.15, 1.16), and the length of in-hospital stay after a medical procedure (RR 1.28, 95%CI 1.27, 1.30). The >10 hours work shifts were associated with a decreased likelihood of the overall length of in-hospital stay (RR 0.94, 95% CI 0.94, 0.95) and length of in-hospital stay after a medical procedure among all occupations (RR 0.94, 95% CI 0.92, 0.97). These associations retained the magnitude and direction in the models additionally adjusted for work, employee, and patient characteristics, and the associations were weaker for nurses than among all occupations. To conclude, compared with the standard work shifts, 8-10 hours work shifts seem to be associated with longer, and >10 hours work shifts with shorter length of in-hospital stay. Administrative data provides feasible possibilities to investigate working hours and length of in-hospital stay.

Sequence analysis of the combinations of work shifts and absences in health care - comparison of two years of administrative data

BACKGROUND

In health care, the shift work is arranged as irregular work shifts to provide operational hours for 24/7 care. We aimed to investigate working hour trends and turnover in health care via identification of time-related sequences of work shifts and absences among health care employees. The transitions between the work shifts (i.e., morning, day, evening, and night shifts), and absences (days off and other leaves) over time were analyzed and the predictors of change in irregular shift work were quantified.

METHODS

A longitudinal cohort study was conducted using employer-owned payroll-based register data of objective and day-to-day working hours and absences of one hospital district in Finland from 2014 to 2019 (n = 4931 employees). The working hour data included start and end of work shifts, any kind of absence from work (days off, sickness absence, parental leave), and employee's age, and sex. Daily work shifts and absences in 2014 and 2019 were used in sequence analysis. Generalized linear model was used to estimate how each identified sequence cluster was associated with sex and age.

RESULTS

We identified four sequence clusters: "Morning" (60% in 2014 and 56% in 2019), "Varying shift types" (22% both in 2014 and 2019), "Employee turnover" (13% in 2014 and 3% in 2019), and "Unstable employment (5% in 2014 and 19% in 2019). The analysis of transitions from one cluster to another between 2014 and 2019 indicated that most employees stayed in the same clusters, and most often in the "Varying shift types" (60%) and "Morning" (72%) clusters. The majority of those who moved, moved to the cluster "Morning" in 2019 from "Employee turnover" (43%), "Unstable employment" (46%) or "Varying shift types" (21%). Women were more often than men in the clusters "Employee turnover" and "Unstable employment", whereas older employees were more often in "Morning" and less often in the other cluster groups.

CONCLUSION

Four clusters with different combinations of work shifts and absences were identified. The transition rates between work shifts and absences with five years in between indicated that most employees stayed in the same clusters. The likelihood of a working hour pattern characterized by "Morning" seems to increase with age.

Nurse understaffing and short work experience as predictors of healthcare-associated infections

Background

Healthcare-associated infections (HAIs) are a serious risk factor for hospital patients leading to more than 90 000 deaths each year in European countries. It has been evaluated that 7% of patients in European acute care hospitals acquire an HAI, and that a large part of cases could be prevented. Good hand hygiene is central in preventing HAIs, which may be compromised under high work pressure. The aim of this study was to analyse the associations between nurse understaffing and short work experience with the risk of HAIs at patient-level. Prior evidence on this topic remains inconclusive due to a reliance on imprecise measurement of these exposures.

Methods

We utilized administrative data on employees’ working hours and patient records from one hospital district in Finland from years 2013-2019. The data included in total 281,672 inpatient periods. We used mixed-effects survival analyses to predict the overall risk of HAIs, and four types of HAIs: bloodstream, Clostridium difficile, surgical-site and pneumonia. To consider the incubation time, exposure to nurse understaffing and short work experience were measured in preceding days in moving time windows when the patients were in the hospital.

Results

Preliminary results showed that exposure to nurse understaffing within two days, measured as low nursing hours relative to planned hours, was associated with increased risk of HAIs (hazard ratio was 1.23, 95% CI 1.05-1.45). Additional analyses showed that this risk was especially pronounced in surgical-site infections, which were also carefully monitored in the hospital district. We did not find associations between exposure to short work experience among nurses and HAI risk.

Conclusions

This study showed that nurse staffing below planned levels was associated with an increased overall risk of HAIs, particularly surgical-site infections, among patients. Adequate levels of nursing staff in hospitals may be important for preventing HAIs.

Key messages

Hospital nurse understaffing and short work experience: associations with mortality among patients

Background

Determining and maintaining optimal staffing level in hospitals is crucial, as understaffing may have serious consequences and even increase mortality risk among patients. There is no consensus, however, on the optimal way to determine staffing requirements in hospitals as patients’ care needs vary between wards and days. Nurse work experience may also affect quality of care and ultimately patients’ survival but research on this topic is scarce.

Methods

Administrative register data on patients (N = 254,308) and employees of 40 hospital units was used in one hospital district in Finland from years 2013-2019. Both nurse understaffing and nurse work experience were measured with two different indicators in each unit-day. Mixed-effects survival models were used to analyse the associations of these exposures with mortality at patient-level, when adjusted for patients’ characteristics, such as age, sex and comorbidities.

Results

Preliminary results showed that every one percent increase in the cumulative proportion of understaffed days - measured as low nursing hours relative to planned - was associated with 1.002-fold mortality risk among patients (95% CI, 1.000-1.004, p-value=0.044). Short work experience was not associated with increased risk of death.

Conclusions

This study supports previous findings on the associations between nurse understaffing and increased mortality risk among patients in Finland although no association with mortality was found for the other three staffing characteristics. However, the average daily shares of actualized nursing hours relative to planned hours were quite high in hospital units. An indicator based on actualized relative to planned working hours in routine administrative data could be useful in evaluating understaffing in hospitals.

Key messages

• Adequate level of nursing professional in hospitals is related to patient survival.

• It is also crucial of develop efficient ways to evaluate understaffing in hospitals.

Concurrent trajectories of self-rated health and working hour patterns in health care shift workers: A longitudinal analysis with 8-year follow-up

Background

The association between health and working hours is hypothesized to be reciprocal, but few longitudinal studies have examined changes in both health and working hour patterns over time. We examined combined trajectories of self-related health and two working hour patterns (working <35 h/week and working night shifts) and the extent to which these trajectories were predicted by employees' lifestyle and mental health.

Methods

Participants of this cohort study with a 8-year follow-up were 5,947 health care shift workers. We linked self-reports of health from three repeated surveys with objective pay-roll based data on working hours. Using group-based multi-trajectory analysis we identified concurrent trajectories for self-rated health and working hour patterns. We examined their associations with baseline lifestyle-related factors (smoking, at-risk alcohol use, obesity, and physical inactivity) and mental health (sleep problems and psychological distress) using multinomial regression analysis.

Results

Three combined trajectories of self-rated health and working <35 h/week and four combined trajectories of self-rated health and night work were identified. Unhealthy lifestyle and poor mental health were associated with trajectories of moderate and declining health. Sleep problems were linked with working <35 h/week. Younger age and good mental health were associated with a combined trajectory of good health and continued night shift work.

Conclusion

Trajectories of suboptimal and declining health are associated with trajectories of reducing working hours and leaving night work, and are more common in employees with unhealthy lifestyle, sleep problems, and psychological distress.

A Longitudinal Study on Trajectories of Night Work and Sickness Absence among Hospital Employees

This study aimed to investigate trajectories of night shift work in irregular shift work across a 12-year follow-up among hospital employees with and without sickness absence (SA). The payroll-based register data of one hospital district in Finland included objective working hours and SA from 2008 to 2019. The number of night shifts per year was used in group-based trajectory modeling (GBTM). The results indicate that, among those who had any sickness absence episodes, the amount of night work decreased prior to the first SA. In general, trajectories of night shift work varied from stably high to low-but-increasing trajectories in terms of the number of shifts. However, a group with decreasing pattern of night work was identified only among those with sickness absence episodes but not among those without such episodes. To conclude, the identified trajectories of night work with or without sickness absences may indicate that, among those with sickness absence episodes, night work was reduced due to increasing health problems. Hence, the hospital employees working night shifts are likely a selected population because the employees who work at night are supposed to be healthier than those not opting for night work.

Telework and perceived workload: Learnings prior to the COVID-19 upheaval

During COVID-19, telework has become a new form of work for broader groups of workers who were not teleworking prior to the pandemic. In this study, we ask what we will be returning to after COVID-19, if teleworking will become a new norm or if most workplaces will merely return to the old forms of work. The main research question of this study was to estimate the role of telework in perception of workload. More specifically, to gain an understanding of the stakes involved when reorganizing work after the pandemic, we analysed the relationship between perceived workload and opportunities to telework. Multilevel analysis utilized representative national data of wage earners in Finland (N = 4091). The findings showed that the opportunity to telework is associated with lower perceived workload in the capital area but not in the rural areas. More specifically, increasing telework opportunities among different-level workers, particularly in educational and social work in the capital area, would be beneficial in terms of increasing well-being at work. There could be good reasons for organizations to reject returning to the status quo ex ante after COVID-19 and to consider the new norm, where opportunities to telework are offered to wider worker groups.

Job insecurity and technology acceptance: an asymmetric dependence

Purpose

Existing research suggests that the competitive advantage provided by technological development depends to a large extent on the speed and coordination of the technology’s implementation, and on how adoptable the technological applications are considered. While accepting this argument, the authors consider the explanatory model to be inadequate. This study aims to contribute to the theoretical discussion by analysing institutionalised industrial relations and other organisation-level factors, which are important for workplace restructuring and societal change.

Design/methodology/approach

The analysis is based on a representative nation-wide work and working conditions survey (N = 4,100) from Finland, which includes a variety of themes, including practices, changes and well-being at work. Changes are understood as organisational changes, focusing on modern technologies such as robotisation and digitalisation.

Findings

The results indicate that occupational division at workplace (low-skilled vs high-skilled occupations) affects job insecurity and acceptance of technologies at work. The characteristics of workplaces, such as the employees’ participation and involvement in the development of the organisation, play a significant part in both the acceptance and the implementation and outcomes of the technological transformations in the workplace.

Practical implications

The research provides new and interesting insights into working life practices. Furthermore, it reveals how technology acceptance and employment perspectives relate to working conditions and lessons learned from past reforms.

Originality/value

The authors consider current theories such as technology acceptance model at the micro level and that way rationalise the need for this study. This study shows the importance of individual, organisational and wider contextual factors in technology acceptance.

Two sides, but not of the same coin: digitalization, productivity and unemployment

Purpose

This paper aims to examine how input from the digital restructuring of the workplace and productivity affects the risk of job loss and unemployment.

Design/methodology/approach

Relying on the concepts of technological unemployment and the productivity paradox as well as the theory of skills-biased technological change, the analysis incorporated micro-level individual determinants of job loss, macro-level economic determinants of input and the contribution from traditional (machinery and equipment) vs innovative (ICT) factors of production. The model has been also controlled for “traditional” indicators of “outsiderness” in the labour market. The Quality of Work Life Survey, which is a broad-based national interview survey produced by Statistics Finland, for 2018, the latest year available (N = 4,110) has been used in the analysis. Binomial logistic regression has been applied in order to estimate the effects of individual- and macro-level factors on the risk of job loss.

Findings

The results support arguments for the divergence between effects from labour- vs total-factor productivity on the risks of job loss, as well as the divergence between effects for temporary (layoff) vs permanent job loss (dismissal or unemployment). While the contribution from “traditional” factors of production to labour productivity potentially decreases the risk of permanent job loss, input from “innovative” factors of production on total-factor productivity potentially causes adverse effects (e.g. growing risks of permanent job loss).

Originality/value

The paper contributes to the theoretical discussion about technological unemployment and productivity by means of including two different concepts into a single econometric model, thus enabling examination of the research problem in an innovative way.