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Introduction
Understaffing is a complex issue that requires the development of an efficient solution. The PICOT question used in the context of this assignment is: In newborn babies and nursing home seniors, how effective is the Excel-based scheduling model (I) versus churn-based adjustments (C) for increasing the level of patient care and addressing understaffing (O) within one month?
Literature Review
Twigg, Gelder, and Myers (2015) studied patient exposure to shifts with understaffed personnel that can lead to adverse health outcomes. Their aim of the research was to explore connections between the exposure to understaffed shifts and nurse-sensitive outcomes at patient level (Twigg et al., 2015, p. 1564). Rochefort, Buckeridge, and Abrahamowicz (2015) posed the question of whether there was an association between the inadequate use of nursing human resources and patient safety.
The researchers had three aims of the study:
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determining whether understaffing contributes to the risk of adverse patient events;
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identifying whether optimal levels of staffing are possible to establish;
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determining whether the complexity of patient requirements influences risks and outcomes of understaffing.
He, Staggs, Bergquist-Beringer, and Dunton (2016) asked the following research question: is there an association between nurse-sensitive patient outcomes and seasonal patterns? Their study aimed to determine whether there was a relationship between seasonal and trend patterns of nursing human resources and nurse-sensitive patient outcomes. Van den Oetelaar, van Stel, van Rhenen, Stellato, and Grolman (2016) studied the lack of methods for workload management that contributes to the inability to address patient needs. The researchers aimed to develop a study protocol for managing nurses workload (planning, support, registration, etc.) and positively influencing nurse-related patient outcomes.
Twigg et al. (2015) conducted a quantitative study; the sample included 36,529 patient admissions collected through the analysis of administrative data from acute care hospitals. They created an understaffed indicator variable from the analyzed data. Logistic regression was performed to estimate the likelihood of decreased patient outcomes during understaffed shifts. It was found that the patient outcomes decreased when they were exposed to understaffed shifts, with all ratios being >1. The most significant issues that resulted from understaffed shifts were infections of wounds, urinary tract infections, pressure injuries, etc. Rochefort et al. (2015) conducted a quantitative study at McGill University Health Centre. The sample included the 2010-2015 cohort of all patients admitted to the facility and monitored during their inpatient stay and 7 days post-discharge. The researchers measured 4 potentially preventable adverse patient conditions such as in-hospital falls, pneumonia, ventilator-associated pneumonia, and venous thromboembolism.
Four Cox proportional hazards regression models were used to determine the association between adverse health outcomes and understaffed nursing resources. It was found that the inadequate use of nursing human resources (duration of exposure, nursing hours per patient) contributed to the decreased health outcomes of patients in four categories of preventable adverse events. He et al. (2016) conducted a mixed-methods study using nursing data gathered from the National Database of Nursing Quality Indicators (2004-2012). Based on data patterns, units were divided into several groups so that the analysis could be conducted at the group level. Important research variables included the percent of nursing hours provided by RNs and total nursing hours per patient days. Weighted linear mixed models were used to examine the associations between nurse staffing and patient outcomes (He et al., 2016, p. 1). It was found that both variables of nurse staffing had an inverse association with all patient outcomes (p<0.001).
With regard to seasonality, a lower rate of events was related to higher staffing (p<0.001). The percent of nursing hours was positively associated with higher rates of falls (p<0.001) and ulcers in patients (p=0.03). Van den Oetelaar et al. (2016) conducted a qualitative study at surgical wards in a research hospital in the Netherlands. The study included 6 of such wards; each of them had a capacity of 15-30 beds. Delphi study for composing a list of characteristics for nursing care was developed; also, within the setting of hospital wards, researchers conducted the time study of nurses activities; the two estimates were used for estimating nurses workload. Estimations of nurses workloads were conducted by dividing the estimate of allocated care time by the estimate of required care time (van den Oetelaar et al., 2016, p. 7). Based on the questionnaire, it was found that nurses lacked engagement-related resources (e.g., colleague support) and related demands (e.g., workload) for providing an optimized level of care to patients. These findings helped the researchers develop an effective method for managing nurses workload in surgical wards.
Twigg et al. (2015) were limited in the timeframe of the research; they recommended using the understaffing variable for determining the likelihood of patients being exposed to the risk of decreased health outcomes. Rochefort et al. (2015) were limited in the method of their measurement; it was advised to identify the existing patterns of nursing staffing and determining whether they present any risk to patients developing preventable adverse conditions. He et al. (2016) recommended reevaluating the existing models of staffing and increasing the availability of nursing personnel to prevent falls and pressure ulcers among patients. The research was limited to only one database. Lastly, van den Oetelaar et al. (2016) were limited only to a surgical setting; the researchers recommended working in cooperation with nurses to measure their workload and develop an appropriate method for workload management.
Conclusion
The review of relevant research on the topic of nurse understaffing showed that there is a positive correlation between adverse patient outcomes and poor management of nursing human resources. The project on the identified Picot question may contribute to the body of research.
References
He, J., Staggs, V., Bergquist-Beringer, S., & Dunton, N. (2016). Nurse staffing and patient outcomes: A longitudinal study on trend and seasonality. BMC Nursing, 15(60), 1-10.
Rochefort, C., Buckeridge, D., & Abrahamowicz, M. (2015). Improving patient safety by optimizing the use of human resources. Implementation Science, 10(89), 1-11.
Twigg, D., Gelder, L., & Myers, H. (2015). The impact of understaffed shifts on nurse-sensitive outcomes. Journal of Advanced Nursing, 71(7), 1564-1572.
van den Oetelaar, W., van Stel, H., van Rhenen, W., Stellato, R., & Grolman, W. (2016). Balancing nurses workload in hospital wards: Study protocol of developing a method to manage workload. BMJ Open, 6, 1-12.
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