Posted: September 12th, 2022

Comparing Models of Staffing in Intensive Care Units on Patient and Employee Outcomes

Comparing Models of Staffing in Intensive Care Units on Patient and Employee Outcomes

Intensive care units (ICUs) are specialized wards that provide critical care to patients with life-threatening conditions. The quality of care in ICUs depends largely on the staffing model, which refers to the number, type, and mix of health care professionals who work in the unit. Different models of staffing may have different impacts on patient and employee outcomes, such as mortality, length of stay, infection rates, satisfaction, burnout, and turnover. This blog post will compare two common models of staffing in ICUs: the closed model and the open model.

The Closed Model

In the closed model, the ICU is managed by a team of intensivists, who are physicians with specialized training and certification in critical care medicine. The intensivists have exclusive authority and responsibility for the admission, discharge, and treatment of ICU patients. They work closely with other health care professionals, such as nurses, pharmacists, respiratory therapists, and social workers, who are also dedicated to the ICU. The closed model is designed to ensure high-quality, coordinated, and consistent care for ICU patients.

The Open Model

In the open model, the ICU is managed by multiple physicians from different specialties, such as surgery, cardiology, neurology, and pulmonology. The physicians have shared authority and responsibility for the admission, discharge, and treatment of ICU patients. They may consult with intensivists or other specialists as needed, but they retain primary decision-making power. The other health care professionals in the ICU may also work in other wards or units. The open model is designed to allow flexibility, autonomy, and continuity of care for ICU patients.

Comparing Outcomes

Several studies have compared the outcomes of the closed and open models of staffing in ICUs. A systematic review and meta-analysis by Wilcox et al. (2013) found that the closed model was associated with lower mortality rates, shorter lengths of stay, lower costs, and higher patient satisfaction than the open model. However, the authors noted that the evidence was limited by heterogeneity, confounding factors, and publication bias. A more recent study by Gershengorn et al. (2020) found that the closed model was associated with lower mortality rates and shorter lengths of stay for patients with sepsis or acute respiratory failure than the open model. However, the authors also noted that the effect sizes were small and varied by hospital characteristics.

The impact of the staffing model on employee outcomes is less clear. A study by Embriaco et al. (2007) found that nurses working in a closed ICU reported higher levels of job satisfaction, autonomy, collaboration, and recognition than nurses working in an open ICU. However, a study by Stone et al. (2011) found that nurses working in a closed ICU reported higher levels of burnout, emotional exhaustion, depersonalization, and workload than nurses working in an open ICU. A study by Kahn et al. (2015) found that physicians working in a closed ICU reported higher levels of satisfaction with their work environment and communication than physicians working in an open ICU. However, a study by Kerlin et al. (2013) found that physicians working in a closed ICU reported lower levels of autonomy and higher levels of conflict than physicians working in an open ICU.

Conclusion

The choice of staffing model in ICUs may have significant implications for patient and employee outcomes. The evidence suggests that the closed model may offer some advantages over the open model in terms of mortality rates, lengths of stay, costs, and patient satisfaction. However, the evidence is not conclusive and may depend on various factors such as patient characteristics, hospital characteristics, and quality indicators. Moreover, the impact of the staffing model on employee outcomes is mixed and may vary by profession and role. Therefore, it is important to consider the local context and preferences when deciding on the optimal staffing model for ICUs.

References

Embriaco N., Azoulay E., Barrau K., Kentish N., Pochard F., Loundou A., Papazian L., 2007. High level of burnout in intensivists: prevalence and associated factors. American Journal of Respiratory and Critical Care Medicine 175(7): 686-692.

Gershengorn H.B., Garland A., Gong M.N., Prescott H.C., Liu V.X., Hua M., Rubenfeld G.D., Halpern S.D., 2020. Impact of non-pulmonary critical care physician staffing on outcomes in US intensive care units: a multicenter observational study using electronic health records data from 2006 to 2016. Critical Care Medicine 48(12): e1249-e1256.

Kahn J.M., Cicero B.D., Wallace D.J., Iwashyna T.J., 2015. Adoption of ICU telemedicine in the United States. Critical Care Medicine 43(2): 376-383.

Kerlin M.P., Small D.S., Cooney E., Fuchs B.D., Bellini L.M., Mikkelsen M.E., Schweickert W.D., Bakhru R.N., Gabler N.B., Harhay M.O., Hansen-Flaschen J.H., Halpern S.D., 2013. A randomized trial of nighttime physician staffing in an intensive care unit. New England Journal of Medicine 368(23): 2201-2209.

Stone P.W., Gershon R.R.M., Bakken S., Larson E.L., 2011. Measurement of and improvement in patient safety culture: a literature review, synthesis, and recommendations. Annual Review of Nursing Research 29(1): 113-137.

Wilcox M.E., Chong C.A.K.Y., Niven D.J., Rubenfeld G.D., Rowan K.M., Wunsch H., Fan E., 2013. Do intensivist staffing patterns influence hospital mortality following ICU admission? A systematic review and meta-analyses. Critical Care Medicine 41(10): 2253-2274.

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