Skip to content

Nurse-Patient Assignments Designed to Address Health Disparities

| June 17, 2021 | Andrew M. Dierkes, PhD, RN (PENN ’18), Assistant Professor, Acute & Tertiary Care, University of Pittsburgh School of Nursing,

Decades of nursing health services and policy research document the impact of the nursing workforce on patient outcomes. Informants of the nursing characteristics in these studies generally include an individual hospital administrator reporting on behalf of the facility or nurse survey responses aggregated by hospital employer to generate reliable estimates of organizational characteristics such as patient-to-nurse staffing ratios, the education of the nursing workforce, and the quality of the hospital work environment. The evidence from these facility-level measures of nursing resources is impactful. Policymakers and administrators in the United States and abroad reference this work to inform and promote workforce development strategies, goals, and policies at the hospital, health system, state, or national level. Nursing workforce development efforts, such as the Institute of Medicine’s 80% BSN recommendation (Institute of Medicine, 2011) and nurse staffing mandates in California and Queensland, Australia, are important movements with implications for patient care and outcomes. They encourage or require hospital administrators to employ more nurses or hire with a preference for BSN-prepared candidates to improve patient safety and outcomes.

Nested within these broader movements is another level of organizational decision making. Every day, in more than 5,000 hospitals across the United States, patients are assigned to nurses for care. The nurse-patient assignment is the fundamental way in which nursing care is organized in hospitals. Despite its importance, there is no consistent, evidence-based approach for assignment design. The process is often accomplished with pencil and paper and varies as widely as the judgement, efficiency, and dedication of the nurse in charge of assignment-making. As a result, every day across the United States, the nation’s largest healthcare professional workforce is inconsistently, if not poorly, aligned with patient needs and preferences. Nurses need an evidence base and tools to improve the process and outcomes of nurse-patient matching. However, the inability to link nurses and patients to a common shift-based assignment within a hospital limits the application of many existing studies to this problem. While the current evidence using aggregated nursing resource measures may inform hiring practices, little evidence informs how to make the best use of available nurses given the patients on the unit on any given shift. An examination of existing research highlights its limited application to this optimization problem, but also hints at the potential for better aligning nurse-patient assignments to improve outcomes with greatest impact among vulnerable patients.

Case Study

A seminal publication by Aiken and colleagues (2002) documented 7% higher odds of death within 30 days of admission for each additional patient per nurse. This finding is the impact of a change in average staffing conditions on average mortality when all other variables (characteristics of the patient and hospital) are fixed. The reality, of course, is that staffing varies by unit and average conditions may not apply to most individual units and patients. This is not to say the findings do not have merit—average conditions may better reflect the reality that a patient may receive care across multiple care areas within a hospital over the course of an admission—but to note the limits of applying this evidence to daily unit-level decision-making.

On any given shift within a unit, 1-patient variations across assignments are inevitable every time the number of patients does not divide evenly by the number of nurses on a shift. For example, a medical-surgical unit with 37 patients and 6 nurses yields five 6-patient assignments and one 7-patient assignment. The evidence suggests that each of the patients in the 7-patient assignment are subject to a 7% increase in odds of death relative to each of the 30 patients distributed across the five 6-patient assignments. It is more likely that individual characteristics of patient and nurse interact to amplify or diminish this effect.

Knowing what assignment characteristics interact can inform better assignment design and empower hospital units to make the best use of their nurses even while the system pursues higher-level workforce development goals. For example, Lasater & McHugh (2016) found in a geriatric surgical population that changes in staffing ratios impacted white and black patients differently. Each additional patient per nurse increased odds of readmission by 15% for black patients vs. 8% for white patients. The presence of significant interactions confirms that not all configurations of nurses and patients are equal. In this example, assuming a black-to-white patient ratio of 5:32 (roughly proportionate to the national population), the unit-level sum of readmission risks for individuals may vary by as much as 35% percentage points depending on assignment design.

This back-of-the-envelope math considers only a limited set of variables. Reality is certainly more complicated. These same staffing changes also disproportionately lower black patients’ odds of survival after in-hospital cardiac arrest relative to white patients (8% vs. 3% reduction for each additional patient per nurse) (Brooks-Carthon et al., 2021). The literature often employs interaction terms to examine racial disparities, but much broader evidence is needed to make a comprehensive assessment of and respond to the needs of all patients. A few studies have begun to address this gap, noting that other assignment characteristics and patient populations interact as well. For example, nurse continuity across shifts disproportionately impacts older and high-mortality risk patients (Yakusheva et al., 2017) and patients with more comorbidities (Bahr et al., 2020).

Future Directions

The alignment of nurses and patients is a critical assignment design decision that disproportionately impacts vulnerable populations. Consequently, it is vulnerable populations who stand to benefit the most from improved assignment design. Innovations to improve nurse-patient assignment process and outcomes must begin with strong and appropriate evidence. Of fundamental importance is the ability to link patient and nurse information to a common, time-stamped shift such that outcomes are the result of nurse-patient pairings, not average conditions in a hospital over an extended period. With support from the Rita and Alex Hillman Foundation, researchers at the University of Pittsburgh are joining the effort to advance this work. An emerging research core of the Nursing Health Services and Policy Research HUB at Pitt’s School of Nursing is poised to study nurse value and innovation, beginning with inpatient nurse staffing and assignments. A novel dataset will anchor the nascent research core. Data from patient flow software enables the researchers to link information from human resource files on nurses and nurse aides to patient information from the electronic health record and associate both with a time-stamped shift. A five-year retrospective data pull is projected to yield over 7 million nurse- or aide-patient pairings. Study aims include an evaluation of nurse-patient interactions, with special attention to dimensions of patient vulnerability. This science will lay a strong foundation for innovation and implementation work to optimize nurse-patient assignments and outcomes. Research informing national policy and unit-level practice can work together to improve outcomes for all patients, especially vulnerable populations.


Aiken, L. H., Clarke, S. P., Sloane, D. M., Sochalski, J., Silber, J. H. (2002). Hospital Nurse Staffing and Patient Mortality, Nurse Burnout, and Job Dissatisfaction. JAMA 288(16):1987–1993. doi:10.1001/jama.288.16.1987

Bahr, S. J., Bang, J., Yakusheva, O., Bobay, K. L., Krejci, J., Costa, L., … & Weiss, M. E. (2020). Nurse continuity at discharge and return to hospital. Nursing research, 69(3), 186-196.

Brooks-Carthon, M., Brom, H., McHugh, M., Sloane, D. M., Berg, R., Merchant, R., Girotra, S., & Aiken, L. H. (2021). Better Nurse Staffing Is Associated With Survival for Black Patients and Diminishes Racial Disparities in Survival After In-Hospital Cardiac Arrests. Medical care, 59(2), 169–176.

IOM (Institute of Medicine). (2011). The Future of Nursing: Leading Change, Advancing Health. Washington, DC: The National Academies Press.

Lasater, K. B., & McHugh, M. D. (2016). Reducing Hospital Readmission Disparities of Older Black and White Adults After Elective Joint Replacement: The Role of Nurse Staffing. Journal of the American Geriatrics Society 64(12), 2593–2598.

Yakusheva, O., Costa, D., Weiss, M. (2017). Patients Negatively Impacted by Discontinuity of Nursing Care During Acute Hospitalization. Medical Care 55(4): 421-427 doi: 10.1097/MLR.0000000000000670

Back To Top