For every additional patient assigned to a medical-surgical nurse in Pennsylvania, there is an associated 8% increase in fatality risk within 30 days, according to a study published April 30 in Medical Care.
The study analyzed outcomes of nearly 550,000 medical and surgical patients who received care at a Pennsylvania hospital in 2022 or 2023. More than 2,700 direct care nurses were included in the study, which compared patient outcomes to med-surg nurse staffing ratios.
Researchers at the Philadelphia-based University of Pennsylvania’s nursing department conducted the study, as well as several others focused on nurse-to-patient ratios. In Pennsylvania hospitals, unit-specific plans govern staffing rather than mandated ratios.
Across 132 Pennsylvania hospitals, each additional patient assigned to a nurse was associated with 8% higher odds of patient death within 30 days, 4% higher odds of hospital readmission and 2% increase in length of stay, the study found.
Hospital nurse staffing varies from three to nine patients per nurse in Pennsylvania, according to a May 5 news release from Penn Nursing. The study found an average of 5.9 patients per med-surg nurse, which researchers said is a high workload that can worsen outcomes and employee well-being.
Each additional patient per nurse was associated with 33% higher odds of increased nurse burnout, 43% higher odds of job dissatisfaction and 27% higher odds of intent to leave, according to the study.
If hospitals imposed a 4-to-1 nurse-to-patient ratio in med-surg units, the researchers estimate Pennsylvania hospitals could annually save $66 million due to lower turnover. They also predicted 70,000 fewer hospital days — aka, lower length of stay — resulting in more than $239 million in savings per year.
“[H]ospital variation in nurse staffing is quite consequential for whether patients survive their hospital stay,” the researchers concluded. “Our study and others suggest that nurse understaffing is associated with turnover and setting minimum safe nurse staffing is a direct intervention to reduce understaffing.”