Predictors and Causes of Implicit Rationing of Nursing Care: Lessons From the COVID-19 Pandemic Crisis in Iran: A Cross-Sectional Study.

BACKGROUND

Rationing of nursing care (RONC) represents a significant challenge for healthcare systems, particularly during pandemics. Effective management of RONC requires thorough examination and identification of the contributing factors within crisis situations. This study aimed to investigate the predictors and causes of implicit RONC amidst the COVID-19 pandemic in Iran.

MATERIALS AND

METHODS

A cross-sectional study was conducted in 2022, involving 200 nurses selected via stratified random sampling from COVID-19-designated hospitals in Kashan city. Data were collected using the Persian version of the Perceived Implicit Rationing of Nursing Care (P-PIRNCA) Questionnaire, the MISSCARE survey, and a questionnaire detailing potential predictors of implicit rationing. Data were analyzed using SPSS version 22, employing one-way ANOVA, Independent t-test, Kruskal-Wallis test, Pearson and Spearman-Brown correlation coefficients, and multiple linear regression.

RESULTS

The mean score for the RONC was 36.02 ± 19.79 (95% CI: 33.28-38.77). Interest in the nursing profession, second job, number of children, and monthly income were reported to be significant in the rationing model (p < 0.0001, R 2 = 0.206). Interest in the nursing profession emerged as the most significant predictor, accounting for 10.5% of the explained variance in nursing care rationing scores. Communication, human, and material factors explained 85.3%, 10.2%, and 4.5% of the variance in importance scores of reasons for missed care, respectively.

CONCLUSION

The RONC was not high at the peak of the pandemic. Selecting nurses from among those interested in the profession, those without a second job, and those with more children, as well as paying attention to professional relationships, can lead to adjustments in the rationing of care during the difficult conditions of the pandemic crisis.