Standardized Nursing Diagnoses in a Surgical Hospital Setting: A Retrospective Study Based on Electronic Health Data

Can an increase in nursing care complexity raise the risk of intra-hospital and intensive care unit transfers in children? A retrospective observational study

INTRODUCTION

Intra-hospital patient transfers (IPTs) and transfers to intensive care units (ICUs) are high-risk events in pediatric care. Nursing care complexity, reflected by nursing diagnoses (NDs) and nursing actions (NAs), may influence the frequency of these transfers. This study explores the association between nursing care complexity and IPTs, including ICU transfers, in hospitalized children.

MATERIALS AND METHODS

A retrospective observational study was conducted at a tertiary care university hospital in Italy. Data from 1013 children aged 2 to 12 years were collected from electronic health records. Sociodemographic, clinical, and nursing data, including NDs and NAs, were analyzed. Latent Class Analysis classified nursing care complexity, while backward elimination regression and binary logistic regression identified predictors of IPTs and ICU transfers.

RESULTS

Significant positive correlations were found between IPTs and both NDs (rs = 0.326, p < 0.001) and NAs (rs = 0.428, p < 0.001). Key predictors of IPTs included Diagnosis Related Groups (DRG) weight, total comorbidities, surgical DRG, the number of medications used, and high nursing care complexity. ICU-transferred patients had significantly higher nursing care complexity (6.54 vs. 3.46 NDs, p < 0.001; 31 vs. 16 NAs, p < 0.001). High nursing care complexity increased the likelihood of ICU transfer by 18 times (OR = 18.413, p < 0.001).

CONCLUSION

Nursing care complexity strongly influences IPTs and ICU transfers. Close monitoring of patients with high nursing care complexity is essential to anticipate transfers and reduce clinical risks.

Exploring the Association between Complexity of Care, Medical Complexity, and Length of Stay in the Paediatric Setting Using a Nursing Minimum Data Set: A Study Protocol

BACKGROUND/OBJECTIVES

The complexity of care requires systematic documentation to fully understand its relationship with medical complexity and its impact on patient outcomes. The Nursing Minimum Data Set (NMDS) plays a crucial role by capturing essential nursing data, enabling a detailed analysis of care and its impact on outcomes, such as length of stay (LOS). However, despite its potential, the use of NMDS in paediatric care remains limited. This study aims to explore the association between nursing and medical complexities and LOS in paediatric patients.

METHODS

A descriptive, retrospective, monocentric study will be conducted. The data will be collected through a nursing information system (Professional Assessment Instrument (PAIped)) and the hospital discharge register of patients admitted to the paediatric department in 2022 in an Italian university hospital. Conclusions and Expected Results: The use of PAIped will allow for the description of the complexity of care and enable an analysis of its relationship with medical complexity and LOS.

Exploring the Impact of Medical Complexity on Nursing Complexity of Care in Paediatric Patients: A Retrospective Observational Study

AIMS

To explore the impact of medical complexity, defined by the number of chronic conditions, on the complexity of care, as described by the frequency of nursing diagnoses (NDs) and nursing actions (NAs), in paediatric patients.

DESIGN

Retrospective observational study.

METHODS

This study was conducted in an Italian university hospital and involved the analysis of electronic health records for neonatal and paediatric patients who were consecutively admitted from January to December 2022. The sample was classified into three categories-non-chronic, single chronic and multimorbid patients-according to their clinical profiles. NDs recorded within the first 24 h from patient hospital admission and NAs performed throughout the hospital stay were counted for each group.

RESULTS

Distinct variations in the prevalence and patterns of NDs and NAs were observed across different levels of medical complexity. A significant moderate positive correlation between the number of NDs and NAs was found. However, the frequency of NDs did not directly correlate with the number of chronic conditions. Conversely, a weak but significant negative correlation was identified between the quantity of NAs and the number of chronic conditions. While the frequency of NDs showed a stable but decreasing trend as the number of chronic conditions increased, a higher number of chronic conditions were associated with a lower quantity of NAs.

CONCLUSIONS

We discovered a notable variation in the complexity of care across varying levels of medical complexity in paediatric patients. Our findings suggest that the complexity of care does not necessarily correspond to the degree of medical complexity. The observed negative relationship between the number of chronic conditions and the quantity of NAs underscores the need for further research to explore this unexpected finding and its implications for clinical practice.

IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE

Without the adoption of standardised nursing terminologies, such as nursing diagnoses (NDs) and nursing actions (NAs), assessing the complexity of care in paediatric settings can be challenging. Integrating clinical nursing information systems that incorporate standardised NDs and NAs into electronic health records is crucial for accurately documenting and analysing the complexity of care and its relationship with medical complexity.

IMPACT

In paediatric patients, the frequency of nursing diagnoses (NDs) at hospital admission is significantly associated with the quantity of nursing actions (NAs) delivered during hospitalisation. However, there is no correlation between the frequency of NDs and medical complexity, as defined by the number of chronic disorders. Specifically, the frequency of NDs decreases with increasing medical complexity, while the quantity of NAs is negatively associated with the number of chronic disorders. This indicates that the complexity of care cannot be inferred solely from medical complexity, and additional factors need to be explored. These findings enhance understanding of how complexity of care relates to medical complexity in paediatric patients. Insights into the prevalence and patterns of NDs and NAs can benefit nurses, managers, researchers and policymakers by informing clinical and organisational decision-making to ensure high-quality care.

REPORTING METHOD

The study adhered to the RECORD Statement.

PATIENT OR PUBLIC CONTRIBUTION

Patients, service users, caregivers or public members were not directly involved in the design, conduct, analysis and interpretation of data or in writing this paper. Patients contributed only to data collection.

Association between health literacy and nursing care in hospital: A retrospective study

AIMS

To describe the health literacy (HL) levels of hospitalised patients and their relationship with nursing diagnoses (NDs), nursing interventions and nursing measures for clinical risks.

DESIGN

Retrospective study.

METHODS

The study was conducted from December 2020 to December 2021 in an Italian university hospital. From 146 wards, 1067 electronic nursing records were randomly selected. The Single-Item Literacy Screener was used to measure HL. Measures for clinical risks were systematically assessed by nurses using Conley Index score, the Blaylock Risk Assessment Screening Score, Braden score, and the Barthel Index. A univariable linear regression model was used to assess the associations of HL with NDs.

RESULTS

Patients with low HL reported a higher number of NDs, interventions and higher clinical risks. HL can be considered a predictor of complexity of care.

CONCLUSIONS

The inclusion of standardised terms in nursing records can describe the complexity of care and facilitate the predictive ability on hospital outcomes.

IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE

HL evaluation during the first 24 h. From hospital admission could help to intercept patients at risk of higher complexity of care. These results can guide the development of interventions to minimise needs after discharge.

PATIENT OR PUBLIC CONTRIBUTION

No patient or public contribution was required to design or undertake this research. Patients contributed only to the data collection.