Nursing Diagnosis Risk for Delayed Surgical Recovery (00246) in Adult and Elderly: A Case‐Control Study

Rembold, Simone Martins; Santana, Rosimere Ferreira; Lopes, Marcos Venícios de Oliveira; Melo, Uyara Garcia

doi:10.1111/2047-3095.12274

Cited by 7 publications

(6 citation statements)

References 29 publications

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“…Nevertheless, the three most frequently identified NDs in our sample were risk NDs, demonstrating the valuable role of nurses in surgical risk assessment and prevention for establishing a standard of safety and quality of care. This was confirmed in the study by Rembold et al (2020) , who showed how identification of the risk factors of clinical practice enables implementation of interventions to prevent or reduce complications during surgical recovery. Eleven NDs were identified as HF-NDs in our sample.…”

Section: Discussionmentioning

confidence: 75%

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

et al. 2023

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Introduction In electronic health records (EHRs), standardized nursing terminologies (SNTs), such as nursing diagnoses (NDs), are needed to demonstrate the impact of nursing care on patient outcomes. Unfortunately, the use of NDs is not common in clinical practice, especially in surgical settings, and is rarely included in EHRs. Objective(s) The aim of the study was to describe the prevalence and trend of NDs in a hospital surgical setting by also analyzing the relationship between NDs and hospital outcomes. Methods A retrospective study was conducted. All adult inpatients consecutively admitted to one of the 15 surgical inpatient units of an Italian university hospital across 1 year were included. Data, including the Professional Assessment Instrument and the Hospital Discharge Register, were collected retrospectively from the hospital's EHRs. Results The sample included 5,027 surgical inpatients. There was a mean of 6.3 ± 4.3 NDs per patient. The average distribution of NDs showed a stable trend throughout the year. The most representative NANDA-I ND domain was safety/protection. The total number of NDs on admission was significantly higher for patient whose length of stay was longer. A statistically significant correlation was observed between the number of NDs on admission and the number of intra-hospital patient transfers. Additionally, the mean number of NDs on admission was higher for patients who were later transferred to an intensive care unit compared to those who were not transferred. Conclusion NDs represent the key to understanding the contribution of nurses in the surgical setting. NDs collected upon admission can represent a prognostic factor related to the hospital's key outcomes.

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Section: Discussionmentioning

confidence: 75%

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

et al. 2023

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“…With respect to the clinical indicator evidence of the interruption of the healing of the surgical area (sensitivity: 0.88; specificity: 0.99), in the studies conducted by Santana et al (2018) and Rembold, Santana, Lopes, and Melo (2020) this indicator also presented a high prognostic value for delayed surgical recovery.…”

Section: Discussionmentioning

confidence: 98%

Prognostic Indicators of Delayed Surgical Recovery in Patients Undergoing Cardiac Surgery

Carmo

Santana

Lopes

et al. 2021

J of Nursing Scholarship

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Purpose The purpose of this study was to analyze the prognostic capacity of the clinical indicators of a delayed surgical recovery nursing diagnosis throughout the hospital stay of patients having cardiac surgery. Design A prospective cohort design was adopted. A sample of inpatients undergoing elective cardiac surgery was followed during the immediate preoperative period and hospitalization. This research was conducted in the southeast region of Brazil at a national reference institution that treats highly complex diseases and performs cardiac surgeries. Data were collected from July 2017 to July 2018. Methods At the end of 1 year of data collection, 181 patients were followed in this study. The Kaplan‐Meier method was used to calculate the survival time related to delayed surgical recovery. In addition, an extended Cox model of time‐dependent covariates was adjusted to identify the clinical signs that influenced the change in the nursing diagnosis status. Results A delayed surgical recovery nursing diagnosis was present in 23.2% of the sample studied. With an expected length of stay of 8 to 10 days, most new cases of delayed surgical recovery were observed on the 10th postoperative day, and the survival rate after this day was decreased until the 29th postoperative day, when the nursing diagnosis no longer appeared. Interrupted healing of the surgical area, loss of appetite, and atrial flutter were indicators related to an increased risk for delayed surgical recovery. Conclusions Timely recognition of selected clinical indicators demonstrates a promising prognostic capacity for delayed surgical recovery. Clinical Relevance Accurate identification of prognostic factors allows nurses to identify early signs of postoperative complications. Consequently, the professional can develop an individualized plan of care, aiming at the satisfactory clinical recovery of the patient.

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“…Of the variables assessed and identified in our review, BMI, 14,55 ASA, 8,56 physical function, 12,57,58 psychological-emotional wellbeing, 9,[59][60][61] comorbidities, 9 previous surgery, 62 and pain 10,13,16,56 are known risk factors for surgical complications and unidimensional recovery. In our review, not all identified risk factors showed an effect on multidimensional recovery in every study.…”

Section: Effect Of Risk Factors Varied By Direction and Surgical Popu...mentioning

confidence: 99%

“…[6][7][8][9][10][11][12][13] Traditional postoperative outcomes have been well investigated in this population: absence of complications, adverse symptomatology (i.e., nausea, vomiting, pain, hypothermia, respiratory distress), length of hospital stay, quality of life, and resource utilization. 1,11,[14][15][16][17] While these traditional performance indicators influence a patient's postoperative status, they are unidimensional and thus may not adequately define the patient's quality of recovery. This has led to redefining postoperative recovery as a multidimensional trajectory occurring in many of the functional domains mentioned above.…”

Section: Introductionmentioning

confidence: 99%

“…There is increasing evidence for risk factors of poor postoperative outcomes within multiple types of major surgery 6–13 . Traditional postoperative outcomes have been well investigated in this population: absence of complications, adverse symptomatology (i.e., nausea, vomiting, pain, hypothermia, respiratory distress), length of hospital stay, quality of life, and resource utilization 1,11,14–17 . While these traditional performance indicators influence a patient's postoperative status, they are unidimensional and thus may not adequately define the patient's quality of recovery.…”

Section: Introductionmentioning

confidence: 99%

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Identifying risk factors for poor multidimensional recovery after major surgery: A systematic review

Ou-Young

Boggett

El-Ansary

et al. 2023

Acta Anaesthesiol Scand

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Traditional risk factors used for predicting poor postoperative recovery have focused on postoperative complications, adverse symptoms (nausea, pain), length of hospital stay, and patient quality of life. Despite these being traditional performance indicators of patient postoperative “status,” they may not fully define the multidimensional nature of patient recovery. The definition of postoperative recovery is thus evolving to include patient‐reported outcomes that are important to the patient. Previous reviews have focused on risk factors for the above traditional outcomes after major surgery. Yet, there remains a need for further study of risk factors predicting multidimensional patient‐focused recovery, and investigation beyond the immediate postoperative period after patients are discharged from the hospital. This review aimed to appraise the current literature identifying risk factors for multidimensional patient recovery.MethodsA systematic review without meta‐analysis was performed to qualitatively summarize preoperative risk factors for multidimensional recovery 4–6 weeks after major surgery (PROSPERO, CRD42022321626). We reviewed three electronic databases between January 2012 and April 2022. The primary outcome was risk factors for multidimensional recovery at 4–6 weeks. A GRADE quality appraisal and a risk of bias assessment were completed.ResultsIn total, 5150 studies were identified, after which 1506 duplicates were removed. After the primary and secondary screening, nine articles were included in the final review. Interrater agreements between the two assessors for the primary and secondary screening process were 86% (k = 0.47) and 94% (k = 0.70), respectively. Factors associated with poor recovery were found to include ASA grade, recovery tool baseline score, physical function, number of co‐morbidities, previous surgery, and psychological well‐being. Mixed results were reported for age, BMI, and preoperative pain. Due to the observational nature, heterogeneity, multiple definitions of recovery, and moderate risk of bias of the primary studies, the quality of evidence was rated from very low to low.ConclusionOur review found that there were few studies assessing preoperative risk factors as predictors for poor postoperative multidimensional recovery. This confirms the need for higher quality studies assessing risk for poor recovery, ideally with a consistent and multi‐dimensional definition of recovery.

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Nursing Diagnosis Risk for Delayed Surgical Recovery (00246) in Adult and Elderly: A Case‐Control Study

Cited by 7 publications

References 29 publications

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

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

Prognostic Indicators of Delayed Surgical Recovery in Patients Undergoing Cardiac Surgery

Identifying risk factors for poor multidimensional recovery after major surgery: A systematic review

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