Risk Factors and Outcomes of Unplanned PICU Postoperative Admissions

Silva, Paulo Sérgio Lucas da; Aguiar, Vânia Euzébio de; Fonseca, Marcelo Cunio Machado

doi:10.1097/pcc.0b013e3182720fab

Cited by 19 publications

(53 citation statements)

References 20 publications

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“…These patients were not obese and, in those who had preoperative polysomnogram, the degree of OSA was usually not severe. Although no true risk‐adjusted benchmark for UIAs is established in children, UIA rates have been described in the literature to range from 0.06% to 2.6% . Because the overall rate of UIA at our institution after T&A is 0.21%, these miscalculations represent the unpredictable nature of this population rather than poor preoperative planning.…”

Section: Discussionmentioning

confidence: 94%

“…Although no true risk-adjusted benchmark for UIAs is established in children, UIA rates have been described in the literature to range from 0.06% to 2.6%. [9][10][11] Because the overall rate of UIA at our institution after T&A is 0.21%, these miscalculations represent the unpredictable nature of this population rather than poor preoperative planning. In comparing patients utilizing ICU resources to those for whom resources were not necessary, our cohort demonstrated an association between resource need and young age, neurological/neuromuscular comorbidity, and gastrostomy tube status.…”

Section: Discussionmentioning

confidence: 99%

“…Selection of the appropriate postoperative location for the high‐risk T&A patient is critical because unanticipated intensive care unit admission (UIA) rate is a validated metric of patient safety due to its association with adverse events (AE) . Several studies have analyzed UIAs in postoperative pediatric patients and have identified airway procedures, higher American Society of Anesthesiologists Classification score, longer anesthesia time, multiple procedures, and infants less than 1 year of age as risk factors . Because high‐risk adenotonsillectomy patients routinely fall into this category, many practitioners admit these patients to a pediatric intensive care unit (PICU) for postoperative observation to avoid a UIA or other AE outside the ICU setting.…”

Section: Introductionmentioning

confidence: 99%

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Critical care resources utilized in high‐risk adenotonsillectomy patients

et al. 2018

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Objective Children at high risk for respiratory complication after adenotonsillectomy are often admitted to a pediatric intensive care unit (PICU) postoperatively. Although many patients receive care in such units, it is unknown how many utilize critical care resources. Methods A review was conducted to audit intensive care needs of postadenotonsillectomy patients admitted to the PICU at a tertiary, academic, pediatric hospital between July 2013, and March 2017. Demographic information, ICU indication, polysomnogram results, and comorbidities were collected. Patients were defined as needing ICU resources based on supplemental oxygen requirements greater than 2 L between 2 to 24 hours postoperatively, more than two desaturation events in a 2‐hour period, or more than hourly nursing intervention. Factors associated with utilization of ICU resources were assessed. Results One hundred and ten patients were admitted to the PICU after adenotonsillectomy. Median age was 4.2 years, median body mass index was 90.8 percentile, and median apnea hypopnea index (AHI) was 34.3. Twenty patients (18.2%) utilized ICU resources by criteria defined. Of these patients, 14 were known to need such resources by 2 hours postoperatively (70%, negative predictive value 93.8%). Neither AHI nor obesity status was correlated with need for resources; however, resource need was associated with young age, gastrostomy tube status, and neuromuscular disorders (P = 0.048, P = 0.002 and 0.013, respectively). Conclusion Most high‐risk adenotonsillectomy patients do not utilize critical care resources despite their increased perioperative risk. Patients with respiratory complications are frequently identifiable within the first 2 hours of surgery. Level of Evidence 4 Laryngoscope, 129:1229–1234, 2019

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Section: Discussionmentioning

confidence: 94%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Critical care resources utilized in high‐risk adenotonsillectomy patients

et al. 2018

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“…[ 5 ] Early identification of indicators predicting postoperative adverse events, such as longer hospital stay, disability, and death, would prevent unfavorable consequences. [ 6 7 ] The present audit was conducted to recognize the causes of postoperative SICU admissions, to identify accountable peri-operative factors, and to determine the outcomes in terms of mortality, morbidity, SICU stay, and discharge.…”

Section: Introductionmentioning

confidence: 99%

Audit of postoperative surgical intensive care unit admissions

Patel

Kacheriwala

Duttaroy

2018

Indian Journal of Critical Care Medicine

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Objective:The objective of this study was to conduct an audit of Surgical Intensive Care Unit (SICU) for identifying the admission risk factors and evaluating the outcomes of postoperative surgical patients.Design:This was a prospective, observational study.Setting:This study was conducted at SICU of a 1500-bedded tertiary care university hospital in Western India.Subject and Methods:Two hundred and forty patients admitted to the SICU postoperatively over a period of 15 months.Results:Planned and unplanned postoperative SICU admission rate was 4.45% and 0.09% of the 5284 patients operated. Indications for planned admissions included preoperative medical illnesses, anticipated blood loss, and anticipated mechanical ventilation while unpredicted intraoperative hypotension was the principal cause of unplanned admittance. Univariate analysis for two groups of the American Society of Anesthesiologists (ASA) physical status indicated that advanced age, high American College of Cardiology/American Heart Association (ACC/AHA) surgical risk, emergency surgery, planned admissions, and mortality were related to high ASA class. Analysis for ACC/AHA surgical risk showed association of high ACC/AHA surgical risk with advanced age, male gender, high ASA physical status, emergency surgery, planned admissions, and mortality. High mortality was observed in patients with SICU stay of >7 days (75.86%) and readmitted cases (72.73%).Conclusion:The need for postoperative critical care is significantly higher in males, elderly, patients with poor preoperative risk stratification scores, preexisting medical illness, major intraoperative hemorrhage, hypotension requiring inotropic support, perioperative respiratory problems and patients undergoing abdominal, trauma, and emergent surgeries. A larger study inclusive of other surgical subspecialties would aid in optimal decision-making for admissions to the SICU.

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“…Several studies have identified airway procedures, higher American Society of Anesthesiologists Classification (ASA) score, longer anesthesia time, multiple procedures, and infants less than 1 year of age as risk factors for unanticipated ICU admissions in postoperative pediatric patients. [8][9][10] As patients receiving care from pediatric otolaryngologists frequently have these risk factors, there is uncertainty of the patient's true postoperative risk. Uncertainty often drives the surgeon to "err on the side of caution" and request an ICU bed if a patient is at risk for unanticipated ICU admission.…”

Section: Introductionmentioning

confidence: 99%

Efficient Postoperative Disposition Selection in Pediatric Otolaryngology Patients: A Novel Approach

et al. 2020

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Objective Pediatric patients undergoing surgery on the aerodigestive tract require a wide range of postoperative airway support that may be difficult predict in the preoperative period. Inaccurate prediction of postoperative resource needs leads to care inefficiencies in the form of unanticipated intensive care unit (ICU) admissions, ICU bed request cancellations, and overutilization of ICU resources. At our hospital, inefficient utilization of pediatric intensive care unit (PICU) resources was negatively impacting safety, access, throughput, and finances. We hypothesized that actionable key drivers of inefficient ICU utilization at our hospital were operative scheduling errors and the lack of predictability of intermediate‐risk patients and that improvement methodology could be used in iterative cycles to enhance efficiency of care. Through testing this hypothesis, we aimed to provide a framework for similar efforts at other hospitals. Study Design Quality improvement initiative. Methods Plan, Do, Study, Act methodology (PDSA) was utilized to implement two cycles of change aimed at improving level‐of‐care efficiency at an academic pediatric hospital. In PDSA cycle 1, we aimed to address scheduling errors with surgical order placement restriction, creation of a standardized list of surgeries requiring PICU admission, and implementation of a hard stop for postoperative location in the electronic medical record surgical order. In the PDSA cycle 2, a new model of care, called the Grey Zone model, was designed and implemented where patients at intermediate risk of airway compromise were observed for 2–5 hours in the post‐anesthesia care unit. After this observation period, patients were then transferred to the level of care dictated by their current status. Measures assessed in PDSA cycle 1 were unanticipated ICU admissions and ICU bed request cancellations. In addition to continued analysis of these measures, PDSA cycle 2 measures were ICU beds avoided, safety events, and secondary transfers from extended observation to ICU. Results In PDSA cycle 1, no significant decrease in unanticipated ICU admissions was observed; however, there was an increase in average monthly ICU bed cancellations from 36.1% to 45.6%. In PDSA cycle 2, average monthly unanticipated ICU admissions and cancelled ICU bed requests decreased from 1.3% to 0.42% and 45.6% to 33.8%, respectively. In patients observed in the Grey Zone, 229/245 (93.5%) were transferred to extended observation, avoiding admission to the ICU. Financial analysis demonstrated a charge differential to payers of $1.1 million over the study period with a charge differential opportunity to the hospital of $51,720 for each additional hospital transfer accepted due to increased PICU bed availability. Conclusions Implementation of the Grey Zone model of care improved efficiency of ICU resource utilization through reducing unanticipated ICU admissions and ICU bed cancellations while simultaneously avoiding overutilization of ICU resources for intermediate‐risk patients. This was a...

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Risk Factors and Outcomes of Unplanned PICU Postoperative Admissions

Abstract: Airway abnormality, anesthetic factors, and hypoxia intraoperative were risk factors associated with UIA. Although preventable events contribute significantly to unplanned PICU admissions, they constitute a room of opportunity in quality improvement programs.

Cited by 19 publications

References 20 publications

Critical care resources utilized in high‐risk adenotonsillectomy patients

Critical care resources utilized in high‐risk adenotonsillectomy patients

Audit of postoperative surgical intensive care unit admissions

Efficient Postoperative Disposition Selection in Pediatric Otolaryngology Patients: A Novel Approach

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