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Risk factors for unplanned readmission within 30 days after pediatric neurosurgery: a nationwide analysis of 9799 procedures from the American College of Surgeons National Surgical Quality Improvement Program.

ABSTRACT: OBJECTIVE Hospital readmission rate is increasingly used as a quality outcome measure after surgery. The purpose of this study was to establish, using a national database, the baseline readmission rates and risk factors for patient readmission after pediatric neurosurgical procedures. METHODS The American College of Surgeons National Surgical Quality Improvement Program-Pediatric database was queried for pediatric patients treated by a neurosurgeon between 2012 and 2013. Procedures were categorized by current procedural terminology (CPT) code. Patient demographics, comorbidities, preoperative laboratory values, operative variables, and postoperative complications were analyzed via univariate and multivariate techniques to find associations with unplanned readmissions within 30 days of the primary procedure. RESULTS A total of 9799 cases met the inclusion criteria, 1098 (11.2%) of which had an unplanned readmission within 30 days. Readmission occurred 14.0 ± 7.7 days postoperatively (mean ± standard deviation). The 4 procedures with the highest unplanned readmission rates were CSF shunt revision (17.3%; CPT codes 62225 and 62230), repair of myelomeningocele > 5 cm in diameter (15.4%), CSF shunt creation (14.1%), and craniectomy for infratentorial tumor excision (13.9%). The lowest unplanned readmission rates were for spine (6.5%), craniotomy for craniosynostosis (2.1%), and skin lesion (1.0%) procedures. On multivariate regression analysis, the odds of readmission were greatest in patients experiencing postoperative surgical site infection (SSI; deep, organ/space, superficial SSI, and wound disruption: OR > 12 and p < 0.001 for each). Postoperative pneumonia (OR 4.294, p < 0.001), urinary tract infection (OR 4.262, p < 0.001), and sepsis (OR 2.616, p = 0.006) also independently increased the readmission risk. Independent patient risk factors for unplanned readmission included Native American race (OR 2.363, p = 0.019), steroid use > 10 days (OR 1.411, p = 0.010), oxygen supplementation (OR 1.645, p = 0.010), nutritional support (OR 1.403, p = 0.009), seizure disorder (OR 1.250, p = 0.021), and longer operative time (per hour increase, OR 1.059, p = 0.029). CONCLUSIONS This study may aid in identifying patients at risk for unplanned readmission following pediatric neurosurgery, potentially helping to focus efforts at lowering readmission rates, minimizing patient risk, and lowering costs for health care systems.

SUBMITTER: Sherrod BA

PROVIDER: S-EPMC5445382 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

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Risk factors for unplanned readmission within 30 days after pediatric neurosurgery: a nationwide analysis of 9799 procedures from the American College of Surgeons National Surgical Quality Improvement Program.

Sherrod Brandon A BA Johnston James M JM Rocque Brandon G BG

Journal of neurosurgery. Pediatrics 20160517 3

OBJECTIVE Hospital readmission rate is increasingly used as a quality outcome measure after surgery. The purpose of this study was to establish, using a national database, the baseline readmission rates and risk factors for patient readmission after pediatric neurosurgical procedures. METHODS The American College of Surgeons National Surgical Quality Improvement Program-Pediatric database was queried for pediatric patients treated by a neurosurgeon between 2012 and 2013. Procedures were categori ...[more]

PMID: 27184348

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Project description:Unplanned hospital readmissions following surgical interventions are associated with adverse events and contribute to increasing health care costs. Despite numerous studies defining risk factors following lower extremity bypass surgery, evidence regarding readmission after endovascular interventions is limited. This study aimed to identify predictors of 30-day unplanned readmission following infrainguinal endovascular interventions.We identified all patients undergoing an infrainguinal endovascular intervention in the targeted vascular module of the American College of Surgeons National Surgical Quality Improvement Program between 2012 and 2014. Perioperative outcomes were stratified by symptom status (chronic limb-threatening ischemia [CLI] vs claudication). Patients who died during index admission and those who remained in the hospital after 30 days were excluded. Indications for unplanned readmission related to the index procedure were evaluated. Multivariable logistic regression was used to identify preoperative and in-hospital (during index admission) risk factors of 30-day unplanned readmission.There were 4449 patients who underwent infrainguinal endovascular intervention, of whom 2802 (63%) had CLI (66% tissue loss) and 1647 (37%) had claudication. The unplanned readmission rates for CLI and claudication patients were 16% (n = 447) and 6.5% (n = 107), respectively. Mortality after index admission was higher for readmitted patients compared with those not readmitted (CLI, 3.4% vs 0.7% [P < .001]; claudication, 2.8% vs 0.1% [P < .01]). Approximately 50% of all unplanned readmissions were related to the index procedure. Among CLI patients, the most common indication for readmission related to the index procedure was wound or infection related (42%), whereas patients with claudication were mainly readmitted for recurrent symptoms of peripheral vascular disease (28%). In patients with CLI, predictors of unplanned readmission included diabetes (odds ratio, 1.3; 95% confidence interval, 1.01-1.6), congestive heart failure (1.6; 1.1-2.5), renal insufficiency (1.7; 1.3-2.2), preoperative dialysis (1.4; 1.02-1.9), tibial angioplasty/stenting (1.3; 1.04-1.6), in-hospital bleeding (1.9; 1.04-3.5), in-hospital unplanned return to the operating room (1.9; 1.1-3.5), and discharge other than to home (1.5; 1.1-2.0). Risk factors for those with claudication were dependent functional status (3.5; 1.4-8.7), smoking (1.6; 1.02-2.5), diabetes (1.5; 1.01-2.3), preoperative dialysis (3.6; 1.6-8.3), procedure time exceeding 120 minutes (1.8; 1.1-2.7), in-hospital bleeding (2.9; 1.2-7.4), and in-hospital unplanned return to the operating room (3.4; 1.2-9.4).Unplanned readmission after endovascular treatment is relatively common, especially in patients with CLI, and is associated with substantially increased mortality. Awareness of these risk factors will help providers identify patients at high risk who may benefit from early surveillance, and prophylactic measures focused on decreasing postoperative complications may reduce the rate of readmission.

Project description:BackgroundExisting readmission reduction solutions tend to focus on complementing inpatient care with enhanced care transition and postdischarge interventions. These solutions are initiated near or after discharge, when clinicians' impact on inpatient care is ending. Preventive intervention during hospitalization is an underexplored area that holds potential for reducing readmission risk. However, it is challenging to predict readmission risk at the early stage of hospitalization because few data are available.ObjectiveThe objective of this study was to build an early prediction model of unplanned 30-day hospital readmission using a large and diverse sample. We were also interested in identifying novel readmission risk factors and protective factors.MethodsWe extracted the medical records of 96,550 patients in 205 participating Cerner client hospitals across four US census regions in 2016 from the Health Facts database. The model was built with index admission data that can become available within 24 hours and data from previous encounters up to 1 year before the index admission. The candidate models were evaluated for performance, timeliness, and generalizability. Multivariate logistic regression analysis was used to identify readmission risk factors and protective factors.ResultsWe developed six candidate readmission models with different machine learning algorithms. The best performing model of extreme gradient boosting (XGBoost) achieved an area under the receiver operating characteristic curve of 0.753 on the development data set and 0.742 on the validation data set. By multivariate logistic regression analysis, we identified 14 risk factors and 2 protective factors of readmission that have never been reported.ConclusionsThe performance of our model is better than that of the most widely used models in US health care settings. This model can help clinicians identify readmission risk at the early stage of hospitalization so that they can pay extra attention during the care process of high-risk patients. The 14 novel risk factors and 2 novel protective factors can aid understanding of the factors associated with readmission.

Dataset Information

Risk factors for unplanned readmission within 30 days after pediatric neurosurgery: a nationwide analysis of 9799 procedures from the American College of Surgeons National Surgical Quality Improvement Program.

Publications

Risk factors for unplanned readmission within 30 days after pediatric neurosurgery: a nationwide analysis of 9799 procedures from the American College of Surgeons National Surgical Quality Improvement Program.

Similar Datasets

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