High Risk Of Unplanned Readmission Research Articles

Impact of mental disorders on unplanned readmissions for congestive heart failure patients: a population-level study.

Reducing preventable hospitalization for congestive heart failure (CHF) patients is a challenge for health systems worldwide. CHF patients who also have a recent or ongoing mental disorder may have worse health outcomes compared with CHF patients with no mental disorders. This study examined the impact of mental disorders on 28day unplanned readmissions of CHF patients. This retrospective cohort study used population-level linked public and private hospitalization and death data of adults aged ≥18years who had a CHF admission in New South Wales, Australia, between 1 January 2014 and 31 December 2020. Individuals' mental disorder diagnosis and Charlson comorbidity and hospital frailty index scores were derived from admission records. Competing risk and cause-specific risk analyses were conducted to examine the impact of having a mental disorder diagnosis on all-cause hospital readmission. Of the 65861 adults with index CHF admission discharged alive (mean age: 78.6±12.1; 48% female), 19.2% (12675) had at least one unplanned readmission within 28days following discharge. Adults with CHF with a mental disorder diagnosis within 12months had a higher risk of 28day all-cause unplanned readmission [hazard ratio (HR): 1.21, 95% confidence interval (CI): 1.15-1.27, P-value<0.001], particularly those with anxiety disorder (HR: 1.49, 95% CI: 1.35-1.65, P-value<0.001). CHF patients aged ≥85years (HR: 1.19, 95% CI: 1.11-1.28), having ≥3 other comorbidities (HR: 1.35, 95% CI: 1.25-1.46), and having an intermediate (HR: 1.34, 95% CI: 1.28-1.40) or high (HR: 1.37, 95% CI: 1.27-1.47) frailty score on admission had a higher risk of unplanned readmission. CHF patients with a mental disorder who have ≥3 other comorbidities and an intermediate frailty score had the highest probability of unplanned readmission (29.84%, 95% CI: 24.68-35.73%) after considering other patient-level factors and competing events. CHF patients who had a mental disorder diagnosis in the past 12months are more likely to be readmitted compared with those without a mental disorder diagnosis. CHF patients with frailty and a mental disorder have the highest probability of readmission. Addressing mental health care services in CHF patient's discharge plan could potentially assist reduce unplanned readmissions.

The Impact of Inadequate Energy Intake on Readmission Burden of Patients With Heart Failure.

Adequate energy intake is essential for good clinical outcomes. The association between energy intake and readmission burden of patients with heart failure (HF) still needs to be clarified. In this study, our aim was to determine the association between energy intake and readmission in patients with HF. A total of 311 inpatients with HF were recruited. Demographic and clinical information were collected during hospitalization; the daily diets of the participants were collected in the second week after discharge using the 3-day diet record, and the energy intake was calculated using a standardized nutrition calculator. The inadequate energy intake was defined as <70% × 25 kcal/kg of ideal body weight. The participants were followed up for 12 weeks after discharge. The number, reasons, and length of stay of unplanned readmissions were collected. Regression analyses were used to evaluate the associations between inadequate energy intake, and readmission rate and readmission days. The median of the energy intake of participants was 1032 (interquartile range, 809-1266) kcal/d. The prevalence of inadequate energy intake was 40%. Patients with inadequate energy intake had a higher risk of unplanned readmission (odds ratio, 5.616; 95% confidence interval, 3.015-10.462; P < .001) and more readmission days (incidence rate ratio, 5.226; 95% confidence interval, 3.829-7.134, P < .001) after adjusting for potential confounders. Patients with HF had a high incidence of inadequate dietary energy intake, and it increases the burden of readmission.

Effects of a Multimodal Transitional Care Intervention in Patients at High Risk of Readmission

Hospital readmissions are frequent, costly, and sometimes preventable. Although these issues have been well publicized and incentives to reduce them introduced, the best interventions for reducing readmissions remain unclear. To evaluate the effects of a multimodal transitional care intervention targeting patients at high risk of hospital readmission on the composite outcome of 30-day unplanned readmission or death. A single-blinded, multicenter randomized clinical trial was conducted from April 2018 to January 2020, with a 30-day follow-up in 4 medium-to-large-sized teaching hospitals in Switzerland. Participants were consecutive patients discharged from general internal medicine wards and at higher risk of unplanned readmission based on their simplified HOSPITAL score (≥4 points). Data were analyzed between April and September 2022. The intervention group underwent systematic medication reconciliation, a 15-minute patient education session with teach-back, a planned first follow-up visit with their primary care physician, and postdischarge follow-up telephone calls from the study team at 3 and 14 days. The control group received usual care from their hospitalist, plus a 1-page standard study information sheet. Thirty-day postdischarge unplanned readmission or death. A total of 1386 patients were included with a mean (SD) age of 72 (14) years; 712 (51%) were male. The composite outcome of 30-day unplanned readmission or death was 21% (95% CI, 18% to 24%) in the intervention group and 19% (95% CI, 17% to 22%) in the control group. The intention-to-treat analysis risk difference was 1.7% (95% CI, -2.5% to 5.9%; P = .44). There was no evidence of any intervention effects on time to unplanned readmission or death, postdischarge health care use, patient satisfaction with the quality of their care transition, or readmission costs. In this randomized clinical trial, use of a standardized multimodal care transition intervention targeting higher-risk patients did not significantly decrease the risks of 30-day postdischarge unplanned readmission or death; it demonstrated the difficulties in preventing hospital readmissions, even when multimodal interventions specifically target higher-risk patients. ClinicalTrials.gov Identifier: NCT03496896.

Evaluating the Impact of Obesity and Different Metabolic Statuses on the Prognosis of Hospitalized Patients with Inflammatory Bowel Disease: A Cohort Study

Introduction: Obesity is associated with an increased risk of inflammatory bowel disease (IBD), whereas not all obese individuals have the same effect. In individuals with obesity, the role of metabolic status in the readmission of IBD remains unclear. Our study aimed to evaluate the association between different obesity metabolic phenotypes and the prognosis of IBD patients. Methods: We conducted a longitudinal cohort study using Nationwide Readmissions Database (NRD) (2018 sample). Out of 12,928,231 discharge records, 63,748 records with a discharge diagnosis of IBD were identified for analysis. Cox proportional hazard ratio (HR) with 95% confidence interval (CI) was calculated, adjusting for potential confounders. Results: During a 180-day follow-up in IBD patients with different obesity metabolic phenotypes, all-cause readmission rate, inpatient mortality rate, unplanned readmission rate, total charge, hospitalized length of stay were statistically different (all p < 0.001). After multivariate Cox regression analysis, IBD patients with metabolically unhealthy nonobese (MUNO) had higher risk of readmission (all-cause and unplanned) (HR 1.04, 95% CI: 1.00–1.08 and HR 1.06, 95% CI: 1.02–1.10), and those with metabolically unhealthy obesity (MUO) had higher risk of unplanned readmission (HR 1.08, 95% CI: 1.02–1.15). In subgroup analysis, both the MUNO group and MUO group had higher risk of readmission (all-cause and unplanned) in the ulcerative colitis (UC) subgroup, but only the MUNO group had higher risk of readmission (all-cause and unplanned) (HR 1.05, 95% CI: 1.00–1.10 and HR 1.06, 95% CI: 1.01–1.12) in the Crohn’s disease (CD) subgroup. Conclusion: Metabolic abnormalities were associated with an increased risk of readmission in patients with IBD, regardless of obesity.

Predictive modeling for 14-day unplanned hospital readmission risk by using machine learning algorithms

BackgroundEarly unplanned hospital readmissions are associated with increased harm to patients, increased medical costs, and negative hospital reputation. With the identification of at-risk patients, a crucial step toward improving care, appropriate interventions can be adopted to prevent readmission. This study aimed to build machine learning models to predict 14-day unplanned readmissions.MethodsWe conducted a retrospective cohort study on 37,091 consecutive hospitalized adult patients with 55,933 discharges between September 1, 2018, and August 31, 2019, in an 1193-bed university hospital. Patients who were aged < 20 years, were admitted for cancer-related treatment, participated in clinical trial, were discharged against medical advice, died during admission, or lived abroad were excluded. Predictors for analysis included 7 categories of variables extracted from hospital’s medical record dataset. In total, four machine learning algorithms, namely logistic regression, random forest, extreme gradient boosting, and categorical boosting, were used to build classifiers for prediction. The performance of prediction models for 14-day unplanned readmission risk was evaluated using precision, recall, F1-score, area under the receiver operating characteristic curve (AUROC), and area under the precision–recall curve (AUPRC).ResultsIn total, 24,722 patients were included for the analysis. The mean age of the cohort was 57.34 ± 18.13 years. The 14-day unplanned readmission rate was 1.22%. Among the 4 machine learning algorithms selected, Catboost had the best average performance in fivefold cross-validation (precision: 0.9377, recall: 0.5333, F1-score: 0.6780, AUROC: 0.9903, and AUPRC: 0.7515). After incorporating 21 most influential features in the Catboost model, its performance improved (precision: 0.9470, recall: 0.5600, F1-score: 0.7010, AUROC: 0.9909, and AUPRC: 0.7711).ConclusionsOur models reliably predicted 14-day unplanned readmissions and were explainable. They can be used to identify patients with a high risk of unplanned readmission based on influential features, particularly features related to diagnoses. The operation of the models with physiological indicators also corresponded to clinical experience and literature. Identifying patients at high risk with these models can enable early discharge planning and transitional care to prevent readmissions. Further studies should include additional features that may enable further sensitivity in identifying patients at a risk of early unplanned readmissions.

Sequencing of Renal Mass Biopsy and Ablation: Results from the National Cancer Database.

We assessed current utilization and sequencing of renal mass biopsy (RMB) and thermal ablation for renal cell carcinoma (RCC) patients in the United States. The 2004-2014 National Cancer Database was queried for adult patients with histopathologically diagnosed American Joint Committee on Cancer stage I RCC ≤5 cm undergoing RMB and thermal ablation. RMB sequencing was stratified into "staged RMB" (separate sessions for RMB/ablation) or "concomitant RMB" (same date RMB/ablation). Demographics, cancer variables and time trends were compared. Univariate and multivariable logistic regression identified predictors of concomitant RMB, and evaluated their impact on inpatient hospital stay and 30-day unplanned readmissions. A total of 6,323 patients were included, of whom 2,913 (46.1%) underwent staged RMB and 3,410 (53.9%) underwent concomitant RMB. Concomitant RMB was more frequently performed until 2012, and staged RMB thereafter (trend p <0.001). In multivariable logistic regression models, private insurance, clear cell RCC, right-sided disease and smaller tumor diameter demonstrated higher probability of concomitant RMB. Furthermore, geographical differences across the United States were evident (concomitant RMB West/South Central region 64.6% versus New England 29.3%, multivariable p <0.05). Concomitant RMB was associated with greater odds of inpatient hospital stay (multivariable OR=1.42, 95% CI=1. 27-1. 60; p <0.001) and 30-day unplanned hospital readmissions (OR=1.55, 95% CI=1.07-2.27; p=0.022). Staged RMB is more frequently performed in more recent years and is associated with lower odds of inpatient hospital stay and unplanned readmissions within 30 days. These potential benefits, combined with the potential to limit ablation of benign tumors, need to be weighed against additional health care costs and inconvenience associated with 2 interventions.

Unplanned readmission or death after discharge for\xa0Aboriginal and non-Aboriginal people with chronic disease in NSW Australia: a retrospective cohort study

BackgroundAdmitted patients with chronic disease are at high risk of an unplanned hospital readmission, however, little research has examined unplanned readmission among Aboriginal people in Australia. This study aimed to examine whether rates of unplanned 28 day hospital readmission, or death, significantly differ between Aboriginal and non-Aboriginal patients in New South Wales, Australia, over a nine-year period.MethodsA retrospective cohort analysis of a sample of de-identified linked hospital administrative data was conducted. Eligible patients were: 1) aged ≥18 years old, 2) admitted to an acute facility in a NSW public hospital between 30th June 2005 and 1st July 2014, and 3) admitted with either cardiovascular disease, chronic respiratory disease, diabetes or renal disease. The primary composite outcome was unplanned readmission or death within 28 days of discharge. Generalized linear models and a test for trend were used to assess rates of unplanned readmission or death over time in Aboriginal and non-Aboriginal patients with chronic disease, accounting for sociodemographic variables.ResultsThe final study cohort included 122,145 separations corresponding to 48,252 patients (Aboriginal = 57.2%, n = 27,601; non-Aboriginal = 42.8%, n = 20,651). 13.9% (n = 16,999) of all separations experienced an unplanned readmission or death within 28 days of discharge. Death within 28 days of discharge alone accounted for only a small number of separations (1.4%; n = 1767). Over the nine-year period, Aboriginal separations had a significantly higher relative risk of an unplanned readmission or death (Relative risk = 1.34 (1.29, 1.40); p-value < 0.0001) compared with non-Aboriginal separations once adjusted for sociodemographic, disease variables and restricted to < 75 years of age. A test for trend, including an interaction between year and Aboriginal status, showed there was no statistically significant change in proportions over the nine-year period for Aboriginal and non-Aboriginal separations (p-value for trend = 0.176).ConclusionAboriginal people with chronic disease had a significantly higher risk of unplanned readmission or death 28 days post discharge from hospital compared with non-Aboriginal people, and there has been no significant change over the nine year period. It is critical that effective interventions to reduce unplanned readmissions for Aboriginal people are identified.

Predicting 7-day, 30-day and 60-day all-cause unplanned readmission: a case study of a Sydney hospital

BackgroundThe identification of patients at high risk of unplanned readmission is an important component of discharge planning strategies aimed at preventing unwanted returns to hospital. The aim of this study was to investigate the factors associated with unplanned readmission in a Sydney hospital. We developed and compared validated readmission risk scores using routinely collected hospital data to predict 7-day, 30-day and 60-day all-cause unplanned readmission.MethodsA combination of gradient boosted tree algorithms for variable selection and logistic regression models was used to build and validate readmission risk scores using medical records from 62,235 live discharges from a metropolitan hospital in Sydney, Australia.ResultsThe scores had good calibration and fair discriminative performance with c-statistic of 0.71 for 7-day and for 30-day readmission, and 0.74 for 60-day. Previous history of healthcare utilization, urgency of the index admission, old age, comorbidities related to cancer, psychosis, and drug-abuse, abnormal pathology results at discharge, and being unmarried and a public patient were found to be important predictors in all models. Unplanned readmissions beyond 7 days were more strongly associated with longer hospital stays and older patients with higher number of comorbidities and higher use of acute care in the past year.ConclusionsThis study demonstrates similar predictors and performance to previous risk scores of 30-day unplanned readmission. Shorter-term readmissions may have different causal pathways than 30-day readmission, and may, therefore, require different screening tools and interventions. This study also re-iterates the need to include more informative data elements to ensure the appropriateness of these risk scores in clinical practice.

Thirty-day outcomes in pediatric epilepsy surgery.

The aim of this study was to use the multicenter American College of Surgeons National Surgical Quality Improvement Program-Pediatric (NSQIP-P) to evaluate and identify risk factors for 30-day adverse events in children undergoing epilepsy surgery. Using the 2015 NSQIP-P database, we identified children (age 0-18years) undergoing pediatric epilepsy surgery and analyzed NSQIP-defined complications, unplanned reoperations, and unplanned readmissions. Multivariable logistic regression analysis was performed using perioperative data to identify risk factors for adverse events within 30days of the index procedure. Two hundred eight pediatric patients undergoing epilepsy surgery were identified for the year 2015 in the NSQIP-P database. The majority of patients were male (51.8%) and white (72.9%). The median age was 10years. Neurological and neuromuscular comorbidities were seen in 62.5% of patients. Surgical blood loss and transfusion was the most common overall NSQIP-defined event (15.7%) and was reported in 40% with hemispherectomy. Nineteen patients (6.8%) had an unplanned reoperation and 20 patients (7.1%) had an unplanned readmission. Multivariable logistic regression analysis showed that African American patients (OR 3.26, 95% CI 1.29-8.21, p=0.01) and hemispherectomy (OR 3.05, 95% CI 1.4-6.65, p=0.01) were independently associated with NSQIP-defined complications. Patients undergoing hemispherectomy (OR 4.11, 95% CI 1.48-11.42, p=0.01) were also at significantly higher risk of unplanned readmission after pediatric epilepsy surgery. Data from the 2015 NSQIP-P database showed that hemispherectomy was significantly associated with higher perioperative events in children undergoing epilepsy surgery. Quality improvement initiatives for hemispherectomy should target surgical blood loss and wound-related complications. Racial disparities in access to cranial pediatric epilepsy surgery and perioperative complications were also highlighted in the present study.

Variation in readmission and mortality following hospitalisation with a diagnosis of heart failure: prospective cohort study using linked data

BackgroundHospitalisation for heart failure is common and post-discharge outcomes, including readmission and mortality, are often poor and are poorly understood. The purpose of this study was to examine patient- and hospital-level variation in the risk of 30-day unplanned readmission and mortality following discharge from hospital with a diagnosis of heart failure.MethodsProspective cohort study using data from the Sax Institute’s 45 and Up Study, linking baseline survey (Jan 2006-April 2009) to hospital and mortality data (to Dec 2011). Primary outcomes in those admitted to hospital with heart failure included unplanned readmission, mortality and combined unplanned readmission/mortality, within 30 days of discharge. Multilevel models quantified the variation in outcomes between hospitals and examined associations with patient- and hospital-level characteristics.ResultsThere were 5074 participants with a heart failure admission discharged from 251 hospitals; 1052 (21%) had unplanned readmissions, 186 (3.7%) died, and 1146 (23%) had either/both outcomes within 30 days of discharge. Crude outcomes varied across hospitals, but between-hospital variation explained little of the total variation in outcomes (intraclass correlation coefficients (ICC) after inclusion of patient factors: 30-day unplanned readmission ICC = 0.0125 (p = 0.24); death ICC = 0.0000 (p > 0.99); unplanned readmission/death ICC = 0.0266 (p = 0.07)). Patient characteristics associated with a higher risk of unplanned readmission included: being male (male vs female, adjusted odds ratio (aOR) = 1.18, 95% CI: 1.00–1.37); prior hospitalisation for cardiovascular disease (aOR = 1.44, 1.08–1.91) and for anemia (aOR = 1.36, 1.14–1.63); comorbidities at admission (severe vs none: aOR = 1.26, 1.03–1.54); lower body-mass-index (obese vs normal weight: aOR = 0.77, 0.63–0.94); and lower social interaction scores. Similarly, risk of 30-day mortality was associated with patient- rather than hospital-level factors, in particular age (≥85y vs 45–< 75y: aOR = 3.23, 1.93–5.41) and comorbidity (severe vs none: aOR = 2.68, 1.82–3.94).ConclusionsThe issue of high readmission and mortality rates in people with heart failure appear to be system-wide, with the variation in these outcomes essentially attributable to variation between patients rather than hospitals. The findings suggest that there are limitations in using these outcomes as hospital performance measures in this patient population and support the need for patient-centred strategies to optimise heart failure management and outcomes.

Factors Related to the Unplanned 90-Day Readmission Rate Among Elderly at a Geriatric Medicine Center

Unplanned readmissions increase healthcare utilization rates and healthcare costs. The Taiwan Healthcare Indicator Series regards the rate of hospital readmission as an important indicator of inpatient-care quality. The elderly face a higher risk of unplanned readmission due to elderly-specific health and disease characteristics such as deteriorating body functions and the relatively high incidence of complications after the treatment of acute diseases. To explore the factors that relate to the unplanned readmission of elderly within 90 days of discharge at a geriatric medical center. We retrospectively reviewed the medical records of inpatients aged ≥65 years who had been admitted between January 2013 and December 2014. Related factors that affected the rate of unplanned readmission within 90 days of discharge were screened and analyzed using the chi-squared test and logistic regression analysis. The 90-day unplanned readmission rate was 20.3%. Factors that were found to relate to unplanned readmissions were: emergency room admission (88.7%), lack of regular outpatient follow-up (60.4%), cerebrovascular incidents (43.4%), osteoporosis (32.1%), gastrointestinal diseases (45.3%), and a hemoglobin level < 10.0 mg/dL (35.8%). The results of the present study may help the healthcare team better understand the factors that affect unplanned readmission in the elderly. We suggest that these teams provide timely health education for elderly, integrative healthcare for chronic diseases, and appropriate nutritional supplements in order to reduce unplanned readmissions.

Prospective validation and adaptation of the HOSPITAL score to predict high risk of unplanned readmission of medical patients.

The HOSPITAL score is a simple prediction model that accurately identifies patients at high risk of readmission and showed good performance in an international multicentre retrospective study. We aimed to demonstrate prospectively its accuracy to predict 30-day unplanned readmission and death. We prospectively screened all consecutive patients aged ≥50 years admitted to the department of general internal medicine of a large community hospital in Switzerland. We excluded patients who refused to give consent, who died during hospitalisation, or who were transferred to another acute care, rehabilitation or palliative care facility. The primary outcome was the first unplanned readmission or death within 30 days after discharge. Some of the predictors of the original score (discharge from an oncology service and length of stay) were adapted according to the setting for practical reasons, before the start of patient inclusion. We also assessed a simplified version of the score, without the variable "any procedure performed during hospitalisation". The performance of the score was evaluated according to its overall accuracy (Brier score), its discriminatory power (C-statistic), and its calibration (Hosmer-Lemeshow goodness-of-fit test). Among the 346 included patients, 40 (11.6%) had a 30-day unplanned readmission or death. The HOSPITAL score showed very good accuracy (Brier score 0.10), good discriminatory power (C-statistic 0.70, 95% confidence interval [CI] 0.62-0.79), and an excellent calibration (p = 0.77). Patients were classified into three risk categories for the primary outcome: low (59%), intermediate (20.8%) and high risk (20.2%). The estimated risks of unplanned readmission/death for each category were 8.2%, 11.3% and 21.6%, respectively. The simplified score showed the same performance, with a Brier score of 0.10, a C-statistic of 0.70 (95% CI 0.61-0.79), and a goodness-of-fit statistic of 0.40. The HOSPITAL score prospectively identified patients at high risk of 30-day unplanned readmission or death with good performance in medical patients in Switzerland. Its simplicity and good performance make it an easy-to-use tool to target patients who might most benefit from intensive transitional care interventions.

PICU Readmissions: Not Just Output but Patient Throughput*

PICU Readmissions: Not Just Output but Patient Throughput*

Development of a predictive model to identify inpatients at risk of re-admission within 30 days of discharge (PARR-30)

ObjectivesTo develop an algorithm for identifying inpatients at high risk of re-admission to a National Health Service (NHS) hospital in England within 30 days of discharge using information that can...

Risk factors of hospitalization and readmission of patients with COPD in Hong Kong population: analysis of hospital admission records.

BackgroundChronic Obstructive Pulmonary Disease (COPD) accounts for around 4% of all public hospital annual admissions in Hong Kong. By year 2020, COPD will be ranked fifth among the conditions with the highest burden to the society. This study identifies admission and unplanned readmission of COPD patients, factors affecting unplanned readmission, and estimates its cost burden on the public healthcare system in Hong Kong.MethodsThis is a retrospective study analyzing COPD admissions to all public hospitals in Hong Kong. All admission episodes to acute medical wards with the principal diagnosis of COPD (ICD-9:490-492, 494-496) from January 2006 to December 2007 were captured. Unplanned readmission was defined as an admission which followed a previous admission within 30 days.ResultsIn 2006 and 2007, 65497 (8.0%) of episodes from medical wards were identified as COPD admissions, and among these, 15882 (24.2%) were unplanned readmissions. The mean age of COPD patients was 76.81 ± 9.59 years and 77% were male. Unplanned readmission was significantly associated with male gender, receiving public assistance and living in nursing homes while no association was found with the Charlson comorbidity index. Patients who were readmitted unplanned had a significant longer acute length of stay (β = 0.3894, P < 0.001) after adjustment for other covariates.ConclusionsUnplanned readmission of COPD patients has a huge impact on the public healthcare system. A systematic approach in programme provision and a good discharge planning process targeting on COPD patients who are at high risk of unplanned readmission are essential.

Risk Factors of Unplanned Readmission After Colorectal Surgery: A Prospective, Multicenter Study

Unplanned readmission after colorectal surgery is a relatively frequent event, knowledge of which often is inaccurate. This study was designed to examine the incidence and causes of readmissions and to determine the criteria that could predict them. From June to September 2002, 1,421 patients were enrolled in a prospective, multicenter study performed by the Association Francaise de Chirurgie. The goal of the study was to determine mortality and morbidity after colorectal surgery for elective or emergency surgical management of diverticular disease or cancer. In the study, readmissions within three months after discharge were assessed. Of 1,421 patients, 342 patients (27 percent) were readmitted once after a mean period of 53 days. Among the readmissions, 248 (19.5 percent) were planned and 94 (7.5 percent) were unplanned (mainly for septic complications). With the multivariate logistic regression analysis, five independent factors were significantly associated with a higher risk of unplanned readmission (in order of importance): surgical field contamination, long duration of operation, need for an associated surgical procedure, hemoglobin level <12 g/dl, and absence of air testing after colorectal anastomosis. The study permitted to individualize several factors significantly associated with a higher risk of unplanned readmission after colorectal surgery.