Development and validation of a risk score to predict unplanned hospital readmissions in ICU survivors: A data linkage study

BACKGROUND

Intensive Care Unit (ICU) follow-up clinics are growing in popularity internationally; however, there is limited evidence as to which patients would benefit most from a referral to this service.

OBJECTIVES

The objective of this study was to develop and validate a model to predict which ICU survivors are most likely to experience an unplanned hospital readmission or death in the year after hospital discharge and derive a risk score capable of identifying high-risk patients who may benefit from referral to follow-up services.

METHODS

A multicentre, retrospective observational cohort study using linked administrative data from eight ICUs was conducted in the state of New South Wales, Australia. A logistic regression model was developed for the composite outcome of death or unplanned readmission in the 12 months after discharge from the index hospitalisation.

RESULTS

12,862 ICU survivors were included in the study, of which 5940 (46.2%) patients experienced unplanned readmission or death. Strong predictors of readmission or death included the presence of a pre-existing mental health disorder (odds ratio [OR]: 1.52, 95% confidence interval [CI]: 1.40-1.65), severity of critical illness (OR: 1.57, 95% CI: 1.39-1.76), and two or more physical comorbidities (OR: 2.39, 95% CI: 2.14-2.68). The prediction model demonstrated reasonable discrimination (area under the receiver operating characteristic curve: 0.68, 95% CI: 0.67-0.69) and overall performance (scaled Brier score: 0.10). The risk score was capable of stratifying patients into three distinct risk groups-high (64.05% readmitted or died), medium (45.77% readmitted or died), and low (29.30% readmitted or died).

CONCLUSIONS

Unplanned readmission or death is common amongst survivors of critical illness. The risk score presented here allows patients to be stratified by risk level, enabling targeted referral to preventative follow-up services.

The effects of a nurse-led discharge planning on the health outcomes of colorectal cancer patients with stomas: A randomized controlled trial

BACKGROUND

Nursing care of colorectal cancer patients with stomas presents unique challenges, particularly during the transition from hospital to home. Early discharge programs can assist patients during this critical period. However, the effects of delivering a nurse-led discharge planning program remain under-studied.

OBJECTIVE

Evaluate the effects of a nurse-led discharge planning on the quality of discharge education, stoma self-efficacy, readiness for hospital discharge, stoma quality of life, incidence of stoma complications, unplanned readmission rate, and length of stays.

DESIGN

Assessor-blind parallel-arm randomized controlled trial with a repeated-measures design.

SETTING(S)

Participants were recruited from inpatients in the colorectal surgery unit of a university-affiliated hospital in Fujian, China.

PARTICIPANTS

A total of 160 patients with colorectal cancer who received enterostomy surgery and were scheduled to be discharged to their homes.

METHOD

Participants were randomly allocated to the experimental and control groups. The former received nurse-led discharge planning in addition to the usual discharge education, while the control group received only the usual discharge education. The program included an assessment, health education, stoma care, stoma support, discharge review, discharge medication and checklist integration, discharge referral, and post-hospital follow-up. Baseline data were collected prior to the intervention (T0). Data on the quality of discharge teaching, readiness for hospital discharge, stoma self-efficacy, and stoma quality of life were measured on the day of discharge from the hospital (T1). Patients' stoma self-efficacy and quality of life were repeat-measured 30 (T2) and 90 days post-discharge (T3). Data on stoma complications (T1, T2, T3), length of stays (T1), and unplanned readmission (T2, T3) were collected from medical records.

RESULTS

Participants in the intervention group showed significant improvement in the quality of discharge teaching, readiness for hospital discharge, stoma self-efficacy, stoma quality of life, complications, and unplanned readmission, compared to the control group (p < 0.001). However, no statistically significant differences were observed in length of stays (p > 0.05).

CONCLUSIONS

The program was effective for improving quality of discharge teaching, readiness for hospital discharge, stoma self-efficacy, and stoma quality of life, as well as for reducing complications and unplanned readmission among stoma patients. Integration of discharge planning into the usual process of care is recommended for clinical practice to facilitate a successful transition from hospital to home.

REGISTRATION

This study was registered at the Chinese clinical trial registry (ChiCTR2200058756) on April 16, 2022, and participant recruitment was initiated in May 2022.

Generalizability of machine learning models predicting 30-day unplanned readmission after primary total knee arthroplasty using a nationally representative database

Unplanned readmission after primary total knee arthroplasty (TKA) costs an average of US $39,000 per episode and negatively impacts patient outcomes. Although predictive machine learning (ML) models show promise for risk stratification in specific populations, existing studies do not address model generalizability. This study aimed to establish the generalizability of previous institutionally developed ML models to predict 30-day readmission following primary TKA using a national database. Data from 424,354 patients from the ACS-NSQIP database was used to develop and validate four ML models to predict 30-day readmission risk after primary TKA. Individual model performance was assessed and compared based on discrimination, accuracy, calibration, and clinical utility. Length of stay (> 2.5 days), body mass index (BMI) (> 33.21 kg/m2), and operation time (> 93 min) were important determinants of 30-day readmission. All ML models demonstrated equally good accuracy, calibration, and discriminatory ability (Brier score, ANN = RF = HGB = NEPLR = 0.03; ANN, slope = 0.90, intercept =  - 0.11; RF, slope = 0.93, intercept =  - 0.12; HGB, slope = 0.90, intercept =  - 0.12; NEPLR, slope = 0.77, intercept = 0.01; AUCANN = AUCRF = AUCHGB = AUCNEPLR = 0.78). This study validates the generalizability of four previously developed ML algorithms in predicting readmission risk in patients undergoing TKA and offers surgeons an opportunity to reduce readmissions by optimizing discharge planning, BMI, and surgical efficiency.

Unplanned readmissions after hernia repair

INTRODUCTION

Several quality indices have been set up for evaluating the impact of the reduction of the length of stay (LOS), such as the 30-day unplanned readmission (UR30) rate. The main goal of our study was to analyze the UR30 following groin hernia repair (GHR), primary- (PVHR), and incisional ventral hernia repairs (IVHR).

METHODS

A French registry-based multicenter study was conducted using prospective data from all consecutive patients registered from 2015 to 2021.

RESULTS

The overall incidence of UR30 was 1.32%. This included 160/18,042 (0.87%) for GHR, 41/4012 (1.02%) for PVHR, and 145/3754 (3.86%) for IVHR. The leading cause of UR30 was postoperative complications (POC). The nature of the predominant complications varied among the three categories. The correlation between UR30 and POC (and risk factors for POC) was strong in GHR but was not in IVHR due to a 'protective' longer LOS in this subgroup. As the LOS has decreased over the last years, this has 'mechanically' resulted in an increase in the occurrence of UR30, but not in a rise of POC, neither in volume nor in severity. The reduction of LOS just shifted the problem from inpatient to outpatient settings.

CONCLUSION

Since the steady development of day-care surgery, the prevention of the UR not only hinges on the prevention of the POC but newly on a better organization of outpatient care which is currently a huge challenge due to a GPs' and nurses' shortage in France.

One-year unplanned readmission after total hip arthroplasty in patients with osteonecrosis of the femoral head: rate, causes, and risk factors

BACKGROUND

The primary objectives of this study were to focus on one - year unplanned readmissions after THA in ONFH patients and to investigate rates, causes, and independent risk factors.

METHODS

Between October 2014 and April 2019, eligible patients undergoing THA were enrolled and divided into unplanned readmission within one year and no readmission in this study. All unplanned readmissions within 1 year of discharge were reviewed for causes and the rate of unplanned readmissions was calculated. Demographic information, ONFH characteristics, and treatment-related variables of both groups were compared and analysed.

RESULTS

Finally, 41 out of 876 patients experienced unplanned readmission. The readmission rate was 1.83% in 30 days 2.63% in 90 days, and 4.68% in 1 year. Prosthesis dislocation was always the most common cause at all time points studied within a year. The final logistic regression model revealed that higher risks of unplanned readmission were associated with age > 60 years (P = 0.001), urban residence (P = 0.001), ARCO stage IV (P = 0.025), and smoking (P = 0.033).

CONCLUSIONS

We recommend the introduction of a strict smoking cessation program prior to surgery and the development of comprehensive management strategies, especially for the elderly and end-stage ONFH patients, and pay more attention to preventing prosthesis dislocation in the early days after surgery.

Causes and Predictors of Unplanned Readmission in Patients Undergoing Intracranial Tumor Resection: A Multicenter Analysis of 31,776 Patients

BACKGROUND

Although unplanned readmission is a postoperative outcome metric associated with significant morbidity and financial burden, precise assessment tools for its prediction have not yet been developed. The Risk Analysis Index (RAI) could potentially be used to help improve the prediction of unplanned readmissions for patients undergoing intracranial tumor resection (ITR). In the present study, we evaluate the predictive accuracy of frailty on 30-day unplanned readmission after ITR using the RAI.

METHODS

Data were obtained from the American College of Surgeons National Surgical Quality Improvement Program database. The baseline characteristics, preoperative clinical status, and outcomes were compared between patients with and without unplanned readmission. Frailty was calculated using the RAI. Univariate and multivariate logistic regression analyses were performed to identify independent associations between unplanned readmissions and patient characteristics.

RESULTS

The unplanned readmission rate for this cohort (n = 31,776) was 10.8% (n = 3420). Of the 3420 readmitted patients, 958 required unplanned reoperation. Multiple characteristics were significantly different between the 2 groups, including age, body mass index, comorbidities, and RAI groups (P < 0.05). The common causes of unplanned readmission included infection (9.4%), seizures (6%), and pulmonary embolism (4%). The patient characteristics identified as reliable predictors of unplanned readmission included age, body mass index, functional status, diabetes, hypertension, hyponatremia, and the patient's RAI score (P < 0.05). Frail status, hyponatremia, leukocytosis, hypertension, and thrombocytosis were significant predictors of unplanned readmissions.

CONCLUSIONS

The RAI is a reliable preoperative frailty index for predicting unplanned readmissions after ITR. Using the RAI could decrease unplanned readmissions by identifying high-risk patients and enabling future implementation of appropriate management guidelines.

Development of a prediction model for the risk of 30-day unplanned readmission in older patients with heart failure: A multicenter retrospective study

BACKGROUND AND AIM

Heart failure (HF) imposes significant global health costs due to its high incidence, readmission, and mortality rate. Accurate assessment of readmission risk and precise interventions have become important measures to improve health for patients with HF. Therefore, this study aimed to develop a machine learning (ML) model to predict 30-day unplanned readmissions in older patients with HF.

METHODS AND RESULTS

This study collected data on hospitalized older patients with HF from the medical data platform of Chongqing Medical University from January 1, 2012, to December 31, 2021. A total of 5 candidate algorithms were selected from 15 ML algorithms with excellent performance, which was evaluated by area under the operating characteristic curve (AUC) and accuracy. Then, the 5 candidate algorithms were hyperparameter tuned by 5-fold cross-validation grid search, and performance was evaluated by AUC, accuracy, sensitivity, specificity, and recall. Finally, an optimal ML model was constructed, and the predictive results were explained using the SHapley Additive exPlanations (SHAP) framework. A total of 14,843 older patients with HF were consecutively enrolled. CatBoost model was selected as the best prediction model, and AUC was 0.732, with 0.712 accuracy, 0.619 sensitivity, and 0.722 specificity. NT.proBNP, length of stay (LOS), triglycerides, blood phosphorus, blood potassium, and lactate dehydrogenase had the greatest effect on 30-day unplanned readmission in older patients with HF, according to SHAP results.

CONCLUSIONS

The study developed a CatBoost model to predict the risk of unplanned 30-day special-cause readmission in older patients with HF, which showed more significant performance compared with the traditional logistic regression model.

[Use of men's support underwear after elective scrotal surgery-a prospective, randomized assessment of postoperative complication rates and health-related quality of life : A prospective, randomized assessment of postoperative complication rates and health-related quality of life]

BACKGROUND

Elective scrotal surgery is associated with a high rate of postoperative complications. There is no specific recommendation for postoperative care.

AIM

We investigated whether support underwear has an impact on postoperative complications and quality of life.

MATERIALS AND METHODS

From July 2020 to November 2021, patients with prior elective scrotal surgery were randomized into the intervention group "support underwear" or the control group. In addition to patient characteristics, intraoperative and postoperative findings were documented. The primary endpoint comprised postoperative complications. Secondary endpoints were prolonged length of hospital stay, emergency visits, unplanned readmissions, increased use of analgesics, and quality of life, which was recorded using the EQ5D (European Quality of Life 5 Dimensions) questionnaire preoperatively, on day 1 and 4 weeks postoperatively.

RESULTS

Data from 50 patients were analyzed. The mean age was 46.7 years (standard deviation [SD] 18.6). Inguinal surgery with/without orchiectomy (52%), hydrocele resection (22%), or ligation of varicocele (14%) were performed most frequently. The mean operating time was 62.8 min (SD 35.2); length hospital stay was 2.6 days (SD 1.2). In all, 20% of the patients suffered a postoperative complication. Type of surgery was significantly associated with postoperative complications (p = 0.01) and unplanned readmission (p = 0.04). Regarding biometric and perioperative data, there were no significant differences between the interventional group (n = 27) and control group (n = 23).

CONCLUSION

A nonnegligible number of complications occurs after elective scrotal surgery. Complications affects quality of life up to 4 weeks after the surgery. Postoperative care with support underwear does not appear to affect the postoperative complication rate, but it positively influences the quality of life in patients with scrotal access.

Current status of unplanned readmission of neonates within 31 days after discharge from the neonatal intensive care unit and risk factors for readmission

OBJECTIVES

To investigate the current status of unplanned readmission of neonates within 31 days after discharge from the neonatal intensive care unit (NICU) and risk factors for readmission.

METHODS

A retrospective analysis was performed on the medical data of 1 561 infants discharged from the NICU, among whom 52 infants who were readmitted within 31 days were enrolled as the case group, and 104 infants who were not readmitted after discharge during the same period of time were enrolled as the control group. Univariate analysis and multivariate logistic regression analysis were performed to identify the risk factors for readmission.

RESULTS

Among the 1 561 infants, a total of 63 readmissions occurred in 52 infants, with a readmission rate of 3.33%. hyperbilirubinemia and pneumonia were the main causes for readmission, accounting for 29% (18/63) and 24% (15/63) respectively. The multivariate logistic regression analysis showed that that gestational age <28 weeks, birth weight <1 500 g, multiple pregnancy, mechanical ventilation, and length of hospital stay <7 days were risk factors for readmission (OR=5.645, 5.750, 3.044, 3.331, and 1.718 respectively, P<0.05).

CONCLUSIONS

Neonates have a relatively high risk of readmission after discharge from the NICU. The medical staff should pay attention to risk factors for readmission and formulate targeted intervention measures, so as to reduce readmission and improve the quality of medical service.

Frequency, Risk Factors, and Outcomes of Unplanned Readmission to the Neurological Intensive Care Unit after Spontaneous Intracerebral Hemorrhage

BACKGROUND

Unplanned readmission to the neurological intensive care unit (ICU) is an underinvestigated topic in patients admitted after spontaneous intracerebral hemorrhage (ICH). The purpose of this study is to investigate the frequency, clinical risk factors, and outcome of bounce back to the neurological ICU in a cohort of patients admitted after ICH.

METHODS

This is a retrospective observational study inspecting bounce back to the neurological ICU in patients admitted with spontaneous ICH over an 8-year period. For each patient, demographics, medical history, clinical presentation, length of ICU stay, unplanned readmission to neurological ICU, cause of readmission, and mortality were reviewed. Bounce back to the neurological ICU was defined as an unplanned readmission to the neurological ICU from a general floor service during the same hospitalization. A multivariable analysis was used to define independent variables associated with bounce back to the neurological ICU as well as association between bounce back to the neurological ICU and mortality. The significance level was set at p < 0.05.

RESULTS

A total of 221 patients were included. Among those, 20 (9%) had a bounce back to the neurological ICU. Respiratory complications (n = 11) was the most common reason for bounce back to the neurological ICU, followed by neurological (n = 5) and cardiological (n = 4) complications. In a multivariable logistic regression, location of hemorrhage in the basal ganglia (odds ratio [OR]: 3.0, 95% confidence interval [CI]: 1.0-8.9, p = 0.03) and dysphagia at the time of transfer (OR: 3.9, 95% CI: 1.0-15.4, p = 0.04) were significantly associated with bounce back to the neurological ICU. After we controlled for ICH score, readmission to the ICU was also independently associated with higher mortality (OR: 14.1, 95% CI: 2.8-71.7, p < 0.01).

CONCLUSIONS

Bounce back to the neurological ICU is not an infrequent complication in patients with spontaneous ICH and is associated with higher hospital length of stay and mortality. We identified relevant and potentially modifiable risk factors associated with bounce back to the neurological ICU. Future prospective studies are necessary to develop patient-centered strategies that may improve transition from the neurological ICU to the general floor.

The impact of unplanned readmission]

Unplanned readmissions after lung cancer surgery impair normal postoperative recovery and are associated with increased postoperative mortality. The objective of this review was to compile a detailed and comprehensive dataset on unplanned readmissions after pulmonary resection so as to better understand the associated factors and how they may be attenuated. Based on the identified risk factors, prevention involves improved preoperative preparation of at-risk patients and preoperative discharge planning so as to help prevent unscheduled readmissions, which are predictive of a poorer prognosis.

Sacrectomy for sacral tumors: perioperative outcomes in a large-volume comprehensive cancer center

BACKGROUND CONTEXT

Sacral tumors are incredibly rare lesions affecting fewer than one in every 10,000 persons. Reported perioperative morbidity rates range widely, varying from 30% to 70%, due to the relatively low volumes seen by most centers. Factors affecting perioperative outcome following sacrectomy remain ill-defined.

PURPOSE

To characterize perioperative outcomes of sacral tumor patients undergoing sacrectomy and identify independent risk factors of perioperative morbidity STUDY DESIGN/SETTING: Retrospective cohort study at a single comprehensive cancer center PATIENT SAMPLE: Consecutively treated sacral tumor patients (primary or metastatic) undergoing sacrectomy for oncologic resection between April 2013 and April 2020 OUTCOME MEASURES: Perioperative complications, hospital length of stay, non-home discharge, 30-day readmission, and 30-day reoperation METHODS: Details were gathered about tumor pathology and morphology, surgery performed, baseline medical comorbidities, preoperative lab data, and patient demographics. Stepwise multivariable regressions were conducted to identify independent risk factors of perioperative outcomes while evaluating predictive accuracy.

RESULTS

57 sacral tumor patients were included (mean age 55.5±13.0 years; 60% female). The complication, non-home discharge, 30-day readmission, and 30-day reoperation rates were 39%, 56%, 16%, and 14%, respectively. Independent predictors of perioperative complications included ASA>2 (OR=10.7; 95%CI [1.3, 86.0]; p=0.026), radicular pain (OR=10.9; p=0.014), platelet count (OR=0.989 per 10³/μL; p=0.049), and instrumentation (OR=10.7; p=0.009). Independent predictors of length of stay included iliac vessel involvement (β=15.8; p=0.005), larger tumor volume (β=0.027 per cm³; p<0.001), a staged procedure (β=10.0; p=0.018), and S1 nerve root sacrifice (OR=15.8; p=.011). The optimal model predictive of non-home discharge included bilateral S3-S5 or higher nerve root sacrifice (OR=3.9; p=0.054), instrumentation (OR=8.6; p=0.005), and vertical rectus abdominis musculocutaneous flap closure (OR=5.3; p=0.067). 30-day readmission was independently predicted by history of chronic kidney disease (OR=26.7; p=0.021), radicular pain (OR=8.1; p=0.039), and preoperative saddle anesthesia (OR=12.6; p=0.026). All multivariable models achieved good discrimination (AUC>0.8 and R²>0.7).

CONCLUSION

Clinical and operative factors were important predictors of complications and 30-day readmission, while tumor-related and operative factors accounted for most of the variability in length of stay and non-home discharge.

Risk Factors for 30-Day Unplanned Readmission After Hepatectomy: Analysis of 438 Pediatric Patients from the ACS-NSQIP-P Database

BACKGROUND

Hepatic resections are uncommon in children. Most studies reporting complications of these procedures and risk factors associated with unplanned readmissions are limited to retrospective data from single centers. We investigated risk factors for 30-day unplanned readmission after hepatectomy in children using the American College of Surgeons National Surgical Quality Improvement-Pediatric database.

METHODS

The database was queried for patients aged 0-18 years who underwent hepatectomy for the treatment of liver lesions from 2012 to 2018. Chi-squared tests were performed to evaluate for potential risk factors for unplanned readmissions. A multivariate regression analysis was performed to identify independent predictors for unplanned 30-day readmissions.

RESULTS

Among 438 children undergoing hepatectomy, 64 (14.6%) had unplanned readmissions. The median age of the hepatectomy cohort was 1 year (0-17); 55.5% were male. Patients readmitted had significantly higher rates of esophageal/gastric/intestinal disease (26.56% vs. 14.97%; p=0.022), current cancer (85.94% vs. 75.67%; p=0.012), and enteral and parenteral nutritional support (31.25% vs. 17.65%; p=0.011). Readmitted patients had significantly higher rates of perioperative blood transfusion (67.19% vs. 52.41%; p=0.028), organ/space surgical site infection (10.94% vs. 1.07%; p<.001), sepsis (15.63% vs. 3.74%; p<.001), and total parenteral nutrition at discharge (9.09% vs. 2.66%; p=0.041). Organ/space surgical site infection was an independent risk factor for unplanned readmission (OR=9.598, CI [2.070-44.513], p=0.004) by multivariable analysis.

CONCLUSION

Unplanned readmissions after liver resection are frequent in pediatric patients. Organ/space surgical site infections may identify patients at increased risk for unplanned readmission. Strategies to reduce these complications may decrease morbidity and costs associated with unplanned readmissions.

Impact of mild cognitive impairment on unplanned readmission in patients with coronary artery disease

AIMS

To investigate the effect of mild cognitive impairment (MCI) on unplanned readmission in patients with coronary artery disease (CAD).

METHODS AND RESULTS

From 2132 CAD patients, MCI was estimated with the Japanese version of the Montreal Cognitive Assessment (MoCA-J) in 243 non-dementia patients who met the study criteria. The primary outcome was unplanned hospital readmission after discharge. The incidence of MCI in this cohort was 33.3%, and 51 patients (21.0%) had unplanned readmission during a mean follow-up period of 418.6 ± 203.5 days. After adjusting for the covariates, MCI (hazard ratio, 2.28; 95% confidence interval: 1.09-4.76; P = 0.03) was independently associated with unplanned readmission in the multivariable Cox proportional hazard regression analysis. In the Kaplan-Meier analysis, the cumulative incidence of unplanned readmission for the MCI group was significantly higher than that for the non-MCI group (log-rank test, P < 0.001). Even after exclusion of the patients readmitted within 30 days of discharge, the main results did not change (log-rank test, P < 0.001).

CONCLUSION

Mild cognitive impairment was independently associated with unplanned readmission after adjustment for many independent variables in CAD patients. In addition to its short-term effects, the adverse effects of MCI had a persistent, long-term impact on CAD patients. Assessment of cognitive function should be conducted by health professionals prior to hospital discharge and during follow-up. To prevent readmission of CAD patients, it will be necessary to support solutions to the problems that inhibit secondary prevention behaviours based on the assessment of the patients' cognitive function.

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

BACKGROUND

Early 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.

METHODS

We 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).

RESULTS

In 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).

CONCLUSIONS

Our 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.

The effect of patient age on discharge destination and complications after lumbar spinal fusion

Age is an important patient characteristic that has been correlated with specific outcomes after lumbar spine surgery. We performed a retrospective cohort study to model the effect of age on discharge destination and complications after a 1-level or multi-level lumbar spine fusion surgery. The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database was used to identify patients who underwent lumbar spinal fusion surgery from 2013 through 2017. Perioperative outcomes were compared across ages 18 to 90 using multivariable nonlinear logistic regressioncontrolling for preoperative characteristics. A total of 61,315 patients were analyzed, with patients over 70 having a higher risk of being discharged to an inpatient rehabilitation center and receiving an intraoperative or postoperative blood transfusion. However, the rates of the other complications and outcomes analyzed in this study were not significantly different as patients age. In conclusion, advanced-age affects the discharge destination after a one- or multi-level fusion and intraoperative/postoperative blood transfusion after a one-level fusion. However, age alone does not significantly affect the risk of the other complications and outcomes assessed in this study. This study will help guide preoperative discussion with advanced-aged patients who are considering a 1-level or multi-level lumbar spine fusion surgery.

Unplanned readmission and survival after video-assisted thoracic surgery and open thoracotomy in patients with non-small-cell lung cancer: a 12-month nationwide cohort study

OBJECTIVES

To compare outcomes at 12 months between video-assisted thoracic surgery (VATS) and open thoracotomy (OT) in patients with non-small-cell lung cancer (NSCLC) using real-world evidence.

METHODS

We did a nationwide propensity-matched cohort study. We included all patients who had a diagnosis of NSCLC and who benefitted from lobectomy between 1 January 2015 and 31 December 2017. We divided this population into 2 groups (VATS and OT) and matched them using propensity scores based on patients' and hospitals' characteristics. Unplanned readmission, mortality, complications, length of stay and hospitalization costs within 12 months of follow-up were compared between the 2 groups.

RESULTS

A total of 13 027 patients from 180 hospitals were included, split into 6231 VATS (47.8%) and 6796 OT (52.2%). After propensity score matching (5617 patients in each group), VATS was not associated with a lower risk of unplanned readmission compared with OT [20.7% vs 21.9%, hazard ratio 1.03 (0.95-1.12)] during the 12-months follow-up. Unplanned readmissions at 90 days were mainly due to pulmonary complications (particularly pleural effusion and pneumonia) and were associated with higher mortality at 12 months (13.4% vs 2.7%, P < 0.0001).

CONCLUSIONS

VATS and OT were both associated with high incidence of unplanned readmissions within 12 months, requiring a better identification of prognosticators of unplanned readmissions. Our study highlights the need to improve prevention, early diagnosis and treatment of pulmonary complications in patients with VATS and OT after discharge. These findings call for improving the dissemination of systematic perioperative care pathway including efficient pulmonary physiotherapy and rehabilitation.

Causes and Predictors of Unplanned Readmission in Cranial Neurosurgery

OBJECTIVE

A better understanding of the risks and reasons for unplanned readmission is an essential component in reducing costs in the health care system and in optimizing patient safety and satisfaction. The reasons for unplanned readmission vary between different disciplines and procedures. The aim of this study was to identify reasons for readmission in view of different diagnoses in cranial neurosurgery.

METHODS

In this single-center retrospective study, adult patients after neurosurgical treatment were analyzed and grouped according to the indication based on International Classification of Diseases and Related Health Problems, Tenth Revision, German Modification diagnosis codes. The main outcome measure was unplanned readmission within 30 days of discharge. Further logistic regression models were performed to identify factors associated with unplanned rehospitalization.

RESULTS

Of the 2474 patients analyzed, 183 underwent unplanned rehospitalization. Readmission rates differed between the diagnosis groups, with 9.19% in neoplasm, 8.26% in hydrocephalus, 5.76% in vascular, 6.13% after trauma, and 8.05% in the functional group. Several causes were considered to be preventable, such as wound healing disorders, seizures, or social reasons. Younger age, length of first stay, surgical treatment, and side diagnoses were predictors for unplanned readmission. Diagnoses with an increased risk of readmission were glioblastoma, traumatic subdural hematoma, or chronic subdural hematoma.

CONCLUSIONS

Reasons and predictors for an unplanned readmission differ considerably among the index diagnosis groups. In addition to well-known reasons for readmission, we identified social indication, meaning a lack of home care, which is particularly prevalent in oncologic and elderly patients. A transitional care program could benefit these vulnerable patients.

Early unplanned readmission of neurosurgical patients after treatment of intracranial lesions: a comparison between surgical and non-surgical intervention group

Background

Recent health care policy making has highlighted the necessity for understanding factors that influence readmission. To elucidate the rate, reason, and predictors of readmissions in neurosurgical patients, we analyzed unscheduled readmissions to our neurosurgical department after treatment for cranial or cerebral lesions.

Methods

From 2015 to 2017, all adult patients who had been discharged from our Department of Neurosurgery and were readmitted within 30 days were included into the study cohort. The patients were divided into a surgical and a non-surgical group. The main outcome measure was unplanned inpatient admission within 30 days of discharge.

Results

During the observation period, 183 (7.4%) of 2486 patients had to be readmitted unexpectedly within 30 days after discharge. The main readmission causes were surgical site infection (34.4 %) and seizure (16.4%) in the surgical group, compared to natural progression of the original diagnosis (38.2%) in the non-surgical group. Most important predictors for an unplanned readmission were younger age, presence of malignoma (OR: 2.44), and presence of cardiovascular side diagnoses in the surgical group. In the non-surgical group, predictors were length of stay (OR: 1.07) and the need for intensive care (OR: 5.79).

Conclusions

We demonstrated that reasons for readmission vary between operated and non-operated patients and are preventable in large numbers. In addition, we identified treatment-related partly modifiable factors as predictors of unplanned readmission in the non-surgical group, while unmodifiable patient-related factors predominated in the surgical group. Further patient-related risk adjustment models are needed to establish an individualized preventive strategy in order to reduce unplanned readmissions.

Electronic supplementary material

The online version of this article (10.1007/s00701-020-04521-4) contains supplementary material, which is available to authorized users.

Clinical risk model to predict 28-day unplanned readmission via the accident and emergency department after discharge from acute psychiatric units for patients with psychotic spectrum disorders

BACKGROUND

Unplanned readmissions rates are an important indicator of the quality of care provided in a psychiatric unit. However, there is no validated risk model to predict this outcome in patients with psychotic spectrum disorders.

AIMS

This paper aims to establish a clinical risk prediction model to predict 28-day unplanned readmission via the accident and emergency department after discharge from acute psychiatric units for patients with psychotic spectrum disorders.

METHOD

Adult patients with psychotic spectrum disorders discharged within a 5-year period from all psychiatric units in Hong Kong were included in this study. Information on the socioeconomic background, past medical and psychiatric history, current discharge episode and Health of the Nation Outcome Scales (HoNOS) scores were used in a logistic regression to derive the risk model and the predictive variables. The sample was randomly split into two to derive (n = 10 219) and validate (n = 10 643) the model.

RESULTS

The rate of unplanned readmission was 7.09%. The risk factors for unplanned readmission include higher number of previous admissions, comorbid substance misuse, history of violence and a score of one or more in the discharge HoNOS overactivity or aggression item. Protective factors include older age, prescribing clozapine, living with family and relatives after discharge and imposition of conditional discharge. The model had moderate discriminative power with a c-statistic of 0.705 and 0.684 on the derivation and validation data-set.

CONCLUSIONS

The risk of readmission for each patient can be identified and adjustments in the treatment for those with a high risk may be implemented to prevent this undesirable outcome.

Spine surgeon specialty differences in single-level percutaneous kyphoplasty

Background

Percutaneous kyphoplasty (PKP) is a procedure performed by a spine surgeon who undergoes either orthopedic or neurosurgical training. The relationship between short-term adverse outcomes and spine specialty is presently unknown. To compare short-term adverse outcomes of single-level PKP when performed by neurosurgeons and orthopedic surgeons in order to develop more concretely preventive strategies for patients under consideration for single-level PKP.

Methods

We evaluated patients who underwent single-level PKP from 2012 to 2014 through the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP). We used univariate analysis and multivariate logistic regression to assess the association between spine surgeon specialty and short-term adverse events, including postoperative complication and unplanned readmission, and to identify different independent risk predictors between two specialties.

Results

Of 2248 patients who underwent single-level PKP procedure, 1229 patients (54.7%) had their operations completed by a neurosurgeon. There were no significant differences in the development of the majority of postoperative complications and the occurrence of unplanned readmission between the neurosurgical cohort (NC) and the orthopedic cohort (OC). A difference in the postoperative blood transfusion rate (0.7% NS vs. 1.7% OC, P = 0.039) was noted and may due to the differences in comorbidities between patients. Multivariate regression analysis revealed different independent predictors of postoperative adverse events for the two spine specialties.

Conclusions

By comparing a large range of demographic feature, preoperative comorbidities, and intraoperative factors, we find that short-term adverse events in single-level PKP patients does not affect by spine surgeon specialty, except that the OC had higher postoperative blood transfusion rate. In addition, the different perioperative predictors of postoperative complications and unplanned readmissions were identified between the two specialties. These findings can lead to better evidence-based patient counseling and provide valuable information for medical evaluation and potentially devise methods to reduce patients’ risk.

Patient-related risk factors for unplanned 30-day readmission following total knee arthroplasty: a protocol for a systematic review and meta-analysis

BACKGROUND

Osteoarthritis is a debilitating condition as well as a growing global health problem, and total knee arthroplasty is an effective treatment for advanced stages of disease. Unplanned 30-day hospital readmission is an indicator of complications, which is a significant financial burden on healthcare systems. The objective is to perform a systematic review of patient-related factors associated with unplanned 30-day readmission following total knee arthroplasty. This information will inform future strategies to improve health outcomes after knee arthroplasty surgery.

METHODS

MEDLINE and EMBASE will be systematically searched using a comprehensive search strategy. Studies of higher quality than case series will be included, in order to optimise the quality of the findings of this review. We will include studies reporting on patient-related risk factors for unplanned 30-day readmission following primary or revision total knee arthroplasty for any indication. Case series will be excluded, as will studies reporting exclusively on intraoperative, clinician, hospital, and health system risk factors. The reference lists of selected papers will then be screened for any additional literature. Two reviewers will independently apply stringent eligibility criteria to titles, abstracts, and full texts of studies identified in the literature search. They will then extract data from the final list of selected papers according to an agreed-upon taxonomy and vocabulary of the data to be extracted. Assessment of risk of bias and quality of evidence will then take place. Finally, the effect size of each identified risk factor will be determined; meta-analysis will be performed where adequate data is available.

DISCUSSION

The findings of this review and subsequent meta-analysis will aid clinicians as they seek to understand the risk factors for 30-day readmission following total knee arthroplasty. Clinicians and patients will be able to use this information to align expectations of the postoperative course, which will enhance the recovery process, and aid in the development of strategies to mitigate identified risks. Another purpose of this review is to assist policy-makers in developing quality indicators for care and provide insights into the drivers of health costs.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42019118154.

Risk factors for early unplanned readmission in patients with bipolar disorder: A retrospective observational study

OBJECTIVES

Evidence regarding the relationships between patient, hospital, and regional factors and early unplanned readmission (short-term outcome) in patients with bipolar disorder is lacking. This study aimed to examine risk factors associated with early unplanned readmission in patients with bipolar disorder.

METHOD

We retrospectively analyzed adult bipolar patients (ICD-10; F31) between April 2012 and March 2014 in the Japanese Diagnosis Procedure Combination database. We examined factors affecting the 30-day unplanned readmission using multivariable logistic regression analysis.

RESULTS

A total of 2688 patients admitted to psychiatric beds were included. Multivariate analysis showed that unchanged or exacerbation discharge outcome (adjusted odds ratio [aOR]: 1.93; 95% confidence interval [CI]: 1.06-3.51, p = 0.031), unplanned or urgent admission settings (aOR: 1.51; 95% CI: 1.00-2.26, p = 0.048), physical comorbidity (chronic pulmonary disease) (aOR: 4.74; 95% CI: 1.30-17.29, p = 0.018), presence of psychiatric acute-care beds (aOR: 1.72; 95% CI: 1.02-2.87, p = 0.040), and intermediate-level hospital psychiatric staffing (aOR: 1.82; 95% CI: 1.14-2.91, p = 0.012) were significantly associated with higher early unplanned readmission, while higher density of psychiatrists in the area (aOR: 0.50; 95% CI: 0.29-0.87, p = 0.014) was significantly associated with lower early unplanned readmission.

CONCLUSIONS

The results suggest that not only careful management of high-risk patients but also consideration of functional differentiation in psychiatric inpatient care, psychiatric resource allocation, and follow-up support for patients with bipolar disorder are needed for reducing the early unplanned readmission rate.

Risk factors associated with 31-day unplanned readmission in 50,912 discharged patients after stroke in China

BACKGROUND

Unplanned readmission within 31 days of discharge after stroke is a useful indicator for monitoring quality of hospital care. We evaluated the risk factors associated with 31-day unplanned readmission of stroke patients in China.

METHODS

We identified 50,912 patients from 375 hospitals in 29 provinces, municipalities or autonomous districts across China who experienced an unplanned readmission after stroke between 2015 and 2016, and extracted data from the inpatients' cover sheet data from the Medical Record Monitoring Database. Patients were grouped into readmission within 31 days or beyond for analysis. Chi-squared test was used to analyze demographic information, health system and clinical process-related factors according to the data type. Multilevel logistic modeling was used to examine the effects of patient (level 1) and hospital (level 2) characteristics on an unplanned readmission ≤31 days.

RESULTS

Among 50,912 patients, 14,664 (28.8%) were readmitted within 31 days after discharge. The commonest cause of readmissions were recurrent stroke (34.8%), hypertension (22.94%), cardio/cerebrovascular disease (13.26%) and diabetes/diabetic complications (7.34%). Higher risks of unplanned readmissions were associated with diabetes (OR = 1.089, P = 0.001), use of clinical pathways (OR = 1.174, P < 0.001), and being discharged without doctor's advice (OR = 1.485, P < 0.001). Lower risks were associated with basic medical insurances (OR ranging from 0.225 to 0.716, P < 0.001) and commercial medical insurance (OR = 0.636, P = 0.021), compared to self-paying for medical services. And patients aged 50 years old and above (OR ranging from 0.650 to 0.985, P < 0.05), with haemorrhagic stroke (OR = 0.467, P < 0.001), with length of stay more than 7 days in hospital (OR ranging from 0.082 to 0.566, P < 0.001), also had lower risks.

CONCLUSIONS

Age, type of stroke, medical insurance status, type of discharge, use of clinical pathways, length of hospital stay and comorbidities were the most influential factors for readmission within 31 days.

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

BACKGROUND

Admitted 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.

METHODS

A 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.

RESULTS

The 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).

CONCLUSION

Aboriginal 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.

The impact of telephone follow up on adverse events for Aboriginal people with chronic disease in new South Wales, Australia: a retrospective cohort study

BACKGROUND

Chronic diseases are more prevalent and occur at a much younger age in Aboriginal people in Australia compared with non-Aboriginal people. Aboriginal people also have higher rates of unplanned hospital readmissions and emergency department presentations. There is a paucity of research on the effectiveness of follow up programs after discharge from hospital in Aboriginal populations. This study aimed to assess the impact of a telephone follow up program, 48 Hour Follow Up, on rates of unplanned hospital readmissions, unplanned emergency department presentations and mortality within 28 days of discharge among Aboriginal people with chronic disease.

METHODS

A retrospective cohort of eligible Aboriginal people with chronic diseases was obtained through linkage of routinely-collected health datasets for the period May 2009 to December 2014. The primary outcome was unplanned hospital readmissions within 28 days of separation from any acute New South Wales public hospital. Secondary outcomes were mortality, unplanned emergency department presentations, and at least one adverse event (unplanned hospital readmission, unplanned emergency department presentation or mortality) within 28 days of separation. Logistic regression models were used to assess outcomes among Aboriginal patients who received 48 Hour Follow Up compared with eligible Aboriginal patients who did not receive 48 Hour Follow Up.

RESULTS

The final study cohort included 18,659 patients with 49,721 separations, of which 8469 separations (17.0, 95% confidence interval (CI): 16.7-17.4) were recorded as having received 48 Hour Follow Up. After adjusting for potential confounders, there were no significant differences in rates of unplanned readmission or mortality within 28 days between people who received or did not receive 48 Hour Follow Up. Conversely, the odds of an unplanned emergency department presentation (Odds ratio (OR) = 0.92; 95% CI: 0.85, 0.99; P = 0.0312) and at least one adverse event (OR = 0.91; 95% CI: 0.85,0.98; P = 0.0136) within 28 days were significantly lower for separations where the patient received 48 Hour Follow Up compared with those that did not receive follow up.

CONCLUSIONS

Receipt of 48 Hour Follow Up was associated with both a reduction in emergency department presentations and at least one  adverse event within 28 days of discharge, suggesting there may be merit in providing post-discharge telephone follow up to Aboriginal people with chronic disease.

Decreasing readmissions by focusing on complications and underlying reasons

BACKGROUND

To analyze demographics and outcomes of patients focusing on 30-day readmission status and identify procedure-specific risk factors.

METHODS

Patients undergoing abdominal colorectal surgery (2011-2013) were identified Demographics and outcomes including in-hospital complications were compared based on readmission status.

RESULTS

A total of 6637 patients were identified with a mean age of 51.2(±17.1) years. Seven hundred and seventy five(11.7%) patients were readmitted at least once within 30-day. The most common index procedures related to readmission were stoma closure (n = 127/775, 16.4%) and total colectomy (n = 105/775, 13.6%). Readmitted patients had longer length of index hospital stay (LOS)(8.2 ± 5.9 vs 7.9 ± 6.9 days,p < 0.001) and operative time(167 ± 104 vs 144 ± 95 min, p < 0.001), higher intraoperative(2% vs 1%,p = 0.04) and in-hospital complication rates(36% vs 28%,p < 0.001). Main reasons for readmissions were gastrointestinal-related causes(n = 222, 29%), small bowel obstruction (n = 133,17%), wound-related complications(n = 108,14%), and dehydration(n = 93,12%). Median readmission LOS was 4(1-71)days and 54%(n = 407) of readmissions occurred within 7 days of discharge.

CONCLUSION

Increased postoperative complications may be the main preventable underlying reason for increased risk of hospital readmission after colorectal surgery. Preventive measures to decrease complications and actions to identify high risk patients for complications would help to reduce readmissions.

Short-Term Adverse Outcomes After Deep Brain Stimulation Treatment in Patients with Parkinson Disease

BACKGROUND

Despite ongoing progress in our understanding of long-term outcomes after neuromodulation procedures, acute adverse outcomes shortly after deep brain stimulation (DBS) treatment have remained remarkably limited.

OBJECTIVE

To identify risk factors associated with acute 30-day outcomes after DBS treatment in patients with Parkinson disease (PD).

METHODS

We evaluated patients who underwent DBS treatment for PD from 2005 to 2014 through the American College of Surgeons National Surgical Quality Improvement Program database. We used bivariate analysis and multivariate logistic regression to identify short-term postoperative outcomes, including 30-day complication, discharge destination, and unplanned readmission.

RESULTS

Overall, 650 patients with PD underwent DBS procedures and complications were identified in 32 patients (4.9%). Of 481 patients who had complete discharge data, 18 patients (3.7%) were discharged to a facility and 16 patients (3.3%) experienced an unplanned readmission. Patients with PD who were obese (P = 0.045), who had preoperative anemia (P = 0.008), and who experienced longer operative durations (P = 0.01) had increased odds of postoperative complications. Inpatient status (P = 0.001), dependent functional status (P < 0.001), and anemia (P = 0.043) were all associated with discharge to a facility other than home. Longer operative duration (P = 0.013), anemia (P = 0.036), and dependent functional status (P = 0.03) were significantly associated with unplanned readmission. As expected, complications increased the likelihood of unplanned readmission (P < 0.001).

CONCLUSIONS

This study provides individualized estimates of the risks associated with short-term adverse outcomes based on patient demographics and comorbidities. These data can be used as an adjunct for short-term risk stratification of patients with PD being considered for DBS treatment.

Impact of socio-economic status on unplanned readmission following injury: A multicenter cohort study

BACKGROUND

Unplanned readmissions cost the US economy approximately $17 billion in 2009 with a 30-day incidence of 19.6%. Despite the recognised impact of socio-economic status (SES) on readmission in diagnostic populations such as cardiovascular patients, its impact in trauma patients is unclear. We examined the effect of SES on unplanned readmission following injury in a setting with universal health insurance. We also evaluated whether additional adjustment for SES influenced risk-adjusted readmission rates, used as a quality indicator (QI).

STUDY DESIGN

We conducted a multicenter cohort study in an integrated Canadian trauma system involving 56 adult trauma centres using trauma registry and hospital discharge data collected between 2005 and 2010. The main outcome was unplanned 30-day readmission; all cause, due to complications of injury and due to subsequent injury. SES was determined using ecological indices of material and social deprivation. Odds ratios of readmission and 95% confidence intervals adjusted for covariates were generated using multivariable logistic regression with a correction for hospital clusters. We then compared a readmission QI validated previously (original QI) to a QI with additional adjustment for SES (SES-adjusted QI) using the mean absolute difference.

RESULTS

The cohort consisted of 52,122 trauma admissions of which 6.5% were rehospitalised within 30 days of discharge. Compared to patients in the lowest quintile of social deprivation, those in the highest quintile had a 20% increase in the odds of all-cause unplanned readmission (95% CI=1.06-1.36) and a 27% increase in the odds of readmission due to complications of injury (95% CI=1.04-1.54). No association was observed for material deprivation or for readmissions due to subsequent injuries. We observed a strong agreement between the original and SES-adjusted readmission (mean absolute difference= 0.04%).

CONCLUSIONS

Patients admitted for traumatic injury who suffer from social deprivation have an increased risk of unplanned rehospitalisation due to complications of injury in the 30 days following discharge. Better discharge planning or follow up for such patients may improve patient outcome and resource use for trauma admissions. Despite observed associations, results suggest that the trauma QI based on unplanned readmission does not require additional adjustment for SES.

Early unplanned hospital readmission after acute traumatic injury: the experience at a state-designated level-I trauma center

BACKGROUND

There is limited literature on early unplanned hospital readmission after acute traumatic injury, especially at suburban facilities.

METHODS

A retrospective review of the trauma registry at a suburban, state-designated, level-I academic trauma center from July 2009 to June 2012 was performed for all admitted (≥24 hours) adult (age ≥18 years) trauma patients who were discharged alive, including unplanned readmissions within 30 days of discharge.

RESULTS

Of 3,622 admitted adult trauma patients, 6.57% were readmitted at a median of 9 days. Major surgery was required in 15.9% patients on readmission. The mortality rate at readmission was 4.6%. Multiple factors were associated with readmission on univariate analysis; however, on multivariate analysis, only major comorbidities (odds ratio [OR], 1.53), hospital length of stay (OR, 1.01), abdominal Abbreviated Injury Score greater than or equal to 3 (OR, 2.10), and discharge to a skilled nursing facility or subacute facility (OR, 1.56) were significant predictors. Meanwhile, index admission to surgical services was associated with a significantly lower readmission risk (OR, .60).

CONCLUSIONS

Trauma patients are infrequently readmitted. Index admission to a surgical service reduces the risk of readmission. Earlier medical follow-up should be considered.