Predictors Of Unplanned Readmission Research Articles

A Multicenter Study of Unplanned Hospital Readmissions after Transsphenoidal Surgery for Cushing's Disease

Abstract Objectives Patients undergoing surgery for Cushing's disease may be more likely to be readmitted to the hospital than other patients with pituitary disorders. We investigated rates, causes, and predictors of unplanned readmission following transsphenoidal surgery for Cushing's disease to identify areas for clinical, financial, and administrative improvements. Design Retrospective cohort study. Setting Academic pituitary centers in the United States participating in a multicenter surgical outcome registry. Participants Five hundred and nineteen patients underwent transsphenoidal surgery for treatment of Cushing's disease by 26 surgeons at nine participating institutions from 2003 to 2023. Main Outcome Measures Unplanned 90-day readmission rates and causes of readmission. Results Unplanned readmissions occurred in 57/519 patients (11.0%), with hyponatremia in 12/57 (21%), cerebrospinal fluid leak evaluation in 8/57 (14%), epistaxis in 6/57 (10%), deep vein thrombosis in 4/57 (7%), syncope in 3/57 (5%), and headache in 3/57 (5%). Factors including no tumor on initial magnetic resonance imaging, return to the operating room during the index admission, lack of early remission, and inpatient complications were associated with a greater probability of readmission on univariate analysis. However, none remained predictive on multivariate analysis. Conclusion Our results show that readmission rates after transsphenoidal surgery for Cushing's disease are comparable to previously reported rates for all pituitary-related disorders, with the most common reason being hyponatremia. High-impact clinical protocols focused on preventing delayed hyponatremia may reduce the risk of readmission. Failure to identify significant predictors of readmission, even in this large clinical dataset, underscores the challenge of identifying high-risk clinical cohorts.

Health-related quality of life is a predictor of readmission following emergency laparotomy.

Health-related quality of life (HRQoL) is a multidimensional concept used to examine the impact of patient-perceived health status on quality of life. Patients' perception of illness affects outcomes in both medical and elective surgical patients; however, not much is known about how HRQoL effects outcomes in the emergency surgical setting. This study aimed to examine if patient-reported HRQoL was a predictor of unplanned readmission after emergency laparotomy. This study included 215 patients who underwent emergency laparotomy at the Copenhagen University Hospital, Herlev, between August 1, 2021, and July 31, 2022. Patient-reported HRQoL was assessed with the EuroQol group EQ5D index (EQ5D5L descriptive system and EQ-VAS). The population was followed from 0 to 180days after discharge, and readmissions and days alive and out of hospital were registered. A Cox proportional hazard model was used to examine HRQoL and the risk of readmission within 30 and 180days. Within 30days, 28.4% of patients were readmitted; within 180days, the number accumulated to 45.1%. Low self-evaluated HRQoL predicted 180-day readmission and was significantly associated with fewer days out of hospital within both 90 and 180days. Low HRQoL and discharge with rehabilitation were independent risk factors for short- (30-day) and long-term (180-day) emergency readmission. Patient-perceived quality of life is an independent predictor of 180-day readmission, and the number of days out of hospital was correlated to self-reported HRQoL.

Unplanned Readmissions and Long-Term Mortality Risk After Incident Heart Failure Hospitalisation in Western Australia, 2001-2015.

To investigate the frequency and predictors of unplanned readmissions after incident heart failure (HF) hospitalisation and the association between readmissions and mortality over two years. We performed a retrospective cohort study using Western Australian morbidity and mortality data to identify all patients, aged 25-94 years, who survived an incident (first-ever) HF hospitalisation (principal diagnosis) between 2001-2015. Ordinal logistic regression models determined the covariates independently associated with unplanned readmission(s). Cox proportional hazards models with time-varying exposures determined the hazard ratios (HR) of one or more readmissions for mortality over two years after incident HF. Of 18,693 patients, 53.4% male, mean age 74.4 (standard deviation [SD] 13.6) years, 61.3% experienced 32,431 unplanned readmissions (39.7% cardiovascular-related) within two years. Leading readmission causes were HF (19.1%), respiratory diseases (12.6%), and ischaemic heart disease (9.6%). All-cause death occurred in 27.2% of the cohort, and the multivariable-adjusted mortality HR of 1 (versus 0) readmission was 2.5 (95% confidence interval [CI], 2.3-2.7) increasing to 5.0 (95% CI, 4.7-5.4) for 2+ readmissions. The adjusted mortality HR of 1 and 2+ (versus 0) HF-specific readmission was 2.0 (95% CI, 1.8-2.1) and 3.6 (95% CI, 3.2-3.9), respectively. Coexistent cardiovascular and other comorbidities were independently associated with increased readmission and mortality risk. This study underlines the high burden of recurrent unplanned cardiovascular and other readmissions within two years after incident HF hospitalisation, and their additive adverse impact on mortality. Integrated multidisciplinary management of concomitant comorbidities, in addition to HF-targeted treatments, is necessary to improve long-term prognosis in HF patients.

Emergent readmission and long-term mortality risk after incident atrial fibrillation hospitalisation

ObjectiveTo assess the frequency and predictors of unplanned readmissions after hospitalisation for incident atrial fibrillation (AF) and the association of readmissions with mortality over 2 years.MethodsWe performed a retrospective cohort...

Nationwide Readmission Rates and Hospital Charges for Patients With Surgical Evacuation of Nontraumatic Subdural Hematomas: Part 1-Craniotomy.

Despite patients experiencing high recurrence and readmission rates after surgical management of nontraumatic subdural hematomas (SDHs), few studies have examined the causes and predictors of unplanned readmissions in this population on a national scale. To analyze independent factors predicting 30-day hospital readmissions after surgical treatment of nontraumatic SDH in patients who survived their index surgery and evaluate hospital readmission rates and charges. Using the Nationwide Readmissions Database, we identified patients who underwent craniotomy for nontraumatic SDH evacuation (2010-2015) using a retrospective cohort observational study design. National estimates and variances within the cohort were calculated after stratifying, hospital clustering, and weighting variables. Among 49 013 patients, 10 643 (21.7%) had at least 1 readmission within 30 days of their index treatment and 38 370 (78.3%) were not readmitted. Annual readmission rates did not change during the study period ( P = .74). The most common primary causes of 30-day readmissions were recurrent SDH (n = 3949, 37.1%), venous thromboembolism (n = 1373, 12.9%), and delayed hyponatremia and syndrome of inappropriate antidiuretic hormone secretion (n = 1363, 12.8%). Comorbidities that independently predicted readmission included congestive heart failure, chronic obstructive pulmonary disease, coagulopathy, diabetes mellitus, liver disease, lymphoma, fluid and electrolyte disorders, metastatic cancer, peripheral vascular disease, psychosis, and renal failure ( P ≤ .03). Household income in the 51st to 75th percentile was associated with a decreased risk of readmission. National trends in 30-day readmission rates after nontraumatic SDH treatment by craniotomy provide quality benchmarks that can be used to drive quality improvement efforts on a national level.

306 Nationwide Readmission Rates and Costs for Patients With Surgical Evacuation of Nontraumatic Subdural Hematomas: Part 1—Craniotomy

INTRODUCTION: Despite patients experiencing high recurrence and readmission rates after surgical management of nontraumatic subdural hematomas (SDHs), few studies have examined the causes and predictors of unplanned readmissions in this population on a national scale. METHODS: Using the Nationwide Readmissions Database, we identified patients who underwent craniotomy for nontraumatic SDH evacuation (2010-2015) using a retrospective cohort observational study design. National estimates and variances within the cohort were calculated after stratifying, hospital clustering, and weighting variables. RESULTS: Among 49,013 patients, 10,643 (21.7%) had at least 1 readmission within 30 days of their index treatment and 38,370 (78.3%) were not readmitted. Annual readmission rates did not change during the study period (P = 0.74). The most common primary causes of 30-day readmissions were recurrent SDH (37.1%), venous thromboembolism (12.9%), and delayed hyponatremia and SIADH (syndrome of inappropriate antidiuretic hormone secretion) (12.8%). Comorbidities that independently predicted readmission included congestive heart failure, chronic obstructive pulmonary disease, coagulopathy, diabetes mellitus, liver disease, lymphoma, fluid and electrolyte disorders, metastatic cancer, peripheral vascular disease, psychosis, and renal failure (P = 0.03). Household income in the 51st-75th percentile was associated with a decreased risk of readmission. CONCLUSION: National trends in 30-day readmission rates after nontraumatic SDH treatment via craniotomy provide quality benchmarks that can be used to drive quality improvement efforts on a national level.

Predictors of Unplanned Readmissions Among Patients With Substance Use Disorders

ABSTRACT Objective: The objective of this study was to evaluate predictors of unplanned readmission to a specialized hospital addiction unit within less than 30 days, between 30 and 60 days and over 60 days post-discharge among individuals with a diagnosis of substance use disorder. Methods: Cox proportional hazards regressions were used to test the effects of potential risk factors on time-to-onset for unplanned readmissions. The outcome (survival time) was the length of time to hospital readmission and the predictors were age, sex, duration of the first hospital stay, Health of Nation Outcome Scales score and Brief Symptom Check List. Results: Of the 750 readmissions analyzed for the reported period 28.0% took place in less than 30 days, 12.0% between 30 and 60 days and 60.0% after 60 days of discharge. Length of the first hospitalization was a statistically significant predictor of readmission between 30 and 60 days and over 60 days but not for less than 30 days. A 10% increase in length of the first hospitalization, holding all other variables constant, was associated with a 5.0% decrease in unplanned readmissions occurring between 30 and 60 days and a 2.2% decrease in readmissions over 60 days post-discharge. Conclusion: Length of the first hospitalization was found to be a protective factor of readmission between 30 and 60 days and over 60 days but not for less than 30 days post-discharge. The longer the duration of the first hospitalization, the less quickly patients were readmitted to hospital. Objectif: L’objectif de cette étude était d’évaluer les prédicteurs de réadmissions non planifiées dans une unité hospitalière spécialisée en addiction en moins de 30 jours, entre 30 et 60 jours et plus de 60 jours après leur sortie chez les personnes ayant un diagnostic de trouble lié à l’utilisation de substances (TUS). Méthode: Les régressions des risques proportionnels de Cox ont été utilisées pour tester les effets des facteurs de risques potentiels sur le temps reliés aux réadmissions non planifiées. Le pronostic (durée de survie) était la durée jusqu’à la réadmission à l’hôpital et les vérifiables étaient l’âge, le sexe, la durée du premier séjour à l’hôpital, le score des résultats du Health of Nation Outcome Scales (HoNOS-F) et la liste de contrôle des symptômes du Brief Symptom Check List (BSCL). Résultats: Sur les 750 réadmissions analysées pour la période rapportée, 28,0% ont eu lieu en moins de 30 jours, 12,0% entre 30 et 60 jours et 60,0% après 60 jours de congé. La durée de la première hospitalisation était une variable prédictive statistiquement significative pour les réadmissions entre 30 et 60 jours et les plus de 60 jours, mais pas pour les moins de 30 jours. Une augmentation de 10% de la durée de la première hospitalisation, en maintenant toutes les autres variables constantes, a été associée avec une diminution de 5,0% des réadmissions imprévues survenant entre 30 et 60 jours et une diminution de 2,2% des réadmissions plus de 60 jours après la libération. Conclusions: La durée de la première hospitalisation s’est avérée être un facteur de protection contre une réadmission entre 30 et 60 jours et au-delà de 60 jours mais pas pour les moins de 30 jours après la libération. Plus la durée de la première hospitalisation est longue, moins les patients sont réadmis rapidement à l’hôpital.

Abstract TP184: Urban-rural Influence On Readmission After Acute Ischemic Stroke In Younger Adults

Introduction: Complications and mortality after ischemic stroke are higher in rural areas. Identifying predictors of readmission is important, especially for younger patients who represent a growing share of new strokes, but studies differ in how they define rurality. Hypothesis: There is an association between urban-rural influence and readmission after acute ischemic stroke among younger adults, and this association depends on how urban-rural influence is defined. Methods: Data from the AHRQ State Inpatient Databases for ischemic stroke survivors aged 19-64 years during 2012-2014 were analyzed for six states: Arkansas, Florida, Georgia, Maryland, New Mexico, and Washington. In-state hospitalization within 30 days of discharge was deemed a readmission, excluding admissions for rehabilitation, psychiatry, or cancer treatment. A four-level urban influence code was used as the patient location variable. To further explore the impact of how rurality was defined, this variable was dichotomized three ways: large metropolitan vs. all others, metropolitan vs. non-metropolitan, and rural vs. all others. Chi-square tests were used to determine if planned and unplanned readmission were associated with each urban-rural variable to determine which variables to advance to multivariable analysis. Logistic regression models were then fitted for both planned and unplanned readmission, using the large metropolitan variable and adjusting for length of stay of the first hospitalization, age, race, sex, payer type, and number of chronic conditions. Results: Patients who lived in a large metropolitan area compared to those who did not had 0.885 (95% CI: 0.697, 1.122) times the odds of planned readmission when controlling for covariates; however, this difference was not statistically significant. The odds of unplanned readmission, however, were 1.071 times higher (95% CI: 1.004, 1.142) if the patient lived in a large metropolitan area compared to those who did not, controlling for covariates. Conclusions: Urban residence can be described as an independent predictor of unplanned readmission for younger adult ischemic stroke survivors. However, researchers should be attentive to the impact of how urban-rural influence is operationalized.

73 High Cost and Resource Utilization of Frostbite Readmissions

Abstract Introduction Frostbite is a high morbidity, high-cost injury that can lead to digit or limb necrosis requiring amputation. Our primary aim is to describe the rate of readmission following frostbite injury. Our secondary aims are to describe the overall burden of care, cost, and characteristics of repeat hospitalizations of frostbite-injured people. Methods Index hospitalizations and readmissions were identified in the 2016 and 2017 Nationwide Readmission Database. Weighted incidence and characteristics of readmissions associated with frostbite injury were calculated and adjusted for by using survey weight, sampling clusters, and stratum. Multivariable logistic regression was clustered by hospital and additionally adjusted for severe frostbite injury, gender, year, payor group, severity, and comorbidity index. Results The unplanned readmission rate following frostbite injury was 35.4% (95% CI 32.2 – 38.6%). In the two-year cohort, 1,065 index hospitalizations resulted in 1,907 total hospitalizations following frostbite injury. Most patients were male (80.3%), lived in metropolitan/urban areas (82.3%), and nearly half were insured with Medicaid (46.4%). Of the 842 readmissions, 53.7% were associated with complications typically associated with frostbite injury. Overall, 29% of frostbite injuries resulted in at least one amputation. The average total cost and total LOS of readmissions was $236,872 and 34.7 days. Drug or alcohol abuse, homelessness, Medicaid insurance, and discharge AMA were independent predictors of unplanned readmission. Factors associated with multiple readmissions include discharge AMA and Medicare Insurance, but not drug or alcohol abuse or homelessness. Conclusions This is the first study examining readmissions following frostbite injury on a national level. Drug or alcohol abuse, homelessness, Medicaid insurance, and discharge AMA were independent predictors of unplanned readmission, while only AMA discharge and Medicare insurance were associated with multiple readmissions.

Causes and Predictors of Unplanned Readmission in Cranial Neurosurgery

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. 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. 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. 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.

Predischarge Prediction of Readmission After Cytoreductive Surgery and Hyperthermic Intraperitoneal Chemotherapy: Derivation and Validation of a Risk Prediction Score

BackgroundNinety-day hospital readmission rates following cytoreductive surgery and hyperthermic intraperitoneal chemotherapy (CRS/HIPEC) range from 20 to 40%.ObjectiveThe aim of this study was to develop and validate a simple score to predict readmissions following CRS/HIPEC.Study DesignUsing a prospectively maintained database, we retrospectively reviewed clinicopathologic, perioperative, and day-of-discharge data for patients undergoing CRS/HIPEC for peritoneal surface malignancies between 2010 and 2018. In-hospital mortalities and discharges to hospice were excluded. Multivariate logistic regression was utilized to identify predictors of unplanned readmission, with three-quarters of the sample randomly selected as the derivation cohort and one-quarter as the validation cohort. Using regression coefficient-based scoring methods, we developed a weighted 7-factor, 10-point predictive score for risk of readmission.ResultsOverall, 1068 eligible discharges were analyzed; 379 patients were readmitted within 90 days (35.5%). Seven factors were associated with readmission: stoma creation, Peritoneal Cancer Index score ≥ 15, hyponatremia, in-hospital major complication, preoperative chemotherapy, anemia, and discharge to nursing home. In the validation cohort, 25 patients (9.2%) were categorized as high risk for readmission, with a predicted rate of readmission of 69.3% and an observed rate of 76.0%. The score had fair discrimination (area under the curve 0.70) and good calibration (Hosmer–Lemeshow goodness-of-fit p-value of 0.77).ConclusionOur proposed risk score, easily obtainable on day of discharge, distinguishes patients at high risk for readmission over 90 days following CRS/HIPEC. This score has the potential to target high-risk individuals for intensive follow-up and other interventions.

Pattern and Predictors of Unplanned Readmission in Patients After Index Hospitalisation for AF in Western Australia, 2001–2015

Hospitalisations constitute the majority of the cost burden associated with atrial fibrillation (AF). Therefore, understanding the pattern and predictors of unplanned readmissions after AF hospitalisation is important.

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

BackgroundRecent 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.MethodsFrom 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.ResultsDuring 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).ConclusionsWe 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.

Factors associated with unplanned readmissions within 1 day of acute care discharge: a retrospective cohort study

BackgroundUnplanned hospital readmissions are a quality and safety indicator. In Australian, 8% to 11.1% of unplanned readmissions occur ≤1 day of acute care discharge. The aim of this study was to explore the reasons for unplanned hospital readmissions ≤1 day of acute care discharge, and determine what proportion of such unplanned hospital readmissions were potentially preventable.MethodsA retrospective exploratory cohort design was used to conduct this two phase study. In Phase 1, organisational data from 170 readmissions ≤1 day and 1358 readmissions between 2 and 28 days were compared using the Cochran-Mantel-Haenszel test. Binary logistic regression was used to examine factors associated with unplanned readmission ≤1 day. In Phase 2, a medical record audit of 162 Phase 1 readmissions ≤1 day was conducted and descriptive statistics used to summarise the study data. Index discharges occurred between 1 August and 31 December 2015.ResultsIn Phase 1, unplanned readmissions ≤1 day were more likely in paediatric patients (< 0.001); index discharges on weekends (p = 0.006), from short stay unit (SSU) (p < 0.001) or against health professional advice (p = 0.010); or when the readmission was for a Diagnosis Related Group (p < 0.001). The significant predictors of unplanned readmission ≤1 day were index discharge against advice or from SSU, and 1–5 hospital admissions in the 6 months preceding index admission.In Phase 2, 88.3% readmissions were unpreventable and 11.7% were preventable. The median patient age was 57 years and comorbidities were uncommon (3.1%). Most patients (94.4%) lived at home and with others (78.9%). Friday was the most common day of index discharge (17.3%) and Saturday was the most common day of unplanned readmission (19.1%). The majority (94.4%) of readmissions were via the emergency department: 58.5% were for a like diagnosis and pain was the most common reason for readmission.ConclusionsAdvanced age, significant comorbidities and social isolation did not feature in patients with an unplanned readmission ≤1 day. One quarter of patients were discharged on a Friday or weekend, one quarter of readmissions occurred on a weekend, and pain was the most common reason for readmission raising issues about access to services and weekend discharge planning.

Postoperative Complications Predict 30-Day Readmission in Geriatric General Surgery Patients

The Affordable Care Act has placed unplanned patient readmissions under more scrutiny than ever. Geriatric patients, in particular, suffer a disproportionate amount of complications from any kind of hospitalization, including readmissions. This study seeks to identify risk factors in this population that predispose them to an unplanned readmission within 30 days after index surgery. The National Surgical Quality Improvement Program database was used to select patients 65 years and older, who underwent general surgery procedures in 2012. Patient demographics, comorbidities, complications, and readmissions were analyzed. A Cox regression survivorship model was used for multivariate analysis. A total of 7712 patients were reviewed; 617 patients (8.0%) had an unplanned readmission within 30 days of their operation. Cox regression revealed five different independent predictors of unplanned readmission within 30 days. They are age [P = 0.009, hazard ratio (HR) = 1.016, 95% confidence interval (CI) = 1.01-1.03], American Society of Anesthesiologists Class >2 (P = 0.037, HR = 1.22, CI = 1.024-1.475), operation time (minutes) (P = 0.001, HR = 1.001, CI = 1.00-1.002), any complication (P = 0.03, HR = 1.449, CI = 1.33-1.852), and deep vein thrombosis (P = 0.03, HR = 1.87, CI = 1.31-3.85). Using Cox regression to adjust for patient length of stay, age, American Society of Anesthesiologists class, any complication, operation time, and venous thromboembolism all independently increased the rate of unplanned readmissions. Patients who suffer any complication or a venous thromboembolism postoperatively are at a particularly high risk of readmission. These patients should be targeted for increased inpatient monitoring and included in preventable readmission programs after discharge.

Rates and risk factors of unplanned 30-day readmission following general and thoracic pediatric surgical procedures

Background/PurposePostoperative unplanned readmissions are costly and decrease patient satisfaction; however, little is known about this complication in pediatric surgery. The purpose of this study was to determine rates and predictors of unplanned readmission in a multi-institutional cohort of pediatric surgical patients. MethodsUnplanned 30-day readmissions following general and thoracic surgical procedures in children <18 were identified from the 2012–2014 National Surgical Quality Improvement Program- Pediatric. Time-dependent rates of readmission per 30 person–days were determined to account for varied postoperative length of stay (pLOS). Patients were randomly divided into 70% derivation and 30% validation cohorts which were used for creation and validation of a risk model for readmission. ResultsReadmission occurred in 1948 (3.6%) of 54,870 children for a rate of 4.3% per 30 person–days. Adjusted predictors of readmission included hepatobiliary procedures, increased wound class, operative duration, complications, and pLOS. The predictive model discriminated well in the derivation and validation cohorts (AUROC 0.710 and 0.701) with good calibration between observed and expected readmission events in both cohorts (p>.05). ConclusionsUnplanned readmission occurs less frequently in pediatric surgery than what is described in adults, calling into question its use as a quality indicator in this population. Factors that predict readmission including type of procedure, complications, and pLOS can be used to identify at-risk children and develop prevention strategies. Level of evidenceIII.

Predictors of Unplanned Readmission for Adults Undergoing Elective Lumbar Spine Fusion

Predictors of Unplanned Readmission for Adults Undergoing Elective Lumbar Spine Fusion

Readmission after percutaneous coronary intervention: an important clinical outcome?—60-day readmission rate after percutaneous coronary intervention: predictors and impact on long-term outcomes

Readmission to hospital after percutaneous coronary intervention (PCI) is a common problem which results in a significant burden to healthcare systems as well as an adverse outcome for patients.1 Thirty-day readmission rates have been identified as a quality metric for a wide variety of medical conditions and procedures, including PCI, and there is now significant interest in understanding why it happens and how it might be avoided. In this issue, researchers from a metropolitan Italian centre studied 60-day readmission rates after PCI with a focus on understanding the predictors of unplanned readmission and its impact on long-term outcomes. Although the authors chose a 60-day time frame, rather than the conventional 30-day period, the manuscript draws attention to an important unwanted event after PCI that has not received the same attention as unplanned readmission after heart failure and myocardial infarction. It is now timely that the factors associated with unplanned readmission after PCI are understood and scrutinized. The study by Moretti and co-workers2 presents data from an observational cohort of 1193 patients, of whom 71 (6.0%) had unplanned 60-day readmissions. Consistent with prior studies,3 the authors demonstrated that the reasons for readmission were varied but not often directly related to procedural complications. More … [↵][1]*Corresponding author. Tel: +44 02037658712, Fax: +44 02035943209, Email: andrew.wragg{at}bartshealth.nhs.uk [1]: #xref-corresp-1-1

MP63-19 PREDICTORS OF READMISSION FOLLOWING OPEN AND MINIMALLY INVASIVE PARTIAL NEPHRECTOMY USING THE NATIONAL SURGICAL QUALITY IMPROVEMENT PROGRAM (NSQIP) DATABASE

You have accessJournal of UrologyKidney Cancer: Surgical Therapy IV1 Apr 2015MP63-19 PREDICTORS OF READMISSION FOLLOWING OPEN AND MINIMALLY INVASIVE PARTIAL NEPHRECTOMY USING THE NATIONAL SURGICAL QUALITY IMPROVEMENT PROGRAM (NSQIP) DATABASE Ahmed Serhan and Ahmad Shabsigh Ahmed SerhanAhmed Serhan More articles by this author and Ahmad ShabsighAhmad Shabsigh More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2015.02.2351AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Post-operative readmissions have a significant impact on the health care cost. They reflect the quality of care and the complexity of our patients. Our objective is to define the rates and the predictors of unplanned readmissions following open and minimally invasive partial nephrectomy for renal tumors. METHODS We performed a retrospective review of prospectively collected database (NSQIP) of all patients who underwent open and minimally invasive partial nephrectomy between 2005 and 2012. Patient's demographics, unplanned readmission rate and its causes were reported. Multivariate analysis was performed to characterize predictors of readmission. RESULTS Between 2005 and 2012, a total of 4872 cases were identified. 2137 patients (43.9%) underwent open partial nephrectomy (OPN) while 2735 patients (56.1%) were managed through minimally invasive partial nephrectomy (MPN). Unplanned readmissions were significantly lower in MPN group (2.1% vs. 3.5%, P= 0.008). For OPN patients, pneumonia, sepsis, wound disruption and deep venous thrombosis were the most common causes of readmission. For MPN group, sepsis was the most common contributor. Logistic regression analysis was performed to define the predictors of readmission. For open partial nephrectomy, bleeding necessitating blood transfusion (OR 1.454, 95%CI: 1.031-2.050, P=0.03), >10% loss of body weight in last 6 months (OR 7.482, 95% CI: 1.918 - 29.190, P= 0.004) were the significant predictors, while Diabetes was near significant predictor (OR 1.818, 95%, CI: 0.965 - 3.425, P=0.064). For MPN, operative time (OR 1.005, 95%, CI: 1.002 - 1.008, P=0.003), and bleeding necessitating blood transfusion (OR 1.908, 95%, CI: 1.184 - 3.076, P= 0.008) were the only significant predictors. CONCLUSIONS In addition to preservation of kidney function and shorter hospital stay, MPN appears to have a lower rate of readmission. Predictors of readmission vary between different treatment options and selection of treatment should be based on general condition as well as tumor characteristics. © 2015 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 193Issue 4SApril 2015Page: e796-e797 Advertisement Copyright & Permissions© 2015 by American Urological Association Education and Research, Inc.MetricsAuthor Information Ahmed Serhan More articles by this author Ahmad Shabsigh More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

MP81-19 PREDICTORS OF READMISSION FOLLOWING OPEN AND MINIMALLY INVASIVE SACRAL COLPOPEXY USING THE NATIONAL SURGICAL QUALITY IMPROVEMENT PROGRAM (NSQIP) DATABASE

You have accessJournal of UrologyUrodynamics/Incontinence/Female Urology: Female Urology1 Apr 2015MP81-19 PREDICTORS OF READMISSION FOLLOWING OPEN AND MINIMALLY INVASIVE SACRAL COLPOPEXY USING THE NATIONAL SURGICAL QUALITY IMPROVEMENT PROGRAM (NSQIP) DATABASE Ahmed Sarhan, Ahmad Shabsigh, and Ketul Shah Ahmed SarhanAhmed Sarhan More articles by this author , Ahmad ShabsighAhmad Shabsigh More articles by this author , and Ketul ShahKetul Shah More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2015.02.2897AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Post-operative readmissions have a significant impact on the health care cost. They reflect the quality of care and the complexity of our patients. Our objective is to define the rates and the predictors of unplanned readmissions following open (OSC) and minimally invasive sacral colpopexy (MISC). METHODS We performed a retrospective review of prospectively collected database (NSQIP) of all patients who underwent open and minimally invasive sacral colpopexy between 2005 and 2012. Patient's demographics, unplanned readmission rate and its causes were reported. Multivariate analysis was performed to characterize predictors of readmission. RESULTS Between 2005 and 2012, a total of 1520 cases were identified. Data regarding readmission rates and possible causes of readmission was available for 2011 and 2012 dataset. Between 2011 and 2012, 1049 underwent sacral colpopexy. 386 patients (36.8%) underwent open sacral colpopexy (OSC) while 663 patients (63.2%) were managed through minimally invasive sacral colpopexy (MISC). Unplanned readmission and reoperation rates were comparable between the two groups (2.3% vs. 3.3%, P= 0.24 and 1.6% vs. 1.8%, P= 0.49 respectively). For both groups, postoperative ileus was the most common causes of readmission but it was significantly higher in OSC group accounting for 44.4% of total readmissions in OSC and 9.1% for MISC group (P= 0.043), other common causes for readmission in OSC group were surgical site infection (11.1 %) and pulmonary embolism (11.1 %). For MISC, other common causes of readmission were postoperative fever (9 %) and unspecified abdominal pain (4.5%). %). Logistic regression analysis was performed to define the predictors of readmission. For OSC, preoperative blood urea nitrogen (BUN) was the only significant predictor for OSC (OR 1.4, 95% CI 1.05-1.87, P= 0.02) while for MISC preoperative serum albumin was the only significant predictor (OR 0.17, 95% CI 0.04-0.67, P= 0.012) and hypertension was near significant predictor (OR 4.5, 95% CI 0.86-23.87, P=0.75). CONCLUSIONS Both OSC and MISC have comparable readmission and reoperation rates. Predictors of readmission vary between different treatment options and selection of approach should be based on general condition as well as local factors. © 2015 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 193Issue 4SApril 2015Page: e1036 Advertisement Copyright & Permissions© 2015 by American Urological Association Education and Research, Inc.MetricsAuthor Information Ahmed Sarhan More articles by this author Ahmad Shabsigh More articles by this author Ketul Shah More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...