The Surgical Revolving Door: Risk Factors for Hospital Readmission

A multicenter, citywide report on recurrent violent injury

INTRODUCTION

The incidence of and risk factors for recurrent violent trauma are not well known. This information is needed to focus violence prevention efforts on at-risk cohorts. The purpose of this study was to determine the incidence of and risk factors for recurrence following violent injury in a large urban setting. We hypothesize that the overall incidence of recurrent violent injury is low but there are specific at-risk cohorts.

METHODS

A retrospective, citywide study of patients who sustained blunt assault or penetrating trauma from 2013 to 2019 was performed. Patients were tracked across all trauma centers using their name and date of birth. The primary outcome was incidence of recurrent violent injury, which was calculated by dividing the number of readmitted patients by the number who survived previous admissions due to penetrating trauma or blunt assault. Associations between readmission and injury severity score, abbreviated injury score, age, sex, hospital, mechanism of injury (MOI), and disposition were determined. Kaplan-Meier curves were plotted to determine the incidence of recurrent injury over time. A multivariable Cox proportional hazard model was used to examine the relationships between characteristics at first admission and time-to-readmission.

RESULTS

The recurrent injury rate was 836 patients (6.33%) out of 13,211 injured patients. Male, age 14-45 years old, discharge to jail or left against medical advice, and moderate/severe head injury were associated with re-injury. There was no association between recurrence and mechanism of injury or overall injury severity. Discharge to home was associated with a lower re-injury rate.

CONCLUSION

The low recurrent injury rate despite high injury prevalence suggests injury prevention efforts should target this demographic and their non-injured peers.

Incidence and predictive factors of problems after fixation of trochanteric hip fractures with sliding hip screw or intramedullary devices

INTRODUCTION

Hip fractures are common and disabling injuries, usually managed surgically. The most common type outside the joint capsule are trochanteric fractures, usually fixed with either sliding hip screw or intramedullary nail. Data are available in the National Hip Fracture Database (NHFD) on early failure and other major complications, but late or subtler complications may escape recording. This study sought to quantify such problems after fixation performed at 3different sites and identify their predictors.

METHODS

Patients with a trochanteric fracture treated at 1 of 3 sites were identified from the NHFD over a 3-year period. Any with further, related episodes of care were identified, and reasons recorded, then age- and sex-matched with those with no such episodes. Data was collected on Arbeitsgemeinschaft für Osteosynthesefragen classification, tip-apex distance, American Society of Anesthesiologists (ASA) grade, Abbreviated Mental Test Score and pre-injury mobility. The cohorts were compared, and a binomial logistic regression model used to identify predictors of problems.

RESULTS

A total of 4010 patients were entered in the NHFD across 3 sites between January 2013 and December 2015. Of these, 1260 sustained trochanteric fractures and 57 (4.5%) subsequently experienced problems leading to re-presentation. The most common was failure of fixation, occurring in 22 patients (1.7%). The binomial logistic regression model explained 47.6% of the variance in incidence of postoperative problems with ASA grade and tip-apex distance being predictive.

DISCUSSION

The incidence of re-presentation with problems was around of 5%. A failure rate of less than 2% was seen, in keeping with existing data. This study has quantified the incidence of subtler postoperative problems and identified their predictors. The type of implant used was not amongst them and patients with both implants experienced problems. Fixation continues to yield imperfect results, but patient health and robust surgical technique remain important factors in a good outcome.

The Association Between Early Versus Late Physical Therapy Initiation and Outcomes of Trauma Patients With and Without Traumatic Brain Injuries

BACKGROUND

There is a lack of literature regarding the most effective timing to initiate physical therapy (PT) among traumatically injured patients. We aim to evaluate the association between early PT/mobilization versus delayed or late PT/mobilization and clinical outcomes of trauma patients.

METHODS

A retrospective cohort analysis of an urban level-I trauma center from 2014 to 2019 was performed. Univariate analyses and multivariable logistic regression were performed with significance defined as P < 0.05.

RESULTS

A total of 11,937 patients were analyzed. Among patients without a traumatic brain injury (TBI), late PT initiation times were associated with 60% lower odds of being discharged home without services (P < 0.05), significantly increased hospital and ICU length of stay (H-LOS, ICU-LOS) (P < 0.05), and significantly higher odds of complications (VTE, pneumonia, pressure ulcers, ARDS) (P < 0.001). Among patients with a TBI, late PT initiation time had 76% lower odds of being discharged home without services (P < 0.05) and significantly longer H-LOS and ICU-LOS (P < 0.05) however did not experience significantly higher odds of complications (P > 0.05).

CONCLUSIONS

Among traumatically injured patients, early PT is associated with decreased odds of complications, shorter H-LOS and ICU-LOS, and a favorable discharge disposition to home without services. Adoption of early PT initiation/mobilization protocols and establishment of prophylactic measures against complications associated with delayed PT is critical to maximize quality of care and trauma patient outcomes. Multi-center prospective studies are needed to ascertain the impact of PT initiation times in greater detail and to minimize trauma patient morbidity.

Musculoskeletal injury survivors' resiliency: A systematic review

BACKGROUND

Musculoskeletal traumas are on the rise in the United States; however, limited studies are available to help trauma providers assess and treat concerns beyond the physical impact. Little is understood about the psychological, social, and spiritual factors that protect patients from adverse effects after a physical trauma or their experiences with each factor afterward.

OBJECTIVE

This systematic review was conducted to investigate and review advancements in research related to risk and resiliency factors experienced by survivors of traumatic musculoskeletal injuries. The use of biopsychosocial-spiritual (BPS-S) framework and resiliency theory guided the analysis.

METHODS

Researchers reviewed 1003 articles, but only seven met the search criteria. Due to the complexity and uniqueness of traumatic brain injuries, studies on that target population were excluded.

RESULTS

Of the seven articles reviewed, three identified psychological protective factors that protect against negative health outcomes; three identified negative psychological, social, or spiritual outcomes; and none investigated social or spiritual health.

CONCLUSIONS

There are significant gaps in the literature surrounding risk and resiliency factors related to the BPS-S health of musculoskeletal injury survivors.

Incidence and Cost of Deep Vein Thrombosis in Emergency General Surgery Over 15 Years

BACKGROUND

Deep vein thromboses (DVTs) are a significant sequela of surgery and are associated with significant of morbidity and mortality in the United States. Operative emergency general surgery (EGS) cases have been demonstrated to have a greater burden of DVT than other types of surgery.

MATERIALS AND METHODS

DVT in EGS cases were identified from the National Inpatient Sample-Healthcare Cost and Utilization Project database from 2001 to 2015 Q3 based on ICD-9 code specification. National incidence of DVT in EGS was calculated using the National Inpatient Sample-Healthcare Cost and Utilization Project sampling methodology, and propensity score matching was used to assess costs associated with DVT.

RESULTS

Among 15,148,352 sample-weighted hospitalizations, 0.623% (94,392) experienced DVT. Incidence of DVT was greatest in GI ulcer surgery (1.705%) and lowest in appendectomy (0.095%). Patients with a perioperative DVT incurred $22,301 more in hospital-related costs than their counterparts who did not have a DVT. Although rates of DVT remained stable over the period analyzed, DVT-associated costs increased at a 2.09% annual rate in excess of inflation during the period analyzed. This increase in costs was most significant for laparotomy, which increased at a rate of 8.09% annually.

CONCLUSIONS

DVT continues to be a significant burden on resources in EGS in spite of efforts with DVT prophylaxis. Considering the increase in costs and little change in incidence, further research on cost-effective management of DVT in EGS is warranted.

Postoperative Anemia Predicts Length of Stay for Geriatric Patients Undergoing Minimally Invasive Lumbar Spine Fusion Surgery

Introduction:

We hypothesize that postoperative anemia will predict length of stay (LOS) for geriatric patients undergoing minimally invasive (MIS) lumbar spine fusions.

Materials and Methods:

Patients who underwent MIS lateral and transforaminal lumbar interbody fusion between January 2017 and March 2018 at an academic tertiary care referral center were selected. Eighty-one patients were included. The primary outcome variable was LOS, measured in days. The predictors studied were preoperative hemoglobin (Hgb), postoperative day 1 Hgb, postoperative nadir Hgb, intraoperative Hgb decrement (preoperative Hgb-postoperative day 1 Hgb), perioperative Hgb decrement (preoperative Hgb-postoperative nadir Hgb), age, American Society of Anesthesiologists–Physical Status (ASA-PS) score, volume of perioperative intravenous (IV) fluids (IVFs), and number of levels fused. Simple linear regression and analysis of variance were used for statistical analysis.

Results:

In the present study, preoperative anemia was not associated with longer LOS (P = .15). Postoperative anemia was associated with longer LOS as both postoperative day 1 Hgb (P = .05*) and postoperative nadir Hgb (P < .0001*) predicted longer LOS. Greater intraoperative Hgb decrement did not predict longer LOS (P = .36); however, greater perioperative Hgb decrement predicted longer LOS (P < .0001*). Older age (P = .01*) and greater number of levels fused (P = .03*) predicted longer LOS; however, a greater ASA-PS classification did not predict longer LOS. Greater IVF administration was associated with longer LOS (P < .0001*).

Discussion:

Postoperative nadir Hgb (P < .0001*) was more predictive of longer LOS than postoperative day 1 Hgb (P = .05*). There is a perioperative Hgb decrement associated with longer LOS (P < .0001*). Geriatric patients may be more susceptible to the potential contributors to Hgb decrement, including occult bleeding post-op and hemodilution from IVF administration.

Conclusion:

Postoperative anemia, perioperative decrement in Hgb, older age, greater number of levels fused, and greater total IVFs administered predict longer LOS. Understanding the impact of these factors on LOS is critical as these procedures increasingly move to the outpatient setting.

Risk factors associated with unplanned readmission following excisional haemorrhoidectomy

AIM

Excisional haemorrhoidectomy is the gold standard for management of advanced symptomatic haemorrhoids. Although an effective treatment, it is associated with significant postoperative morbidity with pain, bleeding and a high readmission rate. This study seeks to investigate potential risk factors that may predict unplanned 30-day readmissions following excisional haemorrhoidectomy.

METHOD

A retrospective cohort review of all haemorrhoidectomies performed at Counties Manukau District Health Board, Auckland, New Zealand, between January 2012 and December 2017 was performed. Baseline demographic data, readmission data and potential variables for readmission were recorded. Univariate and multivariate logistic regression analyses were performed to determine significant variables for readmission within 30 days.

RESULTS

In total, 485 cases of excisional haemorrhoidectomy were included in the final analysis with 62 (12.8%) unplanned readmissions. The demographics between the no readmission and unplanned readmission groups were similar. Multivariate logistic regression analysis demonstrated that male gender (P = 0.018) and the use of non-diathermy devices (P = 0.017) were significant risk factors for readmission. Initial dispensing of opioid analgesia did not decrease the risk of readmission.

CONCLUSION

This study suggests that male gender and surgical technique are associated with increased risk of readmission.

How we use hospice: Hospice enrollment patterns and costs in elderly ovarian cancer patients

OBJECTIVE

To describe disparities in patterns of hospice use and end-of-life costs among ovarian cancer patients.

METHODS

Using Texas Cancer Registry-Medicare data, ovarian cancer patients deceased 2005-2012 with >12 months of continuous Medicare coverage before death were included. Descriptive statistics and multivariable logistic regressions were used to evaluate patterns of hospice use. Cost and resource utilization was obtained from Medicare claims and analyzed using a non-parametric Mann-Whitney test.

RESULTS

2331 patients were assessed: 1788 (77%) white, 359 (15%) Hispanic, 158 (7%) black and 26 (1%) other. 1756 (75%) enrolled in hospice prior to death but only 1580 (68%) died with hospice. 176 (10%) of 1756 patients unenrolled and died without hospice. 346 (20%) unenrolled from hospice multiple times. From 2008 to 2012, patients were less likely to unenroll from hospice prior to death. Black patients were more likely to unenroll from hospice prior to death (OR 2.07 [1.15-3.73]; p = 0.02) compared to white patients. The median amount paid by Medicare during the last six months of life was $38,530 for those in hospice compared to $49,942 if never enrolled in hospice (p < 0.0001) and was higher for black and Hispanic patients compared to white patients. 30% hospice unenrolled patients and 40% multiply enrolled hospice patients received at least one life extending or invasive care procedure following unenrollment from hospice.

CONCLUSION

Recently, more patients remain enrolled in hospice, but black patients have a higher risk of unenrollment. Hospice enrollment was associated with lower costs as long as a patient did not unenroll from hospice.

Healthcare utilization following spinal cord injury: Objective findings from a regional hospital registry

OBJECTIVE

The purpose was to describe the prevalence and characteristics of healthcare utilization among individuals with spinal cord injury (SCI) from a Level I trauma center.

DESIGN

Retrospective data analysis utilizing a local acute trauma registry for initial hospitalization and merged with the Dallas-Fort Worth Hospital Council registry to obtain subsequent health care utilization in the first post-injury year.

SETTING

Dallas, TX, USA.

PARTICIPANTS

Six hundred and sixty four patients were admitted with an acute traumatic SCI from January 2003 through June 2014 to a Level I trauma center. Fifty five patients that expired during initial hospitalization and 18 patients with unspecified SCI (defined by ICD-9 with no etiology or level of injury specified) were not included in the analysis, leaving a final sample of 591.

OUTCOME MEASURES

Data included demographic and clinical characteristics, charges, and healthcare utilization.

RESULTS

Mean age was 46.1 years (±18.9 years), the majority of patients were male (74%), and Caucasian (58%). Of the 591 patients, 345 (58%) had additional inpatient or emergency healthcare utilization accounting for 769 additional visits (median of 3 visits per person). Of the 769 encounters, 534 (69%) were inpatient and 235 (31%) were emergency visits not resulting in an admission. The most prevalent ICD-9 codes listed were pressure ulcer, neurogenic bowel, neurogenic bladder, urinary tract infection, fluid electrolyte imbalance, hypertension, and tobacco use.

CONCLUSION

Individuals with SCI experience high levels of healthcare utilization which are costly and may be preventable. Increasing our understanding of the prevalence and causes for healthcare utilization after acute SCI is important to target preventive strategies.

Predictors of 30-Day Hospital Readmission After Posterior Cervical Fusion in 3401 Patients

STUDY DESIGN

Retrospective cohort study.

OBJECTIVE

The aim of the study was to determine readmission rates and predictors of readmission after posterior cervical fusion (PCF).

SUMMARY OF BACKGROUND DATA

PCFs are common spinal operations for a variety of spinal disorders including cervical myelopathy, unstable fractures, cervical deformity, and tumors. Data elaborating on risk factors for 30-day readmission are limited.

METHODS

Data were collected from the 2006 to 2013 American College of Surgeons National Surgical Quality Improvement Program database. Predictors of 30-day readmission comprising patient demographics, comorbidities, operative features, and postoperative complications were identified through logistic multivariable regression.

RESULTS

A total of 3401 patients met study criteria. Rate of 30-day readmission was 6.20%. Multilevel fusion was performed in 69.16% of patients. Postoperative infection was the most reason, accounting for 17.06% of all readmissions. Age older than 70 years (odds ratio [OR] = 1.61, P = 0.012), renal failure requiring dialysis (OR = 3.69, P = 0.011), anemia (OR = 1.57, P = 0.006), multilevel fusion (OR = 1.61, P = 0.012), surgical site infections (OR = 20.4, P < 0.001), wound dehiscence (OR = 19.08, P < 0.001), postoperative pneumonia (OR = 2.75, P = 0.01), pulmonary embolism (OR = 15.39, P < 0.001), and progressing renal insufficiency (OR = 10.13, P = 0.061) were significant predictors of hospital readmission.

CONCLUSION

The identified predictors of readmission after PCF can improve patient counseling, identification of high-risk patients, and guide changes in healthcare delivery pathways. Patients with modifiable risk factors such as anemia and kidney failure may benefit from preoperative optimization. In addition, postoperative complications represent a key target for intervention.

LEVEL OF EVIDENCE

3.

Inflammatory Bowel Disease: Predictors and Causes of Early and Late Hospital Readmissions

BACKGROUND AND AIMS

The rate of hospital readmission after discharge has been studied extensively in chronic conditions such as hepatic cirrhosis, diabetes mellitus, chronic obstructive pulmonary disease, and heart failure. Causative factors associated with hospital readmission have not been adequately investigated in patients with inflammatory bowel disease (IBD). We studied the rate, causes, and factors that predict readmissions at 1 month, 3 months, and 1 year in patients with IBD.

METHODS

We performed a retrospective cohort study using the electronic medical record of a tertiary academic medical center, encompassing 3 large hospitals to identify patients discharged between January 2007 and December 2010 with a primary discharge diagnosis of either ulcerative colitis or Crohn's disease. The index admission was defined as the first unplanned admission during this period. Readmission was defined as unplanned admission (because of any cause) occurring within 1 week, 1 month, 3 months, and 1 year from the index admission. To identify factors predictive of readmissions, we compared social, demographic, and clinical features at the index admission of patients with readmission and those with no readmissions. Multivariate logistic regression analyses were performed to identify variables associated with 1-month, 3-month, and 1-year readmissions.

RESULTS

A total of 439 index admissions with a primary discharge diagnosis of either ulcerative colitis or Crohn's disease were eligible for inclusion in the study. These patients accounted for a total of 785 admissions to the health system during the study period. The unplanned readmission rates were 5% at 1 week, 14% at 1 month, 23.7% at 3 months, and 39.2% at 1 year. The most common reasons for readmissions were IBD exacerbations, infections, and abdominal pain. On multivariate analysis, receiving total parenteral nutrition (odds ratio [OR] = 2.3; 95% confidence interval [CI], 1.22-4.30) and intensive care unit stay during index admission (OR = 3.61; 95% CI, 1.38-9.46) predicted both early and late readmissions, whereas sex, race, insurer, and outside hospital transfers predicted 1-year readmission. Receiving steroids (OR = 0.52; 95% CI, 0.23-1.15) at index admission was protective against 1-month readmission; being discharged on biologics (OR = 0.44; 95% CI, 0.19-1.02) was protective against 3-month readmission.

CONCLUSIONS

Both early and late hospital readmissions are common in patients with IBD. Because frequent readmissions are indicators of poor quality of care, future prospective studies using larger cohorts of patients are needed to identify modifiable factors in patient care before discharge to improve quality of care, prevent readmissions, and consequently reduce health care costs.

Risk factors and costs associated with nationwide nonelective readmission after trauma

BACKGROUND

Most prior studies of readmission after trauma have been limited to single institutions, whereas multi-institutional studies have been limited to single states and an inability to distinguish between elective and nonelective readmissions. The purpose of this study was to identify the risk factors and costs associated with nonelective readmission after trauma across the United States.

METHODS

The Nationwide Readmission Database was queried for all patients with nonelective admissions in 2013 and 2014 with a primary diagnosis of trauma. Univariate and multivariate logistic regression identified risk factors for 30-day nonelective same- and different-hospital readmission. The diagnosis groups on readmission were evaluated, and the total cost of readmissions was calculated.

RESULTS

There were 1,180,144 patients admitted for trauma, the 30-day readmission rate was 9.4%, and 26.4% of readmissions occurred at a different hospital. The median readmission cost for patients readmitted to the same hospital was $8,298 (interquartile range, $4,899-$14,911), whereas the median readmission cost for patients readmitted to a different hospital was $8,568 (interquartile range, $4,935-$16,078; p < 0.01). Multivariate regression revealed that patients discharged against medical advice were at increased risk of readmission (odds ratio, 2.79; p < 0.01) and readmission to a different facility (odds ratio, 1.58; p < 0.01). Home health care was associated with a decreased risk of readmission to a different hospital (odds ratio, 0.74; p < 0.01). Septicemia and disseminated infections were the most common diagnoses on readmission (8.4%) and readmission to a different hospital (8.6%).

CONCLUSIONS

A significant portion of US readmissions occur at different hospitals with implications for continuity of care, quality metrics, cost, and resource allocation. Home health care reduces the likelihood of nonelective readmission to a different hospital. Infection was the most common reason for readmission, with ramifications for outcomes research and quality improvement.

LEVEL OF EVIDENCE

Care management/epidimeological, level IV.

Preoperative Renal Insufficiency: Underreporting and Association With Readmission and Major Postoperative Morbidity in an Academic Medical Center

BACKGROUND

Making a formal diagnosis of chronic kidney disease (CKD) in the preoperative setting may be challenging because of lack of longitudinal data. We explored the predictive value of a single reduced preoperative estimated glomerular filtration rate (eGFR) value on adverse patient outcomes in the first 30 days after elective surgery. We compared the rate of major postoperative adverse events, including 30-day readmission rate, hospital length of stay, infection, acute kidney injury (AKI), and myocardial infarction across patients with declining preoperative eGFR values. We hypothesized that there is an association between decreasing preoperative eGFR values and major postoperative morbidity including readmission within 30 days of discharge and that the reasons for unplanned readmissions may be associated with poor preoperative renal function.

METHODS

This was a retrospective analysis of the electronic health record of 39 989 adult patients who underwent elective surgery between June 2011 and July 2013 at our institution. Patients with reduced eGFR (<60 mL/min/1.73 m) were identified and categorized by the stages of CKD that correlated with the preoperative eGFR value. Odds of readmission to our hospital within 30 days, as well as new diagnosis of AKI, myocardial infarction, and infection, were determined with multivariate logistic regression. The subset of patients who were readmitted within 30 days also were subdivided further into patients who had an eGFR <60 mL/min/1.73 m and those with an eGFR ≥60 mL/min/1.73 m, as well as whether the readmission was planned or unplanned.

RESULTS

Of the 4053 patients with eGFR <60 mL/min/1.73 m, 3290 (81.2%) did not carry a preoperative diagnosis of CKD. Adjusted odds ratios of being readmitted were 1.48 (99% confidence interval [CI], 1.18-1.87; P < .001) for eGFR 30 to 44 mL/min/1.73 m to 2.06 (99% CI, 1.32-3.23; P < .001) for eGFR <15 mL/min/1.73 m compared with patients with a preoperative eGFR value ≥60 mL/min/1.73 m. Patients with a lower eGFR also demonstrated increasing odds of AKI from 2.78 (99% CI, 1.86-4.17; P < .001) for eGFR 45 to 59 mL/min/1.73 m to 3.81 (99% CI, 1.68-8.16; P < .001) for eGFR <15 mL/min/1.73 m.

CONCLUSIONS

This study highlights that preoperative renal insufficiency may be underreported and appears to be significantly associated with postoperative complications. It extends the association between a single low preoperative eGFR and postoperative morbidity to a broader range of surgical populations than previously described. Our results suggest that preoperative calculation of eGFR may be a relatively low-cost, readily available tool to identify patients who are at an increased risk of readmission within 30 days of surgery and postoperative morbidity in patients presenting for elective surgery.

Early Hospital Readmission and Mortality Risk after Surgical Treatment of Proximal Humerus Fractures in a Community-Based Health Care Organization

CONTEXT

Surgical treatment for proximal humerus fractures has increased exponentially. Recent health care policies incentivize centers to reduce hospital readmission rates. Better understanding of risk factors for readmission and early mortality in this population will assist in identifying favorable risk-benefit patient profiles.

OBJECTIVE

To identify incidence and risk factors of 30-day hospital readmission rate and 1-year mortality rate after open surgery of proximal humerus fractures.

DESIGN

Retrospective cohort analysis from Kaiser Permanente Southern California Region database.

METHODS

Using International Classification of Diseases, Ninth Revision, diagnosis and procedure codes, all operative proximal humerus fractures were validated. Hospital readmission, one-year mortality, and demographic and medical data were collected. A logistic regression test was performed to assess potential risk factors for outcomes.

RESULTS

From 1387 surgical patients, the 30-day all-cause readmission rate was 5.6%. Forty percent of hospital read-missions were due to surgery-related reasons. Severe liver disease (odds ratio [OR], 3.48, 95% confidence interval [CI] = 1.42-8.55) and LACE (length of stay, acuity of admission, comorbidities, and number of Emergency Department visits in the previous 6 months) index score ≥ 10 (OR, 4.47, 95% CI = 2.54-7.86) were independent risk factors of readmission on multivariate analysis. The 1-year mortality rate was 4.86%. Multivariate analysis showed length of hospital stay (OR 1.11, 95% CI = 1.05-1.19), cancer (OR 3.38, 95% CI = 1.61-7.10), 30-day readmission (OR 3.31, 95% CI = 1.34-8.21), and Charlson comorbidity index greater than or equal to 4 (OR 13.94, 95% CI = 4.40-44.17) predicted higher mortality risk.

CONCLUSION

After open treatment of proximal humerus fractures, there was a 5.6% all-cause 30-day hospital readmission rate. Surgical complications accounted for 40% of read-missions. Severe liver disease and LACE score correlated best with postoperative 30-day readmission risk. Length of hospital stay, preexisting cancer, 30-day readmission, and Charlson comorbidity index were predictive of 1-year mortality.

What Factors Predict Hospital Readmission after Colorectal Surgery?

Readmissions pose a significant hardship for patients and constitute a major quality and financial concern for hospitals. We sought to define risk factors associated with hospital readmission after colorectal surgery at a tertiary care hospital. We evaluated readmission among all patients who underwent a colorectal surgical procedure between July 16, 2007 and June 30, 2011. In a cohort of 4879 operative encounters, 492 (10%) were readmitted to the hospital within 30 days of discharge. Procedures with highest readmissions included stoma creation (22%), ileoanal pouch surgery (22%), and total proctocolectomy (30%). In multivariate analysis, the following variables were associated with risk of readmission: postoperative complication, use of anxiolytics, high comorbidity score, patient setting, alcohol use, and stoma creation. Surgeon of record was not associated with readmission. In conclusion, several patient, procedural, and postoperative factors were associated with an increased risk of readmission. Considerably high rates of readmission were noted after stoma creation, ileoanal pouch procedures, and proctocolectomy. Surgeon of record was not associated with risk of read-mission, indicating little value to this metric as a physician-specific indicator of quality.

Hospital Readmission Through the Emergency Department

BACKGROUND

Hospital readmission places a high burden on both health care systems and patients. Most readmissions are thought to be related to the quality of the health care system.

OBJECTIVES

The aim of this study was to examine the causes and rates of early readmission in emergency department in a Tehran hospital.

PATIENTS AND METHODS

A cross-sectional investigation was performed to study readmission of inpatients at a large academic hospital in Tehran, Iran. Patients admitted to hospital from July 1, 2014 to December 30, 2014 via the emergency department were enrolled. Descriptive statistics were used to summarize the distribution demographics in the sample. Data was analyzed by chi2 test using SPSS 20 software.

RESULTS

The main cause of readmission was complications related to surgical procedures (31.0%). Discharge from hospital based on patient request at the patient's own risk was a risk factor for emergency readmission in 8.5%, a very small number were readmitted after complete treatment (0.6%). The only direct complication of treatment was infection (17%).

CONCLUSIONS

Postoperative complications increase the probability of patients returning to hospital. Physicians, nurses, etc., should focus on these specific patient populations to minimize the risk of postoperative complications. Future studies should assess the relative connections of various types of patient information (e.g., social and psychosocial factors) to readmission risk prediction by comparing the performance of models with and without this information in a specific population.

Trauma center care is associated with reduced readmissions after injury

BACKGROUND

Trauma center care has been associated with improved mortality. It is not known if access to trauma center care is also associated with reduced readmissions. We hypothesized that receiving treatment at a trauma center would be associated with improved care and therefore would be associated with reduced readmission rates.

METHODS

We conducted a retrospective analysis of all hospital visits in California using the Office of Statewide Health Planning and Development Database from 2007 to 2008. All hospital admissions and emergency department visits associated with injury were longitudinally linked. Regions were categorized by whether they had trauma centers. We excluded all patients younger than 18 years. We performed univariate and multivariate regression analyses to determine if readmissions were associated with patient characteristics, length of stay for initial hospitalization, trauma center access, and triage patterns.

RESULTS

A total of 211,504 patients were included in the analysis. Of these, 5,094 (2%) died during the index hospitalization. Of those who survived their initial hospitalization, 79,123 (38%) experienced one or more readmissions to any hospital within 1 year. The majority of these were one-time readmissions (62%), but 38% experienced multiple readmissions. Over 67% of readmissions were unplanned and 8% of readmissions were for a trauma. After controlling for patient variables known to be associated with readmissions, primary triage to a trauma center was associated with a lower odds of readmission (odds ratio, 0.89; p < 0.001). The effect of transport to a trauma center remained significantly associated with decreased odds of readmission at 1 year (odds ratio, 0.96; p < 0.001).

CONCLUSION

Readmissions after injury are common and are often unscheduled. While patient factors play a role in this, care at a trauma center is also associated with decreased odds for readmission, even when controlling for severity of injury. This suggests that the benefits of trauma center care extend beyond improvements in mortality to improved long-term outcomes.

LEVEL OF EVIDENCE

Epidemiologic study, level III; therapeutic/care management study, level IV.

Early Hospital Readmission After Simultaneous Pancreas-Kidney Transplantation: Patient and Center-Level Factors

Early hospital readmission is associated with increased morbidity, mortality, and cost. Following simultaneous pancreas-kidney transplantation, rates of readmission and risk factors for readmission are unknown. We used United States Renal Data System data to study 3643 adult primary first-time simultaneous pancreas-kidney recipients from December 1, 1999 to October 31, 2011. Early hospital readmission was any hospitalization within 30 days of discharge. Modified Poisson regression was used to determine the association between readmission and patient-level factors. Empirical Bayes statistics were used to determine the variation attributable to center-level factors. The incidence of readmission was 55.5%. Each decade increase in age was associated with an 11% lower risk of readmission to age 40, beyond which there was no association. Donor African-American race was associated with a 13% higher risk of readmission. Each day increase in length of stay was associated with a 2% higher risk of readmission until 14 days, beyond which each day increase was associated with a 1% reduction in the risk of readmission. Center-level factors were not associated with readmission. The high incidence of early hospital readmission following simultaneous pancreas-kidney transplant may reflect clinical complexity rather than poor quality of care.

Risk of readmission after laparoscopic vs. open colorectal surgery

PURPOSE

Laparoscopic colorectal resection (LC) is associated with known recovery benefits and earlier discharge when compared to open colorectal resection (OC). Whether earlier discharge leads to a paradoxical increase in readmission has not been well characterized. The aim of this study is to compare the risk of readmission after the two procedures in a large, nationally representative sample.

METHODS

Patients who underwent colorectal resection in 2011 were identified from the American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) database. LC and OC patients were compared for patient factors, complications, and readmission rates. A multivariable analysis controlling for significant factors was performed to evaluate factors associated with readmission.

RESULTS

Of 30,428 patients who underwent colorectal resection, 40.2% underwent LC. Length of stay (LOS) after LC was shorter than after OC (5.7 vs. 9.7 days, p < 0.001). LC was associated with a significantly lower rate of surgical site infections (SSI), bleeding, reoperation, 30-day mortality, and complications. Risk of readmission was greater for patients undergoing proctectomy than colectomy (12.7 vs. 10.6 %, p < 0.001), but was lower after laparoscopic than open for both procedures after controlling for confounding factors. Obesity, DM, operating time ≥180 min, steroid use, and ASA class 3-5 were found to be associated with readmission.

CONCLUSION

Despite its technical complexity, LC can be performed without concerns for increased complications or readmission. The shorter length of stay and the lower risk of readmissions underline the true benefits of the laparoscopic approach for colorectal resection.

A validated, risk assessment tool for predicting readmission after open ventral hernia repair

BACKGROUND/PURPOSE

To present a validated model that reliably predicts unplanned readmission after open ventral hernia repair (open-VHR).

STUDY DESIGN

A total of 17,789 open-VHR patients were identified using the 2011-2012 ACS-NSQIP databases. This cohort was subdivided into 70 and 30% random testing and validation samples, respectively. Thirty-day unplanned readmission was defined as unexpected readmission for a postoperative occurrence related to the open-VHR procedure. Independent predictors of 30-day unplanned readmission were identified using multivariable logistic regression on the testing sample (n = 12,452 patients). Subsequently, the predictors were weighted according to β-coefficients to generate an integer-based Clinical Risk Score (CRS) predictive of readmission, which was validated using receiver operating characteristics (ROC) analysis of the validation sample (n = 5337 patients).

RESULTS

The rate of 30-day unplanned readmission was 4.7%. Independent risk factors included inpatient status at time of open-VHR, operation time, enterolysis, underweight, diabetes, preoperative anemia, length of stay, chronic obstructive pulmonary disease, history of bleeding disorders, hernia with gangrene, and panniculectomy (all P < 0.05). ROC analysis of the validation cohort rendered an area under the curve of 0.71, which demonstrates the accuracy of this prediction model. Predicted incidence within each 5 risk strata was statistically similar to the observed incidence in the validation sample (P = 0.18), further highlighting the accuracy of this model.

CONCLUSION

We present a validated risk stratification tool for unplanned readmissions following open-VHR. Future studies should determine if implementation of our CRS optimizes safety and reduces readmission rates in open-VHR patients.

Comorbidity-polypharmacy score predicts readmission in older trauma patients

BACKGROUND

Hospital readmissions are considered to be a measure of quality of care, correlate with worse outcomes, and may soon lead to decreased reimbursement. The comorbidity-polypharmacy score (CPS) is the sum of the number of preinjury medications and comorbidities, and may estimate patient frailty more effectively than patient age. This study evaluates the association between CPS and readmission.

METHODS

Medical records for trauma patients ≥45 y evaluated between January 1 and December 31, 2008, at our American College of Surgeons-verified level 1 trauma center were reviewed to obtain information on demographics, injuries, preinjury comorbidities, and medications, and occurrences of readmission to our facility within 30 d of discharge. Chi-square and Kruskal-Wallis testing was used to evaluate differences between readmitted and nonreadmitted patients, with multiple logistic regression used to evaluate the contribution of independent risk factors for readmission.

RESULTS

A total of 879 patients were included; their ages ranged from 45-103 y (median 58), injury severity scores from 0-50 y (median 5), and CPS from 0-39 y (median 7). A total of 76 patients (8.6%) were readmitted to our facility within 30 d of discharge. The readmitted cohort had higher CPS (median, 9.5, range 0-32, P = 0.031) and injury severity score (median, 9, range 1-38, P = 0.045), but no difference in age (median, 59.5, range 47-99, P = 0.646). Logistic regression demonstrated independent association of higher CPS with increased risk of readmission, with each CPS point increasing readmission likelihood by 3.5% (P = 0.03).

CONCLUSIONS

CPS appears to correlate well with readmissions within 30 d. Frailty defined by CPS was a significantly stronger predictor of readmission than was patient age. Early recognition of elevated CPS may improve discharge planning and help guide interventions to decrease readmission rates in older trauma patients.

The association of acute kidney injury in the critically ill and postdischarge outcomes: a cohort study*

OBJECTIVE

Hospital readmissions contribute significantly to the cost of inpatient care and are targeted as a marker for quality of care. Little is known about risk factors associated with hospital readmission in survivors of critical illness. We hypothesized that acute kidney injury in patients who survived critical care would be associated with increased risk of 30-day postdischarge hospital readmission, postdischarge mortality, and progression to end-stage renal disease.

DESIGN

Two center observational cohort study.

SETTING

Medical and surgical ICUs at the Brigham and Women's Hospital and the Massachusetts General Hospital in Boston, Massachusetts.

PATIENTS

We studied 62,096 patients, 18 years old and older, who received critical care between 1997 and 2012 and survived hospitalization.

INTERVENTIONS

None

MEASUREMENTS AND MAIN RESULTS

: All data was obtained from the Research Patient Data Registry at Partners HealthCare. The exposure of interest was acute kidney injury defined as meeting Risk, Injury, Failure, Loss of kidney function, and End-stage kidney disease Risk, Injury or Failure criteria occurring 3 days prior to 7 days after critical care initiation. The primary outcome was hospital readmission in the 30 days following hospital discharge. The secondary outcome was mortality in the 30 days following hospital discharge. Adjusted odds ratios were estimated by multivariable logistic regression models with inclusion of covariate terms thought to plausibly interact with both acute kidney injury and readmission status. Adjustment included age, race (white vs nonwhite), gender, Deyo-Charlson Index, patient type (medical vs surgical) and sepsis. Additionally, long-term progression to End Stage Renal Disease in patients with acute kidney injury was analyzed with a risk-adjusted Cox proportional hazards regression model. The absolute risk of 30-day readmission was 12.3%, 19.0%, 21.2%, and 21.1% in patients with No Acute Kidney Injury, Risk, Injury, Failure, Loss of kidney function, and End-stage kidney disease class Risk, Risk, Injury, Failure, Loss of kidney function, and End-stage kidney disease class Injury, and Risk, Injury, Failure, Loss of kidney function, and End-stage kidney disease class Failure, respectively. In patients who received critical care and survived hospitalization, acute kidney injury was a robust predictor of hospital readmission and post-discharge mortality and remained so following multivariable adjustment. The odds of 30-day post-discharge hospital readmission in patients with Risk, Injury, Failure, Loss of kidney function, and End-stage kidney disease class Risk, Injury, or Failure fully adjusted were 1.44 (95% CI, 1.25-1.66), 1.98 (95% CI, 1.66-2.36), and 1.55 (95% CI, 1.26-1.91) respectively, relative to patients without acute kidney injury. Further, the odds of 30-day post-discharge mortality in patients with Risk, Injury, Failure, Loss of kidney function, and End-stage kidney disease class Risk, Injury, or Failure fully adjusted per our primary analysis were 1.39 (95% CI, 1.28-1.51), 1.46 (95% CI, 1.30-1.64), and 1.42 (95% CI, 1.26-1.61) respectively, relative to patients without acute kidney injury. The addition of the propensity score to the multivariable model did not change the point estimates significantly. Finally, taking into account age, gender, race, Deyo-Charlson Index, and patient type, we observed a relationship between acute kidney injury and development of end-stage renal disease. Patients with Risk, Injury, Failure, Loss of kidney function, and End-stage kidney disease class Risk, Injury, Failure experienced a significantly higher risk of end-stage renal disease during follow-up than patients without acute kidney injury (hazard ratio, 2.03; 95% CI, 1.56-2.65; hazard ratio, 3.99; 95% CI, 3.04-5.23; hazard ratio, 10.40; 95% CI, 8.54-12.69, respectively).

CONCLUSIONS

Patients who suffer acute kidney injury are among a high-risk group of ICU survivors for adverse outcomes. In patients treated with critical care who survive hospitalization, acute kidney injury is a robust predictor of subsequent unplanned hospital readmission. In critical illness survivors, acute kidney injury is also associated with the odds of 30-day postdischarge mortality and the risk of subsequent end-stage renal disease.

Patients undergoing total laryngectomy: an at-risk population for 30-day unplanned readmission

IMPORTANCE

Patients undergoing total laryngectomy are at high risk for hospital readmission. Hospital readmissions are increasingly scrutinized because they are used as a metric of quality care and are subject to financial penalties.

OBJECTIVE

To determine the rate of, reasons for, and risk factors that predict 30-day unplanned readmission for patients undergoing total laryngectomy.

DESIGN, SETTING, AND PATIENTS

Retrospective cohort study at a single academic tertiary referral medical center. The study population comprised 155 patients who underwent total laryngectomy with or without flap closure between January 2007 and December 2012 as either a primary treatment or salvage treatment for prior nonsurgical management.

INTERVENTIONS

Total laryngectomy.

MAIN OUTCOMES AND MEASURES

Rate of 30-day unplanned readmission, readmission diagnoses, and risk factors for unplanned readmission. Univariable and multivariable logistic regression were performed to identify risk factors for unplanned readmission within 30 days of discharge.

RESULTS

The 30-day unplanned readmission rate for patients following discharge after total laryngectomy was 26.5% (41 of 155). The most common readmission diagnoses were pharyngocutaneous fistula (27% of readmissions; n = 11) and stomal cellulitis (16% of readmissions; n = 7). The median time to unplanned readmission was 7 days. Thirty-four percent of readmissions (14 of 41) occurred within 3 days of discharge. Significant predictors of 30-day unplanned readmission on multivariable analysis were postoperative complication after discharge (odds ratio [OR], 11.50; 95% CI, 4.10-32.28), visit to the emergency department within 30 days after discharge (OR, 5.25; 95% CI, 1.84-14.99), salvage total laryngectomy (OR, 3.52; 95% CI, 1.56-13.12), and chyle fistula during the index hospitalization (OR, 5.25; 95% CI, 0.86-29.92). The discriminative ability of the model to predict unplanned readmission, as measured by the C statistic, was 0.88.

CONCLUSIONS AND RELEVANCE

Patients undergoing total laryngectomy are an at-risk patient population with a high rate of unplanned readmission within 30 days of discharge. By identifying the risk factors that predict 30-day unplanned readmission, these data can be used to design and implement quality-improvement interventions to decrease readmissions.

Examination of unplanned 30-day readmissions to a comprehensive cancer hospital

PURPOSE

The Centers for Medicare and Medicaid Services (CMS), under the Hospitals Readmissions Reductions Program, may withhold regular reimbursements for excessive 30-day readmissions for select diagnoses. Such penalties imply that some readmissions reflect poor clinical decision making or care during the initial hospitalization. We examined factors related to potentially preventable readmissions in CMS patients at a tertiary cancer hospital.

METHODS

The medical records of all CMS patients with unplanned readmissions within 30 days of index admission were reviewed over 6 months (October 15, 2011-April 15, 2012). Each readmission was classified as not preventable or potentially preventable. Factors associated with potentially preventable readmissions were sought.

RESULTS

Of 2,531 inpatient admissions in CMS patients over 6 months, 185 patients experienced at least one readmission for 282 total readmissions (11%). Median time to readmission was 9 days (range, 0 to 30 days). The most common causes for first readmission were new diagnoses not present at first admission (n = 43, 23%), new or worsening symptoms due to cancer progression (n = 40, 21%) and complications of procedures (n = 25, 13%). There were 38 (21%) initial readmissions classified as potentially preventable. Use of total parenteral nutrition at the time of discharge was associated with potentially preventable readmission (P = .028).

CONCLUSION

Most unplanned readmissions to a tertiary cancer hospital are related to progression of disease, new diagnoses, and procedure complications. Minimizing readmissions in complex cancer patients is challenging. Larger multi-institutional datasets are needed to determine a reasonable standard for expected readmission rates.

Readmission incidence and associated factors after a hepatic resection at a major hepato-pancreatico-biliary academic centre

BACKGROUND

Reducing readmission is a key quality improvement target for policymakers. The purpose of the present study was to define incidence and identify factors associated with readmission after a hepatic resection.

METHODS

Thirty-day readmission after discharge and factors associated with a higher risk of readmission were examined among patients undergoing a hepatic resection at Johns Hopkins Hospital between 2008 and 2012.

RESULTS

Among the 338 patients, the median age was 57.9 years and 173 (51.2%) were men. Indications for surgery included colorectal cancer liver metastasis (38.2%), primary hepatic tumours (25.7%) and benign disease (3.3%). Surgical resection consisted of less than a hemi-hepatectomy in the majority of patients (n = 224, 66.3%). The median index hospitalization length-of-stay (LOS) was 5 days; 68.7% patients experienced at least one inpatient complication. Overall 30-day readmission was 14.2% (n = 48). The majority of readmitted patients (n = 46, 95.8%) had a complication prior to readmission. The median LOS for readmission was 4 [interquartile range (IQR) 2-6] days. On multivariable analysis, the strongest independent predictor of readmission was the presence of a major complication [odds ratio (OR) 5.30, 95% confidence interval (CI) 2.38-11.78, P < 0.001].

CONCLUSIONS

Readmission after a hepatic resection occurs in approximately one out of every seven patients. Patients who experience a post-operative complication are greater than five times more likely to be readmitted. Prospective studies are needed to evaluate methods to reduce unplanned readmissions.

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.

Predictors of unplanned readmission in patients undergoing lumbar decompression: multi-institutional analysis of 7016 patients

Object

Unplanned hospital readmission represents a large financial burden on the Centers for Medicare and Medicaid Services, commercial insurance payers, hospitals, and individual patients, and is a principal target for cost reduction. A large-scale, multi-institutional study that evaluates risk factors for readmission has not been previously performed in patients undergoing lumbar decompression procedures. The goal of this multicenter retrospective study was to find preoperative, intraoperative, and postoperative predictive factors that result in unplanned readmission (UR) after lumbar decompression surgery.

Methods

The National Surgical Quality Improvement Program (NSQIP) database was retrospectively reviewed to identify all patients who received lumbar decompression procedures in 2011. Risk-adjusted multivariate logistic regression analysis was performed to estimate independent predictors of UR.

Results

The overall rate of UR among patients undergoing lumbar decompression was 4.4%. After multivariate logistic regression analysis, anemia (odds ratio [OR] 1.48), dependent functional status (OR 3.03), total operative duration (OR 1.003), and American Society of Anesthesiologists Physical Status Class 4 (OR 3.61) remained as independent predictors of UR. Postoperative complications that were significantly associated with UR included overall complications (OR 5.18), pulmonary embolism (OR 3.72), and unplanned reoperation (OR 56.91).

Conclusions

There were several risk factors for UR after lumbar spine decompression surgery. Identification of high-risk patients and appropriate allocation of resources to reduce postoperative incidence may reduce the readmission rate.

Rates, patterns, and determinants of unplanned readmission after traumatic injury: a multicenter cohort study

OBJECTIVE

This study aimed to (i) describe unplanned readmission rates after injury according to time, reason, and place; (ii) compare observed rates with general population rates, and (iii) identify determinants of 30-day readmission.

BACKGROUND

Hospital readmissions represent an important burden in terms of mortality, morbidity, and resource use but information on unplanned rehospitalization after injury admissions is scarce.

METHODS

This multicenter retrospective cohort study was based on adults discharged alive from a Canadian provincial trauma system (1998-2010; n = 115,329). Trauma registry data were linked to hospital discharge data to obtain information on readmission up to 12 months postdischarge. Provincial admission rates were matched to study data by age and gender to obtain expected rates. Determinants of readmission were identified using multiple logistic regression.

RESULTS

Cumulative readmission rates at 30 days, 3 months, 6 months, and 12 months were 5.9%, 10.9%, 15.5%, and 21.1%, respectively. Observed rates persisted above expected rates up to 11 months postdischarge. Thirty percent of 30-day readmissions were due to potential complications of injury compared with 3% for general provincial admissions. Only 23% of readmissions were to the same hospital. The strongest independent predictors of readmission were the number of prior admissions, discharge destination, the number of comorbidities, and age.

CONCLUSIONS

Unplanned readmissions after discharge from acute care for traumatic injury are frequent, persist beyond 30 days, and are often related to potential complications of injury. Several patient-, injury-, and hospital-related factors are associated with the risk of readmission. Injury readmission rates should be monitored as part of trauma quality assurance efforts.

Return to system within 30 days of pediatric neurosurgery

OBJECT

Quality assessment measures have not been well developed for pediatric neurosurgical patients. This report documents the authors' experience in extracting information from an administrative database to establish the rate of return to system within 30 days of pediatric neurosurgical procedures.

METHODS

Demographic, socioeconomic, and clinical characteristics were prospectively collected in administrative, business, and operating room databases. The primary end point was an unexpected return to the hospital system within 30 days from the date of a pediatric neurosurgical procedure. Statistical methods were used to identify clinical and demographic factors associated with the primary end point.

RESULTS

There were 1358 pediatric neurosurgical procedures performed in the Children's Healthcare of Atlanta operating rooms in 2012, with 37.4% of these surgeries being preceded by admissions through the emergency department. Medicare or Medicaid was the payor for 54.9% of surgeries, and 37.6% of surgeries were shunt related. There were 148 unexpected returns to the system within 30 days after surgery, and in 109 of these cases, the patient had a presenting complaint that was attributable to the index surgery (related returns). The most common complaints were headache, nausea, vomiting, or seizure after shunt revision or cranial procedures (n = 62). The next most common reason for re-presentation was for wound concerns (n = 30). Thirty-seven of the 109 related returns resulted in a reoperation. The monthly rate of related returns was 8.1% ± 2.5% over the 12-month study period. When using related returns as the dependent variable, the authors found that patients who underwent a shunt-related surgery were both more likely to unexpectedly return to the system (OR 1.86, p = 0.008) and to require surgery upon readmission (OR 3.28, p = 0.004). Because an extended hospitalization shortened the window of time for readmission after surgery, extended length of stay was protective against return to system within 30 days of surgery. Importantly, if related and unrelated returns were analyzed together as the dependent variable (n = 148), no independent clinical and demographic risk factor could be identified.

CONCLUSIONS

Quality assessment measures need to be clearly and carefully defined, as the definition itself will impact the analytical results. Clinicians must play a leading role in the development of these measures to ensure their clinical meaningfulness.

Early hospital readmission in the trauma population: are the risk factors different?

INTRODUCTION

Hospital readmission rates will soon impact Medicare reimbursements. While risk factors for readmission have been described for medical and elective surgical patients, little is known about their predictive value specifically in trauma patients.

PATIENTS AND METHODS

We retrospectively identified all admissions after trauma resuscitation to our urban level 1 trauma centre from 1/1/2004 to 8/31/2010. All patients discharged alive were included. Data collected included demographics, Injury Severity Score (ISS), and length of stay (LOS). We analyzed these index admissions for the development of complications that have previously been shown to be associated with readmission. Readmissions that occurred within 30 days of index admission were identified. Univariable and multivariable analyses were performed. p<0.05 was considered significant.

RESULTS

We identified 10,306 index admissions, with 447 (4.3%) early (within 30 days) readmissions. Mean ISS was 11.1 (SD 10.4). On multivariable analysis, African-American race (OR 1.3, p=0.009), pre-existing chronic obstructive pulmonary disease (COPD) (OR 1.5, p=0.02), and diabetes mellitus (OR 1.8, p<0.001) were associated with readmission, along with higher ISS (OR 1.01, p<0.001), ICU admission (OR 2.1, p<0.001), and increased LOS (OR 1.01, p<0.001). Among many in-hospital complications examined, only the development of surgical site infection (SSI) (OR 1.9, p=0.02) was associated with increased risk of readmission.

CONCLUSIONS

Trauma patients have a low risk of readmission. In contrast to elective surgical patients, the only modifiable risk factor for readmission in our trauma population was SSI. Other risk factors may present clinicians with opportunities for targeted interventions, such as proactive follow up or early phone contact. With future changes to health care policy, clinicians may have even greater motivation to prevent readmission.

Assessing readmission after general, vascular, and thoracic surgery using ACS-NSQIP

OBJECTIVE

In 2012, Medicare began cutting reimbursement for hospitals with high readmission rates. We sought to define the incidence and risk factors associated with readmission after surgery.

METHODS

A total of 230,864 patients discharged after general, upper gastrointestinal (GI), small and large intestine, hepatopancreatobiliary (HPB), vascular, and thoracic surgery were identified using the 2011 American College of Surgeons National Surgical Quality Improvement Program. Readmission rates and patient characteristics were analyzed. A predictive model for readmission was developed among patients with length of stay (LOS) 10 days or fewer and then validated using separate samples.

RESULTS

Median patient age was 56 years; 43% were male, and median American Society of Anesthesiologists (ASA) class was 2 (general surgery: 2; upper GI: 3; small and large intestine: 2; HPB: 3; vascular: 3; thoracic: 3; P < 0.001). The median LOS was 1 day (general surgery: 0; upper GI: 2; small and large intestine: 5; HPB: 6; vascular: 2; thoracic: 4; P < 0.001). Overall 30-day readmission was 7.8% (general surgery: 5.0%; upper GI: 6.9%; small and large intestine: 12.6%; HPB: 15.8%; vascular: 11.9%; thoracic: 11.1%; P < 0.001). Factors strongly associated with readmission included ASA class, albumin less than 3.5, diabetes, inpatient complications, nonelective surgery, discharge to a facility, and the LOS (all P < 0.001). On multivariate analysis, ASA class and the LOS remained most strongly associated with readmission. A simple integer-based score using ASA class and the LOS predicted risk of readmission (area under the receiver operator curve 0.702).

CONCLUSIONS

Readmission among patients with the LOS 10 days or fewer occurs at an incidence of at least 5% to 16% across surgical subspecialties. A scoring system on the basis of ASA class and the LOS may help stratify readmission risk to target interventions.

Hospital readmission after spine fusion for adult spinal deformity

STUDY DESIGN

Retrospective cohort study.

OBJECTIVE

To assess the rate, causes, and risk factors of unplanned hospital readmission after spine fusion for the treatment of adult spinal deformity.

SUMMARY OF BACKGROUND DATA

Hospital readmissions in the elderly are common, and with increasing emphasis on the quality of health care, readmission rates are used to assess hospital performance. Spine surgery has seen rapidly increased utilization during the past 2 decades. Surgical treatments of complex spinal deformity are known to have higher rates of complications than other types of spine surgery. However, there are no reports describing the rates and causes of hospital readmission after deformity surgery.

METHODS

Patients were identified at a single institution from 2006 through 2011 that received a spine fusion for the treatment of adult spinal deformity. All hospital readmissions within 90 days of discharge were reviewed for cause. Unplanned readmission rates were calculated via Kaplan-Meier failure analysis. Rates were compared across patients receiving different lengths of spine fusion (short: 2-3 vertebra, medium: 4-8, long: 9 or more). Risk factors were assessed using a Cox proportional hazards multivariate model.

RESULTS

Eight hundred thirty-six patients were enrolled (111 short, 402 medium, and 323 long fusions). The overall unplanned readmission rate was 8.4% at 30 days and 12.3% at 90 days. Patients with long spine fusion had higher rates of readmission than patients with medium or short length fusions. Surgical site infection accounted for 45.6% of readmissions. Risk factors for readmission include longer fusion length, higher patient severity of illness, and specific medical comorbidities.

CONCLUSION

Unplanned hospital readmissions after spine fusion for adult spinal deformity are common, and are most often due to surgical site infection. Patient medical comorbidities are an important part of assessing risk and can be used by providers and patients to better assess individual risk prior to treatment.

Risk Factors for Unplanned Hospital Readmission in Otolaryngology Patients

Objective

Identify the risk factors that predict 30-day unplanned readmission in hospitalized otolaryngology patients.

Study Design

Retrospective cohort study.

Setting

Single academic hospital.

Subjects and Methods

All otolaryngology admissions for the 1-year period between January 1, 2011, and December 31, 2011, at an academic hospital were reviewed. Univariate logistic regression and multivariate logistic regression, employing a backward elimination stepwise approach, were performed to identify risk factors for unplanned readmission to the hospital within 30 days of discharge from the otolaryngology service.

Results

There were 1058 patients that accounted for 1271 hospital admissions. The 30-day unplanned readmission rate for patients discharged from the otolaryngology service was 7.3% (93/1271). Significant predictors identified on univariate analysis were used to build a multivariable logistic regression model of risk factors for unplanned readmission. These risk factors included presence of a complication (odds ratio [OR] = 11.60, 95% confidence interval [CI], 7.11-18.93), new total laryngectomy (OR = 4.72, 95% CI, 1.58-14.10), discharge destination of skilled nursing facility (OR = 2.70, 95% CI, 1.21-6.02), severe coronary artery disease or chronic lung disease (OR = 2.33, 95% CI, 1.38-3.93), and current illicit drug use (OR = 2.60, 95% CI, 1.27-5.34). The discriminative ability of the multivariate regression model to predict unplanned readmissions, as measured by the c-statistic, was 0.85.

Conclusion

Otolaryngology patients have unique risk factors that predict unplanned readmission within 30 days of discharge. These data identify specific patient characteristics and care processes that can be targeted with quality improvement interventions to decrease unplanned readmissions.

Risk factors for readmission of orthopaedic surgical patients

BACKGROUND

Reducing hospital readmissions has become a priority in the development of policies aimed at patient safety and cost reduction. Evaluating the incidence of rehospitalization of orthopaedic surgical patients could help to identify targets for more efficient perioperative care. We addressed two questions: What is the incidence of thirty-day readmission for orthopaedic patients at an academic hospital? Can any risk factors for readmission be identified among rehospitalized patients?

METHODS

This is a retrospective cohort study examining 3264 orthopaedic surgical admissions during two fiscal years from the hospital's quality-improvement database. Cases of patients with unplanned readmission within thirty days were subjected to univariate and multivariate analysis to determine the odds ratio (OR) for readmission. Further descriptive analysis was performed with use of electronic medical record data from the cohort of readmitted patients.

RESULTS

The estimated cumulative incidence of unplanned thirty-day readmissions was 4.2% (i.e., 138 of the 3261 patients who were eligible for the study). Multivariate analysis indicated that marital status of "widowed" significantly increased the risk of readmission (OR, 1.846; 95% confidence interval [CI], 1.070 to 3.184; p = 0.03). Race significantly increased the odds of readmission in patients identified as African-American (OR, 2.178; 95% CI, 1.077 to 4.408; p = 0.03), or American Indian or Alaskan Native race (OR, 3.550; 95% CI, 1.429 to 8.815; p = 0.006). The risk of readmission was significant at p &lt; 0.10 (OR 1.547; 95% CI, 0.941 to 2.545; p = 0.09) for patients with Medicaid insurance. Any intensive care unit stay gave the highest OR of readmission (OR, 2.356; 95% CI, 1.361 to 4.079; p = 0.002) for all demographic groups. Mean length of hospital stay was significantly longer, 5.9 days in the unplanned readmission group compared with 3.6 days for non-readmitted patients (OR, 1.038; 95% CI, 1.014 to 1.062; p = 0.002). Chart review of readmitted patients showed that 102 readmissions (73.9%) were classified as surgical; of these, thirty-five readmission events (34.3%) were for infection at the surgical site.

CONCLUSIONS

Longer length of hospital stay or admission to the intensive care unit significantly increased the likelihood of thirty-day readmission, regardless of demographics or discharge disposition. Marital status, Medicaid insurance status, and race may indicate how a patient's social and economic resources can impact his or her risk of being readmitted to the hospital.

LEVEL OF EVIDENCE

Prognostic Level II. See Instructions for Authors for a complete description of levels of evidence.

Relationship between unplanned readmission and total treatment-related hospital days following management of complicated appendicitis at 31 children's hospitals

PURPOSE

To examine the correlation between readmission rate and total hospital days as resource utilization and quality measures for comparative analysis.

METHODS

Retrospective three-year audit of 8948 patients admitted with complicated appendicitis at 31 children's hospitals (6/2008-6/2011). Rates of unplanned readmission and cumulative LOS from all index and readmission encounters were analyzed for each hospital through 90 days of follow-up. The relative number and distribution of outlier hospitals identified by each measure were then compared.

RESULTS

Significant variation was found between hospitals for readmission (aggregate rate: 13.8%, range:5.6-27.1%, chi(2) p<0.0001) and for cumulative LOS (aggregate median: 5 days, range: 4 days [IQR: 3-6] to 7 days [IQR: 4-11],Wilcoxon p<0.0001). Ten (32%) hospitals were identified as outliers by readmission rate and 11 (35%) by cumulative LOS. Although a similar number of outliers were identified for both measures, there was poor agreement in assigning high and low-utilization outlier status to individual hospitals (Weighted Kappa=0.102 [95% CI: -0.167 to 0.386]). Only 2/6 (33%) low-utilizers by readmission rate were low-utilizers by cumulative LOS, and only 2/4 (50%) low-utilizers by cumulative LOS were low-utilizers by readmission rate.

CONCLUSIONS

There is poor correlation between unplanned readmission and total hospital days following treatment for complicated appendicitis in children. Research and reporting for this condition should incorporate both measures to provide a more comprehensive assessment of resource utilization.

Reducing hospital readmissions of postoperative patients with the martin postoperative discharge screening tool

Hospital readmission for postoperative complications, a safety and quality issue for nurse leaders, occurs with 20% of postoperative Medicare patients and costs $15 billion annually. Nurse leaders should evaluate readmission rates for postoperative complications and evaluate ways to reduce the incidence. The Martin Postoperative Discharge Screening Tool was developed to address this vulnerable population and guide clinical staff to develop interventions to improve the readiness of identified patients for discharge. Preliminary results of the project are presented in this article.