Variation in readmission rates among hospitals following admission for traumatic injury

Decreased readmission rates following use of modified trauma-specific frailty index in older trauma patients: A follow-up study

INTRODUCTION

Post-discharge readmission rates using modified Trauma-Specific Frailty Index (mTSFI) compared to the Emergency Severity Index (ESI) are unknown. In our pilot study, we demonstrated that mTSFI usage more accurately triages older trauma patients. In the current study, we hypothesized that adult trauma patients triaged using mTSFI would have lower readmission rates at the 30-day interval post discharge.

METHODS

Retrospective review of readmission rates for 96 trauma patients ≥ 50 years old was performed. The two study groups were categorized as mTSFI-concordant and ESI-concordant. Fisher's exact test was performed.

RESULTS

Mean ages for ESI and mTSFI groups were 63.8 (SD 10.6) and 65.2 (SD 10.8) years. The 30-day readmission rate was 0% (0/32) in the mTSFI group vs 11% (7/64) in the ESI group (p = 0.104).

CONCLUSIONS

Utilization of mTSFI for adult trauma patients may lead to lower 30-day readmission rates compared to using ESI, despite our sample sizes being too small to demonstrate a statistically significant difference.

Safety of Elderly Fallers: Identifying Associated Risk Factors for 30-Day Unplanned Readmissions Using a Clinical Data Warehouse

BACKGROUND

Hospital readmissions are a major problem in the older people as they are frequent, costly, and life-threatening. Falls among older adults are the leading cause of injury, deaths, and emergency department visits for trauma.

OBJECTIVE

The main objective was to determine risk factors associated with a 30-day readmission after index hospital admission for fall-related injuries.

METHODS

A retrospective nested case-control study was conducted. Data from elderly patients initially hospitalized for fall-related injuries in 2019, in 11 of the Greater Paris University Hospitals and discharged home, were retrieved from the clinical data warehouse. Cases were admission of elderly patients who subsequently experienced a readmission within 30 days after discharge from the index admission. Controls were admission of elderly patients who were not readmitted to hospital.

RESULTS

Among 670 eligible index admissions, 127 (18.9%) were followed by readmission within 30 days after discharge. After multivariate analysis, men sex (odds ratio [OR] = 2.29, 95% confidence interval [CI] = 1.45-3.61), abnormal concentration of C-reactive protein, and anemia (OR = 2.22, 95% CI = 1.28-3.85; OR = 1.85, 95% CI = 1.11-3.11, respectively) were associated with a higher risk of readmission. Oppositely, having a traumatic injury at index admission decreased this risk (OR = 0.47, 95% CI = 0.28-0.81).

CONCLUSIONS

Reducing early unplanned readmission is crucial, especially in elderly patients susceptible to falls. Our results indicate that the probability of unplanned readmission is higher for patients with specific characteristics that should be taken into consideration in interventions designed to reduce this burden.

A Multicenter Validation of the Modified Brain Injury Guidelines (mBIG): Are They Safe and Effective?

BACKGROUND

The modified Brain Injury Guidelines (mBIG) are an algorithm for treating patients with traumatic brain injury (TBI) and intracranial hemorrhage (ICH) by which selected patients do not require a repeat head CT, a neurosurgery consult, or even an admission. The mBIG refined the original Brain Injury Guidelines (BIG) to improve safety and reproducibility. The purpose of this study is to assess safety and resource utilization with mBIG implementation.

METHODS

The mBIG were implemented at three level 1 trauma centers in 8/2017. A multicenter retrospective review of prospectively collected data was performed on adult mBIG 1 and 2 patients. The post mBIG implementation period (8/2017-2/2021) was compared to a previous BIG retrospective evaluation (1/2014-12/2016).

RESULTS

There were 764 patients in the two study periods. No differences were identified in demographics, ISS, or admission GCS. Fewer CT scans (2 [1,2] vs 2 [2,3], p < 0.0001) and neurosurgery consults (61.9% vs 95.9%, p < 0.0001) were obtained post mBIG implementation. Hospital (2 [1,4] vs 2 [2,4], p = 0.013) and ICU (0 [0,1] vs 1 [1,2], p < 0.0001) length of stay were shorter after mBIG implementation. No difference was seen in the rate of clinical or radiographic progression, neurosurgery operations, or mortality between the two groups.After mBIG implementation, 8 patients (1.6%) worsened clinically. Six patients that clinically progressed were discharged with GCS 15 without needing neurosurgery intervention. One patient had clinical and radiographic decompensation and required craniotomy. Another patient worsened clinically and radiographically, but due to metastatic cancer, elected to pursue comfort measures and died.

CONCLUSION

This prospective validation shows the mBIG are safe, pragmatic, and can dramatically improve resource utilization when implemented.

LEVEL OF EVIDENCE

II, Therapeutic.

Outcomes after emergency general surgery and trauma care in incarcerated individuals: an EAST multi-center study

BACKGROUND

The US incarcerates more individuals than any other country. Prisoners are the only population guaranteed health care by the US constitution, but little is known about their surgical needs. This multicenter study aimed to describe the acute care surgery (ACS) needs of incarcerated individuals.

METHODS

Twelve centers prospectively identified incarcerated patients evaluated in their emergency department (ED) by the ACS service. Centers collected diagnosis, treatment, and complications from chart review. Patients were classified as either emergency general surgery (EGS) patients or trauma patients and their characteristics and outcomes were investigated. Poisson regression accounting for clustering by center was used to calculate the relative risk (RR) of readmission, re-presentation within 90 days, and failure to follow up as an outpatient within 90 days for each cohort.

RESULTS

Over 12 months, ACS services evaluated 943 patients, 726 (80.3%) from jail, 156 (17.3%) from prison, and 22 (2.4%) from other facilities. Most were men (89.7%) with a median age of 35 years (IQR 27,47). Trauma patients comprised 54.4% (n = 513) of the cohort. Admission rates were similar for trauma (61.5%) and EGS patients (60.2%). Head injuries and facial fractures were the most common injuries, while infections were the most common EGS diagnosis. Self-harm resulted in 102 trauma evaluations (19.9%). Self-inflicted injuries were associated with increased risk of readmission (RR 4.3, 95%CI: 3.02-6.13) and reevaluation within 90 days (RR 4.96, 95%CI 3.07-8.01).

CONCLUSIONS

Incarcerated patients who present with a range of trauma and EGS conditions frequently require admission, and follow-up after hospitalization was low at the treating center. Poor follow-up coupled with high rates of assault, self-harm, mental health, and substance use disorders highlight the vulnerability of this population. Hospital and correctional facility interventions are needed to decrease self-inflicted injuries and assaults while incarcerated.

LEVEL OF EVIDENCE

Prognostic and Epidemiological, III.

Targeting zero preventable trauma readmissions

BACKGROUND

Nearly 1-in-10 trauma patients in the United States are readmitted within 30 days of discharge, with a median hospital cost of more than $8,000 per readmission. There are national efforts to reduce readmissions in trauma care, but we do not yet understand which are potentially preventable. Our study aims to quantify the potentially preventable readmissions (PPRs) in trauma care to serve as the anchor point for ongoing efforts to curb hospital readmissions and ultimately, bring preventable readmissions to zero.

METHODS

We identified inpatient hospitalizations after trauma and readmissions within 90 days in the 2017 National Readmissions Database (NRD). Potentially preventable readmissions were defined as the Agency for Healthcare Research and Quality-defined Ambulatory Care Sensitive Conditions, in addition to superficial surgical site infection, acute kidney injury/acute renal failure, and aspiration pneumonitis. Mean costs for these admissions were calculated using the NRD. A multivariable logistic regression model was used to characterize the relationship between patient characteristics and PPR.

RESULTS

A total of 1,320,083 patients were admitted for trauma care in the 2017 NRD, and 137,854 (10.4%) were readmitted within 90 days of discharge. Of these readmissions, 22.7% were potentially preventable. The mean cost was $10,001/PPR, resulting in $313,802,278 in cost to the US health care system. Of readmitted trauma patients younger than 65 years, Medicaid or Medicare patients had 2.7-fold increased odds of PPRs compared with privately insured patients. Patients of any age with congestive heart failure had 2.9 times increased odds of PPR, those with chronic obstructive pulmonary disease or complicated diabetes mellitus had 1.8 times increased odds, and those with chronic kidney disease had 1.7 times increased odds. Furthermore, as the days from discharge increased, the proportion of readmissions due to PPRs increased.

CONCLUSION

One-in-five trauma readmissions are potentially preventable, which account for more than $300 million annually in health care costs. Improved access to postdischarge ambulatory care may be key to minimizing PPRs, especially for those with certain comorbidities.

LEVEL OF EVIDENCE

Economic and value-based evaluations, level II.

Utility of 30-Day Readmission Metrics in the Burn Population: Navigating Quality Metric Limitations in Special Populations

Hospital readmission data may be a useful tool in identifying risk factors leading to higher costs of care or poorer overall outcomes. Several studies have emerged utilizing these datasets to examine the trauma and burn population, which have been unable to distinguish planned from unplanned readmissions. The 2014 Nationwide Readmissions Database was queried for 363 burn-specific ICD-9 DX codes and filtered by age and readmission status to capture the adult burn population. Additionally, burn-related excision and grafting procedures were filtered from 25 ICD-9 SG codes to distinguish planned readmissions. A total of 26,719 burn patients were identified with 781 all-cause unscheduled 30-day readmissions. Further filtering by burn-related excision and grafting procedures then identified 468 patients undergoing a burn-related excision and grafting procedure on readmission, reducing the dataset to 313 patients and identifying up to 60% of readmissions as possibly improperly coded planned readmissions. From this dataset, nonoperative management on initial admission was found to have the strongest correlation with readmission (OR 5.00; 3.33-7.14). Notably corrected data, when stratified by annual burn patient admission volume, identified a significant likelihood of readmission (OR 4.57; 2.15-9.70) of centers receiving the lowest annual number of burn patients, which was not identified in the unfiltered dataset. Healthcare performance statistics may be a powerful metric when utilized appropriately; however, these databases must be carefully applied to small and special populations. This study has determined that as many as 60% of burn patient readmissions included in prior studies may be improperly coded planned readmissions.