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

The incidence and risk factors for unplanned readmission within 90 days after surgical treatment of spinal fractures

INTRODUCTION

Unplanned readmissions after spine surgery are undesired, and cause significant functional, and financial distress to the patients and healthcare system. Though critical, knowledge about readmissions after surgery for traumatic spinal injuries (TSI) is scarce and under-evaluated.

METHODS

Consecutive patients surgically treated for TSI and who had unplanned readmission within 90 days post-discharge were studied. Peri-operative demographic and surgical variables, surgical treatment, level of injury, delay in surgery, ASIA score, other organ injuries, peri-operative complications, smoking, ICU stay, co-morbidity, and the length of hospital stay were studied and correlated with the causes for readmission.

RESULTS

Among 884 patients, 4.98% (n = 44) had unplanned readmissions within 90 days of discharge. Notably, 50% (n = 22) patients were readmitted within the first 30 days. The common causes of readmissions were urinary tract related problems (27%, n = 12), pressure ulcers (20.4%, n = 9), respiratory problems (13.6%, n = 6), surgical wound related problems (14%, n = 7,) limb injuries (11.4%, n = 5), and others (11%, n = 5). The total beds lost secondary to readmissions was 314 days, and the mean bed-days lost per patient was 7.2 ± 5.1. Thirteen peri-operative risk factors were associated with unplanned readmissions, among which, smoking (OR 2.2), diabetes (OR 2.4), and pressure sore during index admission (OR 16.7) were strong independent predictors.

CONCLUSION

The incidence of unplanned readmissions after TSI was 5%, which was similar to elective spine surgeries but the causes and risk factors are different. Non-surgical complications related to urinary tract, respiratory care and pressure sores were the most common causes. Pre-operative smoking status, diabetes mellitus and pressure sores noted in the index admission were important independent risk factors.

Fragmentation of Care After Geriatric Trauma: A Nationwide Analysis of outcomes and Predictors

The health care system for the elderly is fragmented, that is worsened when readmission occurs to different hospitals. There is limited investigation into the impact of fragmentation on geriatric trauma patient outcomes. The aim of this study was to compare the outcomes following readmissions after geriatric trauma. The Nationwide Readmissions Database (2016-2017) was queried for elderly trauma patients (aged ≥65 years) readmitted due to any cause. Patients were divided into 2 groups according to readmission: index vs non-index hospital. Outcomes were 30 and 180-day complications, mortality, and the number of subsequent readmissions. Multivariable logistic regression was performed to analyze the independent predictors of fragmentation of care. A total of 36,176 trauma patients were readmitted, of which 3856 elderly patients (aged ≥65 years) were readmitted: index hospital (3420; 89%) vs non-index hospital (436; 11%). Following 1:2 propensity matching, elderly with non-index hospital readmission had higher rates of death and MI within 180 days (P = .01 and .02, respectively). They had statistically higher 30 and 180-day pneumonia (P < .01), CHF (P < .01), arrhythmias (P < .01), MI (P < .01), sepsis (P < .01), and UTI (P < .01). On multivariable binary logistic regression analysis, pneumonia (OR 1.70, P = .03), congestive heart failure (CHF) (OR 1.80, P = .03), female gender (OR .72, P = .04), and severe Head and Neck trauma (AIS≥3) (OR 1.50, P < .01) on index admission were independent predictors of fragmentation of care. While the increase in time to readmission (OR 1.01, P < .01) was also associated independently with non-index hospital admission. Fragmented care after geriatric trauma could be associated with higher mortality and complications.

Readmission after thoracic endovascular aortic repair following blunt thoracic aortic injury

PURPOSE

Thoracic endovascular aortic repair (TEVAR) is increasingly utilized to treat blunt thoracic aortic injury (BTAI), but post-discharge outcomes remain underexplored. We examined 90-day readmission in patients treated with TEVAR following BTAI.

METHODS

Adult patients discharged alive after TEVAR for BTAI in the Nationwide Readmissions Database between 2016 and 2019 were included. Outcomes examined were 90-day non-elective readmission, primary readmission reasons, and 90-day mortality. As a complementary analysis, 90-day outcomes following TEVAR for BTAI were compared with those following TEVAR for acute type B aortic dissection (TBAD).

RESULTS

We identified 2085 patients who underwent TEVAR for BTAI. The median age was 43 years (IQR, 29-58), 65% of all patients had an ISS ≥ 25, and 13% were readmitted within 90 days. The main primary causes for readmission were sepsis (8.8%), wound complications (6.7%), and neurological complications (6.5%). Two patients developed graft thrombosis as primary readmission reasons. Compared with acute TBAD patients, BTAI patients had a significantly lower rate of readmission within 90 days (BTAI vs. TBAD; 13% vs. 29%; p < .001).

CONCLUSION

We found a significant proportion of readmission in patients treated with TEVAR for BTAI. However, the 90-day readmission rate after TEVAR for BTAI was significantly lower compared with acute TBAD, and the common cause for readmission was not related to residual aortic disease or vascular devices. This represents an important distinction from other patient populations treated with TEVAR for acute vascular conditions. Elucidating differences between trauma-related TEVAR readmissions and non-traumatic indications better informs both the clinician and patients of expected post-discharge course. Level of evidence/study type: IV, Therapeutic/care management.

Stepped collaborative care versus American College of Surgeons Committee on Trauma required screening and referral for posttraumatic stress disorder: Clinical trial protocol

BACKGROUND

Each year in the US, approximately 1.5-2.5 million individuals are so severely injured that they require inpatient hospital admissions. The American College of Surgeons Committee on Trauma (College) now requires that trauma centers have in place protocols to identify and refer hospitalized patients at risk injury psychological sequelae. Literature review revealed no investigations that have identified optimal screening, intervention, and referral procedures in the wake of the College requirement.

METHODS

The single-site pragmatic trial investigation will individually randomize 424 patients (212 intervention and 212 control) to a brief stepped care intervention versus College required mental health screening and referral control conditions. Blinded follow-up interviews at 1-, 3-, 6-, and 12-months post-injury will assess the symptoms of PTSD and related comorbidity for all patients. The emergency department information exchange (EDIE) will be used to capture population-level automated emergency department and inpatient utilization data for the intent-to-treat sample. The investigation aims to test the primary hypotheses that intervention patients will demonstrate significant reductions in PTSD symptoms and emergency department/inpatient utilization when compared to control patients. The study incorporates a Rapid Assessment Procedure-Informed Clinical Ethnography (RAPICE) implementation process assessment.

CONCLUSIONS

The overarching goal of the investigation is to advance the sustainable delivery of high-quality trauma center mental health screening, intervention, and referral procedures for diverse injury survivors. An end-of-study policy summit will harness pragmatic trial data to inform the capacity for US trauma centers to implement high-quality acute care mental health screening, intervention and referral services for diverse injured patient populations.

TRIAL REGISTRATION

Clinicaltrials.govNCT05632770.

On Scene Injury Severity Prediction (OSISP) model for trauma developed using the Swedish Trauma Registry

BACKGROUND

Providing optimal care for trauma, the leading cause of death for young adults, remains a challenge e.g., due to field triage limitations in assessing a patient's condition and deciding on transport destination. Data-driven On Scene Injury Severity Prediction (OSISP) models for motor vehicle crashes have shown potential for providing real-time decision support. The objective of this study is therefore to evaluate if an Artificial Intelligence (AI) based clinical decision support system can identify severely injured trauma patients in the prehospital setting.

METHODS

The Swedish Trauma Registry was used to train and validate five models - Logistic Regression, Random Forest, XGBoost, Support Vector Machine and Artificial Neural Network - in a stratified 10-fold cross validation setting and hold-out analysis. The models performed binary classification of the New Injury Severity Score and were evaluated using accuracy metrics, area under the receiver operating characteristic curve (AUC) and Precision-Recall curve (AUCPR), and under- and overtriage rates.

RESULTS

There were 75,602 registrations between 2013-2020 and 47,357 (62.6%) remained after eligibility criteria were applied. Models were based on 21 predictors, including injury location. From the clinical outcome, about 40% of patients were undertriaged and 46% were overtriaged. Models demonstrated potential for improved triaging and yielded AUC between 0.80-0.89 and AUCPR between 0.43-0.62.

CONCLUSIONS

AI based OSISP models have potential to provide support during assessment of injury severity. The findings may be used for developing tools to complement field triage protocols, with potential to improve prehospital trauma care and thereby reduce morbidity and mortality for a large patient population.

Relationship between systolic blood pressure and mortality in older vs younger trauma patients - a retrospective multicentre observational study

BACKGROUND

The population of older trauma patients is increasing. Those patients have heterogeneous presentations and need senior-friendly triaging tools. Systolic blood pressure (SBP) is commonly used to assess injury severity, and some authors advocated adjusting SBP threshold for older patients. We aimed to describe and compare the relationship between mortality and SBP in older trauma patients and their younger counterparts.

METHODS

We included patients admitted to three level-I trauma centres and performed logistic regressions with age and SBP to obtain mortality curves. Multivariable Logistic regressions were performed to measure the association between age and mortality at different SBP ranges. Subgroup analyses were conducted for major trauma and severe traumatic brain injury admissions.

RESULTS

A total of 47,661 patients were included, among which 12.9% were aged 65-74 years and 27.3% were ≥ 75 years. Overall mortality rates were 3.9%, 8.1%, and 11.7% in the groups aged 16-64, 65-74, and ≥ 75 years, respectively. The relationship between prehospital SBP and mortality was nonlinear (U-shape), mortality increased with each 10 mmHg SBP decrement from 130 to 50 mmHg and each 10-mmHg increment from 150 to 220 mmHg across all age groups. Older patients were at higher odd for mortality in all ranges of SBP. The highest OR in patients aged 65-74 years was 3.67 [95% CI: 2.08-6.45] in the 90-99 mmHg SBP range and 7.92 [95% CI: 5.13-12.23] for those aged ≥ 75 years in the 100-109 mmHg SBP range.

CONCLUSION

The relationship between SBP and mortality is nonlinear, regardless of trauma severity and age. Older age was associated with a higher odd of mortality at all SBP points. Future triage tools should therefore consider SBP as a continuous rather than a dichotomized predictor.

Injury-related emergency department visits and unplanned readmissions are associated with worse long-term mental and physical health

BACKGROUND

The risk factors for unplanned emergency department (ED) visits and readmission after injury and the impact of these unplanned visits on long-term outcomes are not well understood. We aim to: 1) describe the incidence of and risk factors for injury-related ED visits and unplanned readmissions following injury and, 2) explore the relationship between these unplanned visits and mental and physical health outcomes 6-12 months post-injury.

METHODS

Trauma patients with moderate-to-severe injury admitted to one of three Level-I trauma centers were asked to complete a phone survey to assess mental and physical health outcomes at 6-12 months. Patient reported data on injury-related ED visits and readmissions was collected. Multivariable regression analyses were performed controlling for sociodemographic and clinical variables to compare subgroups.

RESULTS

Of 7,781 eligible patients, 4675 were contacted and 3,147 completed the survey and were included in the analysis. 194 (6.2%) reported an unplanned injury-related ED visit and 239 (7.6%) reported an injury-related readmission. Risk factors for injury-related ED visits included: younger age, Black race, a lower level of education, Medicaid insurance, baseline psychiatric or substance abuse disorder and penetrating mechanism. Risk factors for unplanned injury-related readmission included younger age, male sex, Medicaid insurance, substance abuse disorder, greater injury severity and penetrating mechanism of injury. Injury-related ED visits and readmissions were associated with significantly higher rates of PTSD, chronic pain and new injury-related functional limitations in addition to lower SF-12 mental and physical composite scores.

CONCLUSIONS

Injury-related ED visits and unplanned readmissions are common after hospital discharge following treatment of moderate-severe injury and are associated with worse mental and physical health outcomes.

Retrospective Analysis of Causes and Risk Factors of 30-Day Readmission After Spine Surgery for Thoracolumbar Trauma

STUDY DESIGN

Retrospective Case Series.

OBJECTIVE

This study aims to evaluate readmission rates, risk factors, and reason for unplanned 30-day readmissions after thoracolumbar spine trauma surgery.

METHODS

A retrospective chart review was conducted for patients undergoing operative treatment for thoracic or lumbar trauma with open or minimally invasive surgical approach at a Level 1 urban trauma center. Patients were divided into two groups based on 30-day readmission status. Reason for readmission, reoperation rates, injury type, trauma severity, and incidence of polytrauma were compared between the two groups.

RESULTS

A total of 312 patients, 69.9% male with an average age of 47 ± 19 years were included. The readmitted group included 16 patients (5.1%) of which 9 (56%) were readmitted for medical complications and 7 for surgical complications. Wound complications (31.3% of readmissions) were the most common cause of readmission, followed by non-wound related sepsis (18.9% of readmissions). A total of 6 patients (37.5%) required reoperation; 2 instrumentation failures underwent revision surgery, and 4 wound complications underwent irrigation and debridement. Patients with higher Injury Severity Scale (ISS) were more likely to be readmitted (27.8% vs 22.1%, P = .045). Concomitant lower limb surgery increased odds of readmission (OR, 4.40; 95% CI, 1.10-17.83; P = .037).

CONCLUSION

Spine trauma 30-day readmission rate was 5.1%, comparable to those reported in the elective spine surgery literature. Readmitted patients were more likely to sustain concomitant operative lower limb trauma. Wound complications were the most common cause of readmission, and almost half of the patients were readmitted due to surgery-related complications.

Predictors of care discontinuity in geriatric trauma patients

BACKGROUND

Readmission to a non-index hospital, or care discontinuity, has been shown to have worse outcomes among surgical patients. Little is known about its effect on geriatric trauma patients. Our goal was to determine predictors of care discontinuity and to evaluate its effect on mortality in this geriatric population.

METHODS

This was a retrospective analysis of Medicare inpatient claims (2014-2015) of geriatric trauma patients. Care discontinuity was defined as readmission within 30 days to a non-index hospital. Demographic and clinical characteristics (including readmission diagnosis category) were collected. Multivariate logistic regression analysis was performed to identify predictors of care discontinuity and to assess its association with mortality.

RESULTS

We included 754,313 geriatric trauma patients. Mean age was 82.13 years (SD, 0.50 years), 68% were male and 91% were White. There were 21,615 (2.87%) readmitted within 30 days of discharge. Of these, 34% were readmitted to a non-index hospital. Overall 30-day mortality after readmission was 25%. In unadjusted analysis, readmission to index hospitals was more likely to be due to surgical infection, GI complaints, or cardiac/vascular complaints. After adjusted analysis, predictors of care discontinuity included readmission diagnoses, patient- and hospital-level factors. Care discontinuity was not associated with mortality (OR, 0.93; 95% confidence interval, 0.86-1.01).

CONCLUSION

More than a third of geriatric trauma patients are readmitted to a non-index hospital, which is driven by readmission diagnosis, travel time and hospital characteristics. However, unlike other surgical settings, this care discontinuity is not associated with increased mortality. Further work is needed to understand the reasons for this and to determine which standardized processes of care can benefit this population.

LEVEL OF EVIDENCE

Prognostic and Epidemiological; Level IV.

Distal and Proximal Predictors of Rehospitalization Over 10 Years Among Survivors of TBI: A National Institute on Disability, Independent Living, and Rehabilitation Research Traumatic Brain Injury Model Systems Study

OBJECTIVE

To describe the rates and causes of rehospitalization over a 10-year period following a moderate-severe traumatic brain injury (TBI) utilizing the Healthcare Cost and Utilization Project (HCUP) diagnostic coding scheme.

SETTING

TBI Model Systems centers.

PARTICIPANTS

Individuals 16 years and older with a primary diagnosis of TBI.

DESIGN

Prospective cohort study.

MAIN MEASURES

Rehospitalization (and reason for rehospitalization) as reported by participants or their proxies during follow-up telephone interviews at 1, 2, 5, and 10 years postinjury.

RESULTS

The greatest number of rehospitalizations occurred in the first year postinjury (23.4% of the sample), and the rates of rehospitalization remained stable (21.1%-20.9%) at 2 and 5 years postinjury and then decreased slightly (18.6%) at 10 years postinjury. Reasons for rehospitalization varied over time, but seizure was the most common reason at 1, 2, and 5 years postinjury. Other common reasons were related to need for procedures (eg, craniotomy or craniectomy) or medical comorbid conditions (eg, diseases of the heart, bacterial infections, or fractures). Multivariable logistic regression models showed that Functional Independence Measure (FIM) Motor score at time of discharge from inpatient rehabilitation was consistently associated with rehospitalization at all time points. Other factors associated with future rehospitalization over time included a history of rehospitalization, presence of seizures, need for craniotomy/craniectomy during acute hospitalization, as well as older age and greater physical and mental health comorbidities.

CONCLUSION

Using diagnostic codes to characterize reasons for rehospitalization may facilitate identification of baseline (eg, FIM Motor score or craniotomy/craniectomy) and proximal (eg, seizures or prior rehospitalization) factors that are associated with rehospitalization. Information about reasons for rehospitalization can aid healthcare system planning. By identifying those recovering from TBI at a higher risk for rehospitalization, providing closer monitoring may help decrease the healthcare burden by preventing rehospitalization.

Mortality after discharge from a public tertiary cardiovascular referral hospital

It is critically important for stakeholders with distinct foci of attention on healthcare to understand patient evolution in the presence of an established diagnosis or with a suspected diagnosis of various diseases, specially considering death as an outcome. To study the long-term mortality of patients at a cardiovascular referral hospital. Deterministic binding (selection of pairs of registers from the hospital electronic health records and the mortality records of São Paulo state) from 2002 to 2017 was performed. Studied variables were: age, sex, hospital treatment unit where the first visit occurred (Emergency Unit, Outpatient Unit, Hospital Admissions, Diagnostics Services), treatment type, elapsed time between the first visit and death, diagnosis at first and last visits and variables related to death. Statistical Methods: descriptive, survival (with Kaplan-Meier method), correspondence and competitive risks analyses; in case of nonoccurrence of death until the end of 2017, the patients were considered alive. Statistical significance was set at values of P < .05. Median age at the first visit to the Hospital was 51.9 years. Birth locations included 4496 cities, 17.33% in São Paulo, 0.41% in Rio de Janeiro, 0.40% in Osasco, 24.04% in other cities. Sex included females (46.7%), males (44.2%), not defined (6.3%), and other (2.8%). We observed an association between diseases in ICD-10 Chapter 16 (certain conditions originating in the perinatal period) and Chapter 17 (congenital malformations, deformations, and chromosomal abnormalities), both as diagnoses and underlying causes of death, as well as between neoplasms as diagnoses and as the underlying cause of death. In this sample, there was an association between admission diagnoses and underlying causes of death, such as neoplasms, cardiovascular diseases, and congenital heart malformations. Additionally, patients who underwent a cardiac intervention had a smaller less mortality rate than those who were not operated on. There were also differences in cardiovascular mortality between distinct treatment units of the hospital ((Emergency Unit, Outpatient Unit, Hospital Admissions, Diagnostic Services).

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.

Emergency department visit patterns in the recently discharged, violently injured patient: Retrospective cohort review

BACKGROUND

Analysis of the costs associated with emergency department (ED) visits after discharge for violent injury could highlight subgroups for the development of cost-effective interventions to support healing and prevent treatment failures in violently injured patients.

METHODS

A retrospective cohort review was conducted of all patients with return ED visits within 90 days of discharge after treatment for a violent injury occurring between July 1, 2016, and June 30, 2018. Hospital costs were calculated for each incidence and analyzed against demographic and injury type variables to identify trends.

RESULTS

218 return ED visits were identified. Hospital costs showed a high frequency of low-cost visits. For more complex visits, distinct cost patterns were observed for Black and LatinX males compared to White males as a function of age.

CONCLUSIONS

Analysis of hospital cost per visit identified trends among different subgroups. Underlying etiologies presumably vary between groups, but hypothesis-driven further investigation and needs assessment is required. Understanding the driving forces behind these cost trends may aid in developing effective interventions.

Hospital readmission after blunt traumatic rib fractures

BACKGROUND

Hospital readmissions are resource intensive, associated with increased morbidity, and often used as hospital-level quality indicators. The factors that determine hospital readmission after blunt thoracic trauma have not been sufficiently defined. We sought to identify predictors of hospital readmission in patients with traumatic rib fractures.

METHODS

We performed an 8-year (2011-2019) retrospective chart review of patients with traumatic rib fractures who required unplanned readmission within 30 days of discharge at a Level 1 trauma center. Patient characteristics, injury severity, and hospital complications were examined using quantitative analysis to identify readmission risk factors.

RESULTS

There were 13,046 trauma admissions during the study period. The traumatic rib fracture cohort consisted of 3,720 patients. The cohort included 206 patients who were readmitted within 30 days of discharge. The mean age of the traumatic rib fracture cohort was 57 years, with a 6-day median length of stay. The 30-day mortality rate was 5%. Use of anticoagulation (11.0 vs. 5.4; p = 0.029), diagnosis of a psychiatric disorder (10.2 vs. 5.3; p = 0.01), active smoking (7.3 vs. 5.0; p = 0.008), associated hemothorax (8.3 vs. 5.2; p = 0.010), higher abdominal Abbreviated Injury Scale (33.3 vs. 8.4 vs. 6.5; p = 0.002), rapid response activation (8.9 vs. 5.2; p = 0.005), admission to intensive care unit (7.7 vs. 4.5; p = 0.001), and diagnosis of in-hospital pneumonia (10.1 vs. 5.4; p = 0.022) were predictors of hospital readmission. On multivariate analysis, prescribed anticoagulation (odds ratio [OR], 2.22; p = 0.033), active smoking (OR, 1.58; p = 0.004), higher abdominal Abbreviated Injury Scale (OR, 1.50; p = 0.054), and diagnosis of a psychiatric disorder (OR, 2.00; p = 0.016) predicted hospital readmission.

CONCLUSION

In patients with traumatic rib fractures, those with anticoagulant use, those who actively smoke, those with a psychiatric diagnosis, or those with associated abdominal injuries are at the highest risk of rehospitalization following discharge. Quality improvement should focus on strategies and protocols directed toward these groups to reduce nonelective readmissions.

LEVEL OF EVIDENCE

Prognostic and Epidemiological; Level IV.

Victims of Violence and Post-Discharge Adverse Events: A Prospective Modified Trauma Quality Improvement Program (TQIP) Study

Introduction

Trauma patients frequently return to an emergency department (ED) soon after discharge; often for non-urgent reasons. Social factors contribute to higher ED usage. At present, there is no standardized system for reporting of ED visits and readmissions among trauma care. We hypothesized that victims of violent crime suffer from many early post-discharge adverse events that has not been captured by current methods.

Methods

We prospectively consented and enrolled injured patients from January 1st, 2019 to December 31st, 2019. We documented 30-day post-discharge events using post-discharge phone calls and detailed chart abstraction. Patients were categorized as victims of violence (VV) or unintentional traumatic injury (UT).

Results

During the study period, 444 patients were enrolled. Fifty-one (11.5%) were victims of violence and 393 (88.5%) experienced unintentional injuries. The VV patients were younger (40.10 vs 60.36; p<0.0001), and more predominantly male (92.16% vs 57.51%; p<0.0001). Total injury severity score (ISS), critical care length of stay (LOS), and total LOS were similar. VV patients were more likely discharged home (70.59% vs 55.47%; p=0.0403). They were significantly more likely to return to an emergency department (47.06% vs 23.16%; p<0.0005) and had more total number of ED visits per patient. Readmission rates, however, were not different (21.57% vs 16.28%; p=NS). The VV patients more frequently were underinsured (72.5%, vs 20.6%, p<0.005).

Discussion

Victims of violence presented to the ED significantly more often, despite similar injury scores, LOS, and being of younger age. Of these patients, only 26.2% of ED presentations resulted in readmission, suggesting the majority of patient complaints may have been able to be managed in an office-based setting. VV had significantly more underinsured or subsidized patients. Victims of violence are vulnerable and may benefit from more resources provided in the early post-discharge period.

Determinants of long-term unplanned readmission and mortality following self-inflicted and non-self-inflicted major injury: a retrospective cohort study

PURPOSE

To describe the characteristics of major injury and identify determinants of long-term unplanned readmission and mortality after self-inflicted and non-self-inflicted injury to inform potential readmission screening.

METHOD

A retrospective cohort study of 11,269 individuals aged ≥ 15 years hospitalised for a major injury during 2013-2017 in New South Wales, Australia. Unplanned readmission and mortality up to 27-month post-injury were examined. Logistic regression was used to examine predictors of unplanned readmission.

RESULTS

During the 27-month follow-up, 2700 (24.8%) individuals with non-self-inflicted and 98 (26.1%) with self-inflicted injuries had an unplanned readmission. Individuals with an anxiety-related disorder and a non-self-inflicted injury who were discharged home were three times more likely (OR: 3.27; 95%CI 2.28-4.69) or if they were discharged to a psychiatric facility were four times more likely (OR: 4.11; 95%CI 1.07-15.80) to be readmitted. Compared to individuals aged 15-24 years, individuals aged ≥ 65 years were 3 times more likely to be readmitted (OR 3.12; 95%CI 2.62-3.70). Individuals with one (OR 1.60; 95%CI 1.39-1.84) or ≥ 2 (OR 1.88; 95%CI 1.52-2.32) comorbidities, or who had a drug-related dependence (OR 1.88; 95%CI 1.52-2.31) were more likely to be readmitted. The post-discharge age-adjusted mortality rate following a self-inflicted injury (35.6%; 95%CI 29.9-41.8) was higher than for individuals with a non-self-inflicted injury (11.0%; 95%CI 10.4-11.8).

CONCLUSIONS

Unplanned readmission after injury is associated with injury intent, age, and comorbid health. Screening for anxiety and drug-related dependence after major injury, accompanied by service referrals and post-discharge follow-up, has potential to prevent readmission.

Fragmentation of care in the blunt abdominal trauma patient: Capturing our true outcomes and impact on care

BACKGROUND

Trauma care is associated with unplanned readmissions, which may occur at facilities other than the index treatment facility. This "fragmentation of care" may be associated with adverse outcomes. We evaluated a statewide database that includes readmissions to analyze the incidence and impact of FC.

METHODS

The California Office of Statewide Health Planning and Development patient discharge data set was evaluated for calendar years 2016 to 2018. Patients 15 years or older diagnosed with blunt abdominal solid organ injury during the index admission were identified. Readmissions were evaluated postdischarge at 1, 3, and 6 months. Patients readmitted within 6 months to a facility other than the index admission facility (fragmented care [FC]) were compared with those readmitted to their index admission facility (non-FC). Logistic regression modeling was used to evaluate risk of FC.

RESULTS

Of the total 1,580 patients, there were 752 FC (47.6%) and 828 (52.4%) non-FC. Readmissions representing FC at months 1, 3, and 6 were 40.3%, 49.3%, and 53.4%, respectively. At index admission, the groups were demographically and clinically similar, with similar rates of abdominal operations and complications. Non-FC patients had a higher rate of abdominal reoperation at readmission (5.8% non-FC vs. 2.9% FC, p = 0.006). In an adjusted model, multiple readmissions (odds ratio [OR] 1.11, p = 0.014), readmission >30 days after index facility discharge (OR, 1.98; p < 0.001), and discharge to a nonmedical facility (OR, 2.46; p < 0.0001) were associated with increased odds of FC. Operative intervention at index admission was associated with lower odds of FC (OR, 0.77; p = 0.039). However, FC was not independently associated with demographic or insurance characteristics.

CONCLUSION

The rate of FC among patients with blunt abdominal injury is high. The risk of FC is mitigated when patients are managed operatively during the index admission. Trauma systems should implement measures to ensure that these patients are followed postdischarge.

LEVEL OF EVIDENCE

Prognostic and epidemiological, level III; Care management, level IV.

High occurrence of postintensive care syndrome identified in surgical ICU survivors after implementation of a multidisciplinary clinic

BACKGROUND

Postintensive care syndrome (PICS) has been identified in a large proportion of medical intensive care unit survivors; however, the occurrence surgical intensive care unit (SICU) survivors is unknown. We implemented a multidisciplinary critical care outpatient clinic (CCOC) to identify the occurrence of PICS in SICU survivors.

METHODS

Seventy acute care surgery and trauma patients, 18 years or older, who remained in the SICU for 72 hours or longer at a Level I trauma center were seen in CCOC at 2 weeks, 12 weeks, and 24 weeks after hospital discharge. The CCOC staffing included a nurse coordinator, social worker, critical care pharmacist, physical therapist, and acute care surgeon who identified PICS sequelae in their respective specialties by clinical criteria and screening questionnaires.

RESULTS

Of 82 eligible patients, 70 (85.4%) were seen at least once for 116 total visits. Forty-three (61.4%) patients suffered traumatic injuries and 27 (38.6%) underwent emergent general surgery. Sixty-seven (95.7%) demonstrated at least one PICS criterion. Over all visits, 26 (37.1%) patients presented with one PICS criterion, 24 (34.3%) patients with two, and 17 (24.3%) with three. Cognitive impairment was observed in 29 (41.4%) patients, psychiatric in 30 (42.9%), and physical symptoms in 65 (92.9%). Activity Measure for Post-Acute Care scores improved from severe impairment at admission to full function by 12 weeks postdischarge, yet 6 Minute Walk Test scores remained below age-matched references through all visits. Patients expressed mild to moderate depression based on Patient Health Questionnaire-9 scores. A medication reconciliation was completed at 96.5% (112/116) of the visits with 116 total medication recommendations. By 24 weeks following discharge, only 26.4% (14/53) of previously employed patients had resumed work.

CONCLUSION

Through the successful implementation of a multidisciplinary CCOC, this study identifies an exorbitant rate of PICS among SICU survivors.

LEVEL OF EVIDENCE

Therapeutic/epidemiological, level III.

Readmission Following Hospitalization for Traumatic Brain Injury: A Nationwide Study

OBJECTIVE

To determine whether sociodemographic and clinical factors were associated with nonelective readmission within 30 days of hospitalization for traumatic brain injury (TBI). Secondary objectives were to examine the effects of TBI severity on readmission and characterize primary reasons for readmission.

SETTING

Hospitalized patients in the United States, using the 2014 Nationwide Readmission Database.

PARTICIPANTS

All patients hospitalized with a primary diagnosis of TBI between January 1, 2014, and November 30, 2014. We excluded patients (1) with a missing or invalid length of stay or admission date, (2) who were nonresidents, and 3) who died during their index hospitalization.

DESIGN

Observational study; cohort study.

MAIN MEASURES

Survey weighting was used to compute national estimates of TBI hospitalization and nonelective 30-day readmission. Associations between sociodemographic and clinical factors with readmission were assessed using unconditional logistic regression with and without adjustment for suspected confounders.

RESULTS

There were 135 542 individuals who were hospitalized for TBI; 8.9% of patients were readmitted within 30 days of discharge. Age (strongest association for 65-74 years vs 18-24 years: adjusted odds ratio [AOR], 2.57; 95% CI: 2.02-3.27), documentation of a fall (AOR, 1.24; 95% CI: 1.13-1.35), and intentional self-injury (AOR, 3.13; 95% CI: 1.88-5.21) at the index admission were positively associated with readmission. Conversely, history of a motor vehicle (AOR, 0.69; 95% CI: 0.62-0.78) or cycling (AOR, 0.56; 95% CI: 0.40-0.77) accident was negatively associated with readmission. Females were also less likely to be readmitted following hospitalization for a TBI (AOR, 0.87; 95% CI: 0.82-0.92).

CONCLUSIONS

Many sociodemographic and clinical factors were found to be associated with acute readmission following hospitalizations for TBI. Future studies are needed to determine the extent to which readmissions following TBI hospitalizations are preventable.

Derivation and validation of actionable quality indicators targeting reductions in complications for injury admissions

PURPOSE

Approximately, one out of five patients hospitalized following injury will develop at least one hospital complication, more than three times that observed for general admissions. We currently lack actionable Quality Indicators (QI) targeting specific complications in this population. We aimed to derive and validate QI targeting hospital complications for injury admissions and develop algorithms to identify patient charts to review.

METHODS

We conducted a retrospective cohort study including patients with major trauma admitted to any level I or II adult trauma center an integrated Canadian trauma system (2014-2019). We used the trauma registry to develop five QI targeting deep vein thrombosis/pulmonary embolism (DVT/PE), decubitus ulcers, delirium, pneumonia and urinary tract infection (UTI). We developed algorithms to identify patient charts to revise on consultation with a group of clinical experts.

RESULTS

The study population included 14,592 patients of whom 5.3% developed DVT or PE, 2.7% developed a decubitus ulcer, 8.6% developed delirium, 14.7% developed pneumonia and 7.3% developed UTI. The indicators demonstrated excellent predictive performance (Area Under the Curve 0.81-0.87). We identified 4 hospitals with a higher than average incidence of at least one of the targeted complications. The algorithms identified on average 50 and 20 charts to be reviewed per year for level I and II centers, respectively.

CONCLUSION

In line with initiatives to improve the quality of trauma care, we propose QI targeting reductions in hospital complications for injury admissions and algorithms to generate case lists to facilitate the review of patient charts.

Association of Psychosocial Factors and Hospital Complications with Risk for Readmission After Trauma

BACKGROUND

Unplanned hospital readmissions are associated with morbidity and high cost. Existing literature on readmission after trauma has focused on how injury characteristics are associated with readmission. We aimed to evaluate how psychosocial determinants of health and complications of hospitalization combined with injury characteristics affect risk of readmission after trauma.

MATERIALS AND METHODS

We conducted a retrospective cohort study of adult trauma admissions from July 2015 to September 2017 to Harborview Medical Center in Seattle, Washington. We assessed patient, injury, and hospitalization characteristics and estimated associations between risk factors and unplanned 30-d readmission using multivariable generalized linear Poisson regression models.

RESULTS

Of 8916 discharged trauma patients, 330 (3.7%) had an unplanned 30-d readmission. Patients were most commonly readmitted with infection (41.5%). Independent risk factors for readmission among postoperative patients included public insurance (adjusted Relative Risk (aRR) 1.34, 95% CI 1.02-1.76), mental illness (aRR 1.39, 1.04-1.85), and chronic renal failure (aRR 2.17, 1.39-3.39); undergoing abdominal, thoracic, or neurosurgical procedures; experiencing an index hospitalization surgical site infection (aRR 4.74, 3.00-7.50), pulmonary embolism (aRR 3.38, 2.04-5.60), or unplanned ICU readmission (aRR 1.74, 1.16-2.62); shorter hospital stay (aRR 0.98/d, 0.97-0.99), and discharge to jail (aRR 4.68, 2.63-8.35) or a shelter (aRR 4.32, 2.58-7.21). Risk factors varied by reason for readmission. Injury severity, trauma mechanism, and body region were not independently associated with readmission risk.

CONCLUSIONS

Psychosocial factors and hospital complications were more strongly associated with readmission after trauma than injury characteristics. Improved social support and follow-up after discharge for high-risk patients may facilitate earlier identification of postdischarge complications.

Improving transition from inpatient rehabilitation following traumatic brain injury: Protocol for the BRITE pragmatic comparative effectiveness trial

Moderate to severe traumatic brain injury (TBI) is a common cause of long-term disability. Due to challenges that include inconsistent access to follow-up care, persons with TBI being discharged from inpatient rehabilitation facilities (IRFs) are at risk for rehospitalization, poor reintegration into the community, family stress, and other unfavorable outcomes resulting from unmet needs. In a six-center randomized pragmatic comparative effectiveness study, the BRITE trial (Brain Injury Rehabilitation: Improving the Transition Experience, ClinicalTrials.govNCT03422276), we compare the effectiveness of two existing methods for transition from IRF to community living or long-term nursing care. The Rehabilitation Discharge Plan (RDP) includes patient/family education and referrals for continued care. The Rehabilitation Transition Plan (RTP) provides RDP plus individualized, manualized care management via phone or videoconference, for 6 months. Nine hundred patients will be randomized (1:1) to RDP or RTP, with caregivers also invited to participate and contribute caregiver-reported outcomes. Extensive stakeholder input, including active participation of persons with TBI and their families, has informed all aspects of trial design and implementation planning. We hypothesize that RTP will result in better patient- and caregiver-reported outcomes (societal participation, quality of life, caregiver well-being) and more efficient use of healthcare resources at 6-months (primary outcome) and 12-months post-discharge, compared to RDP alone. Planned analyses will explore which participants benefit most from each transition model. With few exclusion criteria and other pragmatic features, the findings of this trial are expected to have a broad impact on improving transitions from inpatient TBI rehabilitation. TRIAL REGISTRATION: ClinicalTrials.gov identifier NCT03422276.

Australian Injury Comorbidity Indices (AICIs) to predict burden and readmission among hospital-admitted injury patients

BACKGROUND

Existing comorbidity measures predict mortality among general patient populations. Due to the lack of outcome specific and patient-group specific measures, the existing indices are also applied to non-mortality outcomes in injury epidemiology. This study derived indices to capture the association between comorbidity, and burden and readmission outcomes for injury populations.

METHODS

Injury-related hospital admissions data from July 2012 to June 2014 (161,334 patients) for the state of Victoria, Australia were analyzed. Various multivariable regression models were run and results used to derive both binary and weighted indices that quantify the association between comorbidities and length of stay (LOS), hospital costs and readmissions. The new and existing indices were validated internally among patient subgroups, and externally using data from the states of New South Wales and Western Australia.

RESULTS

Twenty-four comorbidities were significantly associated with overnight stay, twenty-seven with LOS, twenty-eight with costs, ten with all-cause and eleven with non-planned 30-day readmissions. The number of and types of comorbidities, and their relative impact were different to the associations established with the existing Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Measure (ECM). The new indices performed equally well to the long-listed ECM and in certain instances outperformed the CCI.

CONCLUSIONS

The more parsimonious, up to date, outcome and patient-specific indices presented in this study are better suited for use in present injury epidemiology. Their use can be trialed by hospital administrations in resource allocation models and patient classification models in clinical settings.

Prediction of 7-Day Readmission Risk for Pediatric Trauma Patients

BACKGROUND

Pediatric patients admitted for trauma may have unique risk factors of unplanned readmission and require condition-specific models to maximize accuracy of prediction. We used a multicenter data set on trauma admissions to study risk factors and predict unplanned 7-day readmissions with comparison to the 30-day metric.

METHODS

Data from 28 hospitals in the United States consisting of 82,532 patients (95,158 encounters) were retrieved, and 75% of the data were used for building a random intercept, mixed-effects regression model, whereas the remaining were used for evaluating model performance. The variables included were demographics, payer, current and past health care utilization, trauma-related and other diagnoses, medications, and surgical procedures.

RESULTS

Certain conditions such as poisoning and medical/surgical complications during treatment of traumatic injuries are associated with increased odds of unplanned readmission. Conversely, trauma-related conditions, such as trauma to the thorax, knee, lower leg, hip/thigh, elbow/forearm, and shoulder/upper arm, are associated with reduced odds of readmission. Additional predictors include the current and past health care utilization and the number of medications. The corresponding 7-day model achieved an area under the receiver operator characteristic curve of 0.737 (0.716, 0.757) on an independent test set and shared similar risk factors with the 30-day version.

CONCLUSIONS

Patients with trauma-related conditions have risk of readmission modified by the type of trauma. As a result, additional quality of care measures may be required for patients with trauma-related conditions that elevate their risk of readmission.

A comparative effectiveness trial of an information technology enhanced peer-integrated collaborative care intervention versus enhanced usual care for US trauma care systems: Clinical study protocol

Annually approximately 2-3 million Americans are so severely injured that they require inpatient hospitalization. The study team, which includes patients, clinical researchers, front-line provider and policy maker stakeholders, has been working together for over a decade to develop interventions that target improvements for US trauma care systems nationally. This pragmatic randomized trial compares a multidisciplinary team collaborative care intervention that integrates front-line trauma center staff with peer interventionists, versus trauma team notification of patient emotional distress with mental health consultation as enhanced usual care. The peer-integrated collaborative care intervention will be supported by a novel emergency department exchange health information technology platform. A total of 424 patients will be randomized to peer-integrated collaborative care (n = 212) and surgical team notification (n = 212) conditions. The study hypothesizes that patient's randomized to peer integrated collaborative care intervention will demonstrate significant reductions in emergency department health service utilization, severity of patient concerns, post traumatic stress disorder symptoms, and physical limitations when compared to surgical team notification. These four primary outcomes will be followed-up at 1- 3-, 6-, 9- and 12-months after injury for all patients. The Rapid Assessment Procedure Informed Clinical Ethnography (RAPICE) method will be used to assess implementation processes. Data from the primary outcome analysis and implementation process assessment will be used to inform an end-of-study policy summit with the American College of Surgeons Committee on Trauma. The policy summit will facilitate acute care practice changes related to patient-centered care transitions over the course of a single 5-year funding cycle. Trial registration: (Clinicaltrials.govNCT03569878).

Readmissions after nonoperative trauma: Increased mortality and costs with delayed intervention

BACKGROUND

We sought to examine patterns of readmission after nonoperative trauma, including rates of delayed operative intervention and mortality.

METHODS

The Nationwide Readmissions Database (2013-2014) was queried for all adult trauma admissions and 30-day readmissions. Index admissions were classified as operative (OI) or nonoperative (NOI), and readmissions examined for major operative intervention (MOR). Multivariable regression modeling was used to evaluate risk for readmission requiring MOR and in-hospital mortality.

RESULTS

Of 2,244,570 trauma admissions, there were 59,573 readmissions: 66% after NOI, and 35% after OI. Readmission rate was higher after NOI compared with OI (3.6% vs. 1.7% p < 0.001). Readmitted NOI patients were older, with a higher proportion of Injury Severity Score ≥15 and were readmitted earlier (NOI median 8 days vs. OI 11 days). Thirty-one percent of readmitted NOI patients required MOR and experienced higher overall mortality compared with OI patients with operative readmission (NOI 2.9% vs. OI 2%, p = 0.02). Intracranial hemorrhage was an independent risk factor for NOI readmission requiring MOR in both the overall (hazard ratio, 1.11; 95% confidence interval [CI], 1.01-1.22) and Injury Severity Score of 15 or greater cohorts (hazard ratio, 1.46; 95% CI, 1.24-1.7), with a predominance of nonspine neurosurgical procedures (20.3% and 55.1%, respectively). Operative readmission after NOI cost a median of $17,364 (interquartile range, US $11,481 to US $27,816) and carried a total annual cost of US $147 million (95% CI, US $141 million to $154 million).

CONCLUSIONS

Nonoperative trauma patients have a higher readmission rate than operative index patients and nearly one third require operative intervention during readmission. Operative readmission carries a higher overall mortality rate in NOI patients and together accounts for nearly US $150 million in annual costs.

LEVEL OF EVIDENCE

Epidemiological, level III.

Readmission and reinjury patterns in pediatric assault victims

INTRODUCTION

Repeated pediatric assault should be a never event. The purpose of this study was to evaluate the readmission and reinjury patterns in pediatric victims of assault including readmissions to different hospitals across the US.

METHODS

The 2010-2014 Nationwide Readmissions Database was queried for all nonelective admissions for patients under the age of 18 years. Primary outcomes were readmission or reinjury within 1 year. Results were weighted for national estimates.

RESULTS

Assault-related injury occurred in 46,294 pediatric patients with 11.4% of patients being readmitted within 1 year. Of those readmitted, 35.2% presented to a different hospital. Reinjury within 1 year occurred in about 1% of patients, with 14.8% of those presenting to a different hospital. Age < 13 years, firearm-injury, ISS > 15, female gender, and leaving AMA were found to be independent prognostic indicators of readmission within 1 year among pediatric assault patients.

CONCLUSION

Care of children who are admitted and discharged for assault injuries is more fragmented that previously thought. Quality metrics fail to capture this previously hidden population. Our results identify treatable factors which could improve the care of children after assault.

Readmissions Are Not What They Seem: Incidence and Classification of 30-Day Readmissions After Orthopedic Trauma Surgery

OBJECTIVES

To evaluate the causes of 30-day readmissions after orthopedic trauma surgery and classify them based on their relation to the index admission.

DESIGN

Retrospective chart review.

SETTING

One large, academic, medical center.

PARTICIPANTS

Patients admitted to a large, academic, medical center for a traumatic fracture injury over a 9-year period.

INTERVENTION

Assignment of readmission classification.

MAIN OUTCOME MEASURES

Readmissions within 30 days of discharge were identified and classified into orthopedic complications, medical complications, and noncomplications. A χ test was performed to assess any difference in the proportion of readmissions between the hospital-reported readmission rate and the orthopedic complication readmission rate.

RESULTS

One thousand nine hundred fifty-five patients who were admitted between 2011 and 2018 for an acute orthopedic trauma fracture injury were identified. Eighty-nine patients were readmitted within 30 days of discharge with an overall readmission rate of 4.55%. Within the 30-day readmission cohort, 30 (33.7%) were the direct result of orthopedic treatment complications, 36 (40.4%) were unrelated medical conditions, and 23 (25.8%) were noncomplications. Thus, the readmission rate directly due to orthopedic treatment complications was 1.53%. A χ test of homogeneity revealed a statistically significant difference between the hospital-reported readmission rate and the orthopedic-treatment complication readmission rate (P < 0.0005).

CONCLUSION

The use of 30-day readmissions as a measure of hospital quality of care overreports the number of preventable readmissions and penalizes surgeons and hospitals for caring for patients with less optimal health.

LEVEL OF EVIDENCE

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

Nationwide Outcomes and Risk Factors for Reinjury After Penetrating Trauma

BACKGROUND

Previous studies have shown that a notable portion of patients who are readmitted for reinjury after penetrating trauma present to a different hospital. The purpose of this study was to identify the risk factors for reinjury after penetrating trauma including reinjury admissions to different hospitals.

METHODS

The 2010-2014 Nationwide Readmissions Database was queried for patients surviving penetrating trauma. E-codes identified patients subsequently admitted with a new diagnosis of blunt or penetrating trauma. Univariable analysis was performed using 44 injury, patient, and hospital characteristics. Multivariable logistic regression using significant variables identified risk factors for the outcomes of reinjury, different hospital readmission, and in-hospital mortality after reinjury.

RESULTS

There were 443,113 patients identified. The reinjury rate was 3.5%. Patients presented to a different hospital in 30.0% of reinjuries. Self-inflicted injuries had a higher risk of reinjury (odds ratio [OR]: 2.66, P < 0.05). Readmission to a different hospital increased risk of mortality (OR: 1.62, P < 0.05). Firearm injury on index admission increased risk of mortality after reinjury (OR: 1.94, P < 0.05).

CONCLUSIONS

This study represents the first national finding that one in three patients present to a different hospital for reinjury after penetrating trauma and have a higher risk of mortality due to this fragmentation of care. These findings have implications for quality and cost improvements by identifying areas to improve continuity of care and the implementation of penetrating injury prevention programs.

[Analysis of causes and factors associated with hospital readmission in mild and moderate polythraumatism: An observational study]

BACKGROUND

Early readmissions (ER) occur during the 30 days after discharge, ER are common and expensive, associated with a decrease in the quality of care. The rate of ER in polytraumatic patients (PTP) is estimated between 4.3-15%. Our objective was to identify those factors associated with ER and its characteristics after suffering mild-moderate trauma in our area.

MATERIAL AND METHOD

This is a retrospective observational study, including data of patients with (PTP) mild or moderate admitted between July 2012 and June 2017 in our institution and their ER in public hospitals and/or outpatient centers. Demographic variables, diagnoses, procedures and characteristics of readmissions were collected. After a bivariant analysis was done, a Logistic regression had benn performed to determine risk factors for ER.

RESULTS

1013 patients were included, with median age of 38 years, ISS of 3 points and initial hospital stay of 1 day. 185 patients were readmitted (18.3%). Independent factors associated with ER were: injury mechanism, especially bicycle accident (OR 2.26), comorbidities highlighting HBP (OR 1.83) and COPD (OR 1.98), fracture immobilization (OR 1.99) and hospital admission in the initial care (OR 0.56). The causes of ER were: pain 61.6%, wound infection 15.1%, scheduled cures and deferred interventions 12.97%, medical 6.4% and psychiatric decompensation. 2.7% CONCLUSION: The ERs in mild-moderate PTP are multifactorial, our results show an association between factors such as injury mechanism, the presence of comorbidities and the procedures performed in the sentinel episode and the rate of ER. The implementation of simple interventions at discharge could reduce its incidence clearly.

Factors associated with unplanned readmissions in a major Australian health service

Objective The aim of the present study was to gain an understanding of the factors associated with unplanned hospital readmission within 28 days of acute care discharge from a major Australian health service. Methods A retrospective study of 20575 acute care discharges from 1 August to 31 December 2015 was conducted using administrative databases. Patient, index admission and readmission characteristics were evaluated for their association with unplanned readmission in ≤28 days. Results The unplanned readmission rate was 7.4% (n=1528) and 11.1% of readmitted patients were returned within 1 day. The factors associated with increased risk of unplanned readmission in ≤28 days for all patients were age ≥65 years (odds ratio (OR) 1.3), emergency index admission (OR 1.6), Charlson comorbidity index >1 (OR 1.1-1.9), the presence of chronic disease (OR 1.4) or complications (OR 1.8) during the index admission, index admission length of stay (LOS) >2 days (OR 1.4-1.8), hospital admission(s) (OR 1.7-10.86) or emergency department (ED) attendance(s) (OR 1.8-5.2) in the 6 months preceding the index admission and health service site (OR 1.2-1.6). However, the factors associated with increased risk of unplanned readmission ≤28 days changed with each patient group (adult medical, adult surgical, obstetric and paediatric). Conclusions There were specific patient and index admission characteristics associated with increased risk of unplanned readmission in ≤28 days; however, these characteristics varied between patient groups, highlighting the need for tailored interventions. What is known about the topic? Unplanned hospital readmissions within 28 days of hospital discharge are considered an indicator of quality and safety of health care. What does this paper add? The factors associated with increased risk of unplanned readmission in ≤28 days varied between patient groups, so a 'one size fits all approach' to reducing unplanned readmissions may not be effective. Older adult medical patients had the highest rate of unplanned readmissions and those with Charlson comorbidity index ≥4, an index admission LOS >2 days, left against advice and hospital admission(s) or ED attendance(s) in the 6 months preceding index admission and discharge from larger sites within the health service were at highest risk of unplanned readmission. What are the implications for practitioners? One in seven discharges resulted in an unplanned readmission in ≤28 days and one in 10 unplanned readmissions occurred within 1 day of discharge. Although some patient and hospital characteristics were associated with increased risk of unplanned readmission in ≤28 days, statistical modelling shows there are other factors affecting the risk of readmission that remain unknown and need further investigation. Future work related to preventing unplanned readmissions in ≤28 days should consider inclusion of health professional, system and social factors in risk assessments.

A systematic review and meta-analysis of 30-day readmission rates following burns

INTRODUCTION

Unplanned hospital readmissions in surgical areas account for high costs and have become an area of focus for health care providers and insurance companies. The aim of this systematic review is to identify the rate and common reasons for unplanned 30-day readmission following burns.

METHODS

This study was performed following the PRISMA guidelines. Pubmed, Web of Science and CENTRAL databases were searched for publications without date or language restrictions. Extracted outcomes included 30-day readmission rate and reasons for readmission. Pooled 30-day readmission rate was estimated from weighted individual study estimates using random-effect models. Pooled estimates for risk factors are reported as odds ratios (ORs) and 95% confidence intervals (CIs).

RESULTS

A total of eight studies were included into qualitative analysis and six (four adults, two children) into quantitative analysis. The overall readmission rate was 7.4% (95% CI 4.1-10.7) in adults and 2.7% (95% CI 2.2-3.2) in children. Based on two studies in 112,312 adult burn patients, burn size greater than 20% total body surface area (TBSA) was not a significant predictor of readmission rate (OR 1.75, 95% CI 0.64-4.75; NS). The most common reasons were infection/sepsis, wound healing complications, and pain in both adults and children.

DISCUSSION

Unplanned readmissions following burns are generally low and appear more common in adults than in pediatric patients. However, only few studies are reporting on 30-day readmission rates following burns. Evidence is limited to support a significant association between greater burn size and higher readmission rates. Since cost effectiveness and utilized hospital capacity are becoming an area of focus for improvement in health care, future studies should assess the risk factors of unplanned readmission following burns. Follow-up assessments and outpatient resources, even if not underlined by this data, could reduce readmission rates.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO: CRD42019117649.

Hospital readmissions in paediatric trauma patients: A 10-year Australian review

AIM

Readmission of paediatric trauma patients is associated with increased hospital length of stay, additional operative procedures and significant costs to the health-care system. The rates and causes of readmission of paediatric trauma patients are not well reported outside of the USA or single centres. This nation-wide study is the first in Australia to examine the readmission rates, costs and characteristics of Australian paediatric trauma patients.

METHODS

This was a retrospective examination of linked hospitalisation and mortality data for injured children aged 16 or younger from 1 July 2001 to 30 June 2012, readmitted to hospital within 28 days of discharge. Data including injury severity, nature of injury, episodes of care and costs were extracted from hospitalisation data.

RESULTS

There were 37 603 injury children aged ≤16 years readmitted to hospital within 28 days during the 10-year period, a readmission rate of 5.5%. The most common principal injury requiring readmission was fracture (52.6%) and burns (19.3%). A total of 66% of all patients had a readmission diagnosis of injury, complication of their initial injury or complication of surgical and medical care; 30% were readmitted for a specific procedure or follow-up care. The total cost of readmissions was AU$108 million.

CONCLUSIONS

Hospital readmission rates of paediatric trauma patients in Australia are due to injury or a complication of injury and are associated with significant costs. Early identification of at-risk patients and the prevention of complications are needed to prevent the ongoing burden of readmission.

Readmissions After Acute Hospitalization for Traumatic Brain Injury

BACKGROUND

Traumatic brain injury (TBI) is associated with functional deficits, impaired cognition, and medical complications that continue well after the initial injury. Many patients seek medical care at other health care facilities after discharge, rather than returning to the admitting trauma center, making assessment of readmission rates and readmission diagnoses difficult to determine. The objective of this study was to determine the incidence and factors associated with readmission to any acute care hospital after an index admission for TBI.

MATERIALS AND METHODS

The Nationwide Readmission Database was queried for all patients admitted with a TBI during the first 3 mo of 2015. Nonelective readmissions for this population were then collected for the remainder of 2015. Patients who died during the index admission were excluded. Demographic data, injury mechanism, type of TBI, the number of readmissions, days from discharge to readmission, readmission diagnosis, and mortality were studied.

RESULTS

Of the 15,277 patients with an index admission for TBI, 5296 patients (35%) required at least 1 readmission. Forty percent of readmissions occurred within the first 30 d after discharge from the index trauma admission. The most common primary diagnosis on readmission was SDH, followed by septicemia, urinary tract infection, and aspiration. Readmission rates increased with age, with 75% of readmissions occurring in patients aged >65 y. Initial discharge to a skilled nursing facility (Relative Risk [RR], 1.60) or leaving the hospital against medical advice (RR, 1.59) increased the risk of readmission. Patients with fall as their mechanism of injury and a subdural hematoma were more likely to require readmission compared with other types of mechanisms with TBI (RR, 1.59 and RR, 1.21, respectively; P < 0.001). Notably, the first readmission was to a different hospital for 39.5% of patients and 46.9% of patients had admissions to at least one facility outside that of their original presentation.

CONCLUSIONS

Hospital readmission is common for patients discharged after TBI. Elderly patients who fall with resultant subdural hematoma are at especially high risk for complications and readmission. Understanding potentially preventable causes for readmission can be used to guide discharge planning pathways to decrease morbidity in this patient population.

The role of sociodemographics in the occurrence of orthopaedic trauma

INTRODUCTION

We sought to determine the effects of sociodemographic factors on the occurrence of orthopaedic injuries in an adult population presenting to a level 1 trauma center.

MATERIALS AND METHODS

We conducted a retrospective chart review of patients who received orthopaedic trauma care at a level 1 academic trauma center.

RESULTS

20,919 orthopaedic trauma injury cases were treated at an academic level 1 trauma center between 01 January 1993 and 27 August 2017. Following application of inclusion/exclusion criteria, a total of 14,654 patients were retrieved for analysis. Out of 14,654 patients, 4602 (31.4%) belonged to low socioeconomic status (SES), 4961 (32.0%) to middle SES and 5361 (36.6%) to high SES. Following adjustment for age, sex, race, insurance status and injury severity score (ISS), patients belonging to middle SES vs. low SES (OR 0.77 [95% CI 0.63-0.94]; p = 0.009) or high SES vs. low SES (OR 0.77 [95% CI 0.62-0.95]; p = 0.016) had lower odds of receiving a penetrating injury as compared to a blunt injury.

CONCLUSION

The results from this study indicate that a link exists between sociodemographic factors and the occurrence of orthopaedic injuries presenting to a level 1 trauma center. The most common cause of injury varied within age groups, by sex, and within the different socioeconomic groups.

Complications, burden and in-hospital death among hospital treated injury patients in Victoria, Australia: a data linkage study

Background

A wide range of outcome measures can be calculated for hospital-treated injury patients. These include mortality, use of critical care services, complications, length of stay, treatment costs, readmission and nursing care after discharge. Each address different aspects and phases of injury recovery and can yield vastly different results. This study aims to: (1) measure and report this range of outcomes in hospital-treated injury patients in a defined population; and (2) describe the associations between injury characteristics, socio-demographics and comorbidities and the various outcomes.

Methods

A retrospective analysis was conducted of injury-related hospital admissions from July 2012 to June 2014 (152,835 patients) in Victoria, Australia. The admission records were linked within the dataset, enabling follow-up, to assess the outcomes of in-hospital death, burden, complications and 30-day readmissions. Associations between factors and outcomes were determined using univariate regression analysis.

Results

The proportion of patients who died in hospital was 0.9%, while 26.8% needed post-discharge care. On average patients had 2.4 complications (confidence interval (CI) 2.4–2.5) related to their initial injury, the mean cost of treating a patient was Australian dollars 7013 (CI 6929–7096) and the median length of stay was one day (inter quartile range 1–3). Intensive-care-unit-stay was recorded in 3% of the patients. All-cause 30-day readmissions occurred in 12.3%, non-planned 30-day readmissions in 7.9%, while potentially avoidable 30-day readmissions were observed in 3.2% of the patients. Increasing age was associated with all outcomes. The need for care post-discharge from hospital was highest among children and the oldest age group (85 years and over). Injury severity was associated with all adverse outcomes. Increasing number of comorbidities increased the likelihood of all outcomes. Overall, outcomes are shown to differ by age, gender, comorbidities, body region injured, injury type and injury severity, and to a lesser extent by socio-economic areas.

Conclusions

Outcomes and risk factors differ depending on the outcome measured, and the method used for measuring the outcome. Similar outcomes measured in different ways produces varying results. Data linkage has provided a valuable platform for a comprehensive overview of outcomes, which can help design and target secondary and tertiary preventive measures.

Electronic supplementary material

The online version of this article (10.1186/s12889-019-7080-y) contains supplementary material, which is available to authorized users.

Using clinical analysis to classify 30-day trauma readmissions

BACKGROUND

Unplanned hospital readmissions are common across specialties. Descriptive readmission studies commonly query large administrative databases, which some speculate lack clinical granularity. This article provides the framework for a process improvement initiative aimed at identifying clinically meaningful reasons for trauma readmission. Our study hypothesizes an expected difference between the clinically abstracted reasons for readmission and those documented by the data processing staff in the trauma registry and that those differences will be the starting point to target performance improvement.

METHODS

This is a retrospective, cohort study from 2014 to 2016 involving 18,998 trauma evaluations at a Level I trauma center. The systematic categorization of trauma readmissions was completed via clinical chart review. Readmissions were categorized following an organizational flowchart. The chart reviews ultimately resulted in two readmission categories: primary and secondary reasons for 30-day trauma readmission.

RESULTS

There were 413 readmissions, an overall readmission rate of 2.7%. The highest rate of readmission, by mechanism of injury, was gunshot wounds (11%). Secondary reasons for readmission predominated (76.1%). Complications led (41%), followed by observation (8.8%) and pain (8.6%). Following readmission chart review and categorization, the trauma registry data were queried and categorized via the same method. When the two methods of data collection were compared, there was a significant difference (p < 0.0001).

CONCLUSIONS

The granular dissection of readmission charts proved to assist in isolating clinically significant readmission variables, providing clarity into the reasons behind trauma readmission. If determined solely by the trauma registry data, our performance and quality improvement initiatives would be misguided. We recommend clinical oversight of databases, with clinical review of key areas in order to guide performance improvement.

What is the impact on the readmission ratio of taking into account readmissions to other hospitals? A cross-sectional study

OBJECTIVES

Readmissions are used widespread as an indicator of the quality of care within hospitals. Including readmissions to other hospitals might have consequences for hospitals. The aim of our study is to determine the impact of taking into account readmissions to other hospitals on the readmission ratio.

DESIGN AND SETTING

We performed a cross-sectional study and used administrative data from 77 Dutch hospitals (2 333 173 admissions) in 2015 and 2016 (97% of all hospitals). We performed logistic regression analyses to calculate 30-day readmission ratios for each hospital (the number of observed admissions divided by the number of expected readmissions based on the case mix of the hospital, multiplied by 100). We then compared two models: one with readmissions only to the same hospital, and another with readmissions to any hospital in the Netherlands. The models were calculated on the hospital level for all in-patients and, in more detail, on the level of medical specialties.

MAIN OUTCOME MEASURES

Percentage of readmissions to another hospital, readmission ratios same hospital and any hospital and C-statistic of each model in order to determine the discriminative ability.

RESULTS

The overall percentage of readmissions was 10.3%, of which 91.1% were to the same hospital and 8.9% to another hospital. Patients who went to another hospital were younger, more often men and had fewer comorbidities. The readmission ratios for any hospital versus the same hospital were strongly correlated (r=0.91). There were differences between the medical specialties in percentage of readmissions to another hospital and C-statistic.

CONCLUSIONS

The overall impact of taking into account readmissions to other hospitals seems to be limited in the Netherlands. However, it does have consequences for some hospitals. It would be interesting to explore what causes this difference for some hospitals and if it is related to the quality of care.

Trauma transitional care coordination: A mature system at work

BACKGROUND

We have previously demonstrated effectiveness of a Trauma Transitional Care Coordination (TTCC) Program in reducing 30-day readmission rates for trauma patients most at risk. With program maturation, we achieved improved readmission rates for specific patient populations.

METHODS

TTCC is a nursing driven program that supports patients at high risk for 30-day readmission. The TTCC interventions include calls to patients within 72 hours of discharge, complete medication reconciliation, coordination of medical appointments, and individualized problem solving. Account IDs were used to link TTCC patients with the Health Services Cost Review Commission database to collect data on statewide unplanned 30-day readmissions.

RESULTS

Four hundred seventy-five patients were enrolled in the TTCC program from January 2014 to September 2016. Only 10.5% (n = 50) of TTCC enrollees were privately insured, 54.5% had Medicaid (n = 259), and 13.5% had Medicare (n = 64). Seventy-three percent had Health Services Cost Review Commission severity of injury ratings of 3 or 4 (maximum severity of injury = 4). The most common All Patient Refined Diagnosis Related Groups for participants were: lower-extremity procedures (n = 67, 14%); extensive abdominal/thoracic procedures (n = 40, 8.4%); musculoskeletal procedures (n = 37, 7.8%); complicated tracheostomy and upper extremity procedures (n = 29 each, 6.1%); infectious disease complications (n = 14, 2.9%); major chest/respiratory trauma, major small and large bowel procedures and vascular procedures (n = 13 each, 2.7%). The TTCC participants with lower-extremity injury, complicated tracheostomy, and bowel procedures had 6-point reduction (10% vs. 16%, p = 0.05), 11-point reduction (13% vs. 24%, p = 0.05), and 16-point reduction (11% vs. 27%, p = 0.05) in 30-day readmission rates, respectively, compared to those without TTCC.

CONCLUSION

Targeted outpatient support for high-risk patients can decrease 30-day readmission rates. As our TTCC program matured, we reduced 30-day readmission in patients with lower-extremity injury, complicated tracheostomy and bowel procedures. This represents over one million-dollar savings for the hospital per year through quality-based reimbursement.

LEVEL OF EVIDENCE

Therapeutic/care management, level III.

Nationwide risk factors for hospital readmission for subsequent injury after motor vehicle crashes

OBJECTIVE

Some drivers involved in motor vehicle crashes across the United States may be identified as at risk of subsequent injury by a similar mechanism. The purpose of this study was to perform a national review of the risk factors for hospitalization for a new injury due to a subsequent motor vehicle crash. It was hypothesized that presenting to a different hospital after subsequent injury would result in worse patient outcomes when compared to presentation at the same hospital.

METHODS

The Nationwide Readmissions Database for 2010-2014 was queried for all inpatient hospitalizations with injury related to motor vehicle traffic. The primary patient outcome of interest was subsequent motor vehicle crash-related injury within 1 year. The secondary patient outcomes were different hospital subsequent injury presentation, higher Injury Severity Score (ISS), longer length of stay (LOS), and in-hospital death after subsequent injury. The analysis of secondary patient outcomes was performed only on patients who were reinjured. Univariable analysis was performed for each outcome using all variables during the index admission. Multivariable logistic regression was performed using all significant (P < .05) variables on univariate analysis. Results were weighted for national estimates.

RESULTS

During the study period, 1,008,991 patients were admitted for motor vehicle-related injury; 12,474 patients (1.2%) suffered a subsequent injury within 1 year. From the reinjured patients, 32.9% presented to a different hospital, 48.9% had a higher ISS, and 22.1% had a longer LOS. The in-hospital mortality rate after subsequent injury was 1.1%. Presentation to a different hospital for subsequent injury was associated with a longer LOS (odds ratio [OR] = 1.32; 95% confidence interval [CI], 1.20-1.45; P < .01) and a higher ISS (OR = 1.38; 95% CI, 1.27-1.49; P < .01). Motorcyclists were more likely to suffer subsequent injury (OR = 1.39; 95% CI, 1.32-1.46; P < .01) and motorcycle passengers were more likely to present to a different hospital with a subsequent injury (OR = 2.49; 95% CI, 1.73-3.59; P < .01). Alcohol abuse was associated with subsequent injury (OR = 1.12; 95% CI, 1.07-1.18; P < .01).

CONCLUSIONS

Nearly a third of patients suffering subsequent motor vehicle crash-related injury after an initial motor vehicle crash in the United States present to a different hospital. These patients are more likely to suffer more severe injuries and longer hospitalizations due to their subsequent injury. Future efforts to prevent these injuries must consider the impact of this fragmentation of care and the implications for quality and cost improvements.

Readmissions after Firearm Injury Requiring Vascular Repair

BACKGROUND

Firearm injuries can be morbid and potentially have high resource utilization. Historically, trauma and vascular surgery patients are at higher risk for readmissions. Our goal was to assess the risk for readmission among patients undergoing vascular repair after a firearm injury.

METHODS

The National Readmission Database was queried from 2011 to 2014. All firearm injuries with or without vascular repair were analyzed. Multivariable analysis was conducted to assess the effect of concurrent vascular repair on readmissions at 30, 90, and 180 days.

RESULTS

There were 42,184 firearm injury admissions identified, where 93.3% did not undergo vascular repair and 6.7% required vascular repair. The overall in-hospital death rate was 8.2%. Average age was 29.9 ± 0.2 years, and 89.2% were male. Intent was most frequently assault (61.2%) followed by unintentional injury (26.5%), suicide (5.2%), and legal intervention (3.1%). Patients with vascular repair compared to those without vascular repair were more frequently admitted at teaching hospitals (85.2% vs. 81.8%, P = 0.042), had higher Agency for Healthcare Research and Quality (AHRQ) extreme severity of illness, AHRQ risk of mortality, New Injury Severity Score (NISS), and had more diagnoses and procedures (P < 0.0001). Patients with vascular repair compared to those without vascular repair also more frequently sustained abdominal/pelvis injury (40.4% vs. 23.4%, P < 0.0001) and were more likely to have anemia (5.9% vs. 3.6%, P = 0.009). Patients undergoing vascular repair had a higher rate for 30-day (8.9% vs. 5.5%, P = 0.0001), 90-day (18.1% vs 9.5%, P < 0.0001), and 180-day (22.3% vs. 13%, P < 0.0001) readmission. Kaplan-Meier analysis of unadjusted data showed a higher readmission rate over time with vascular repair. Multivariable analysis demonstrated that vascular repair was not associated with higher 30-day readmission (odds ratio [OR] 1.26, 95% confidence interval [CI] 0.92-1.72, P = 0.14) but was for 90-day (OR 1.38, 95% CI 1.14-1.68, P = 0.001) and 180-day readmission (OR 1.24, 95% CI 1.06-1.45, P = 0.009). Additional factors associated with 30-day readmission were higher NISS, discharge to a care facility, and Elixhauser score. Other factors associated with 90-day readmission were unintentional intent of injury, NISS, discharge to a care facility, and Elixhauser score. Factors also associated with 180-day readmission were insurance type, unintentional intent of injury, NISS, care facility discharge, and Elixhauser score.

CONCLUSIONS

Firearm injury resulting in vascular injury was associated with increased readmissions at 90 and 180 days. This study establishes baseline rates for readmission after vascular repair for firearm traumas and allows opportunity for improvement through targeted interventions for these patients. Vascular surgeons can have a more active role in managing this high-profile public health issue.

Unwarranted clinical variation in the care of children and young people hospitalised for injury: a population-based cohort study

INTRODUCTION

Injury is a leading cause of death and disability among children and young people. Recovery may be negatively affected by unwarranted clinical variation such as representation to an emergency department (ED), readmission to a hospital, and mortality. The aim of this study was to examine unwarranted clinical variation across providers of care of children and young people who were hospitalised for injury in New South Wales (NSW).

MATERIALS AND METHODS

Retrospective population-based cohort study using linked ED, hospital, and mortality data of all children and young people aged ≤25 years who were injured and hospitalised during 1 January 2010-30 June 2014 in NSW. Unwarranted clinical variation across providers was examined using three indicators. That is, for each hospital that treated ≥100 cases per year, risk standardised ratios were calculated with 95% and 99.8% confidence limits using the number of observed and expected events of (1) representations to ED within 72 h, (2) unplanned readmissions to hospital within 28 days, and (3) all-cause mortality within 30 days.

RESULTS

There were 189,990 injury-related hospitalisations of children and young people. Of these, 4.4% represented to an ED, 8.7% were readmitted to hospital, and 0.2% died. Of the 45 public hospitals that treated ≥100 cases per year, higher than expected rates of ED representations, hospital readmissions, and mortality were observed in eleven, six, and two hospitals, respectively.

CONCLUSION

The rates of ED representations, hospital readmissions, and mortality among children and young people hospitalised for injury in NSW were similar to the rates reported in other countries. However, unwarranted clinical variation across public hospitals was observed for all three indicators. These findings suggest that by improving routine follow-up support services post-discharge for children and young people and their families, it may be possible to reduce unwarranted clinical variation and improve health outcomes.

Readmission following hypoxic ischemic brain injury: a population-based cohort study

BACKGROUND

Readmission to acute care is common and is associated with indicators of suboptimal care and health system inefficiencies. The objective of this study was to identify independent determinants of readmission following survival of hypoxic ischemic brain injury.

METHODS

We conducted a population-based retrospective cohort study using Ontario's administrative health data. Survivors of hypoxic ischemic brain injury aged 20 years or more discharged from acute care between fiscal years 2002/03 and 2010/11 were included. Multivariable negative binomial regression was used to identify independent determinants of both number of readmissions and cumulative duration of hospital stay(s) within 1 year after the index discharge.

RESULTS

Of the 593 patients with hypoxic ischemic brain injury, 233 (39.3%) were readmitted within 1 year of the index acute care discharge. The number of readmissions was associated with age (35-49 yr v. 65-79 yr: rate ratio [RR] 0.57, 95% confidence interval [CI] 0.38-0.85; ≥ 80 yr v. 65-79 yr: RR 0.58, 95% CI 0.34-0.97) and higher comorbidity score (Johns Hopkins Aggregated Diagnosis Groups score > 30 v. < 10: RR 1.60, 95% CI 1.11-2.31). Cumulative readmission stay was associated with increased index acute care length of stay (31-90 d v. ≥ 90 d: RR 4.17, 95% CI 1.38-12.64), prior use of health care services (minimal v. very high: RR 0.15, 95% CI 0.05-0.49) and discharge disposition (home v. continuing/long-term care: RR 0.44, 95% CI 0.21-0.91).

INTERPRETATION

The findings indicate a high readmission rate in the first year after the index acute care admission for survivors of hypoxic ischemic brain injury, reflecting care gaps and system inefficiencies. This suggests that bolstered discharge and home care planning and support are needed to address the specific needs of those with hypoxic ischemic brain injury.

Association of Medicaid Expansion Under the Affordable Care Act With Outcomes and Access to Rehabilitation in Young Adult Trauma Patients

Importance

Trauma is the leading cause of death and disability among young adults in the United States. Young adults are also the age group most likely to be uninsured. Implementation of Medicaid expansion through the Affordable Care Act (ACA) has increased insurance coverage, but its associations with trauma care and outcomes among young adults nationwide remain unknown. We examined whether Medicaid expansion, in its first year, was associated with changes in insurance coverage and improved outcomes in young adults hospitalized for traumatic injury.

Objective

To assess the associations of ACA Medicaid expansion with insurance coverage, in-hospital mortality, failure to rescue, access to rehabilitation, and unplanned readmissions among hospitalized young adult trauma patients across many US states.

Design, Setting, and Participants

We used the Healthcare Cost and Utilization Project State Inpatient Databases to examine changes in insurance coverage and risk adjusted outcomes among young adults (age 19 to 44 years) who were hospitalized for injuries before and after Medicaid expansion and open enrollment occurred (2012-2013 vs 2014) in 11 US states that expanded Medicaid through the ACA. We also performed difference-in-difference analyses to compare these changes between 3 expansion states and 3 non-expansion states within the same geographic region.

Results

Of the 141 187 trauma patients hospitalized across 11 Medicaid expansion states, 43 871 (31.1%) were women, and the mean (SD) age was 31.4 (7.6) years. Medicaid expansion was associated with an increase in Medicaid coverage from 16 229 individuals (16.7%) to 15 358 individuals (34.9%) (difference: 18.2% [95% CI, 16.5%-20.0%]; P < .001), a decrease in lack of insurance from 27 016 individuals (27.8%) to 5589 individuals (12.7%) (difference: -15.1% [95% CI, -16.8% to -13.5%]; P < .001), and an increase in discharge to rehabilitation from 9220 individuals (11.4%) to 4736 individuals (12.6%) (difference: 1.16% [95% CI, 0.55%-1.77%]; P < .001). We found no significant reductions in in-hospital mortality, failure to rescue, or unplanned readmissions. Similar results were found when 3 of these states were compared with 3 geographically and demographically similar states that had not enacted Medicaid expansion.

Conclusions and Relevance

The first year of implementation of Medicaid expansion and open enrollment across 11 selected US states was associated with significant increases in Medicaid coverage, reductions in uninsured rates, and increased access to postdischarge rehabilitation among young adults hospitalized for injury. However, this study found no significant reductions in in-hospital mortality, failure to rescue, or unplanned readmissions.

US pediatric trauma patient unplanned 30-day readmissions

PURPOSE

We sought to determine readmission rates and risk factors for acutely injured pediatric trauma patients.

METHODS

We produced 30-day unplanned readmission rates for pediatric trauma patients using the 2013 National Readmission Database (NRD).

RESULTS

In US pediatric trauma patients, 1.7% had unplanned readmissions within 30days. The readmission rate for patients with index operating room procedures was no higher at 1.8%. Higher readmission rates were seen in patients with injury severity scores (ISS)=16-24 (3.4%) and ISS ≥25 (4.9%). Higher rates were also seen in patients with LOS beyond a week, severe abdominal and pelvic region injuries (3.0%), crushing (2.8%) and firearm injuries (4.5%), and in patients with fluid and electrolyte disorders (3.9%). The most common readmission principal diagnoses were injury, musculoskeletal/integumentary diagnoses and infection. Nearly 39% of readmitted patients required readmission operative procedures. Most common were operations on the musculoskeletal system (23.9% of all readmitted patients), the integumentary system (8.6%), the nervous system (6.6%), and digestive system (2.5%).

CONCLUSIONS

Overall, the readmission rate for pediatric trauma patients was low. Measures of injury severity, specifically length of stay, were most useful in identifying those who would benefit from targeted care coordination resources.

LEVEL OF EVIDENCE

This is a Level III retrospective comparative study.

Effects of Medicaid expansion on disparities in trauma care and outcomes in young adults

BACKGROUND

Racial/ethnic and socioeconomic disparities in trauma care and outcomes among young adults are well documented. As the Patient Protection and Affordable Care Act Medicaid expansion has increased insurance coverage among young adults, we aimed to investigate its impact on disparities in insurance coverage and outcomes among hospitalized young adult trauma patients.

MATERIALS AND METHODS

We used the healthcare cost and utilization project state inpatient databases to examine changes in insurance coverage and risk-adjusted outcomes from before (2012-2013) to after (2014) Medicaid expansion among young adults (age 19-44) hospitalized for injury across 11 Medicaid expansion states. Changes were compared across racial/ethnic and community-level income groups. We also compared changes in disparities between three expansion and three nonexpansion states in the US south.

RESULTS

In the first year of Medicaid expansion, non-Hispanic black trauma patients experienced a large decrease in uninsurance (34.3%-14.2%, P < 0.01), reducing the disparity in uninsurance between non-Hispanic black and non-Hispanic white patients (P < 0.05). There were no differences across racial/ethnic groups in changes in in-hospital mortality, failure to rescue, discharge to rehabilitation, or 30-d unplanned readmissions. Socioeconomic disparities in discharge to rehabilitation decreased (1.63% versus 0.06% increase among patients from the lowest and highest income communities, P < 0.05). In contrast, in the selected southern states, Medicaid expansion was associated with the introduction of a disparity in discharge to inpatient rehabilitation between Hispanics and non-Hispanic whites.

CONCLUSIONS

Medicaid expansion, in its first year, decreased racial and socioeconomic disparities in uninsurance and socioeconomic disparities in access to rehabilitation.