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

Early unplanned trauma readmissions in a safety net hospital are resource intensive but not due to resource limitations

BACKGROUND

In an era of decreasing reimbursements, the incentive to decrease readmissions has never been greater. It has been suggested that trauma readmission is an indicator of poor hospital care or fragmented discharge. Even though trauma readmissions are relatively low, readmissions add significant cost, tie up already limited resources and lead to worse outcomes, including mortality. The literature on trauma readmissions is sparse, and the reasons and risk factors for readmission are inconsistent across studies. If readmissions are to serve as useful indicators of quality of care, we must elucidate factors that may predict readmissions.

METHODS

We performed a retrospective review of all admissions to our urban Level I trauma center from July 1, 2012, to June 30, 2015. All patients aged 16 years or older who were discharged alive were included. We identified all unplanned readmissions that occurred within 30 days of discharge and performed an extensive chart review to determine the reasons for readmission. We performed univariate and multivariable analyses.

RESULTS

We identified 6,026 index trauma admissions, with 158 (2.6%) unplanned readmissions within 30 days of discharge. The most common reasons for readmission were disease/symptom progression (30.2%), wound complications (28.9%), and pain control (11.8%). On multivariate analysis, only Injury Severity Score (odds ratio [OR], 1.02; 95% confidence interval [CI], 1.00-1.05; p=0.016), penetrating injuries (OR, 1.9; 95% CI, 1.12-3.24; p=0.018), and smoking (OR, 1.73; 95% CI, 1.05-2.86; p=0.031) were found to be significant. Hospital length of stay, insurance status, and race were not significant.

CONCLUSION

In a resource-limited environment, we expected a lack of access to care would lead to increased trauma readmissions; however, we were still able to achieve similar readmission rates, irrespective of insurance status and race. Our trauma readmission rate is low and consistent with previously published studies. Our results at our Level I trauma center support previously published studies that found Injury Severity Score and penetrating injury to be risk factors for readmission; however, more ubiquitous risk factors, such as hospital length of stay and discharge destination, were not significant. With no consensus on the risk factors for unplanned early trauma readmission, individual trauma centers should evaluate their specific risk factors for readmission to improve patient outcomes and decrease hospital costs.

LEVEL OF EVIDENCE

Care management, level IV; Epidemiologic, level IV.

Outpatient follow-up does not prevent emergency department utilization by trauma patients

BACKGROUND

Although most trauma centers have a regularly scheduled trauma clinic, research demonstrates that trauma patients do not consistently attend follow-up appointments and often use the emergency department (ED) for outpatient care.

METHODS

A retrospective review of outpatient follow-up of adult patients admitted to the trauma service (January 2014-December 2014) at an urban level I trauma center was conducted (n = 2134).

RESULTS

A total of 219 patients (10%) were evaluated in trauma clinic after discharge from the hospital. Twenty-one percent of patients seen in trauma clinic visited the ED within 30 d compared with 12% of those not seen in clinic (P < 0.001). A total of 104 patients were readmitted within 30 d of discharge; no difference existed in the rate of hospital readmission between patients seen in clinic and those not seen in clinic (P = 0.25). Stepwise logistic regression showed that clinic follow-up was not a significant predictor of decreased ED utilization (adjusted odds ratio [OR] 1.16 [95% confidence interval 0.78-1.72], P = 0.461) and also showed that while ED use was a significant predictor of readmission (adjusted OR 216 [93-500], P < 0.001), clinic visits were not (adjusted OR 0.74 [0.33-1.69], P = 0.48).

CONCLUSIONS

Outpatient follow-up in the trauma clinic does not decrease ED utilization or hospital readmissions indicating that interventions aimed at improving access to a conventional outpatient clinic will not impact ED utilization rates. Further study is necessary to determine the best system for providing clinically appropriate and cost-effective outpatient follow-up for trauma patients.

Risk factors of adverse health outcomes after hospital discharge modifiable by clinical pharmacist interventions: a review with a systematic approach

The present review assessed the evidence on risk factors for the occurrence of adverse health outcomes after discharge (i.e. unplanned readmission or adverse drug event after discharge) that are potentially modifiable by clinical pharmacist interventions. The findings were compared with patient characteristics reported in guidelines that supposedly indicate a high risk of drug-related problems. First, guidelines and risk assessment tools were searched for patient characteristics indicating a high risk of drug-related problems. Second, a systematic PubMed search was conducted to identify risk factors significantly associated with adverse health outcomes after discharge that are potentially modifiable by a clinical pharmacist intervention. After the PubMed search, 37 studies were included, reporting 16 risk factors. Only seven of 34 patient characteristics mentioned in pertinent guidelines corresponded to one of these risk factors. Diabetes mellitus (n = 11), chronic obstructive lung disease (n = 9), obesity (n = 7), smoking (n = 5) and polypharmacy (n = 5) were the risk factors reported most frequently in the studies. Additionally, single studies also found associations of adverse health outcomes with different drug classes {e.g. warfarin [hazard ratio 1.50; odds ratio (OR) 3.52], furosemide [OR 2.25] or high beta-blocker starting doses [OR 3.10]}. Although several modifiable risk factors were found, many patient characteristics supposedly indicating a high risk of drug-related problems were not part of the assessed risk factors in the context of an increased risk of adverse health outcomes after discharge. Therefore, an obligatory set of modifiable patient characteristics should be created and implemented in future studies investigating the risk for adverse health outcomes after discharge.

Missed injuries and unplanned readmissions in pediatric trauma patients

BACKGROUND

We sought to determine the incidence and characteristics of missed injuries and unplanned readmissions at a Level-1 pediatric trauma center.

METHODS

We conducted a retrospective review of all trauma patients who presented to our ACS-verified Level-1 pediatric trauma center from 2009 to 2014.

RESULTS

Overall, there were 27 readmissions and 27 missed injuries (0.38%). Patients who were unplanned readmissions had a greater Injury Severity Score (ISS) (8.6 vs 5.2, p=0.03), had longer hospitalizations (4.9 vs 2.5days, p=0.02), and were more likely to have required operative intervention (51.9% vs 32.3%, p=0.04). Similarly, patients identified with missed injuries had a higher ISS (15.2 vs 5.2, p<0.0001), greater length of stay (12.7 vs 2.5days, p<0.0001), and were also more likely to be intubated (25.9% vs 3.6%, p<0.0001) or require critical care (48.1% vs 10.3%, p<0.0001). Seven missed injuries were in patients who were deemed nonaccidental trauma (25.9%) and significantly altered their hospital course while 10 patients (37%) required operative intervention. On multivariate analysis, only ISS was found to be an independent risk factor for readmissions and missed injuries.

CONCLUSIONS

Missed injuries and unplanned readmissions were rare occurrences among our pediatric patient population. These events, however, did result in longer hospitalizations and additional procedures. Patients with multisystem injuries and compromised physical exam are at higher risk.

LEVEL OF EVIDENCE

IV.

Trauma advanced practice provider programme development in an academic setting to optimize care coordination

Background

Benchmark data from the Trauma Quality Improvement Program (TQIP) identified an opportunity for improvement in our trauma programme. Our unexpected return to the intensive care unit (ICU) was found to be higher than the national averages and we also noticed that our readmission rate had increased. We chose to address these complications as continuous quality improvement projects. It was hypothesized that restructuring the workflow of the trauma advanced practice providers (APPs) to focus on the delivery of comprehensive clinical care would decrease return to ICU and readmission rates of trauma patients.

Methods

The development of the APP programme occurred from 2012 to 2014. First, APP daily shifts were extended to mirror the resident physicians’ coverage. Second, the APPs’ original job description was expanded from ‘task-oriented’ workflow to providing comprehensive clinical care. Third, the APPs were involved in the evaluation and decision-making process for transferring trauma patients from the ICU. Finally, the APPs implemented a new discharge process that included all information in a standardized format and a follow-up phone call 24–48 hours after discharge. The trauma registry at our verified, academic level I trauma center was use to assess our ICU and hospital readmission rates during the time we instituted the new APP workflow programme.

Results

In 2012, our ICU readmission rate was 5.7% (TQIP=1.9%) but then decreased to 4.4% in 2013 (TQIP=2.5%) and 2.1% in 2014 (TQIP=2.8%). Our hospital readmission rate was 2.0% in 2012 but then decreased to 1.38% and 0.96% over the next 2 years.

Conclusions

After extending the APP service coverage, implementing a comprehensive clinical care model and standardizing the discharge process, our unplanned return to ICU rates have decreased to below the TQIP national average and hospital readmission rates have also decreased by half.

Level of evidence

III.

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

CONTEXT

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

OBJECTIVE

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

DESIGN

Retrospective cohort analysis from Kaiser Permanente Southern California Region database.

METHODS

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

RESULTS

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

CONCLUSION

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

Hospital Readmission Through the Emergency Department

BACKGROUND

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

OBJECTIVES

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

PATIENTS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

Trauma center care is associated with reduced readmissions after injury

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

LEVEL OF EVIDENCE

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

The truth about trauma readmissions

BACKGROUND

There is a paucity of data on the causes and associated patient factors for unplanned readmissions among trauma patients.

METHODS

We examined patients admitted for traumatic injuries between 2007 and 2011 in the California State Inpatient Database. Using chi-square tests and multivariate logistic regression models, we determined rates, reasons, locations, and patient factors associated with 30-day readmissions.

RESULTS

Among 252,752 trauma discharges, the overall readmission rate was 7.56%, with 36% of readmissions occurring at a hospital different from the hospital of initial admission. Predictors of readmissions included being discharged against medical advice (odds ratio [OR]: 2.56 [2.35 to 2.76]); Charlson scores ≥2 (OR: 2.00 [1.91 to 2.10]); and age ≥45 years (OR: 1.29 [1.25 to 1.33]). Major reasons for readmissions were musculoskeletal complaints (22.29%), psychiatric conditions (9.40%), and surgical infections (6.69%).

CONCLUSIONS

Health and social vulnerabilities influence readmission among trauma patients, with many readmitted at other hospitals. Targeted interventions among high-risk patients may reduce readmissions after traumatic injuries.

The Impact of a Mandated Trauma Center Alcohol Intervention on Readmission and Cost per Readmission in Arizona

BACKGROUND

Persons appearing in trauma centers have a higher prevalence of unhealthy alcohol use than the general population. Screening and brief intervention (SBI) is designed to moderate drinking levels and avoid costly future readmissions, but few studies have examined the impact of SBI on hospital readmissions and health care costs in a trauma population.

RESEARCH DESIGN

This study uses comparative interrupted time-series and the Arizona State Inpatient Database to estimate the effect of the American College of Surgeons Committee on Trauma SBI mandate on the probability of readmission and cost per readmission in Arizona trauma centers. We compare individuals with and without an alcohol diagnosis code before and after the mandate was implemented.

RESULTS

The mandate resulted in a 2.2 percentage point reduction (44%) in the probability of readmission. Total health care and readmission costs were not affected by the mandate.

CONCLUSIONS

The estimates are consistent with a differential effect of SBI: SBI reduces readmissions among those who present with a less serious alcohol-related problem. Persons with more serious alcohol problems are less likely to respond to SBI. These higher risk individuals likely have a higher cost, which may explain the lack of change in readmission costs. Our study is a macrolevel intent-to-treat analysis of SBI's impact that corroborates the potential of SBI implied by efficacy studies in trauma centers and other settings. This study provides a framework for future research involving more states and health systems and evaluating other SBI policies.

Comorbidity-polypharmacy score predicts readmission in older trauma patients

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Risk factors for unplanned readmissions in older adult trauma patients in Washington State: a competing risk analysis

BACKGROUND

Hospital readmission is a significant contributor to increasing health care use related to caring for older trauma patients. This study was undertaken with the following aims: determine the proportion of older adult trauma patients who experience unplanned readmission, as well as risk factors for these readmissions and identify the most common readmission diagnoses among these patients.

STUDY DESIGN

We conducted a retrospective cohort study of trauma patients age 55 years and older who survived their hospitalization at a statewide trauma center between 2009 and 2010. Linking 3 statewide databases, nonelective readmission rates were calculated for 30 days, 6 months, and 1 year after index discharge. Competing risk regression was used to determine risk factors for readmission and account for the competing risk of dying without first being readmitted. Subhazard ratios (SHR) are reported, indicating the relative risk of readmission by 30 days, 6 months, and 1 year.

RESULTS

The cumulative readmission rates for the 14,536 participants were 7.9%, 18.9%, and 25.2% at 30 days, 6 months, and 1 year, respectively. In multivariable models, the strongest risk factors for readmission at 1 year (based on magnitude of SHR) were severe head injury (adjusted SHR = 1.47; 95% CI, 1.24-1.73) and disposition to a skilled nursing facility (SHR = 1.54; 95% CI, 1.39-1.71). The diagnoses most commonly associated with readmission were atrial fibrillation, anemia, and congestive heart failure.

CONCLUSIONS

In this statewide study, unplanned readmissions after older adult trauma occurred frequently up to 1 year after discharge, particularly for patients who sustained severe head trauma and who could not be discharged home independently. Examining common readmission diagnoses might inform the development of interventions to prevent unplanned readmissions.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Compliance to advanced trauma life support protocols in adult trauma patients in the acute setting

INTRODUCTION

Advanced Trauma Life Support (ATLS) protocols provide a common approach for trauma resuscitations. This was a quality review assessing compliance with ATLS protocols at a Level I trauma center; specifically whether the presence or absence of a trauma team leader (TTL) influenced adherence.

METHODS

This retrospective study was conducted on adult major trauma patients with acute injuries over a one-year period in a Level I Canadian trauma center. Data were collected from the Alberta Trauma Registry, and adherence to ATLS protocols was determined by chart review.

RESULTS

The study identified 508 patients with a mean Injury Severity Score of 24.5 (SD 10.7), mean age 39.7 (SD 17.6), 73.8% were male and 91.9% were involved in blunt trauma. The overall compliance rate was 81.8% for primary survey and 75% for secondary survey. The TTL group compared to non-TTL group was more likely to complete the primary survey (90.9% vs. 81.8%, p = 0.003), and the secondary survey (100% vs. 75%, p = 0.004). The TTL group was more likely than the non-TTL group to complete the following tasks: insertion of two large bore IVs (68.2% vs. 57.7%, p = 0.014), digital rectal exam (64.6% vs. 54.7%, p = 0.023), and head to toe exam (77% vs. 67.1%, p = 0.013). Mean times from emergency department arrival to diagnostic imaging were also significantly shorter in the TTL group compared to the non-TTL group, including times to pelvis xray (mean 68min vs. 107min, p = 0.007), CT chest (mean 133min vs. 172min, p = 0.005), and CT abdomen and pelvis (mean 136min vs. 173min, p = 0.013). Readmission rates were not significantly different between the TTL and non-TTL groups (3.5% vs. 4.5%, p = 0.642).

CONCLUSIONS

While many studies have demonstrated the effectiveness of trauma systems on outcomes, few have explored the direct influence of the TTL on ATLS compliance. This study demonstrated that TTL involvement during resuscitations was associated with improved adherence to ATLS protocols, and increased efficiency (compared to non TTL involvement) to diagnostic imaging. Findings from this study will guide future quality improvement and education for early trauma management.