Failure-to-rescue after injury is associated with preventability: The results of mortality panel review of failure-to-rescue cases in trauma

Surveillance of Health Care-Associated Violence Using Natural Language Processing

BACKGROUND AND OBJECTIVES

Patient and family violent outbursts toward staff, caregivers, or through self-harm, have increased during the ongoing behavioral health crisis. These health care-associated violence (HAV) episodes are likely under-reported. We sought to assess the feasibility of using nursing notes to identify under-reported HAV episodes.

METHODS

We extracted nursing notes across inpatient units at 2 hospitals for 2019: a pediatric tertiary care center and a community-based hospital. We used a workflow for narrative data processing using a natural language processing (NLP) assisted manual review process performed by domain experts (a nurse and a physician). We trained the NLP models on the tertiary care center data and validated it on the community hospital data. Finally, we applied these surveillance methods to real-time data for 2022 to assess reporting completeness of new cases.

RESULTS

We used 70 981 notes from the tertiary care center for model building and internal validation and 19 332 notes from the community hospital for external validation. The final community hospital model sensitivity was 96.8% (95% CI 90.6% to 100%) and a specificity of 47.1% (39.6% to 54.6%) compared with manual review. We identified 31 HAV episodes in July to December 2022, of which 26 were reportable in accordance with the hospital internal criteria. Only 7 of 26 cases were reported by employees using the self-reporting system, all of which were identified by our surveillance process.

CONCLUSIONS

NLP-assisted review is a feasible method for surveillance of under-reported HAV episodes, with implementation and usability that can be achieved even at a low information technology-resourced hospital setting.

A Predictive Model of Failure to Rescue After Thoracolumbar Fusion

OBJECTIVE

Although failure to rescue (FTR) has been utilized as a quality-improvement metric in several surgical specialties, its current utilization in spine surgery is limited. Our study aims to identify the patient characteristics that are independent predictors of FTR among thoracolumbar fusion (TLF) patients.

METHODS

Patients who underwent TLF were identified using relevant diagnostic and procedural codes from the National Surgical Quality Improvement Program (NSQIP) database from 2011-2020. Frailty was assessed using the risk analysis index (RAI). FTR was defined as death, within 30 days, following a major complication. Univariate and multivariable analyses were used to compare baseline characteristics and early postoperative sequelae across FTR and non-FTR cohorts. Receiver operating characteristic (ROC) curve analysis was used to assess the discriminatory accuracy of the frailty-driven predictive model for FTR.

RESULTS

The study cohort (N = 15,749) had a median age of 66 years (interquartile range, 15 years). Increasing frailty, as measured by the RAI, was associated with an increased likelihood of FTR: odds ratio (95% confidence interval [CI]) is RAI 21-25, 1.3 [0.8-2.2]; RAI 26-30, 4.0 [2.4-6.6]; RAI 31-35, 7.0 [3.8-12.7]; RAI 36-40, 10.0 [4.9-20.2]; RAI 41- 45, 21.5 [9.1-50.6]; RAI ≥ 46, 45.8 [14.8-141.5]. The frailty-driven predictive model for FTR demonstrated outstanding discriminatory accuracy (C-statistic = 0.92; CI, 0.89-0.95).

CONCLUSION

Baseline frailty, as stratified by type of postoperative complication, predicts FTR with outstanding discriminatory accuracy in TLF patients. This frailty-driven model may inform patients and clinicians of FTR risk following TLF and help guide postoperative care after a major complication.

Failure to rescue as a patient safety indicator for neurosurgical patients: are we there yet? A systematic review

Failure to rescue (FTR) is a standardized patient safety indicator (PSI-04) developed by the Agency for Healthcare Research and Quality (AHRQ) to assess the ability of a healthcare team to prevent mortality following a major complication. However, FTR rates vary and are impacted by non-modifiable individual patient characteristics such as baseline frailty. This raises concerns regarding the validity of FTR as an objective quality metric, as not all patients have the same baseline frailty level, or physiological reserve, to recover from major complications. Literature from other surgical specialties has identified flaws in FTR and called for risk-adjusted metrics. Currently, knowledge of factors influencing FTR and its subsequent implementation in neurosurgical patients are limited. The present review assesses trends in FTR utilization to assess how FTR performs as an objective neurosurgery quality metric. This review then proposes how FTR may be best modified to optimize use in neurosurgical patients. A PubMed search was performed to identify articles published until August 9, 2023. Studies that reported FTR as an outcome in patients undergoing neurosurgical procedures were included. A qualitative assessment was performed using the Newcastle Ottawa Scale (NOS). The initial search revealed 1232 citations. After a title and abstract screen, followed by a full text screen, 12 studies met criteria for inclusion. These articles measured FTR across a total of 764,349 patients undergoing neurosurgical procedures. Five studies analyzed FTR with regard to hospital characteristics, and three studies utilized patient characteristics to predict FTR. All studies were considered high quality based on the NOS. Modifications in criteria to measure FTR are necessary since FTR depends on patient characteristics like frailty. This would allow for the incorporation of risk-adjusted FTR metrics that would aid in clinical decision making in neurosurgical patients.

The evolution of technical prerequisites and local boundary conditions for optimization of mitral valve interventions-Emphasis on skills development and institutional risk performance

This viewpoint report describes how the evolution of transcatheter mitral valve intervention (TMVI) is influenced by lessons learned from three evolutionary tracks: (1) the development of treatment from mitral valve surgery (MVS) to transcutaneous procedures; (2) the evolution of biomedical engineering for research and development resulting in predictable and safe clinical use; (3) the adaptation to local conditions, impact of transcatheter aortic valve replacement (TAVR) experience and creation of infrastructure for skills development and risk management. Thanks to developments in computer science and biostatistics, an increasing number of reports regarding clinical safety and effectiveness is generated. A full toolbox of techniques, devices and support technology is now available, especially in surgery. There is no doubt that the injury associated with a minimally invasive access reduces perioperative risks, but it may affect the effectiveness of the treatment due to incomplete correction. Based on literature, solutions and performance standards are formulated with an emphasis in technology and positive outcome. Despite references to Heart Team decision making, boundary conditions such as hospital infrastructure, caseload, skills training and perioperative risk management remain underexposed. The role of Biomedical Engineering is exclusively defined by the Research and Development (R&D) cycle including the impact of human factor engineering (HFE). Feasibility studies generate estimations of strengths and safety limitations. Usability testing reveals user friendliness and safety margins of clinical use. Apart from a certification requirement, this information should have an impact on the definition of necessary skills levels and consequent required training. Physicians Preference Testing (PPT) and use of a biosimulator are recommended. The example of the interaction between two Amsterdam heart centers describes the evolution of a professional ecosystem that can facilitate innovation. Adaptation to local conditions in terms of infrastructure, referrals and reimbursement, appears essential for the evolution of a complete mitral valve disease management program. Efficacy of institutional risk management performance (IRMP) and sufficient team skills should be embedded in an appropriate infrastructure that enables scale and offers complete and safe solutions for mitral valve disease. The longstanding evolution of mitral valve therapies is the result of working devices embedded in an ecosystem focused on developing skills and effective risk management actions.

Collaborative and Interprofessional Educational Program to Maintain Trauma-Focused Education During the COVID-19 Pandemic

Failure to rescue is prevalent among patients with traumatic injury who are admitted to medical-surgical units. These units are traditionally staffed by new graduate nurses who require mentorship and ongoing continuing education. The coronavirus disease 2019 (COVID-19) pandemic prompted nurse educators to develop and implement new methods of providing routine and just-in-time education in the hospital setting. This article describes a trauma-focused educational program with live sessions and online educational activities created with survey software. [J Contin Educ Nurs. 2023;54(6):275-280.].

Cardiac Surgery Outcomes During the COVID-19 Pandemic Worsened Across All Socioeconomic Statuses

BACKGROUND

Increasing socioeconomic distress has been associated with worse cardiac surgery outcomes. The extent to which the pandemic affected cardiac surgical access and outcomes remains unknown. We sought to examine the relationship between the COVID-19 pandemic and outcomes after cardiac surgery by socioeconomic status.

METHODS

All patients undergoing a Society of Thoracic Surgeons (STS) index operation in a regional collaborative, the Virginia Cardiac Services Quality Initiative (2011-2022), were analyzed. Patients were stratified by timing of surgery before vs during the COVID-19 pandemic (March 13, 2020). Hierarchic logistic regression assessed the relationship between the pandemic and operative mortality, major morbidity, and cost, adjusting for the Distressed Communities Index (DCI), STS predicted risk of mortality, intraoperative characteristics, and hospital random effect.

RESULTS

A total of 37,769 patients across 17 centers were included. Of these, 7269 patients (19.7%) underwent surgery during the pandemic. On average, patients during the pandemic were less socioeconomically distressed (DCI 37.4 vs DCI 41.9; P < .001) and had a lower STS predicted risk of mortality (2.16% vs 2.53%, P < .001). After risk adjustment, the pandemic was significantly associated with increased mortality (odds ratio 1.398; 95% CI, 1.179-1.657; P < .001), cost (+$4823, P < .001), and STS failure to rescue (odds ratio 1.37; 95% CI, 1.10-1.70; P = .005). The negative impact of the pandemic on mortality and cost was similar regardless of DCI.

CONCLUSIONS

Across all socioeconomic statuses, the pandemic is associated with higher cost and greater risk-adjusted mortality, perhaps related to a resource-constrained health care system. More patients during the pandemic were from less distressed communities, raising concern for access to care in distressed communities.

Deterioration Index in Critically Injured Patients: A Feasibility Analysis

INTRODUCTION

Continuous prediction surveillance modeling is an emerging tool giving dynamic insight into conditions with potential mitigation of adverse events (AEs) and failure to rescue. The Epic electronic medical record contains a Deterioration Index (DI) algorithm that generates a prediction score every 15 min using objective data. Previous validation studies show rapid increases in DI score (≥14) predict a worse prognosis. The aim of this study was to demonstrate the utility of DI scores in the trauma intensive care unit (ICU) population.

METHODS

A prospective, single-center study of trauma ICU patients in a Level 1 trauma center was conducted during a 3-mo period. Charts were reviewed every 24 h for minimum and maximum DI score, largest score change (Δ), and AE. Patients were grouped as low risk (ΔDI <14) or high risk (ΔDI ≥14).

RESULTS

A total of 224 patients were evaluated. High-risk patients were more likely to experience AEs (69.0% versus 47.6%, P = 0.002). No patients with DI scores <30 were readmitted to the ICU after being stepped down to the floor. Patients that were readmitted and subsequently died all had DI scores of ≥60 when first stepped down from the ICU.

CONCLUSIONS

This study demonstrates DI scores predict decompensation risk in the surgical ICU population, which may otherwise go unnoticed in real time. This can identify patients at risk of AE when transferred to the floor. Using the DI model could alert providers to increase surveillance in high-risk patients to mitigate unplanned returns to the ICU and failure to rescue.

Failure to Rescue in Emergency General Surgery: Impact of Fragmentation of Care

OBJECTIVE

Compare EGS patient outcomes after index and nonindex hospital readmissions, and explore predictive factors for nonindex readmission.

BACKGROUND

Readmission to a different hospital leads to fragmentation of care. The impact of nonindex readmission on patient outcomes after EGS is not well established.

METHODS

The Nationwide Readmissions Database (2017) was queried for adult patients readmitted after an EGS procedure. Patients were stratified and propensity-matched according to readmission destination: index versus nonindex hospital. Outcomes were failure to rescue (FTR), mortality, number of subsequent readmissions, overall hospital length of stay, and total costs. Hierarchical logistic regression was performed to account for clustering effect within hospitals and adjusting for patient- and hospital-level potential confounding factors.

RESULTS

A total of 471,570 EGS patients were identified, of which 79,127 (16.8%) were readmitted within 30 days: index hospital (61,472; 77.7%) versus nonindex hospital (17,655; 22.3%). After 1:1 propensity matching, patients with nonindex readmission had higher rates of FTR (5.6% vs 4.3%; P < 0.001), mortality (2.7% vs 2.1%; P < 0.001), and overall hospital costs [in $1000; 37 (27-64) vs 28 (21-48); P < 0.001]. Nonindex readmission was independently associated with higher odds of FTR [adjusted odds ratio 1.18 (1.03-1.36); P < 0.001]. Predictors of nonindex readmission included top quartile for zip code median household income [1.35 (1.08-1.69); P < 0.001], fringe county residence [1.08 (1.01-1.16); P = 0.049], discharge to a skilled nursing facility [1.28 (1.20-1.36); P < 0.001], and leaving against medical advice [2.32 (1.81-2.98); P < 0.001].

CONCLUSION

One in 5 readmissions after EGS occur at a different hospital. Nonindex readmission carries a heightened risk of FTR.

LEVEL OF EVIDENCE

Level III Prognostic.

STUDY TYPE

Prognostic.

Preventable death in trauma: A systematic review on definition and classification

PURPOSE

Trauma-related preventable death (TRPD) has been used to assess the management and quality of trauma care worldwide. However, due to differences in terminology and application, the definition of TRPD lacks validity. The aim of this systematic review is to present an overview of current literature and establish a designated definition of TRPD to improve the assessment of quality of trauma care.

METHODS

A search was conducted in PubMed, Embase, the Cochrane Library and the Web of Science Core Collection. Including studies regarding TRPD, published between January 1, 1990, and April 6, 2021. Studies were assessed on the use of a definition of TRPD, injury severity scoring tool and panel review.

RESULTS

In total, 3,614 articles were identified, 68 were selected for analysis. The definition of TRPD was divided in four categories: I. Clinical definition based on panel review or expert opinion (TRPD, trauma-related potentially preventable death, trauma-related non-preventable death), II. An algorithm (injury severity score (ISS), trauma and injury severity score (TRISS), probability of survival (Ps)), III. Clinical definition completed with an algorithm, IV. Other. Almost 85% of the articles used a clinical definition in some extend; solely clinical up to an additional algorithm. A total of 27 studies used injury severity scoring tools of which the ISS and TRISS were the most frequently reported algorithms. Over 77% of the panels included trauma surgeons, 90% included other specialist; 61% emergency medicine physicians, 46% forensic pathologists and 43% nurses.

CONCLUSION

The definition of TRPD is not unambiguous in literature and should be based on a clinical definition completed with a trauma prediction algorithm such as the TRISS. TRPD panels should include a trauma surgeon, anesthesiologist, emergency physician, neurologist, and forensic pathologist.

The potential of artificial intelligence to improve patient safety: a scoping review

Artificial intelligence (AI) represents a valuable tool that could be used to improve the safety of care. Major adverse events in healthcare include: healthcare-associated infections, adverse drug events, venous thromboembolism, surgical complications, pressure ulcers, falls, decompensation, and diagnostic errors. The objective of this scoping review was to summarize the relevant literature and evaluate the potential of AI to improve patient safety in these eight harm domains. A structured search was used to query MEDLINE for relevant articles. The scoping review identified studies that described the application of AI for prediction, prevention, or early detection of adverse events in each of the harm domains. The AI literature was narratively synthesized for each domain, and findings were considered in the context of incidence, cost, and preventability to make projections about the likelihood of AI improving safety. Three-hundred and ninety-two studies were included in the scoping review. The literature provided numerous examples of how AI has been applied within each of the eight harm domains using various techniques. The most common novel data were collected using different types of sensing technologies: vital sign monitoring, wearables, pressure sensors, and computer vision. There are significant opportunities to leverage AI and novel data sources to reduce the frequency of harm across all domains. We expect AI to have the greatest impact in areas where current strategies are not effective, and integration and complex analysis of novel, unstructured data are necessary to make accurate predictions; this applies specifically to adverse drug events, decompensation, and diagnostic errors.

Failure to rescue patients after emergency laparotomy for large bowel perforation: analysis of the National Emergency Laparotomy Audit (NELA)

Background

Past studies have highlighted variation in in-hospital mortality rates among hospitals performing emergency laparotomy for large bowel perforation. The aim of this study was to investigate whether failure to rescue (FTR) contributes to this variability.

Methods

Patients aged 18 years or over requiring surgery for large bowel perforation between 2013 and 2016 were extracted from the National Emergency Laparotomy Audit (NELA) database. Information on complications were identified using linked Hospital Episode Statistics data and in-hospital deaths from the Office for National Statistics. The FTR rate was defined as the proportion of patients dying in hospital with a recorded complication, and was examined in hospitals grouped as having low, medium or high overall postoperative mortality.

Results

Overall, 6413 patients were included with 1029 (16.0 per cent) in-hospital deaths. Some 3533 patients (55.1 per cent) had at least one complication: 1023 surgical (16.0 per cent) and 3332 medical (52.0 per cent) complications. There were 22 in-hospital deaths following a surgical complication alone, 685 deaths following a medical complication alone, 150 deaths following both a surgical and medical complication, and 172 deaths with no recorded complication. The risk of in-hospital death was high among patients who suffered either type of complication (857 deaths in 3533 patients; FTR rate 24.3 per cent): 172 deaths followed a surgical complication (FTR-surgical rate 16.8 per cent) and 835 deaths followed a medical complication (FTR-medical rate of 25.1 per cent). After adjustment for patient characteristics and hospital factors, hospitals grouped as having low, medium or high overall postoperative mortality did not have different FTR rates (P = 0.770).

Conclusion

Among patients having emergency laparotomy for large bowel perforation, efforts to reduce the risk of in-hospital death should focus on reducing avoidable complications. There was no evidence of variation in FTR rates across National Health Service hospitals in England.

Risk Factors of Fat Embolism Syndrome After Trauma: A Nested Case-Control Study With the Use of a Nationwide Trauma Registry in Japan

BACKGROUND

Fat embolism syndrome (FES) is a rare syndrome resulting from a fat embolism, which is defined by the presence of fat globules in the pulmonary microcirculation; it is associated with a wide range of symptoms.

RESEARCH QUESTION

What are the specific unknown risk factors for FES after we have controlled for basic characteristics and patient's severity?

STUDY DESIGN AND METHODS

This was a nested case-control study that used the Japan Trauma Data Bank database from 2004 and 2017. We included patients with FES and identified patients without FES as control subjects using a propensity score matching. The primary outcome was the presence of FES during a hospital stay.

RESULTS

There were 209 (0.1%) patients with FES after trauma; they were compared with 2,090 matched patients from 168,835 candidates for this study. Patients with FES had long bone and open fractures in their extremities more frequently than those without FES. Regarding treatments, patients with FES received bone reduction and fixation more than those without FES. Among patients who received bone reduction and fixation, time to operation was not different between the groups (P = .63). The overall in-hospital mortality rate was 5.8% in patients with FES and 3.4% in those without FES (P = .11). Conditional logistic regression models to identify risk factors associated with FES shows long bone and open fractures in extremities injury were associated with FES. Primary bone reduction and fixation was not associated independently with FES (OR, 1.80; 95% CI, 0.92-3.54), but delay time to the operation was associated with FES (OR, 2.21; 95% CI, 1.16-4.23).

INTERPRETATION

Long bone and open fractures in injuries to the extremities were associated with FES. Although bone reduction and fixation were not associated with FES, delay time to the operation was associated with FES.

Pulmonary complications in trauma: Another bellwether for failure to rescue?

BACKGROUND

Pulmonary complications are the most common adverse event after injury and second greatest cause of failure to rescue (death after pulmonary complications). It is not known whether readily accessible trauma center data can be used to stratify center-level performance for various complications. Performance variation between trauma centers would allow sharing of best practices among otherwise similar hospitals. We hypothesized that high-, average-, and low-performing centers for pulmonary complication and failure to rescue could be identified and that hospital factors associated with success and failure could be discovered.

METHODS

Pennsylvania state trauma registry data (2007-2015) were abstracted for pulmonary complications. Burns and age <17 were excluded. Multivariable logistic regression models were developed for pulmonary complication and failure to rescue, using demographics, comorbidities, and injuries/physiology. Expected event rates were compared with observed rates to identify outliers. Center-level variables associated with outcomes of interest were taken from the American Hospital Association Annual Survey Database and assessed for inclusion.

RESULTS

Included in the study were 283,121 patients (male [60%] blunt trauma [92%]). Of these patients, 3% (8,381 of 283,121) developed pulmonary complications (center-level range 0.18%-5.8%). The percentage of failure-to-rescue patients was 13.4% (1,120/8,381, center-level range 0.0%-22.6%). For pulmonary complications, 13 out of 27 centers were high performers (95% CI for O:E ratio <1) and 7 out of 27 were low (95% CI for an O:E ratio >1). For failure-to-rescue patients, 2 out of 27 centers were low performers and the remainder average. There was little concordance between performance for pulmonary complications and failure to rescue. Research programs, large non-teaching hospitals, those with advanced practice providers, and those with health maintenance organizations had reduced failure-to-rescue patients.

CONCLUSION

Factors associated with complications were distinct from those affecting failure to rescue and center-level success in reducing complications often did not translate into success in preventing death once they occurred. Our data demonstrate that high- and low-performing centers and the factors driving success or failure are identifiable. This work serves as a guide for comparing practices and improving outcomes with readily available data.

Cardiac complications and failure to rescue after injury in a mature state trauma system: Towards identifying opportunities for improvement

INTRODUCTION

Cardiac complications (CC) after injury are rare but contribute disproportionately to mortality. Variability in rates of CC and failure to rescue (FTR) after CC (FTR-C) within trauma systems may suggest opportunities for improvement, but we have not yet demonstrated the ability to identify high and low performers. We examined center-level rates of CC and FTR-C in a mature trauma system with the hypothesis that high-performing centers for each of these outcomes could be identified.

METHODS

Using a statewide trauma registry from 2007-2015, we developed multivariable logistic regression models on CC and FTR-C including patient demographics, physiology, comorbidity, and injury data. Predicted probabilities of each outcome were summed to generate expected event rates, which were compared to observed event rates to generate centerlevel observed-to-expected (O:E) ratios. We measured internal consistency between CC and FTR-C for centers using Cronbach's alpha.

RESULTS

Cardiac complications occurred in 5,079/278,042 (1.8%; center-level range: 0.9-3.8%) of included patients (median age 55 (IQR 34-76), 84% Caucasian, 60% male, 92% blunt, median ISS 9 (IQR5-16)). Death after CC occurred in 982/5,097 patients for an FTR-C rate of 19.3% (center-level range: 7.8-30.4%). 10/27 centers were high-performers (95% confidence interval for O:E ratio <1) for CC and 2/27 centers were high-performers for FTR-C, but internal consistency between these metrics was poor (alpha = 0.31).

CONCLUSION

Rates of CC and FTR-C vary significantly between hospitals in mature trauma systems but high-performing centers can be identified. Inconsistent performance between metrics suggests unknown institutional factors underlie performance for CC and FTR.

Number and Type of Complications Associated With Failure to Rescue in Trauma Patients

BACKGROUND

Failure to rescue (FTR) is becoming a ubiquitous metric of quality care. The aim of our study is to determine the type and number of complications associated with FTR after trauma.

METHODS

We reviewed the Trauma Quality Improvement Program including patients who developed complications after admission. Patients were divided as the following: "FTR" if the patient died or "rescued" if the patient did not die. Logistic regression was used to ascertain the effect of the type and number of complications on FTR.

RESULTS

A total of 25,754 patients were included with 972 identified as FTR. Logistic regression identified sepsis (odds ratio [OR] = 6.61 [4.72-9.27]), pneumonia (OR = 2.79 [2.15-3.64]), acute respiratory distress syndrome (OR = 4.6 [3.17-6.69]), and cardiovascular complications (OR = 24.22 [19.39-30.26]) as predictors of FTR. The odds ratio of FTR increased by 8.8 for every single increase in the number of complications.

CONCLUSIONS

Specific types of complications increase the odds of FTR. The overall complication burden will also increase the odds of FTR linearly.

LEVEL OF EVIDENCE

Level III Prognostic.

Establishing a regional pediatric trauma preventable/potentially preventable death rate

PURPOSE

Although trauma is the leading cause of death for the pediatric population, few studies have addressed the preventable/potentially preventable death rate (PPPDR) attributable to trauma.

METHODS

This is a retrospective study of trauma-related death records occurring in Harris County, Texas in 2014. Descriptive and Chi-squared tests were conducted for two groups, pediatric and adult trauma deaths in relation to demographic characteristics, mechanism of injury, death location and survival time.

RESULTS

There were 105 pediatric (age < 18 years) and 1738 adult patients. The PPPDR for the pediatric group was 21.0%, whereas the PPPDR for the adult group was 37.2% (p = 0.001). Analysis showed fewer preventable/potentially preventable (P/PP) deaths resulting from any blunt trauma mechanism in the pediatric population than in the adult population (19.6% vs. 48.4%, p < 0.001). Amongst the pediatric population, P/PP traumatic brain injury (TBI) were more common in the youngest age range (age 0-5) vs. the older (6-12 years) pediatric and adolescent (13-17 years) patients.

CONCLUSION

Our results identify areas of opportunities for improving pediatric trauma care. Although the overall P/PP death rate is lower in the pediatric population than the adult, opportunities for improving initial acute care, particularly TBI, exist.

Failure to Rescue as an Outcome Metric for Pediatric and Congenital Cardiac Catheterization Laboratory Programs: Analysis of Data From the IMPACT Registry

Background

Risk‐adjusted adverse event (AE) rates have been used to measure the quality of pediatric and congenital cardiac catheterization laboratories. In other settings, failure to rescue (FTR) has demonstrated utility as a quality metric.

Methods and Results

A multicenter retrospective cohort study was performed using data from the IMPACT (Improving Adult and Congenital Treatment) Registry between January 2010 and December 2016. A modified FTR metric was developed for pediatric and congenital cardiac catheterization laboratories and then compared with pooled AEs. The associations between patient‐ and hospital‐level factors and outcomes were evaluated using hierarchical logistic regression models. Hospital risk standardized ratios were then calculated. Rankings of risk standardized ratios for each outcome were compared to determine whether AEs and FTR identified the same high‐ and low‐performing centers. During the study period, 77 580 catheterizations were performed at 91 hospitals. Higher annual hospital catheterization volume was associated with lower odds of FTR (odds ratio: 0.68 per 300 cases; P=0.0003). No association was seen between catheterization volume and odds of AEs. Odds of AEs were instead associated with patient‐ and procedure‐level factors. There was no correlation between risk standardized ratio ranks for FTR and pooled AEs (P=0.46). Hospital ranks by catheterization volume and FTR were associated (r=−0.28, P=0.01) with the largest volume hospitals having the lowest risk of FTR.

Conclusions

In contrast to AEs, FTR was not strongly associated with patient‐ and procedure‐level factors and was significantly associated with pediatric and congenital cardiac catheterization laboratory volume. Hospital rankings based on FTR and AEs were not significantly correlated. We conclude that FTR is a complementary measure of catheterization laboratory quality and should be included in future research and quality‐improvement projects.

Failure to rescue as a center-level metric in pediatric trauma

BACKGROUND

Failure to rescue is defined as death after a complication and has been used to evaluate quality of care in adult trauma patients, but there are no published studies on failure to rescue in pediatric trauma. The aim of this study was to define the relationship among rates of mortality, complications, and failure to rescue at centers caring for pediatric (<18 years of age) trauma patients in a nationally representative database.

METHODS

We performed a retrospective cohort study of the 2015 and 2016 National Trauma Data Bank. We included patients <18 years of age with an Injury Severity Score of ≥9. We excluded centers with <50 pediatric patients or that reported no complications. We calculated the complication, failure to rescue, mortality, and precedence rates by center and divided centers into tertiles of mortality. We compared complication and failure-to-rescue rates between high and low tertiles of mortality using the Kruskal-Wallis test.

RESULTS

Of 62,190 patients from 284 centers, 2,204 patients had at least 1 complication for an overall complication rate of 4% (center level 0%-15%), and 120 patients died after a complication for an overall failure-to-rescue rate of 5% (center level 0%-67%). High-mortality centers had both higher failure-to-rescue rates (10% vs 0.6%, P < .001) and higher complication rates (5% vs 4%, P = .001) than lower-mortality hospitals. The overall precedence rate was 15% with a median rate of 0% (interquartile range 0%-25%).

CONCLUSION

Both complication and failure-to-rescue rates are low in the pediatric injury population, but both complication and failure-to-rescue rates are higher at higher-mortality centers. The low overall complication rates and precedence rates likely limit the utility of failure to rescue as a valid center-level metric in this population, but further investigation into individual failure-to-rescue cases may reveal important opportunities for improvement.

The Location and Timing of Failure-to-Rescue Events Across a Statewide Trauma System

BACKGROUND

Failure to rescue (FTR) refers to death after a major complication. Defining the optimal context in which to reduce FTR after injury requires knowledge of where and when FTR events occur.

MATERIALS AND METHODS

Retrospective observational study of patients >16 y with a minimum Abbreviated Injury Score ≥2 at all 30 level I and II Pennsylvania trauma centers (2007-2015). Location and timing of the first major complication were collected. Complication, mortality, and FTR rates were calculated by location (prehospital, emergency department, operating room, stepdown unit, interventional radiology, intensive care unit (ICU), radiology, and the surgical ward) and by postadmission day. Kruskal-Wallis and chi-squared tests were used to compare variables.

RESULTS

Major complications occurred in 15,388 of 178,602 (8.6%) patients. The median age was 58 y (interquartile range [IQR] 37-77 y), 78% were Caucasian, 68% were male, 89% were bluntly injured, and the median Injury Severity Score was 19 (IQR 10-29). Death occurred in 2512 of 15,388 patients with a major complication, for an FTR rate of 16.3%. Compared with non-FTR, FTR had earlier major complications (median day 2 [IQR 0-5 d] versus day 4 [IQR 2-8 d], P < 0.001). FTR rates were highest in the prehospital setting (42%), the operating room (33%), and the emergency department (32%), but the greatest number (1608 of 2512 total FTR events, 64%) occurred in the ICU. Pulmonary (32%) and cardiac (26%) complications most frequently contributed to FTR deaths.

CONCLUSIONS

Interventions designed to reduce FTR after injury should focus on pulmonary and cardiac complications in the ICU.

A metric of our own: Failure to rescue after trauma

BACKGROUND

Failure to rescue (FTR) is defined as death after an adverse event. The original metric was derived in elective surgical populations and reclassifies deaths not preceded by recorded adverse events as FTR cases under the assumption these deaths resulted from missed adverse events. This approach lacks face validity in trauma because patients often die without adverse events as a direct result of injury. Another common approach simply excludes deaths without recorded adverse events, but this approach reduces the reliability of the FTR metric. We hypothesized that a hybrid metric excluding expected deaths but otherwise including patients without recorded adverse events in FTR analysis would improve face validity and reliability relative to existing methods.

METHODS

Using 3 years of single-state adult trauma registry data from 30 trauma centers, we constructed 3 FTR metrics: (1) excluding deaths not preceded by adverse events (FTR-E), (2) reclassifying deaths not preceded by adverse events (FTR-R), and (3) including deaths not preceded by adverse events in FTR analysis except those with predicted mortality or greater than 50% (FTR-T). Mortality, adverse event, and FTR rates were calculated under each method, and reliability was tested using Spearman correlation for split-sample center rankings.

RESULTS

A total of 89,780 patients were included (median age, 57 years [interquartile range, 26-73 years]; 85% were white; 59% were male; 92% had blunt mechanism of injury; median Injury Severity Score, 9 [interquartile range, 5-14]). The FTR rates varied by metric (FTR-E, 11.2%; FTR-R, 31.2%; FTR-T, 21.4%), as did the proportion of deaths preceded by adverse events (FTR-E, 28%; FTR-R, 100%; FTR-T, 60%). Spit-sample reliability was higher FTR-T than FTR-E (ρ = 0.59 vs. = 0.27, p < 0.001).

CONCLUSIONS

A trauma-specific FTR metric increases face validity and reliability relative to other FTR methods that may be used in trauma populations. Future trauma outcomes studies examining FTR rates should use a metric designed for this cohort.

LEVEL OF EVIDENCE

Retrospective cohort study, outcomes, level III.