The overlooked factor: The impact of disability on postoperative complications after emergency general surgery procedures.

BACKGROUND: Despite more than 61 million people in the United States living with a disability, studies on the impact of disability on health care disparities in surgical patients remain limited. Therefore, we aimed to understand the impact of disability on postoperative outcomes. METHODS: We performed a retrospective cohort study using the Nationwide Readmission Database (2019). We compared patients ≥18 years undergoing emergency general surgery procedures with a disability condition with those without a disability. In accordance with the Centers for Disease Control and Prevention, disability was defined as severe hearing, visual, intellectual, or motor impairment/caregiver dependency. The primary outcome was 30-day readmission rates. Secondary outcomes included hospital length of stay and 30-day complications and mortality. Patients were 1:1 propensity-matched using patient, procedure, and hospital characteristics. RESULTS: Among our population of 378,733 patients, 5,877 (1.6%) patients had at least 1 disability condition. A higher proportion of patients with a disability had low household income, $1 to $45,999, and an Elixhauser Comorbidity score ≥3. Among 5,768 matched pairs, patients with a disability had a significantly higher incidence of 30-day readmission (17.2% vs 12.7%; P < .001), infectious complications (29.8% vs 19.5%; P < .001), and a longer length of stay (8 vs 6 days; P < .001). Motor impairment, the most common disability, was associated with the greatest increase in patient readmission, morbidity, and length of stay. CONCLUSION: Severe intellectual, hearing, visual, or motor impairments were associated with higher readmission, morbidity, and longer length of stay. Further research is needed to understand the mechanisms responsible for these disparities and to develop interventions to ameliorate them.

Nationwide, County-Level Analysis of the Patterns, Trends, and System-Level Predictors of Opioid Prescribing in Surgery in the US: Social Determinants and Access to Mental Health Services Matter.

BACKGROUND: The diversion of unused opioid prescription pills to the community at large contributes to the opioid epidemic in the US. In this county-level population-based study, we aimed to examine the US surgeons' opioid prescription patterns, trends, and system-level predictors in the peak years of the opioid epidemic. STUDY DESIGN: Using the Medicare Part D database (2013 to 2017), the mean number of opioid prescriptions per beneficiary (OPBs) was determined for each US county. Opioid-prescribing patterns were compared across counties. Multivariable linear regression was performed to determine relationships between county-level social determinants of health (demographic, eg median age and education level; socioeconomic, eg median income; population health status, eg percentage of current smokers; healthcare quality, eg rate of preventable hospital stays; and healthcare access, eg healthcare costs) and OPBs. RESULTS: Opioid prescription data were available for 1,969 of 3,006 (65.5%) US counties, and opioid-related deaths were recorded in 1,384 of 3,006 counties (46%). Nationwide, the mean OPBs decreased from 1.08 ± 0.61 in 2013 to 0.87 ± 0.55 in 2017; 81.6% of the counties showed the decreasing trend. County-level multivariable analyses showed that lower median population age, higher percentages of bachelor's degree holders, higher percentages of adults reporting insufficient sleep, higher healthcare costs, fewer mental health providers, and higher percentages of uninsured adults are associated with higher OPBs. CONCLUSIONS: Opioid prescribing by surgeons decreased between 2013 and 2017. A county's suboptimal access to healthcare in general and mental health services in specific may be associated with more opioid prescribing after surgery.

Patience is key: Association of surgical timing with clinical outcomes in elderly patients with sigmoid volvulus.

BACKGROUND: Current guidelines for sigmoid volvulus recommend endoscopy as a first line of treatment for decompression, followed by colectomy as early as possible. Timing of the latter varies greatly. This study compared early (≤2 days) versus delayed (>2 days) sigmoid colectomy. METHODS: 2016-2019 NRD database was queried to identify patients aged ≥65 years admitted for sigmoid volvulus who underwent sequential endoscopic decompression and sigmoid colectomy. Outcomes included mortality, complications, hospital length of stay, readmissions, and hospital costs. RESULTS: 842 patients were included, of which 409 (48.6 â€‹%) underwent delayed sigmoid colectomy. Delayed sigmoid colectomy was associated with reduced cardiac complications (1.1 â€‹% vs 0.0 â€‹%, p â€‹= â€‹0.045), reduced ostomy rate (38.3 â€‹% vs 29.4 â€‹%, p â€‹= â€‹0.013), an increased overall length of stay (12 days vs 8 days, p â€‹< â€‹0.001) and increased overall costs (27,764 dollar vs. 24,472 dollar, p â€‹< â€‹0.001). CONCLUSION: In geriatric patient with sigmoid volvulus, delayed surgical resection after decompression is associated with reduced cardiac complications and reduced ostomy rate, while increasing overall hospital length of stay and costs.

Missing Narrative: Examining the Impact of Disability on Post-Operative Infectious Complications.

Background: More than 20% of the population in the United States suffers from a disability, yet the impact of disability on post-operative outcomes remains understudied. This analysis aims to characterize post-operative infectious complications in patients with disability. Patients and Methods: This was a retrospective review of the National Readmission Database (2019) among patients undergoing common general surgery procedures. As per the U.S. Centers for Disease Control and Prevention (CDC), disability was defined as severe hearing, visual, intellectual, or motor impairment/caregiver dependency. A propensity-matched analysis comparing patients with and without a disability was performed to compare outcomes, including post-operative septic shock, sepsis, bacteremia, pneumonia, catheter-associated urinary tract infection (CAUTI), urinary tract infection (UTI), catheter-associated blood stream infection, Clostridioides Difficile infection, and superficial, deep, and organ/space surgical site infections during index hospitalization. Patients were matched using age, gender, comorbidities, illness severity, income, neighborhood, insurance, elective procedure, and the hospital's bed size and type. Results: A total of 710,548 patients were analysed, of whom 9,451(1.3%) had at least one disability. Motor disability was the most common (3,762; 40.5%), followed by visual, intellectual, and hearing impairment. Patients with disability were older (64 vs. 57 years; p < 0.001), more often insured under Medicare (65.2% vs. 37.3% p < 0.001) and had more medical comorbidities (Elixhauser comorbidity score ≥3; 69.2% vs. 41.9%; p < 0.001). After matching, 9,292 pairs were formed. Patients with a disability had a higher incidence of pneumonia (10.1% vs. 6.5%; p < 0.001), aspiration pneumonia (5.2% vs. 1.4%; p < 0.001), CAUTI (1.0% vs. 0.4%; p < 0.001), UTI (10.4% vs. 6.2%; p < 0.001), and overall infectious complications (21.8% vs. 14.5%; p < 0.001). Conclusions: Severe intellectual, hearing, visual, or motor impairments were associated with a higher incidence of infectious complications. Further investigation is needed to develop interventions to reduce disparities among this high-risk population.

Burden of Social and Behavioral Determinants of Health on Infectious Complications in Emergency General Surgery.

Background: Infectious complications lead to worse post-operative outcomes and are used to compare hospital performance in pay-for-performance programs. However, the impact of social and behavioral determinants of health on infectious complication rates after emergency general surgery (EGS) remains unclear. Patients and Methods: All patients undergoing EGS in the 2019 Nationwide Readmissions Database were included. The primary outcome of the study was the rate of infectious complications within 30 days, defined as a composite outcome including all infectious complications occurring during the index hospitalization or 30-day re-admission. Secondary outcomes included specific infectious complication rates. Multivariable regression analyses were used to study the impact of patient characteristics, social determinants of health (insurance status, median household income in the patient's residential zip code), and behavioral determinants of health (substance use disorders, neuropsychiatric comorbidities) on post-operative infection rates. Results: Of 367,917 patients included in this study, 20.53% had infectious complications. Medicare (adjusted odds ratio [aOR], 1.3; 95% confidence interval [CI], 1.26-1.34; p < 0.001), Medicaid (aOR, 1.24; 95% CI,1.19-1.29; p < 0.001), lowest zip code income quartile (aOR, 1.17; 95% CI, 1.13-1.22; p < 0.001), opioid use disorder (aOR,1.18; 95% CI,1.10-1.29; p < 0.001), and neurodevelopmental disorders (aOR, 2.16; 95% CI, 1.90-2.45; p < 0.001) were identified as independent predictors of 30-day infectious complications. A similar association between determinants of health and infectious complications was also seen for pneumonia, urinary tract infection (UTI), methicillin-resistant Staphylococcus aureus (MRSA) sepsis, and catheter-association urinary tract infection (CAUTI). Conclusions: Social and behavioral determinants of health are associated with a higher risk of developing post-operative infectious complications in EGS. Accounting for these factors in pay-for-performance programs and public reporting could promote fairer comparisons of hospital performance.

Development of a Machine Learning-Based Prescriptive Tool to Address Racial Disparities in Access to Care After Penetrating Trauma.

Importance: The use of artificial intelligence (AI) in clinical medicine risks perpetuating existing bias in care, such as disparities in access to postinjury rehabilitation services. Objective: To leverage a novel, interpretable AI-based technology to uncover racial disparities in access to postinjury rehabilitation care and create an AI-based prescriptive tool to address these disparities. Design, Setting, and Participants: This cohort study used data from the 2010-2016 American College of Surgeons Trauma Quality Improvement Program database for Black and White patients with a penetrating mechanism of injury. An interpretable AI methodology called optimal classification trees (OCTs) was applied in an 80:20 derivation/validation split to predict discharge disposition (home vs postacute care [PAC]). The interpretable nature of OCTs allowed for examination of the AI logic to identify racial disparities. A prescriptive mixed-integer optimization model using age, injury, and gender data was allowed to "fairness-flip" the recommended discharge destination for a subset of patients while minimizing the ratio of imbalance between Black and White patients. Three OCTs were developed to predict discharge disposition: the first 2 trees used unadjusted data (one without and one with the race variable), and the third tree used fairness-adjusted data. Main Outcomes and Measures: Disparities and the discriminative performance (C statistic) were compared among fairness-adjusted and unadjusted OCTs. Results: A total of 52 468 patients were included; the median (IQR) age was 29 (22-40) years, 46 189 patients (88.0%) were male, 31 470 (60.0%) were Black, and 20 998 (40.0%) were White. A total of 3800 Black patients (12.1%) were discharged to PAC, compared with 4504 White patients (21.5%; P < .001). Examining the AI logic uncovered significant disparities in PAC discharge destination access, with race playing the second most important role. The prescriptive fairness adjustment recommended flipping the discharge destination of 4.5% of the patients, with the performance of the adjusted model increasing from a C statistic of 0.79 to 0.87. After fairness adjustment, disparities disappeared, and a similar percentage of Black and White patients (15.8% vs 15.8%; P = .87) had a recommended discharge to PAC. Conclusions and Relevance: In this study, we developed an accurate, machine learning-based, fairness-adjusted model that can identify barriers to discharge to postacute care. Instead of accidentally encoding bias, interpretable AI methodologies are powerful tools to diagnose and remedy system-related bias in care, such as disparities in access to postinjury rehabilitation care.

Assessing the Relationship Between Race, Language, and Surgical Admissions in the Emergency Department.

INTRODUCTION: English proficiency and race are both independently known to affect surgical access and quality, but relatively little is known about the impact of race and limited English proficiency (LEP) on admission for emergency surgery from the emergency department (ED). Our objective was to examine the influence of race and English proficiency on admission for emergency surgery from the ED. METHODS: We conducted a retrospective observational cohort study from January 1-December 31, 2019 at a large, quaternary-care urban, academic medical center with a 66-bed ED Level I trauma and burn center. We included ED patients of all self-reported races reporting a preferred language other than English and requiring an interpreter or declaring English as their preferred language (control group). A multivariable logistic regression was fit to assess the association of LEP status, race, age, gender, method of arrival to the ED, insurance status, and the interaction between LEP status and race with admission for surgery from the ED. RESULTS: A total of 85,899 patients (48.1% female) were included in this analysis, of whom 3,179 (3.7%) were admitted for emergent surgery. Regardless of LEP status, patients identifying as Black (odds ratio [OR] 0.456, 95% CI 0.388-0.533; P<0.005), Asian [OR 0.759, 95% CI 0.612-0.929]; P=0.009), or female [OR 0.926, 95% CI 0.862-0.996]; P=0.04) had significantly lower odds for admission for surgery from the ED compared to White patients. Compared to individuals on Medicare, those with private insurance [OR 1.25, 95% CI 1.13-1.39; P <0.005) were significantly more likely to be admitted for emergent surgery, whereas those without insurance [OR 0.581, 95% CI 0.323-0.958; P=0.05) were significantly less likely to be admitted for emergent surgery. There was no significant difference in odds of admission for surgery between LEP vs non-LEP patients. CONCLUSION: Individuals without health insurance and those identifying as female, Black, or Asian had significantly lower odds of admission for surgery from the ED compared to those with health insurance, males, and those self-identifying as White, respectively. Future studies should assess the reasons underpinning this finding to elucidate impact on patient outcomes.

The Emergency Surgery Score is a powerful predictor of outcomes across multiple surgical specialties: Results of a retrospective nationwide analysis.

BACKGROUND: The Emergency Surgery Score was recently validated in a prospective multicenter study as an accurate predictor of mortality in emergency general surgery patients. The Emergency Surgery Score is easily calculated using multiple demographic, comorbidity, laboratory, and acuity of disease variables. We aimed to investigate whether the Emergency Surgery Score can predict 30-day postoperative mortality across patients undergoing emergency surgery in multiple surgical specialties. METHODS: Our study is a retrospective cohort study using data from the national American College of Surgeons National Surgical Quality Improvement Program database (2007-2017). We included patients that underwent emergency gynecologic, urologic, thoracic, neurosurgical, orthopedic, vascular, cardiac, and general surgical procedures. The Emergency Surgery Score was calculated for each patient, and the correlation between the Emergency Surgery Score and 30-day mortality was assessed for each specialty using the c-statistics methodology. RESULTS: Of 6,485,915 patients, 173,890 patients were included. The mean age was 60 years, 50.6% were female patients, and the overall mortality was 9.7%. The Emergency Surgery Score predicted mortality best in emergency gynecologic, general, and urologic surgery (c-statistics: 0.97, 0.87, 0.81, respectively). The Emergency Surgery Score predicted mortality moderately well in emergency thoracic, neurosurgical, orthopedic, and vascular surgery (c-statistics 0.73-0.79). For example, the mortality of gynecology patients with an Emergency Surgery Score of 5, 9, and 13 was 2%, 27%, and 50%, respectively. The Emergency Surgery Score performed poorly in cardiac surgery. CONCLUSION: The Emergency Surgery Score accurately predicts mortality across patients undergoing emergency surgery in multiple surgical specialties, especially general, gynecologic, and urologic surgery. The Emergency Surgery Score can prove useful for perioperative patient counseling and for benchmarking the quality of surgical care.

Early prediction of level-of-care requirements in patients with COVID-19.

This study examined records of 2566 consecutive COVID-19 patients at five Massachusetts hospitals and sought to predict level-of-care requirements based on clinical and laboratory data. Several classification methods were applied and compared against standard pneumonia severity scores. The need for hospitalization, ICU care, and mechanical ventilation were predicted with a validation accuracy of 88%, 87%, and 86%, respectively. Pneumonia severity scores achieve respective accuracies of 73% and 74% for ICU care and ventilation. When predictions are limited to patients with more complex disease, the accuracy of the ICU and ventilation prediction models achieved accuracy of 83% and 82%, respectively. Vital signs, age, BMI, dyspnea, and comorbidities were the most important predictors of hospitalization. Opacities on chest imaging, age, admission vital signs and symptoms, male gender, admission laboratory results, and diabetes were the most important risk factors for ICU admission and mechanical ventilation. The factors identified collectively form a signature of the novel COVID-19 disease.

The new coronavirus (now named SARS-CoV-2) causing the disease pandemic in 2019 (COVID-19), has so far infected over 35 million people worldwide and killed more than 1 million. Most people with COVID-19 have no symptoms or only mild symptoms. But some become seriously ill and need hospitalization. The sickest are admitted to an Intensive Care Unit (ICU) and may need mechanical ventilation to help them breath. Being able to predict which patients with COVID-19 will become severely ill could help hospitals around the world manage the huge influx of patients caused by the pandemic and save lives. Now, Hao, Sotudian, Wang, Xu et al. show that computer models using artificial intelligence technology can help predict which COVID-19 patients will be hospitalized, admitted to the ICU, or need mechanical ventilation. Using data of 2,566 COVID-19 patients from five Massachusetts hospitals, Hao et al. created three separate models that can predict hospitalization, ICU admission, and the need for mechanical ventilation with more than 86% accuracy, based on patient characteristics, clinical symptoms, laboratory results and chest x-rays. Hao et al. found that the patients' vital signs, age, obesity, difficulty breathing, and underlying diseases like diabetes, were the strongest predictors of the need for hospitalization. Being male, having diabetes, cloudy chest x-rays, and certain laboratory results were the most important risk factors for intensive care treatment and mechanical ventilation. Laboratory results suggesting tissue damage, severe inflammation or oxygen deprivation in the body's tissues were important warning signs of severe disease. The results provide a more detailed picture of the patients who are likely to suffer from severe forms of COVID-19. Using the predictive models may help physicians identify patients who appear okay but need closer monitoring and more aggressive treatment. The models may also help policy makers decide who needs workplace accommodations such as being allowed to work from home, which individuals may benefit from more frequent testing, and who should be prioritized for vaccination when a vaccine becomes available.

Spontaneous Retroperitoneal and Rectus Sheath Hemorrhage-Management, Risk Factors and Outcomes.

BACKGROUND: Spontaneous retroperitoneal and rectus sheath hemorrhage (SRRSH) is associated with high mortality in the literature, but studies on the subject are lacking. The objective of this study was to identify early predictors of the need for angiographic or surgical intervention (ASI) in patients with SRRSH and define risk factors for mortality. METHODS: We conducted a retrospective cohort study at a tertiary academic hospital. All patients with computed tomography-identified SRRSH between 2012 to 2017 were included. Exclusion criteria were age below 18 years, possible mechanical cause of SRRSH, aortic aneurysm rupture or dissection, and traumatic or iatrogenic sources of SRRSH. The primary outcome was the incidence of ASI and/or mortality. RESULTS: Of 100 patients included (median age 70 years, 52% males), 33% were transferred from another hospital, 82% patients were on therapeutic anticoagulation, and 90% had serious comorbidities. Overall mortality was 22%, but SRRSH-related mortality was only 6%. Sixteen patients underwent angiographic intervention (n = 10), surgical intervention (n = 5), or both (n = 1). Flank pain (OR 4.15, 95% CI 1.21-14.16, p = 0.023) and intravenous contrast extravasation (OR 3.89, 95% CI 1.23-12.27, p = 0.020) were independent predictors of ASI. Transfer from another hospital (OR 3.72, 95% CI 1.30-10.70, p = 0.015), age above 70 years (OR 4.24, 95% CI 1.25-14.32, p = 0.020), and systolic blood pressure below 110 mmHg at the time of diagnosis (OR 4.59, 95% CI 1.19-17.68, p = 0.027) were independent predictors of mortality. CONCLUSIONS: SRRSH is associated with high mortality but is typically not the direct cause. Most SRRSHs are self-limited and require no intervention. Pattern identification of ASI is hard.

Refugee Access to Surgical Care in Lebanon: A Post Hoc Analysis of the SCAR Study.

BACKGROUND: Lebanon hosts an estimated one million Syrian refugees registered with the United Nations High Commissioner for Refugees (UNHCR). The UNHCR contracts with select Lebanese hospitals to provide affordable primary and emergency care to refugees. We aimed to assess the surgical capabilities of UNHCR-affiliated hospitals in Lebanon. METHODS: Cross-sectional data from the Surgical Capacity in Areas with Refugees study were combined with hospital affiliation data obtained from the UNHCR. The Surgical Capacity in Areas with Refugees study evaluated surgical capacity in Lebanon by mapping all acute care hospitals and administering the five domain Personnel, Infrastructure, Procedures, Equipment, and Supplies (PIPES) tool to each hospital. Mean PIPES indices and mean numbers of hospital beds, surgeons, and anesthesiologists were compared between UNHCR-affiliated and nonaffiliated hospitals. Geographically, the distribution of UNHCR-affiliated hospitals was cross-referenced with refugee population distributions. RESULTS: One hundred and twenty nine hospitals were included, 35 (27.1%) of which were affiliated with the UNHCR. The PIPES tool was administered across all hospitals. Mean PIPES indices and mean number of hospital beds, general surgeons, and anesthesiologists were similar between UNHCR-affiliated and nonaffiliated hospitals. Geographical mapping of hospitals and refugee populations across Lebanon revealed a disparity in the Northeastern region of the country: that region had the highest number of refugees but lacked sufficient UNHCR coverage. CONCLUSIONS: Hospitals covered by the UNHCR performed similarly to nonaffiliated hospitals with respect to all aspects of the PIPES surgical capacity tool. However, there is a concerning geographic mismatch between UNHCR coverage and refugee density, specifically in the governorates of Akkar, Bekaa, and Baalbek-Hermel.

Cost savings associated with transfer of trauma patients within an accountable care organization.

BACKGROUND: The Patient Protection and Affordable Care Act supports the establishment of accountable care organizations (ACOs) as care delivery models designed to save costs. The potential for these cost savings has been demonstrated in the primary care and inpatient populations, but not for patients with emergency conditions or traumatic injuries. METHODS: Our study evaluated adult trauma patients transferred to the tertiary care hospitals of a pioneer ACO, comparing those who were transferred from within the ACO to those from outside the ACO in terms of overall cost of hospitalization. Hospital length of stay and number of imaging studies were predetermined secondary outcomes. RESULTS: The study population included 7696 hospitalizations for traumatic injuries over a 5-year period, 85.1% of which were for patients transferred from outside the ACO. Patients transferred from within the ACO had a 7.2% lower overall cost of hospitalization (P = .032). Mean injury severity scores were not significantly different between groups. Differences in mortality, intensive care unit length of stay, and overall hospital length of stay were not significant. However, analysis of radiology studies performed during the hospitalization revealed that patients transferred from within the ACO had, on average, 0.47 fewer advanced imaging studies per hospitalization than did those transferred from outside the ACO (3.55 vs 4.02 studies per hospitalization, P = .003). CONCLUSIONS: Adult trauma patients transferred from within an ACO have significantly lower total costs of hospitalization than do those transferred from outside the system, without significant differences in disease burden, hospital length of stay, or mortality.

The nature, patterns, clinical outcomes, and financial impact of intraoperative adverse events in emergency surgery.

BACKGROUND: Little is known about intraoperative adverse events (iAEs) in emergency surgery (ES). We sought to describe iAEs in ES and to investigate their clinical and financial impact. METHODS: The 2007 to 2012 administrative and American College of Surgeons-National Surgical Quality Improvement Program databases at our tertiary academic center were: (1) linked, (2) queried for all ES procedures, and then (3) screened for iAEs using the ICD-9-CM-based Patient Safety Indicator "accidental puncture/laceration". Flagged cases were systematically reviewed to: (1) confirm or exclude the occurrence of iAEs (defined as inadvertent injuries during the operation) and (2) extract additional variables such as procedure type, approach, complexity (measured by relative value units), need for adhesiolysis, and extent of repair. Univariate and multivariate analyses were performed to assess the independent impact of iAEs on 30-day morbidity, mortality, and hospital charges. RESULTS: Of a total of 9,288 patients, 1,284 (13.8%) patients underwent ES, of which 23 had iAEs (1.8%); 18 of 23 (78.3%) of the iAEs involved the small bowel or spleen, 10 of 23 (43.5%) required suture repair, and 8 of 23 (34.8%) required tissue or organ resection. Compared with those without iAEs, patients with iAEs were older (median age 62 vs 50; P = .04); their procedures were more complex (total relative value unit 46.7, interquartile range [27.5 to 52.6] vs 14.5 [.5 to 30.2]; P < .001), longer in duration (>3 hours: 52% vs 8%; P < .001), and more often required adhesiolysis (39.1% vs 13.5% P = .001). Patients with iAEs had increased total charges ($31,080 vs $11,330, P < .001), direct charges ($20,030 vs $7,387, P < .001), and indirect charges ($11,460 vs $4,088, P < .001). On multivariable analyses, iAEs were independently associated with increased 30-day morbidity (odds ratio, 3.56 [CI, 1.10 to 11.54]; P = .03) and prolonged postoperative length of stay (LOS; LOS >7 days; odds ratio, 5.60 [1.54 to 20.35]; P = .01]. A trend toward increased mortality did not reach statistical significance. CONCLUSIONS: In ES, iAEs are independently associated with significantly higher postoperative morbidity and prolonged LOS.

The financial impact of intraoperative adverse events in abdominal surgery.

BACKGROUND: Little evidence currently exists regarding the clinical or financial impact of intraoperative adverse events (iAEs). We sought to study the additional health care charges attributable to the occurrence of an iAE. METHODS: The administrative and ACS-NSQIP databases at our tertiary academic medical center were linked for all patients undergoing abdominal surgery (January 2007-October 2012). The ICD-9-CM-based Patient Safety Indicator "accidental puncture/laceration" was used to screen the linked database for potential iAEs. All iAEs were confirmed subsequently through standardized review of all flagged medical records. Multivariate analyses controlling for demographics, comorbidities/laboratory values, procedure type, and approach and complexity of surgery were performed to assess the increase in health care charges independently predicted by the occurrence of iAEs. RESULTS: Of 9,111 patients, 183 were confirmed to have iAEs. Patients in the iAE group had higher median total charges ($27,169 [IQR, 17,302-44,952] vs $13,312 [IQR, 8,586-22,012]; P < .001), direct charges ($17,808 [IQR, 11,520-28,930] vs $8,738 [IQR, 5,686-14,227]; P < .001) and indirect charges ($9,396 [IQR, 5,932-16,144] vs $4,568 [IQR, 2,887-7,824]; P < .001) when compared with patients without iAEs. Multivariate analyses demonstrated that iAEs independently predict an increase in total hospitalization charges by 41% (95% CI, 30-52%; P < .001). Specifically, the direct, indirect, operating room, laboratory/radiology, and alimentation/medical therapy charges increased by 42, 39, 27, 54, and 48%, respectively (all P < .001). CONCLUSION: In addition to the morbidity incurred by patients, the occurrence of an iAE is associated with major additional health care charges. In an era of value-based health care, understanding and preventing iAEs can lead to major cost savings alongside improvements in patient safety and surgical quality.

Potentially avoidable blood transfusion during trauma resuscitation.

INTRODUCTION: Red blood cell (RBC) transfusion is often essential during trauma resuscitation but is associated with high cost and potential adverse outcomes. This study aimed to determine the incidence of potentially avoidable RBC transfusions (PAT) among adult major trauma patients. MATERIALS AND METHODS: A retrospective review of data collected by Registry on patients presenting between Jan 2006 and Dec 2011 was conducted. Eligible patients received at least 1 unit of RBC in the first 24h following presentation to the Emergency Department (ED). Episodes of PAT were determined according to haemodynamic stability and post-transfusion haemoglobin levels. RESULTS: There were 621 patients included, of whom 224 (36.1%; 95% CI: 32.3-40.0) received PAT. Of them, 132 (58.9%) were haemodynamically stable on arrival and did not require a surgical procedure. Patients with PAT had significantly lower injury severity scores (30 vs 34, p<0.01), higher presenting systolic blood pressure (129 vs 112mm Hg, p<0.01) and a lower frequency of a shock index ≥1 (24.1 vs 65.0%, p<0.01), compared to those without PAT. They also had a significantly lower mortality (13.4 vs 21.7%, p<0.01). CONCLUSIONS: PAT after trauma was common and often delivered to haemodynamically stable patients who did not require surgical procedures. Clinical decision pathways for trauma resuscitation should aim to limit PAT.

Patterns of injury, outcomes, and predictors of in-hospital and 1-year mortality in nonagenarian and centenarian trauma patients.

IMPORTANCE: With the dramatic growth in the very old population and their concomitant heightened exposure to traumatic injury, the trauma burden among this patient population is estimated to be exponentially increasing. OBJECTIVE: To determine the clinical outcomes and predictors of in-hospital and 1-year mortality in nonagenarian and centenarian trauma patients (NCTPs). DESIGN, SETTING, AND PARTICIPANTS: All patients 90 years or older admitted to a level 1 academic trauma center between January 1, 2006, and December 31, 2010, with a primary diagnosis of trauma were included. Standard trauma registry data variables were supplemented by systematic medical record review. Cumulative mortality rates at 1, 3, 6, and 12 months after discharge were investigated using the Social Security Death Index. Univariate and multivariable analyses were performed to identify the predictors of in-hospital and 1-year postdischarge cumulative mortalities. MAIN OUTCOMES AND MEASURES: Length of hospital stay, in-hospital mortality, and cumulative mortalities at 1, 3, 6, and 12 months after discharge. RESULTS: Four hundred seventy-four NCTPs were included; 71.7% were female, and a fall was the predominant mechanism of injury (96.4%). The mean patient age was 93 years, the mean Injury Severity Score was 12, and the mean number of comorbidities per patient was 4.4. The in-hospital mortality was 9.5% but cumulatively escalated at 1, 3, 6, and 12 months after discharge to 18.5%, 26.4%, 31.3%, and 40.5%, respectively. Independent predictors of in-hospital mortality were the Injury Severity Score (odds ratio [OR], 1.09; 95% CI, 1.02-1.16; P = .01), mechanical ventilation (OR, 6.23; 95% CI, 1.42-27.27; P = .02), and cervical spine injury (OR, 4.37; 95% CI, 1.41-13.50; P = .01). Independent predictors of cumulative 1-year mortality were head injury (OR, 2.65; 95% CI, 1.24-5.67; P = .03) and length of hospital stay (OR, 1.06; 95% CI, 1.02-1.11; P = .005). Cumulative 1-year mortality in NCTPs with a head injury was 51.1% and increased to 73.2% if the Injury Severity Score was 25 or higher and to 78.7% if mechanical ventilation was required. Most NCTPs required rehabilitation; only 8.9% were discharged to home. CONCLUSIONS AND RELEVANCE: Despite low in-hospital mortality, the cumulative mortality rate among NCTPs at 1 year after discharge is significant, particularly in the presence of head injury, spine injury, mechanical ventilation, high injury severity, or prolonged length of hospital stay. These considerations can help guide clinical decisions and family discussions.

Excessively long hospital stays after trauma are not related to the severity of illness: let's aim to the right target!

IMPORTANCE: Reduction in length of hospital stay is a veritable target in reducing the overall costs of health care. However, many existing approaches are flawed because the assumptions of what cause excessive length of stay are incorrect; we methodically identified the right targets in this study. OBJECTIVE: To identify the causes of excessively prolonged hospitalization (ExProH) in trauma patients. DESIGN: The trauma registry, billing databases, and medical records of trauma admissions were reviewed. Excessively prolonged hospitalization was defined by the standard method used by insurers, which is a hospital stay that exceeds the Diagnosis Related Group-based trim point. The causes of ExProH were explored in a unique potentially avoidable days database, used by our hospital's case managers to track discharge delays. SETTING: Level I academic trauma center. PARTICIPANTS: Adult trauma patients admitted between January 1, 2006, and December 31, 2010. MAIN OUTCOMES AND MEASURES: Excessively prolonged hospitalization and hospital cost. RESULTS: Of 3237 patients, 155 (5%) had ExProH. The patients with ExProH compared with non-ExProH patients were older (mean [SD] age, 53 [21] vs 47 [22] years, respectively; P = .001), were more likely to have blunt trauma (92% vs 84%, respectively; P = .03), were more likely to be self-payers (16% vs 11%, respectively; P = .02) or covered by Medicare/Medicaid (41% vs 30%, respectively; P = .002), were more likely to be discharged to post-acute care facilities than home (65% vs 35%, respectively; P < .001), and had higher hospitalization cost (mean, $54 646 vs $18 444, respectively; P < .001). Both groups had similar Injury Severity Scores, Revised Trauma Scores, baseline comorbidities, and in-hospital complication rates. Independent predictors of mortality were discharge to a rehabilitation facility (odds ratio = 4.66; 95% CI, 2.71-8.00; P < .001) or other post-acute care facility (odds ratio = 5.04; 95% CI, 2.52-10.05; P < .001) as well as insurance type that was Medicare/Medicaid (odds ratio = 1.70; 95% CI, 1.06-2.72; P = .03) or self-pay (odds ratio = 2.43; 95% CI, 1.35-4.37; P = .003). The reasons for discharge delays were clinical in only 20% of the cases. The remaining discharges were excessively delayed because of difficulties in rehabilitation facility placement (47%), in-hospital operational delays (26%), or payer-related issues (7%). CONCLUSIONS AND RELEVANCE: System-related issues, not severity of illness, prolong hospital stay excessively. Cost-reduction efforts should target operational bottlenecks between acute and postacute care.

Presenting blood pressure in traumatic brain injury: a bimodal distribution of death.

BACKGROUND: Recent research explores the relationship between vital signs on arrival to the emergency department and early outcomes. This work has not included traumatic brain injury (TBI). We aimed to evaluate the relationship of the initial emergency department systolic blood pressure (EDSBP) with outcome. METHODS: By using the National Trauma Data Bank (v7), we analyzed patients older than 16 years with isolated moderate to severe blunt TBI. TBI was defined by International Classification of Diseases--9th Rev diagnosis codes and Abbreviated Injury Scale scores. We determined mortality rates while controlling for age, gender, race, payment type, and injury severity using logistic regression. Survival analysis was performed to determine 3-day survival rates. Scores and rates were plotted against EDSBP. RESULTS: A total of 7,238 patients were included in the analysis. Plots of adverse outcomes versus EDSBP demonstrated bimodal distributions. The mortality curve had one inflection point at EDSBP 120 mm Hg, indicating higher mortality when blood pressures were lower than this threshold. Another inflection began at EDSBP 140 mm Hg. The mortality rate was 21% when EDSBP was <120 mm Hg, 9% when it was between 120 mm Hg and 140 mm Hg, and 19% when EDSBP was ≥140 mm Hg. Multivariate analysis demonstrated that patients presenting with an EDSBP of <120 mm Hg and ≥140 mm Hg were 2.7 (95% confidence interval =2.13,3.48) and 1.6 (95% confidence interval =1.32,1.96) times more likely to die, respectively, than those who presented with a EDSBP of 120 mm Hg to 140 mm Hg. CONCLUSIONS: Mortality in moderate to severe TBI has a bimodal distribution. Like hypotension, hypertension at hospital admission seems to be associated with increased mortality in TBI, even after controlling for other factors.