Joseph F. Golob

Moving Beyond Traditional Measurement of Mortality after Injury: Evaluation of Risks for Late Death

BACKGROUND The purpose of this study was to evaluate long-term mortality after trauma, and to determine risk factors and possible disparities related to mortality after hospital discharge. STUDY DESIGN Level I trauma center registry data from a 6-year period (2000 through 2005) were linked to patient electronic medical records, the National Death Index with cause of death codes, and census data using geographic information science (GIS) methodologies. Census data provided supplemental demographic and socioeconomic information from patient neighborhoods. RESULTS The hospital mortality rate for 15,285 patients was 3.3%, and mortality after discharge was 4.8%. Overall mortality for the study period was 8.1% (average follow-up, 2.8 years, 1-year mortality, 5.4%). Mortality after discharge was related to the initial injury in 33%, possibly related in 23%, and unrelated in 44% of patients. Logistic regression analysis demonstrated that independent predictors of hospital mortality were age, Injury Severity Score, gunshot injury, significant head injury, fall, and spinal cord injury. In contrast, independent risk factors for mortality after discharge were age, hospital length of stay, discharge from the hospital to a locale other than home, and the presence of spinal cord injury. Intoxication at hospital admission and injury due to a gunshot wound or motor vehicle collision were protective for late mortality. Bivariate analysis of census data demonstrated that lower socioeconomic status was associated with improved hospital survival, and non-native status was associated with mortality after discharge. CONCLUSIONS There is significant mortality attributable to trauma for up to 1 year after hospital discharge. These findings suggest that mortality after trauma needs to be measured beyond hospital discharge in order to assess the complete impact of injury.

Isolated cervical spine fractures in the elderly: a deadly injury.

BACKGROUND Traumatic injury in the elderly is an increasing problem and studies have shown that elderly patients (>/=65 years old) with cervical spine fractures and spinal cord injury (SCI) carry a mortality rate of 21% to 30%. However, little has been described with regard to outcomes for elderly patients with isolated cervical spine fractures (ICSF). HYPOTHESIS Outcomes for elderly patients with ICSF will be similar to elderly patients with cervical fractures and associated traumatic injuries (ATI) or SCI. METHODS A 9-year retrospective analysis was performed on all patients >/=65 years old admitted to a level I trauma center with any cervical spine fracture. Primary outcomes were defined as favorable (discharge to home or rehabilitation hospital) or unfavorable (death, discharge to a long-term acute care facility, or a skilled nursing facility). ICSF was defined as those fractures without ATI or SCI. Long-term mortality data were gathered using the Social Security Death Index. RESULTS A total of 177 patients with mean age of 78 +/- 1 and Injury Severity Score of 17 +/- 1 were evaluated. Fifty-six percent were men and falls were the most common mechanism (62%). An unfavorable outcome was seen in 56% of the study population with a mortality rate of 25%. ATIs were seen in 57% of the population and 22% had SCI. Patients with SCI had a significantly higher mortality compared with patients without SCI (38% vs. 22%, p = 0.032). However, there was no difference in unfavorable outcomes. Patients with ICSF had no differences in unfavorable outcomes compared with patients with SCI or ATI. Long-term survival analysis after discharge (mean = 2.8 years) demonstrated that patients with a favorable outcome had a significantly improved survival compared with patients with unfavorable outcomes (p < 0.001). CONCLUSION ICSFs were associated with an unfavorable outcome in the elderly population regardless of ATI or SCI. These unfavorable outcomes were also associated with long-term mortality. Strategies to reduce morbidity and mortality in this devastating injury will be essential to improve outcomes and maximize resource utilization.

Follow-up disparities after trauma: a real problem for outcomes research

INTRODUCTION The objectives of this study were to (1) determine risk factors associated with failure to follow-up (FTF) after traumatic injury and (2) in those patients who do follow up, to determine if information within the electronic medical record (EMR) is an adequate data-collection tool for outcomes research. METHODS A 6-year retrospective analysis was conducted on all admitted trauma patients using data from the trauma registry, National Death Index, 2000 Census Data, and the EMR. Bivariate and logistic regression analyses identified risk factors for FTF. A subgroup analysis evaluated the utility of using the EMR to determine basic functional outcomes (Glasgow outcome scale, diet, ambulation, and employment status). RESULTS A total of 14,784 patients were discharged, and 61% had follow-up appointments. Lower income, higher poverty rates, and lower education were significantly (P<.05) associated with FTF. Logistic regression analysis (excluding census data) identified that older age, lower Injury Severity Score, less severe head injury, nonwhite race, blunt injury, death after discharge, zip code within 25 miles, and patients discharged to home independently predicted FTF after traumatic injury. A subgroup analysis of the EMR showed the inability to reliably determine functional outcomes. CONCLUSIONS There are several disparities related to follow-up after trauma. Furthermore, charting deficiencies, even with an EMR, highlight the weaknesses of data available for trauma outcomes research. Trauma process improvement programs could target patients at risk for not following up and use a structured electronic outpatient note.

Validation of Surgical Intensive Care-Infection Registry: a medical informatics system for intensive care unit research, quality of care improvement, and daily patient care.

BACKGROUND We developed a prototype electronic clinical information system called the Surgical Intensive Care-Infection Registry (SIC-IR) to prospectively study infectious complications and monitor quality of care improvement programs in the surgical and trauma intensive care unit. The objective of this study was to validate SIC-IR as a successful health information technology with an accurate clinical data repository. STUDY DESIGN Using the DeLone and McLean Model of Information Systems Success as a framework, we evaluated SIC-IR in a 3-month prospective crossover study of physician use in one of our two surgical and trauma intensive care units (SIC-IR unit versus non SIC-IR unit). Three simultaneous research methodologies were used: a user survey study, a pair of time-motion studies, and an accuracy study of SIC-IRs clinical data repository. RESULTS The SIC-IR user survey results were positive for system reliability, graphic user interface, efficiency, and overall benefit to patient care. There was a significant decrease in prerounding time of nearly 4 minutes per patient on the SIC-IR unit compared with the non SIC-IR unit. The SIC-IR documentation and data archiving was accurate 74% to 100% of the time depending on the data entry method used. This accuracy was significantly improved compared with normal hand-written documentation on the non SIC-IR unit. CONCLUSIONS SIC-IR proved to be a useful application both at individual user and organizational levels and will serve as an accurate tool to conduct prospective research and monitor quality of care improvement programs.

Theraputic anticoagulation in the trauma patient: Is it safe?

PURPOSE Trauma patients who require therapeutic anticoagulation pose a difficult treatment problem. The purpose of this study was to determine: (1) the incidence of complications using therapeutic anticoagulation in trauma patients, and (2) if any patient factors are associated with these complications. METHODS An 18-month retrospective review was performed on trauma patients >or= 15 years old who received therapeutic anticoagulation using unfractionated heparin (UH) and/or fractionated heparin (FH). Forty different pre-treatment and treatment patient characteristics were recorded. Complications of anticoagulation were documented and defined as any unanticipated discontinuation of the anticoagulant for bleeding or other adverse events. RESULTS One-hundred-fourteen trauma patients were initiated on therapeutic anticoagulation. The most common indication for anticoagulation was deep venous thrombosis (46%). Twenty-four patients (21%) had at least 1 anticoagulation complication. The most common complication was a sudden drop in hemoglobin concentration requiring blood transfusion (11 patients). Five patients died (4%), 3 of whom had significant hemorrhage attributed to anticoagulation. Bivariate followed by logistic regression analysis identified chronic obstructive pulmonary disease (OR = 9.2, 95%CI = 1.5-54.7), UH use (OR = 3.8, 95%CI = 1.1-13.0), and lower initial platelet count (OR = 1.004, 95%CI = 1.000-1.008) as being associated with complications. Patients receiving UH vs. FH differed in several characteristics including laboratory values and anticoagulation indications. CONCLUSION Trauma patients have a significant complication rate related to anticoagulation therapy, and predicting which patients will develop a complication remains unclear. Prospective studies are needed to determine which treatment regimen, if any, is appropriate to safely anticoagulate this high risk population.

The Surgical Intensive Care-infection Registry: a research registry with daily clinical support capabilities.

Infections in the surgical and trauma intensive care unit (STICU) are responsible for significant patient morbidity and mortality. Research into these infectious complications often uses administrative databases or clinical information systems designed for documenting and billing daily patient care. Neither of these sources is intended for research, and many investigators have questioned their accuracy. The Surgical Intensive Care–Infection Registry (SIC-IR) was developed as a research data repository to use to monitor STICU infections. SIC-IR is a relational database application designed to collect quality data and to integrate with daily patient care. SIC-IR prospectively collects and archives more than 100 clinical variables daily on each STICU patient to ensure completeness and correctness of the registry. Furthermore, SIC-IR aids in clinical activities by providing patient summaries and medical record documentation. SIC-IR provides accurate data for STICU infection research and enables the users to easily undertake quality-of-care improvement initiatives. (Am J Med Qual 2009;24:29-34)

Who is monitoring your infections: shouldn't you be?

BACKGROUND In the era of pay for performance and outcome comparisons among institutions, it is imperative to have reliable and accurate surveillance methodology for monitoring infectious complications. The current monitoring standard often involves a combination of prospective and retrospective analysis by trained infection control (IC) teams. We have developed a medical informatics application, the Surgical Intensive Care-Infection Registry (SIC-IR), to assist with infection surveillance. The objectives of this study were to: (1) Evaluate for differences in data gathered between the current IC practices and SIC-IR; and (2) determine which method has the best sensitivity and specificity for identifying ventilator-associated pneumonia (VAP). METHODS A prospective analysis was conducted in two surgical and trauma intensive care units (STICU) at a level I trauma center (Unit 1: 8 months, Unit 2: 4 months). Data were collected simultaneously by the SIC-IR system at the point of patient care and by IC utilizing multiple administrative and clinical modalities. Data collected by both systems included patient days, ventilator days, central line days, number of VAPs, and number of catheter-related blood steam infections (CR-BSIs). Both VAPs and CR-BSIs were classified using the definitions of the U.S. Centers for Disease Control and Prevention. The VAPs were analyzed individually, and true infections were defined by a physician panel blinded to methodology of surveillance. Using these true infections as a reference standard, sensitivity and specificity for both SIC-IR and IC were determined. RESULTS A total of 769 patients were evaluated by both surveillance systems. There were statistical differences between the median number of patient days/month and ventilator-days/month when IC was compared with SIC-IR. There was no difference in the rates of CR-BSI/1,000 central line days per month. However, VAP rates were significantly different for the two surveillance methodologies (SIC-IR: 14.8/1,000 ventilator days, IC: 8.4/1,000 ventilator days; p = 0.008). The physician panel identified 40 patients (5%) who had 43 VAPs. The SIC-IR identified 39 and IC documented 22 of the 40 patients with VAP. The SIC-IR had a sensitivity and specificity of 97% and 100%, respectively, for identifying VAP and for IC, a sensitivity of 56% and a specificity of 99%. CONCLUSIONS Utilizing SIC-IR at the point of patient care by a multidisciplinary STICU team offers more accurate infection surveillance with high sensitivity and specificity. This monitoring can be accomplished without additional resources and engages the physicians treating the patient.

Critical Analysis of Empiric Antibiotic Utilization: Establishing Benchmarks

AIM We critically evaluated empiric antibiotic practice in the surgical and trauma intensive care unit (STICU) with three specific objectives: (1) To characterize empiric antibiotics practice prospectively; (2) to determine how frequently STICU patients started on empiric antibiotics subsequently have a confirmed infection; and (3) to elucidate the complications associated with unnecessary empiric antibiotic therapy. METHODS We collected data prospectively using the Surgical Intensive Care-Infection Registry (SIC-IR) including all 1,185 patients admitted to the STICU for >2 days from March 2007 through May 2008. Empiric antibiotics were defined as those initiated because of suspected infections. RESULTS The mean patient age was 56 years and 62% were male. The mean STICU length of stay was eight days, and the mortality rate was 4.6%. Empiric antibiotics were started for 26.3% of the patients. The average length of antibiotic use was three days. Of the 312 patients started on empiric antibiotics, only 25.6% were found to have an infection. Factors associated with correctly starting empiric antibiotics were a longer STICU stay (5 vs. 3 days), prior antibiotics (29% vs. 17%), and mechanical ventilation (93% vs. 79%). Patients who were started on antibiotics without a subsequent confirmed infection were compared with patients not given empiric antibiotics. Incorrect use of empiric antibiotics was associated with younger age (p < 0.001), more STICU days (10.6 vs. 5.9 days; p < 0.001), more ventilator days (p < 0.001), more development of acute renal failure (24.1% vs. 12.1%; p < 0.001), and a significant difference in mortality rate (8.6% vs. 3.2%; p < 0.001). CONCLUSIONS After admission to the STICU, 26% of patients received at least one course of empiric antibiotics. Only 25.6% of these patients were confirmed to have an infection. These results provide key benchmark data for the critical care community to improve antibiotic stewardship.

Enhancing the fever workup utilizing a multi-technique modeling approach to diagnose infections more accurately.

BACKGROUND Differentiation between infectious and non-infectious etiologies of the systemic inflammatory response syndrome (SIRS) in trauma patients remains elusive. We hypothesized that mathematical modeling in combination with computerized clinical decision support would assist with this differentiation. The purpose of this study was to determine the capability of various mathematical modeling techniques to predict infectious complications in critically ill trauma patients and compare the performance of these models with a standard fever workup practice (identifying infections on the basis of fever or leukocytosis). METHODS An 18-mo retrospective database was created using information collected daily from critically ill trauma patients admitted to an academic surgical and trauma intensive care unit. Two hundred forty-three non-infected patient-days were chosen randomly to combine with the 243 infected-days, which created a modeling sample of 486 patient-days. Utilizing ten variables known to be associated with infectious complications, decision trees, neural networks, and logistic regression analysis models were created to predict the presence of urinary tract infections (UTIs), bacteremia, and respiratory tract infections (RTIs). The data sample was split into a 70% training set and a 30% testing set. Models were compared by calculating sensitivity, specificity, positive predictive value, negative predictive value, overall accuracy, and discrimination. RESULTS Decision trees had the best modeling performance, with a sensitivity of 83%, an accuracy of 82%, and a discrimination of 0.91 for identifying infections. Both neural networks and decision trees outperformed logistic regression analysis. A second analysis was performed utilizing the same 243 infected days and only those non-infected patient-days associated with negative microbiologic cultures (n = 236). Decision trees again had the best modeling performance for infection identification, with a sensitivity of 79%, an accuracy of 83%, and a discrimination of 0.87. CONCLUSION The use of mathematical modeling techniques beyond logistic regression can improve the robustness and accuracy of predicting infections in critically ill trauma patients. Decision tree analysis appears to have the best potential to use in assisting physicians in differentiating infectious from non-infectious SIRS.