James P. Marcin

An estimate of the U.S. Government's undercount of nonfatal occupational injuries.

Learning ObjectivesEstimate how many workers—and in which occupations—are presently excluded from the Bureau of Labor Statistics Annual Survey of Occupational Illnesses and Injuries.Consider possible reasons for under-reporting of injuries by private firms and their employees.Provide the best estimate of the degree of under-reporting, and note the possible consequences for workers’ health. Debate surrounds the size of the underestimate of nonfatal occupational injuries produced by the U.S. Bureau of Labor Statistics (BLS). We developed models that separated categories of injuries: BLS Annual Survey, federal government, agriculture, state and local government, self-employed outside agriculture, and all other. The models generated varying estimates depending on the assumptions for each category pertaining to job risks and amount of underreporting. We offered justification for the assumptions based on published studies as well as our own analyses of BLS data. The models suggested the Annual Survey missed from 0% to 70% of the number of injuries (from private firms, excluding the self-employed) it was designed to capture. However, when we included firms and governments the Annual Survey was not designed to capture, and considered reasonable assumptions regarding underreporting, we estimated the BLS missed between 33% and 69% of all injuries. We concluded that there was substantial undercapture in the BLS Annual Survey, some due to the excluded categories of government workers and the self-employed, as well as some due to underreporting.

Frequency of sub‐clinical cerebral edema in children with diabetic ketoacidosis

Abstract:  Symptomatic cerebral edema occurs in approximately 1% of children with diabetic ketoacidosis (DKA). However, asymptomatic or subclinical cerebral edema is thought to occur more frequently. Some small studies have found narrowing of the cerebral ventricles indicating cerebral edema in most or all children with DKA, but other studies have not detected narrowing in ventricle size. In this study, we measured the intercaudate width of the frontal horns of the lateral ventricles using magnetic resonance imaging (MRI) in children with DKA during treatment and after recovery from the DKA episode. We determined the frequency of ventricular narrowing and compared clinical and biochemical data for children with and without ventricular narrowing. Forty‐one children completed the study protocol. The lateral ventricles were significantly smaller during DKA treatment (mean width, 9.3 ± 0.3 vs. 10.2 ± 0.3 mm after recovery from DKA, p < 0.001). Children with ventricular narrowing during DKA treatment (22 children, 54%) were more likely to have mental status abnormalities than those without narrowing [12/22 vs. 4/19 with Glasgow Coma Scale (GCS) scores below 15 during therapy, p = 0.03]. Multiple logistic regression analysis revealed that a lower initial PCO2 level was significantly associated with ventricular narrowing [odds ratio (OR) = 0.88, 95% confidence interval (95% CI) = 0.78–0.99, p = 0.047). No other variables analyzed were associated with ventricular narrowing in the multivariate analysis. We conclude that narrowing of the lateral ventricles is evident in just over half of children being treated for DKA. Although children with ventricular narrowing did not exhibit neurological abnormalities sufficient for a diagnosis of ‘symptomatic cerebral edema’, mild mental status abnormalities occurred frequently, suggesting that clinical evidence of cerebral edema in children with DKA may be more common than previously reported.

Long-stay patients in the pediatric intensive care unit.

ObjectiveLength of stay in the pediatric intensive care unit (PICU) is a reflection of patient severity of illness and health status, as well as PICU quality and performance. We determined the clinical profiles and relative resource use of long-stay patients (LSPs) and developed a prediction model to identify LSPs for early quality and cost saving interventions. DesignNonconcurrent cohort study. SettingA total of 16 randomly selected PICUs and 16 volunteer PICUs. PatientsA total of 11,165 consecutive admissions to the 32 PICUs. InterventionsNone. Measurements and Main Results LSPs were defined as patients having a length of stay greater than the 95th percentile (>12 days). Logistic regression analysis was used to determine which clinical characteristics, available within the first 24 hrs after admission, were associated with LSPs and to create a predictive algorithm. Overall, LSPs were 4.7% of the population but represented 36.1% of the days of care. Multivariate analysis indicated that the following factors are predictive of long stays: age <12 months, previous ICU admission, emergency admission, no CPR before admission, admission from another ICU or intermediate care unit, chronic care requirements (total parenteral nutrition and tracheostomy), specific diagnoses including acquired cardiac disease, pneumonia, and other respiratory disorders, having never been discharged from the hospital, need for ventilatory support or an intracranial catheter, and a Pediatric Risk of Mortality III score between 10 and 33. The performance of the prediction algorithm in both the training and validation samples for identifying LSPs was good for both discrimination (area under the receiver operating characteristics curve of 0.83 and 0.85, respectively), and calibration (goodness of fit, p = .33 and p = .16, respectively). LSPs comprised from 2.1% to 8.1% of individual ICU patients and occupied from 15.2% to 57.8% of individual ICU bed days. ConclusionsLSPs have less favorable outcomes and use more resources than non-LSPs. The clinical profile of LSPs includes those who are younger and those that require chronic care devices. A predictive algorithm could help identify patients at high risk of prolonged stays appropriate for specific interventions.

A population-based analysis of socioeconomic status and insurance status and their relationship with pediatric trauma hospitalization and mortality rates

OBJECTIVES We investigated socioeconomic disparities in injury hospitalization rates and severity-adjusted mortality for pediatric trauma. METHODS We used 10 years of pediatric trauma data from Sacramento County, Calif, to compare trauma hospitalization rates, trauma mechanism and severity, and standardized hospital mortality across socioeconomic strata (median household income, proportion of households in poverty, insurance). RESULTS Children from lower-socioeconomic status (SES) communities had higher injury hospitalization and mortality rates, and presented more frequently with more lethal mechanisms of injury (pedestrian, firearm), but did not have higher severity-adjusted mortality. CONCLUSIONS Higher injury mortality rates among children of lower SES in Sacramento County are explained by a higher incidence of trauma and more fatal mechanisms of injury, not by greater injury severity or poorer inpatient care.

Nurse staffing and unplanned extubation in the pediatric intensive care unit

Objective: To determine the association between unplanned extubations and years of nurse experience and nurse-to-patient ratio in the pediatric intensive care unit (PICU). Design: Case-control study. Setting: University-affiliated children’s hospital PICU. Patients: Unplanned extubations were identified from January 1999 through December 2002. Three control patients for each of the patients experiencing an unplanned extubation were selected on three matching factors: age, intubation duration, and severity of illness as defined by the Pediatric Risk of Mortality (PRISM) III. Interventions: None. Measurements and Main Results: Fifty-five of 1,004 intubated patients (5.5%) experienced an unplanned extubation during the 4-yr period. A conditional logistic regression analysis was used to evaluate the association between a patient’s risk of an unplanned extubation and the nurse’s years of PICU experience and nurse-to-patient ratio. Factors associated with unplanned extubations included the documentation of patient agitation (odds ratio, 2.99; 95% confidence interval, 1.14, 7.86) and a nurse-to-patient ratio of 1:2 (one nurse caring for two patients) relative to a nurse-to-patient ratio of 1:1 (odds ratio, 4.24; 95% confidence interval, 1.00, 19.10). Years of PICU nursing experience, patient restraints, and the method of sedation delivery (continuous infusion vs. intermittent bolus) were not associated with unplanned extubations. Conclusions: Pediatric patients are more likely to experience an unplanned extubation when being cared for by a nurse assigned to two patients compared with a nurse caring for one patient. To provide safe patient care, health care policymakers and hospital administrators should consider the nurse-to-patient ratio and its potential association with adverse events in hospitalized children.

Case Volume and Mortality in Pediatric Cardiac Surgery Patients in California, 1998–2003

Background— Previous reports have found an inverse relationship between pediatric cardiac surgery case volume and in-hospital mortality. This association has been noted recently to be decreasing for coronary artery bypass grafting, possibly because of improved training programs, quality improvement activities, or other innovations to improve outcomes. It is unknown whether the volume-mortality association among pediatric cardiac surgery patients is decreasing similarly. Methods and Results— We used data from the state of Californias patient discharge data set from the years 1998–2003 to replicate 4 previous research studies of pediatric cardiac surgery volume and mortality. The total number of pediatric surgeries varied from 12 801 to 13 971 depending on the selection criteria applied. Using this larger and more contemporary data set, we found a weaker and less consistent volume-mortality relationship than had been reported previously. We also developed a new model, which incorporated elements of the old models, and found a statistically significant relationship with higher volume and lower mortality (odds ratio=0.86 per 100-patient increase in annual volume; 95% CI, 0.81 to 0.92). Post hoc analyses show that this relationship was related to the performance of the single largest-volume hospital. Conclusions— With the use of data from California, the volume-mortality relationship among pediatric cardiac surgery patients has changed since previous research, such that the old models no longer describe a clear or consistent association. With the use of a continuous definition of volume and an updated model, an association is observed but is dependent on highly leveraged covariate patterns found in the largest-volume hospital.

Triage scoring systems, severity of illness measures, and mortality prediction models in pediatric trauma

Trauma triage scores, severity of illness measures, and mortality prediction models quantitate severity of injury and stratify patients according to a specified outcome. Triage scoring systems are typically used to assist prehospital personnel determine which patients require trauma center care, but they are not recommended as the sole determinant of triage. Severity of illness measures and mortality prediction models are used in clinical and health services research for risk-adjusted outcomes analyses and institutional benchmarking. As clinicians and researchers, it is imperative that we be knowledgeable of the methodologies and applications of these scoring and risk prediction systems to ensure their quality and appropriate utilization.

Review of the methodologies and applications of scoring systems in neonatal and pediatric intensive care

Scoring systems and risk prediction rules quantitate the severity of clinical conditions and stratify patients according to a specified outcome. In intensive care medicine, the complexity and number of clinical scoring systems is increasing as their utility in both health services research and clinical medicine broadens. We anticipate that with increasing healthcare costs and competition, the demand for risk adjusted outcomes and institutional benchmarking will increase. As academicians and clinicians, it is vital to be knowledgeable regarding the methodologies and applications of these scoring and risk prediction systems to ensure their quality and appropriate utilization.

Correlation of Clinical and Biochemical Findings with Diabetic Ketoacidosis-Related Cerebral Edema in Children Using Magnetic Resonance Diffusion-Weighted Imaging

OBJECTIVE To determine clinical and biochemical factors influencing cerebral edema formation during diabetic ketoacidosis (DKA) in children. STUDY DESIGN We used magnetic resonance diffusion-weighted imaging to quantify edema formation. We measured the apparent diffusion coefficient (ADC) of brain water during and after DKA treatment in 26 children and correlated ADC changes with clinical and biochemical variables. RESULTS Mean ADC values were elevated during DKA treatment compared with baseline (8.13 +/- 0.47 vs 7.74 +/- 0.49 x 10(-4) mm(2)/sec, difference in means 0.40, 95% CI: 0.25 to 0.55, P < .001). Children with altered mental status during DKA had greater elevation in ADC. ADC elevation during DKA was positively correlated with initial serum urea nitrogen concentration (correlation coefficient 0.41, P = .03) and initial respiratory rate (correlation coefficient 0.61, P < .001). ADC elevation was not significantly correlated with initial serum glucose, sodium or effective osmolality, nor with changes in glucose, sodium or osmolality during treatment. Multivariable analyses identified the initial urea nitrogen concentration and respiratory rate as independently associated with ADC elevation. CONCLUSIONS The degree of edema formation during DKA in children is correlated with the degree of dehydration and hyperventilation at presentation, but not with factors related to initial osmolality or osmotic changes during treatment. These data support the hypothesis that CE is related to cerebral hypoperfusion during DKA, and that osmotic fluctuations during DKA treatment do not play a primary causal role.

Impact of between-hospital volume and within-hospital volume on mortality and readmission rates for trauma patients in California.

Objective:Previous research assessing the impact of between-hospital trauma volume (high volume centers vs. low volume centers) and outcomes has been inconsistent. Furthermore, previous research has not considered temporal variations in within-hospital volume (a center having higher than average volume vs. lower than average volume) as a covariate. The objective of this study was to determine the relationship of between-hospital and within-hospital trauma volume and two measures of hospital quality of care. Design:Multivariable, hierarchical, mixed effects, logistic regression analyses of a population-based nonconcurrent cohort from 1995 to 1999. Setting:Thirty-nine nonfederal California hospitals included in the California Patient Discharge Data Set designated by local Emergency Medical Services authorities as adult trauma centers. Patients:All nonelderly adult trauma patients, 16–64 yrs (n = 54,352), and elderly adult trauma patients, >65 yrs (n = 47,656), admitted with an Injury Severity Score >9. Interventions:None. Measurements and Main Results:Severity adjusted in-hospital mortality rate and 30-day trauma-related readmissions were analyzed. Among nonelderly adult patients, higher annual between-hospital trauma volume was not associated with mortality rate (odds ratio, 1.02 for each 100 admissions; 95% confidence interval, 0.99, 1.06) but was associated with higher risk of readmission (odds ratio, 1.19 for each 100 admissions; 95% confidence interval, 1.13, 1.26). Among elderly adult patients, higher annual between-hospital trauma volume was associated with lower mortality (odds ratio, 0.79 for each 100 admissions; 95% confidence interval, 0.71, 0.87) but was not associated with risk of readmission (odds ratio, 0.96 for each 100 admissions; 95% confidence interval, 0.90, 1.04). Higher than average monthly within-hospital trauma volume was associated with higher odds of readmission (odds ratio, 1.11 for a volume deviation of ten patients per month; 95% confidence interval, 1.01, 1.21) among elderly adult patients. Conclusions:The findings of this study in the context of previous research suggest that relationships between trauma volume and outcomes exist but depend on which patient populations are studied and how the data are analyzed. Furthermore, trauma centers may be subject to the detrimental effects of high temporal volume overextending existing services and capacity. Since this study found that both between-hospital volume and within-hospital volume measures are associated with outcomes, we recommend that both measures be included in future volume-outcome investigations.