Arkansas — Targeted Issue

Author(s)/Presenter(s)

Tilford JM, Parker JG

Abstract/Description

No abstract available

Author(s)/Presenter(s)

John M Tilford

Abstract/Description

Studies to assess the cost-effectiveness of alternative treatment or prevention strategies for children are far fewer than those for adults. This article highlights specific issues relevant to the conduct of cost-effectiveness analysis (CEA) in pediatric populations following the recommendations of the US Panel on Cost-effectiveness in Health and Medicine and discusses CEA applications relevant to emergency medical services for children. The article addresses whether patient time should be included in measures of costs, whether caregiver time costs are included and measured properly, and most importantly, whether the study can use quality adjusted life years (QALYs) as an outcome measure. Pediatric researchers may be unable to follow the panel's recommendations for including QALYs as an outcome measure in CEA studies involving young children. Developing preference weights applicable to young children may be a productive field for pediatric researchers. Without such efforts, the field of child health services research in general and the field of emergency medical services for children in particular will continue to lag behind adult fields in assessing the costs and outcomes of the services they provide.

Author(s)/Presenter(s)

Tilford JM, Simpson PM, Green JW, Lensing S, Fiser DH

Abstract/Description

Context: Pediatric intensive care units (PICUs) have expanded nationally, yet few studies have examined the potential impact of regionalization and no study has demonstrated whether a relationship between patient volume and outcome exists in these units. Documentation of an inverse relationship between volume and outcome has important implications for regionalization of care.

Objectives: This study examines relationships between the volume of patients and other unit characteristics on patient outcomes in PICUs. Specifically, we investigate whether an increase in patient volume improves mortality risk and reduces length of stay.

Design and setting: A prospective multicenter cohort design was used with 16 PICUs. All of the units participated in the Pediatric Critical Care Study Group. Participants. Data were collected on 11 106 consecutive admissions to the 16 units over a 12-month period beginning in January 1993.

Main outcome measures: Risk-adjusted mortality and length of stay were examined in multivariate analyses. The multivariate models used the Pediatric Risk of Mortality score and other clinical measures as independent variables to risk-adjust for illness severity and case-mix differences.

Results: The average patient volume across the 16 PICUs was 863 with a standard deviation of 341. We found significant effects of patient volume on both risk-adjusted mortality and patient length of stay. A 100-patient increase in PICU volume decreased risk-adjusted mortality (adjusted odds ratio:.95; 95% confidence interval:.91-.99), and reduced length of stay (incident rate ratio:.98; 95% confidence interval:.975-.985). Other PICU characteristics, such as fellowship training program, university hospital affiliation, number of PICU beds, and children's hospital affiliation, had no effect on risk-adjusted mortality or patient length of stay.

Conclusions: The volume of patients in PICUs is inversely related to risk-adjusted mortality and patient length of stay. A further understanding of this relationship is needed to develop effective regionalization and referral policies for critically ill children.

Author(s)/Presenter(s)

Fiser DH, Tilford JM, Roberson PK

Abstract/Description

Objective: The purpose of this study was to establish relationships between illness severity, length of stay, and functional outcomes in the pediatric intensive care unit (PICU) by using multi-institutional data. We hypothesized that a positive relationship exists between functional outcome scores, severity of illness, and length of stay.

Design: The study used a prospective multicentered inception cohort design.

Setting: The study was conducted in 16 PICUs across the United States that were member institutions of the Pediatric Critical Care Study Group of the Society of Critical Care Medicine.

Patients: In total, 11,106 patients were assessed, representing all admissions to these intensive care units for 12 consecutive months.

Measurements: Functional outcomes were measured by the Pediatric Overall Performance Category (POPC) and Pediatric Cerebral Performance Category (PCPC) scales. Both scales were assessed at baseline and discharge from the PICU. Delta scores were formed by subtracting baseline scores from discharge scores. Other measurements included admission Pediatric Risk of Mortality scores, age, operative status, length of stay in the PICU, and diagnoses. Interrater reliability was assessed by using a set of ten standardized cases on two occasions 6 months apart.

Main results: Baseline, discharge, and delta POPC and PCPC outcome scores were associated with length of stay in the PICU and with predicted risk of mortality (p < .01). Incorporation of baseline functional status in multivariate length of stay analyses improved measured fit. Mild baseline cerebral deficits in children were associated with 18% longer PICU stays after controlling for other patient and institutional characteristics. Moderate and severe baseline deficits for both the POPC and PCPC score predict increased length of stay of between 30% and 40%. On the standardized cases, interrater consensus was achieved on 82% of scores with agreement to within one neighboring class for 99.7% of scores.

Conclusions: These data establish current relationships for the POPC and PCPC outcome scales based on multi-institutional data. The reported relationships can be used as reference values for evaluating clinical programs or for clinical outcomes research.

Author(s)/Presenter(s)

Goldstein B, Fiser DH, Kelly MM, Mickelsen D, Ruttimann U, Pollack MM

Abstract/Description

Objectives: To determine if decomplexification of heart rate dynamics occurs in critically ill and injured pediatric patients. We hypothesized that heart rate power spectra, a measure of heart rate dynamics, would inversely correlate with measures of severity of illness and outcome.

Design: A prospective clinical study.

Setting: A 12-bed pediatric intensive care unit (ICU) in a tertiary care children's hospital.

Patients: One hundred thirty-five consecutive pediatric ICU admissions.

Interventions: None.

Measurements and main results: We compared heart rate power spectra with the Pediatric Risk of Mortality (PRISM) score, the Pediatric Cerebral Performance Category (PCPC), and the Pediatric Overall Performance Category (POPC). We found significant negative correlations between minimum low-frequency and high-frequency heart rate power spectral values recorded during ICU stay and the maximum PRISM score (log low-frequency heart rate power vs. PRISM, r2 = .293, p < .001; and log high-frequency heart rate power vs. PRISM, r2 = .243, p < .001) and outcome at ICU discharge (log low-frequency heart rate power vs. POPC or PCPC, r2 = .429, p < .001; and log high-frequency heart rate power vs. POPC or PCPC, r2 = .271, p < .001).

Conclusions: Our data support the hypothesis that measures of heart rate power spectra are inversely related and negatively correlated to severity of illness and outcome in critically ill and injured children. The phenomenon of decomplexification of physiologic dynamics may have important clinical implications in critical illness and injury.

Author(s)/Presenter(s)

Tilford JM, Roberson PK, Lensing S, Fiser DH

Abstract/Description

Objectives: To compare pediatric intensive care unit (ICU) mortality risk using models from two distinct time periods; and to discuss the implications of changing mortality risk for severity systems and quality-of-care assessment.

Data sources and setting: Consecutive admissions (n = 10,833) from 16 pediatric ICUs across the United States that participate in the Pediatric Critical Care Study Group were recorded prospectively. Data collection occurred during a 12-mo period beginning in January 1993.

Methods: Data collection for the development and validation of the original Pediatric Risk of Mortality (PRISM) score occurred from 1980 to 1985. The original PRISM coefficients were used to calculate mortality probabilities in the current data set. Updated estimates of mortality probabilities were calculated, using coefficients from a logistic regression analysis using the original PRISM variable set. Quality-of-care tests were performed using standardized mortality ratios.

Results: Risk of mortality from pediatric ICU admission improved considerably between the two periods. Overall, the reduction in mortality risk averaged 15% (p < .001). Analysis of mortality risk by age indicated a large improvement for younger infants. The mortality risk for infants <1 mo improved by 39% (p < .001). Mortality risk improved by 28% (p < .001) for infants between 1 and 12 mos. Analysis of mortality risk by principal diagnosis indicated substantial improvement in respiratory diseases, including respiratory diseases developing in the perinatal period. The mortality risk for respiratory diseases improved by 45% (p < .001). The improvement in mortality risk substantially deteriorated the calibration of the original PRISM severity system (p < .001). As a result of changing mortality risk, the standardized mortality ratios across the 16 pediatric ICUs demonstrated substantial disparities, depending on the choice of models.

Conclusions: This study documents differences in pediatric ICU risk of mortality over time that are consistent with a general improvement in the quality of pediatric intensive care. Despite continued widespread use of the original PRISM, recent improvements in pediatric ICU quality of care have negated its usefulness for many intended applications, including quality-of-care assessment.

Author(s)/Presenter(s)

Ruttimann UE, Pollack MM, Fiser DH

Abstract/Description

Objective: To develop a method based on admission day data for predicting patient outcome status as independently functional, compromised functional, or dead.

Design: Prospectively acquired development and validation samples.

Setting: A pediatric intensive care unit located in a tertiary care center.

Patients: Consecutive admissions (n = 1,663) for predictor development, and consecutive admissions (n = 1,153) for predictor validation.

Methods: Pediatric Risk of Mortality score, baseline Pediatric Overall Performance Category score, age, operative status, and primary diagnosis classified into ten organ systems and nine etiologies were recorded at the time of intensive care unit admission. Predictor was developed by stepwise polychotomous logistic regression analysis for the outcome functional, compromised, and dead. Model fit was evaluated by chi-square statistics; prediction performance was measured by the area under the receiver operating characteristic curve, and classification table analysis of observed vs. predicted outcomes.

Measurements and main results: The resulting predictor included Pediatric Risk of Mortality, baseline Pediatric Overall Performance Category, operative status, age, and diagnostic factors from four systems (cardiovascular, respiratory, neurologic, gastrointestinal), and six etiologies (infection, trauma, drug overdose, allergy/immunology, diabetes, miscellaneous/undetermined). Its application to the validation sample yielded good agreement between the total number expected and the observed outcomes for each state (chi-square = 3.16, 2 degrees of freedom, p = .206), with area indices of 0.96 +/- 0.01 for discrimination of fully functional vs. the combination of the two poor outcome states (compromised or death), and 0.94 +/- 0.02 for discrimination of fully or compromised functional vs. death. The 3 x 3 classification resulted in correct classification rates of 83.2%, 74.4%, and 81.3%, for the outcomes functional, compromised, and death, respectively.

Conclusions: Prediction of three outcome states using physiologic status, baseline functional level, and broad-based diagnostic groupings at admission is feasible and may improve the relevance of quality of care assessment.

Author(s)/Presenter(s)

Tilford JM, Roberson PK, Fiser DH

Author(s)/Presenter(s)

Fiser DH

Abstract/Description

In recent years, interest in assessing quality of care has blossomed. Quality care may be defined as providing the most appropriate treatment and providing it with great technical and managerial skill and proficiency in a manner that gains patient acceptance. For assessment purposes, variation in risk-adjusted outcomes between providers should be attributable to quality of care differences. Some methods for measuring outcomes and risk-adjustment for pediatric intensive care populations have been developed, but additional tools are needed for applications in outcomes management, continuous quality improvement, and outcomes research.