Objective . To assess the effect on risk-adjustment of inpatient mortality rates of progressively enhancing administrative claims data with clinical data that are increasingly expensive to obtain. Data Sources . Claims and abstracted clinical data on patients hospitalized for 5 medical conditions and 3 surgical procedures at 188 Pennsylvania hospitals from July 2000 through June 2003. Methods . Risk-adjustment models for inpatient mortality were derived using claims data with secondary diagnoses limited to conditions unlikely to be hospital-acquired complications. Models were enhanced with one or more of 1) secondary diagnoses inferred from clinical data to have been present-on-admission (POA), 2) secondary diagnoses not coded on claims but documented in medical records as POA, 3) numerical laboratory results from the first hospital day, and 4) all available clinical data from the first hospital day. Alternative models were compared using c-statistics, the magnitude of errors in prediction for individual cases, and the percentage of hospitals with aggregate errors in prediction exceeding specified thresholds. Results . More complete coding of a few under-reported secondary diagnoses and adding numerical laboratory results to claims data substantially improved predictions of inpatient mortality. Little improvement resulted from increasing the maximum number of available secondary diagnoses or adding additional clinical data. Conclusions . Increasing the completeness and consistency of reporting a few secondary diagnosis codes for findings POA and merging claims data with numerical laboratory values improved risk adjustment of inpatient mortality rates. Expensive abstraction of additional clinical information from medical records resulted in little further improvement.

Objective:To evaluate whether administrative claims data (ADM) from hospital discharges can be transformed by present-on-admission (POA) codes and readily available clinical data into a refined database that can support valid risk stratification (RS) of surgical outcomes. Summary Background Data:ADM from hospital discharges have been used for RS of medical and surgical outcomes, but results generally have been viewed with skepticism because of limited clinical information and questionable predictive accuracy. Methods:We used logistic regression analysis to choose predictor variables for RS of mortality in abdominal aortic aneurysm repair, coronary artery bypass graft surgery, and craniotomy, and for RS of 4 postoperative complications (ie, physiologic/metabolic derangement, respiratory failure, pulmonary embolism/deep vein thrombosis, and sepsis) after selected operations. RS models were developed for age only (Age model), ADM only (ADM model), ADM enhanced with POA codes for secondary diagnoses (POA-ADM model), POA-ADM supplemented with admission laboratory data (Laboratory model), Laboratory model supplemented with admission vital signs and additional laboratory data (VS model), VS model supplemented with key clinical findings abstracted from medical records (KCF model), and KCF model supplemented with composite clinical scores (Full model). Models were evaluated using c-statistics, case-based errors in predictions, and measures of hospital-based systematic bias. Results:The addition of POA codes and numerical laboratory results to ADM was associated with substantial improvements in all measures of analytic performance. In contrast, the addition of difficult-to-obtain key clinical findings resulted in only small improvements in predictions. Conclusions:Enhancement of ADM with POA codes and readily available laboratory data can efficiently support accurate risk-stratified measurements of clinical outcomes in surgical patients.

Tools that support screening for medical errors can help to identify potential patient safety events for further investigation and can provide benchmarks against which providers, localities, and states can compare themselves. The Agency for Healthcare Research and Quality Patient Safety Indicators, which are based solely on hospital administrative or claims data, represent one such tool. Without sufficient clinical detail, measures based on claims data may not accurately reflect hospital quality of care. To construct risk-adjustment models, we used hospital discharge data from July 2000 to June 2003 from 188 Pennsylvania hospitals supplied by the Pennsylvania Health Care Cost Containment Council. We augmented the hospital claims data with clinical data (also supplied by the Pennsylvania Health Care Cost Containment Council) abstracted from medical records using MediQual's proprietary Atlas™ (MediQual, Westborough, MA, a subsidiary of CardinalHealth) clinical information system. Clinical data elements included such items as patient history, laboratory results, vital signs, and other clinical findings. Our cost-effectiveness analyses strongly support the value of enhancing administrative claims data with a present-on-admission code and adding a limited set of numerical laboratory values. Reasonable additional benefit may be gained by adding vital signs to this data set, but the trade-off between effectiveness and cost is not as clear. Also, more accurate International Classification of Diseases, Ninth Revision, Clinical Modification coding of specific secondary diagnoses that are currently undercoded could improve the validity of risk-adjustment equations without the added cost of abstracting clinical findings from medical records. There seems to be little justification for secondary abstraction of medical records to obtain data for risk-adjusting the Agency for Healthcare Research and Quality Patient Safety Indicators.

ContextComparisons of risk-adjusted hospital performance often are important components of public reports, pay-for-performance programs, and quality improvement initiatives. Risk-adjustment equations used in these analyses must contain sufficient clinical detail to ensure accurate measurements of hospital quality.ObjectiveTo assess the effect on risk-adjusted hospital mortality rates of adding present on admission codes and numerical laboratory data to administrative claims data.Design, Setting, and PatientsComparison of risk-adjustment equations for inpatient mortality from July 2000 through June 2003 derived by sequentially adding increasingly difficult-to-obtain clinical data to an administrative database of 188 Pennsylvania hospitals. Patients were hospitalized for acute myocardial infarction, congestive heart failure, cerebrovascular accident, gastrointestinal tract hemorrhage, or pneumonia or underwent an abdominal aortic aneurysm repair, coronary artery bypass graft surgery, or craniotomy.Main Outcome MeasuresC statistics as a measure of the discriminatory power of alternative risk-adjustment models (administrative, present on admission, laboratory, and clinical for each of the 5 conditions and 3 procedures).ResultsThe mean (SD) c statistic for the administrative model was 0.79 (0.02). Adding present on admission codes and numerical laboratory data collected at the time of admission resulted in substantially improved risk-adjustment equations (mean [SD] c statistic of 0.84 [0.01] and 0.86 [0.01], respectively). Modest additional improvements were obtained by adding more complex and expensive to collect clinical data such as vital signs, blood culture results, key clinical findings, and composite scores abstracted from patients' medical records (mean [SD] c statistic of 0.88 [0.01]).ConclusionsThis study supports the value of adding present on admission codes and numerical laboratory values to administrative databases. Secondary abstraction of difficult-to-obtain key clinical findings adds little to the predictive power of risk-adjustment equations.

We studied the impact of an endoluminally placed stented aortic graft on the geometry of a surgically created abdominal aortic dilation (AAD) in nonatherosclerotic mongrel dogs. Patulous iliac vein patch infrarenal aortoplasty produced a fusiform AAD, doubling the aorta diameter. Lumbar and mesenteric aortic tributaries were preserved and no mural thrombus formed. AADs created in 23 dogs were endoluminally excluded through transfemoral placement of a thin-wall Dacron graft 4 +/- 2 months later. Balloon-expandable stents were used to anchor each end of the graft to the aorta. The graft was crimped radially in its body and longitudinally at its ends to provide longitudinal and radial expandability in these respective zones. Serial color duplex, angiography, and direct caliper measurements were made. Before graft placement, a 19% +/- 11% diameter growth was observed. At graft placement, flow arrest immediately occurred in the space between the graft and the AAD intima in all cases. Although microscopic recanalization of the thrombus in this space was seen at sacrifice 6 and 12 months later, no macroscopic duplex flow was imaged. A 10% +/- 11% reduction in AAD diameter was measured at 6 months (p < 0.001), with no further reduction at 12 months. Graft dimensions remained stable. No anastomotic leaks developed. AAD growth stopped during the first year after effective endoluminal exclusion in normotensive dogs despite patent side branches (< 1.5 mm internal diameter) and no mural thrombus at the time of graft placement. Whether microscopic recanalization of the thrombus that forms outside the graft has an impact after 1 year remains to be seen.

A series of aryl bis-maleimides (BMIs) and bis-citraconimides (BCIs) were characterized by d.s.c. using both temperature scans and isothermal experiments. Impurities in the BMIs tend to increase the temperature at which thermal polymerization starts, while the converse is true for BCIs. This was attributed to the presence of an itaconimide impurity in the BCIs. In particular, the thermal polymerization kinetics of the compounds were investigated. Effects of structure and monomer purity on the thermal polymerization characteristics were identified.

Two aryl bismaleimides and the corresponding biscitraconimides, in which the imide groups were attached to the ends of aromatic residues containing four phenylene rings, were prepared and then purified by preparative high-performance liquid chromatography. Rigorous purification in this way was found to have marked effects on the thermal polymerization characteristics of these compounds as determined by the differential scanning calorimetry technique. The polymerization of bis-4-maleimidophenylmethane and of bis-4-maleimidophenyl ether was also affected by rigorous purification. Samples of the corresponding two bisnadimides containing four phenylene rings were also prepared.

Examination by d.s.c. of the thermal cure of two aryl bis-maleimides and the corresponding pair of citraconimides, in which the imide groups are attached to the ends of aromatic residues containing four phenylene rings, indicates that the pure bis-maleimides polymerize at lower temperatures than the corresponding citraconimides. A second reaction occurs after polymerization of the pure bis-maleimides has stopped; this appears from FTi.r. to involve residual maleimido groups; pure samples of bis-4-maleimidophenylmethane and bis-4-maleimidophenyl ether also showed this effect. Weight reduction commensurate with evolution of about 1.2 moles of cyclopentadiene occurred on curing the corresponding two bis-nadimides containing four phenylene rings at atmospheric pressure, the extent of this loss being independent of temperature in the range 250-350-degrees-C. Resins from the bis-maleimides containing four phenylene rings showed thermal/oxidative stability, measured by t.g.a., similar to that found for resins from bis-4-maleimidophenylmethane and bis-4-maleimidophenyl ether; resins from the bis-maleimides were rather more stable than those from the corresponding bis-citraconimides and bis-nadimides.