Inter-rater Agreement for Abstraction of the Early Management Bundle, Severe Sepsis/Septic Shock (SEP-1) Quality Measure in a Multi-Hospital Health System.

BACKGROUND: The Early Management Bundle, Severe Sepsis/Septic Shock (SEP-1) quality measure is complex to abstract, which may lead to discrepancies between abstractors. This study was designed to evaluate inter-rater agreement between abstractors at individual hospitals in a health system and a lead abstractor on abstraction elements and measure compliance for SEP-1. METHODS: Patient cases qualifying for abstraction for SEP-1 over a four-month period in 2016 were initially abstracted at a local hospital and then centrally by a lead abstractor. Abstraction results were retrospectively compared to determine inter-rater agreement. RESULTS: A total of 580 SEP-1 cases were abstracted locally and centrally. Each site contributed a median (interquartile range) of 63 (49, 86) cases. There was complete concordance of measure-related elements in 391 cases (67%) (inter-rater agreement: κ = 0.40, p < 0.01). The most common discrepancy (60 cases) was severe sepsis presentation time. There was a weak correlation between SEP-1 compliance adjudicated locally and centrally (r2 = 0.41, p < 0.01). The average change in monthly SEP-1 measure compliance at each site after central adjudication was a 1% increase but ranged from a 49% decrease to a 40% increase. CONCLUSIONS: Concordance on SEP-1 abstraction elements between local and expert adjudicators was fair, and SEP-1 performance varied considerably from initial site-reported performance. The detailed nature of SEP-1 can lead to unreliable abstraction, which may lead to inaccurate reporting of compliance with the measure and affect comparability of performance between hospitals. Abstraction by a dedicated team for SEP-1 can reduce variability and improve efficiency.

Prediction of outcome in acute lower-gastrointestinal haemorrhage based on an artificial neural network: internal and external validation of a predictive model.

BACKGROUND: Models based on artificial neural networks (ANN) are useful in predicting outcome of various disorders. There is currently no useful predictive model for risk assessment in acute lower-gastrointestinal haemorrhage. We investigated whether ANN models using information available during triage could predict clinical outcome in patients with this disorder. METHODS: ANN and multiple-logistic-regression (MLR) models were constructed from non-endoscopic data of patients admitted with acute lower-gastrointestinal haemorrhage. The performance of ANN in classifying patients into high-risk and low-risk groups was compared with that of another validated scoring system (BLEED), with the outcome variables recurrent bleeding, death, and therapeutic interventions for control of haemorrhage. The ANN models were trained with data from patients admitted to the primary institution during the first 12 months (n=120) and then internally validated with data from patients admitted to the same institution during the next 6 months (n=70). The ANN models were then externally validated and direct comparison made with MLR in patients admitted to an independent institution in another US state (n=142). FINDINGS: Clinical features were similar for training and validation groups. The predictive accuracy of ANN was significantly better than that of BLEED (predictive accuracy in internal validation group for death 87% vs 21%; for recurrent bleeding 89% vs 41%; and for intervention 96% vs 46%) and similar to MLR. During external validation, ANN performed well in predicting death (97%), recurrent bleeding (93%), and need for intervention (94%), and it was superior to MLR (70%, 73%, and 70%, respectively). INTERPRETATION: ANN can accurately predict the outcome for patients presenting with acute lower-gastrointestinal haemorrhage and may be generally useful for the risk stratification of these patients.

Success and shortcomings of a clinical care pathway in the management of acute nonvariceal upper gastrointestinal bleeding.

OBJECTIVES: Acute nonvariceal upper gastrointestinal (GI) bleeding is the most common medical emergency encountered by gastroenterologists resulting in high patient morbidity and cost. We sought to establish if a GI bleeding clinical care pathway could improve the quality and cost effectiveness of inpatient medical care. METHODS: A disease management program for acute upper GI bleeding was established. Length of stay, time to endoscopy, utilization of potentially unnecessary radiological tests, acid suppression, and cost of care were compared between patients pre- and postinitiation of GI bleeding pathway guidelines. RESULTS: The instituted GI bleeding management program significantly reduced the use of intravenous H2-blockade from 65.3% to 47.7% (p = 0.002). The use of radiological tests, time to endoscopy, and length of hospital of stay were unchanged. There was a trend toward a reduction in total cost and variable direct cost per patient admitted with acute upper GI bleeding, from $5,381 to $4,627 and from $2,269 to $1,952, respectively. CONCLUSION: A clinical care pathway may affect the management of acute upper GI bleeding and reduce costs. However, there are significant limitations and barriers to the overall effectiveness of such a pathway in actual clinical practice.