An electronic tool for venous thromboembolism prevention in medical and surgical patients.

BACKGROUND AND OBJECTIVES: Venous thromboembolism (VTE) is a complex disorder influenced by numerous risk factors, and occurs frequently in at-risk hospitalized patients. Because appropriate prevention with thromboprophylaxis is underused, we wanted to create an electronic tool to provide a simple risk assessment and suggest appropriate prophylaxis. DESIGN AND METHODS: To develop the risk matrix, iterative rating of odds ratios was performed for 60 predisposing VTE risk factors, using analytical methods that account for multiple risk factors in a single patient and their non-independence. For exposing risk factors, a single score was assigned to each set of factors, both medical (25 items) and surgical conditions (144 items). A CART regression model was used to integrate the risk scales into a 4-level measure of overall risk. The validity of the level of risk and the appropriateness of 11 different prophylactic approaches was assessed using the RAND/UCLA appropriateness method and validated by expert opinion ratings (n=1998) on sample case scenarios (n=108). RESULTS: Correlation between the level of risk calculated by the risk matrix and that offered by expert opinion for individual surgical and medical clinical cases was high (65% and 70%, respectively). The matrix over-estimated the level of risk, compared with that offered by expert opinion, in 28% and 20% of surgical and medical cases, respectively, but the appropriate prophylaxis suggested was no different. Between-expert agreement on the appropriateness of the prophylaxis recommendations was high (90-94% of indications). INTERPRETATION AND CONCLUSIONS: This computer-based electronic tool for individualized assessment of venous thromboembolic risk successfully identified both the perceived risk of thrombosis and the appropriate prophylactic approach for medical and surgical patients.

OncoSurge: a strategy for improving resectability with curative intent in metastatic colorectal cancer.

PURPOSE: Most patients with colorectal liver metastases present to general surgeons and oncologists without a specialist interest in their management. Since treatment strategy is frequently dependent on the response to earlier treatments, our aim was to create a therapeutic decision model identifying appropriate procedure sequences. METHODS: We used the RAND Corporation/University of California, Los Angeles Appropriateness Method (RAM) assessing strategies of resection, local ablation and chemotherapy. After a comprehensive literature review, an expert panel rated appropriateness of each treatment option for a total of 1,872 ratings decisions in 252 cases. A decision model was constructed, consensus measured and results validated using 48 virtual cases, and 34 real cases with known outcomes. RESULTS: Consensus was achieved with overall agreement rates of 93.4 to 99.1%. Absolute resection contraindications included unresectable extrahepatic disease, more than 70% liver involvement, liver failure, and being surgically unfit. Factors not influencing treatment strategy were age, primary tumor stage, timing of metastases detection, past blood transfusion, liver resection type, pre-resection carcinoembryonic antigen (CEA), and previous hepatectomy. Immediate resection was appropriate with adequate radiologically-defined resection margins and no portal adenopathy; other factors included presence of < or = 4 or > 4 metastases and unilobar or bilobar involvement. Resection was appropriate postchemotherapy, independent of tumor response in the case of < or = 4 metastases and unilobar liver involvement. Resection was appropriate only for > 4 metastases or bilobar liver involvement, after tumor shrinkage with chemotherapy. When possible, resection was preferred to local ablation. CONCLUSION: The results were incorporated into a decision matrix, creating a computer program (OncoSurge). This model identifies individual patient resectability, recommending optimal treatment strategies. It may also be used for medical education.