An Analysis of VTE Prophylaxis Practice in Oncology Patients after Implementation of a Standardized Mandatory Computerized Clinical Decision Support Tool

![Graphic][1] Introduction: Venous thromboembolism (VTE) is an important cause of morbidity and mortality in oncology patients. Prophylaxis reduces the risk of VTE by 60% but many patients are not prescribed risk-appropriate VTE prophylaxis. We developed mandatory computerized clinical decision support-enabled, service-specific (CCDS) order sets to improve our institution’s VTE prophylaxis performance. The order sets require providers to complete short check lists to assess VTE risk factors and contraindications to pharmacologic prophylaxis. Based upon the answers to these questions, the order sets display the risk-appropriate VTE prophylaxis regimen for each individual patient. The purpose of this retrospective study is to evaluate VTE prophylaxis and events rates in hospitalized cancer patients admitted using a CCDS medical oncology VTE order set. Methods: Using electronic administrative records, we retrospectively collected prescription and clinical data on patients admitted to the solid tumor and hematologic malignancy services at the Johns Hopkins Sidney Kimmel Comprehensive Cancer Center (JHSKCCC) from October 17, 2010 (date of order set implementation) through June 30, 2014. A two-sided student’s t test or chi-square test were used for statistical analyses, as appropriate. Results: 7920 patients were admitted from 10/17/2010 to 6/30/14. The mean age was 57 years and 46% were female. The median length of stay was 4 days. Solid tumor service providers were more likely to prescribe risk-appropriate VTE prophylaxis (Table 1) and patients on the solid tumor service were more likely to be assessed as being at high risk for VTE (Table 2). Pharmacologic prophylaxis was more common on the solid tumor service while ambulation was the most common form of prophylaxis on the hematologic malignancy service. (Table 3) Risk-appropriate VTE prophylaxis was high on both services ([Figure 1][2]). Data on objectively-confirmed hospital-acquired VTE will be presented at the meeting. Conclusion: We report the largest analysis to date of VTE prophylaxis practices in hospitalized cancer patients. Significant differences in perceived VTE risk and prescribed prophylaxis were noted between services. Use of a computerized decision support-enabled VTE prophylaxis order set was associated with high rates of risk-appropriate VTE prophylaxis. | | Solid Tumor | Heme Malignancy | P-Value | | ---------------------------- | ----------- | --------------- | ------- | | Total – no. | 4995 | 2925 | | | Mean Age – no. (SD) | 58.0 (13.2) | 56.1 (14.7) | <0.001 | | Female – no. | 2290 (46%) | 1303 (45%) | | | Median length of stay (IQR) | 4 (3-6) | 5 (3-10.5) | | | Risk Appropriate Prophylaxis | 4410 (88%) | 2474 (85%) | <0.001 | Table 1: Patient Population Characteristics | VTE Risk Category | Solid Tumor | Heme Malignancy | P-value | | -------------------------- | ----------- | --------------- | ------- | | High Risk – no. (%) | 4782 (96%) | 2338 (80%) | <0.001 | | High Risk w/ CI –no. (%) | 1222 (25%) | 1789 (61%) | <0.001 | | High Risk w/o CI - no. (%) | 3560 (71%) | 549 (19%) | <0.001 | | Moderate Risk – no. (%) | 213 (4%) | 587 (20%) | <0.001 | | Mod. Risk w/ CI – no. (%) | 41 (1%) | 506 (17%) | <0.001 | | Mod. Risk w/o CI – no. (%) | 172 (3%) | 81 (3%) | <0.001 | Table 2: VTE Risk Assessment of Patient Population CI= Contraindication to pharmacologic prophylaxis | | Medical Oncology | Heme Malignancy | P-value | | ------------------------- | ---------------- | --------------- | ------- | | Pharm Only – no. (%) | 2992 (69%) | 412 (15%) | <0.001 | | Mech Only – no. (%) | 700 (16%) | 563 (20%) | | | Pharm + Mech – no. (%) | 388 (9%) | 87 (3%) | | | Ambulation Only – no. (%) | 230 (5%) | 1699 (61%) | <0.001 | Table 3: VTE Prophylaxis Orders Pharm= pharmacologic prophylaxis (i.e. unfractionated or low molecular weight heparin, fondaparinux), Mech= graduate compression stockings or sequential compression devices or both ![Figure 1:][3] Figure 1: Disclosures Streiff: Boehringer-Ingelheim: Consultancy; Daiichi-Sankyo: Consultancy; Janssen Healthcare: Consultancy; Pfizer: Consultancy; Portola: Research Funding. [1]: /embed/inline-graphic-2.gif [2]: #F1 [3]: pending:yes