Implementing a Computerized Care Process Management System To Determine The Feasibility Of Utilizing, and Concomitantly Validating, a Prediction Tool For The Risk Of Venous Thromboembolism In Cancer Patients

Cancer patients have a significantly higher risk of developing a venous thromboembolism (VTE) compared to non-cancer patients. VTE result in reduced quality of life, and increased morbidity and mortality. However, studies suggest VTE risk among ambulatory cancer patients varies widely. Therefore, although several studies demonstrate that prophylaxis is effective, given the cost and concomitant bleeding risk it is not the standard of care to administer prophylaxis. Khorana and colleagues have developed a predictive model for chemotherapy-associated VTE in cancer patients. However, Methods to implement this model into clinical practice have not been developed. The purpose of this study was to create and assess an innovative computerized Care Process Management System(CPMS ) (that would calculate in real-time the risk for VTE by utilizing clinical information and laboratory tests contained in patient electronic records, based on the proposed predictive model, notifying staff to enable patient education about VTE risk and to concomitantly validate the model.

Over a four month period new cancer referrals to the Ottawa Regional Cancer Center, the sole provider of cancer care for a region of 1.2 million inhabitants, were assessed by the Khorana tool (Blood 2008;111:4902-7). This model consists of the following five predictive variables: (1) site of cancer (2 points for very high-risk site (brain, stomach, pancreas), 1 point for high-risk site (lung, lymphoma, gynecologic, bladder, and testicular), (2) platelet count ≥350 x 10⁹/L, (3) hemoglobin <10 g/dL and/or use of erythropoiesis-stimulating agents, (4) leukocyte count >11 x 10⁹/L, and (5) body mass index (BMI) ≥35 kg/m² (1 point each). High risk was defined as a score or ≥2. We approached all new cancer patients but excluded patients if they were: (1) tumours not included as very high risk or high risk according to the prediction model; 2) to be followed up or treated at another facility other than The Ottawa Hospital; 3) had a confirmed VTE/arterial embolism (stroke or peripheral arterial embolism) within the prior 3 months; 4) were receiving continuous anticoagulation; 5) had previously been treated for cancer. Patients with a very high risk tumour site were approached first. Those with other tumour sites had the predictive variables calculated through the CPMS. In all cases the clinic nurse was notified electronically of when patients presented to clinic and of their risk. Patients’ demographics, medical history, malignancy characteristics, diagnostic laboratory features, imaging information, BMI and plan of anti-cancer treatment were documented prior to initiation of their cancer treatment. Educational material was provided to high risk patients regarding the signs and symptoms of VTE and their risk for VTE, in order to prevent delayed diagnosis. Patients were followed-up at 3 months (±7 days) following the initial consult to determine if they were diagnosed with VTE.

699 new referrals were determined to have a cancer diagnosis for the first time as identified by the computer software and qualified for our study and 580 were eligible. On the basis of very high risk tumour site alone, 71 patients were initially deemed at high risk of developing a VTE (score ≥2) and 509 patients were deemed at low risk (score ≤1). Among the initial cohort of patients at low risk, 72 were elevated to high risk based on BMI and pre-chemotherapy blood work. In total 25% had high risk for VTE and during the 3-month follow up period, 16 of the 143 (11%) developed a VTE which further validates the Khorana model for identifying high risk patients. Patients uniformly were receptive to receiving counseling about their VTE risk at enrolment. In summary, we have demonstrated the feasibility of utilizing a computerized CPMS linked to the electronic medical record to populate a predictive tool that is based on clinical information and laboratory data to identify and stratify cancer patients into high and low risk of developing a VTE. Our future aim is to utilize this innovative tool in clinical practice to enable 1) identification of all cancer patients at high risk for VTE, 2) education that will potentially decrease the time between symptom onset, VTE investigation, and treatment, and 3) enrollment in randomized trials of VTE prophylaxis.