ABC | Volume 114, Nº3, March 2020

Original Article Silva et al. Warfarin therapy in NVAF patients in Brazil Arq Bras Cardiol. 2020; 114(3):457-466 end of the recommended levels of anticoagulation (near 60%). 4,8 In Brazil, some observational studies in the public setting showed that most patients had good anticoagulation control, though TTR levels were in the lower end of the threshold. 9-11 Managing OAC use, including INR monitoring, are costly and inaccessible for many patients in Latin America. 4 To date, few studies have been conducted in private settings in the region. Associations of TTR levels with clinical or economic outcomes were generally not reported. The objective of this study was to develop a profile of patients receiving warfarin for NVAF in a private setting in Brazil, and to evaluate the quality of anticoagulation control and clinical/economic outcomes. Methods Data Sources Data from May 1, 2014 to April 30, 2016 were pulled from a large private health insurance dataset in Brazil – AMIL. AMIL is one of the largest health insurance companies in Brazil, with over 4 million beneficiaries and clinical care programs with integrated and structured information of prevalent diseases. The AMIL dataset combines electronic medical records containing information on patient demographics, enrolment and clinical history, with medical claims from outpatient and inpatient hospital admissions, ambulatory care facilities and emergency departments. For warfarin-treated patients, AMIL runs a private anticoagulation phone monitoring program named VIVA AMIL. 12 Within this program, trained nurses and nursing technicians make monthly phone calls to patients to collect patient data, self-reported results of the last INR test, occurrence of thromboembolic and bleeding events, medication regularity and adverse effects. An existing template, created to capture data from the monitored patients, was used to ensure the test results, experienced events and patterns were reported consistently to meet the program needs. An initial call was made to collect clinical and demographic data (if otherwise not available), including the presence of chronic conditions and medications under use. Each patient then received monthly outbound calls, but patients also had the option to call as needed. In case the patient did not have a current or recent INR test result, a nurse would support them by requesting the test and reminding them to call back and report the results. In the situation in which the INR results reported by the patient were out of the target range (INR 2-3), the nurse would discuss dose adjustments with the patient and advise them to seek medical advice in person. Patient Selection Patients aged 18 or older were included if they had an AF diagnosis (ICD-10-CM code I48) or were assessed for AF in a specific system form in the electronic medical record, if they received at least one prescription for VKA during the study period, had continuous health plan coverage and if they were followed by the phone-monitoring program for at least 4 months with a record of the calls in at least 50% of the months during the study period. Patients with evidence of moderate/severe mitral stenosis, VTE or a mechanical prosthetic valve were excluded. The research protocol was approved by the local Institutional Review Board. Variables and Outcome Measures Key characteristics of patients receiving warfarin were analyzed from claims, electronic medical records and self‑reports: demographics and clinical history (CHA 2 DS 2 -VASc score, comorbidities, prior stroke or bleeds, INR and TTR). Specifically, patients were classified as having chronic renal failure when there was at least one of the selected ICD-10 codes (Appendix A) linked to them in the dataset during the entire study period, or if chronic renal failure was present in the data collection formmanaged by the nurse. Concomitant medication utilization and INR frequency patterns were also assessed. Consistent with guidelines and prior studies, 2,6 the quality of INR control was based on the percentage of time during which a patient receiving warfarin was within therapeutic range (2.0-3.0) over the entire follow-up period. Good control was defined as TTR ≥ 65%. The number of INR tests for each patient was obtained through the claims dataset, which did not record the INR values. During the phone monitoring calls, the trained nurse would ask the patient to report the values of the INR tests undertaken since the last call. The INR test frequency was used to calculate the total and mean INR tests per patient. Since the INR is a low-complexity and low-cost procedure, the test could have been paid out-of-pocket by the patient and therefore not reported in claims. In order to reduce the impact of unstated INR tests, during the phone monitoring calls the nurse would ask the patient to also report the date of the INR test, along with the INR values. For those cases in which a corresponding claim was absent, the nurse would manually add the test frequency information in the electronic medical record. TTR was calculated using the Rosendaal method, computed using the INR values that were recorded in the electronic medical records. 13 The clinical outcomes assessed were major and minor bleeding events, identified using the ICD-10 codes of inpatient claims listed in Appendix A. 14 Self-reported situations were also considered. The diagnosis codes used for major bleeds were based on a validated administrative claim-based algorithm, as well as the International Society on Thrombosis and Hemostasis definition of major bleeding. 15,16 Bleeding rates were calculated as the number of patients with at least one self-reported bleeding episode during the monitoring period, divided by the total number of patients. To assess the outcomes, patients were followed until April 30, 2016, unless health plan disenrollment or death occurred first. All-cause direct medical costs were assessed from the claims of each patient for office elective visits, emergency department visits, outpatient tests/procedures, inpatient admissions, and home health/care transition admissions. The costs represented the actual costs borne by the insurance provider (AMIL). Out‑of‑pocket costs were not included. The costs were available in the data source over the study period and were annualized by dividing themby the months of the study period andmultiplying them by 12. After this calculation, costs were expressed 458