Prediction Score for Anticoagulation Control Quality Among Older Adults The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Lin, Kueiyu Joshua, Daniel E. Singer, Robert J. Glynn, Suzanne Blackley, Li Zhou, Jun Liu, Gina Dube, Lynn B. Oertel, and Sebastian Schneeweiss. 2017. “Prediction Score for Anticoagulation Control Quality Among Older Adults.” Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease 6 (10): e006814. doi:10.1161/JAHA.117.006814. http://dx.doi.org/10.1161/ JAHA.117.006814. Published Version doi:10.1161/JAHA.117.006814 Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:34651988 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA SYSTEMATIC REVIEW AND META-ANALYSIS Prediction Score for Anticoagulation Control Quality Among Older Adults Kueiyu Joshua Lin, MD, ScD, MPH; Daniel E. Singer, MD; Robert J. Glynn, PhD, ScD; Suzanne Blackley, MA; Li Zhou, MD, PhD; Jun Liu, MD; Gina Dube, PharmD, CACP, RPh; Lynn B. Oertel, MS, ANP-BC, CACP; Sebastian Schneeweiss, MD, ScD Background-—Time in the therapeutic range (TTR) is associated with the effectiveness and safety of vitamin K antagonist (VKA) therapy. To optimize prescribing of VKA, we aimed to develop and validate a prediction model for TTR in older adults taking VKA for nonvalvular atrial fibrillation and venous thromboembolism. Methods and Results-—The study cohort comprised patients aged ≥65 years who were taking VKA for atrial fibrillation or venous thromboembolism and who were identified in the 2 US electronic health record databases linked with Medicare claims data from 2007 through 2014. With the predictors identified from a systematic review and clinical knowledge, we built a prediction model for TTR, using one electronic health record system as the training set and the other as the validation set. We compared the performance of the new models to that of a published prediction score for TTR, SAMe-TT2R2. Based on 1663 patients in the training set and 1181 in the validation set, our optimized score included 42 variables and the simplified model included 7 variables, abbreviated as PROSPER (Pneumonia, Renal dysfunction, Oozing blood [prior bleeding], Staying in hospital ≥7 days, Pain medication use, no Enhanced [structured] anticoagulation services, Rx for antibiotics). The PROSPER score outperformed SAMe-TT2R2 when predicting both TTR ≥70% (area under the receiver operating characteristic curve 0.67 versus 0.55) and the thromboembolic and bleeding outcomes (area under the receiver operating characteristic curve 0.62 versus 0.52). Conclusions-—Our geriatric TTR score can be used as a clinical decision aid to select appropriate candidates to receive VKA therapy and as a research tool to address confounding and treatment effect heterogeneity by anticoagulation quality. ( J Am Heart Assoc. 2017;6:e006814. DOI: 10.1161/JAHA.117.006814.) Key Words: anticoagulant • atrial fibrillation • quality control • stroke • venous thromboembolism itamin K antagonist (VKA; eg, warfarin) therapy is an measured by the time in therapeutic range (TTR), for which V effective anticoagulation option for stroke prevention in INR 2.0 to 3.0 is the standard therapeutic range for AF and patients with nonvalvular atrial fibrillation (AF) and for VTE.4–6 Patients on VKA with poor anticoagulation quality (ie, treatment and secondary prevention of venous thromboem- low TTR) have been shown to have a higher risk of bolism (VTE; including deep vein thrombosis and pulmonary thromboembolic and bleeding complications and thus a worse embolism).1–3 The safety and effectiveness of VKAs, however, risk–benefit ratio.4,7,8 depends on regular international normalized ratio (INR) Although clinical trials have shown that direct-acting oral monitoring and anticoagulation control quality, often anticoagulants (DOACs) are therapeutically advantageous over From the Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA (K.J.L., R.J.G., J.L., S.S.); Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA (K.J.L., D.E.S.); Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA (K.J.L., D.E.S., R.J.G., S.S.); Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA (L.Z.); Clinical and Quality Analysis, Information Systems, Partners HealthCare System, Boston, MA (S.B.); Clinical Informatics, Partners eCare, Partners HealthCare System, Boston, MA (L.Z.); Department of Pharmacy, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA (G.D.); Anticoagulation Management Service, Department of Nursing, Massachusetts General Hospital, Boston, MA (L.B.O.). Accompanying Data S1, Tables S1 through S7 and Figures S1, S2 are available at http://jaha.ahajournals.org/content/6/10/e006814/DC1/embed/inline-supple mentary-material-1.pdf Correspondence to: Kueiyu Joshua Lin, MD, ScD, MPH, Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, 1620 Tremont St. Suite 3030, Boston, MA 02120. E-mail: [email protected] Received May 31, 2017; accepted August 23, 2017. ª 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. DOI: 10.1161/JAHA.117.006814 Journal of the American Heart Association 1 Predicting Anticoagulation Control Quality Lin et al SYSTEMATIC REVIEW AND META-ANALYSIS Clinical Perspective Methods Data Source What Is New? We linked electronic health record (EHR) data from 2 large US • In patients aged ≥65 years, our prediction model for academic provider networks with Medicare claims data. The anticoagulation control quality outperformed the published first network consists of 1 tertiary hospital, 2 community score, SAMe-TT2R2. hospitals, 17 primary care centers, and 1 anticoagulation • ≥ Time in the therapeutic range was 70% (area under clinic that manages VKA-related care for all patients within the receiver operating characteristic curve 0.71 versus 0.57, a network. The second network includes 1 tertiary hospital, 1 significant difference.). community hospital, 16 primary care centers, and an anticoagulation clinic. Patients in network 1 were used as What Are the Clinical Implications? the training set for the prediction model derivation, and those • Our prediction score for anticoagulation quality can help in network 2 were used as the validation set. The EHR clinicians select the appropriate older adult candidates to database contains information on patient demographics, receive vitamin K antagonist therapy and can provide diagnosis and procedure codes, medications, lifestyle factors, researchers with a tool to adjust for confounding and to laboratory data, and various clinical notes. Both inpatient and investigate treatment effect heterogeneity due to predicted outpatient EHR data were used in this study. The Medicare anticoagulation quality. claims data contain information on demographics, inpatient and outpatient diagnosis and procedure codes, and dispensed or at least noninferior to VKAs,9–11 clinical equipoise still exists medications.26 This study was approved by Partners Health- when patients are likely to have good anticoagulation control Care Institutional Review Board (IRB). based on pretreatment characteristics.7,12 This choice is particularly difficult to make in older adults because DOACs have been associated with a higher risk of major gastrointesti- Study Population nal bleeding than VKAs in the older population.13–15 Moreover, In the linked Medicare claims–EHR data, we identified all chronic kidney disease is highly prevalent in older adults,16 patients aged ≥65 years with nonvalvular AF or VTE which makes lack of routine monitoring tests for DOACs a initiating a VKA from January 1, 2007, to December 31, challenge rather than an advantage because some DOACs are 2014, with no use of any oral anticoagulants (VKAs or substantially renally excreted (eg, 80% for dabigatran). Conse- DOACs) in the prior 90 days (new user design27). The VKA quently, it is critical to understand how patient characteristics initiation date was the index (cohort entry) date. The study are associated with anticoagulation quality so we can identify cohort was required to have at least 180 days of contin- the ideal candidates for VKA therapy. uous enrollment in Medicare inpatient, outpatient, and In the existing literature, there is only 1 published prescription benefits with at least 1 EHR encounter with prediction score for anticoagulation quality: the SAMe-TT2R2 date of service after January 1, 2007, and before the index score.17 It did not consider some clinically important predic- date. To ensure our ability to assess the primary outcome tors for TTR (eg, polypharmacy, hospitalizations, antibiotic reliably, patients were required to have at least 5 INR use)18–22 and was found to have suboptimal performance in values recorded in