Impact of Certified CME in Atrial Fibrillation on Administrative Claims
Published Online: May 08, 2012
Stephanie A. Stowell, MPhil; Allison J. Gardner, PhD; Joseph S. Alpert, MD; Gerald V. Naccarelli, MD; Thomas P. Harkins, MA, MPH; Anthony M. Louder, PhD, RPh; and Leonardo Tamariz, MD, MPH
Atrial fibrillation (AF) is associated with significant morbidity and mortality, and affects nearly 2.3 million Americans.1 AF is becoming increasingly prevalent with the aging of the US population; the incidence of AF doubles with each decade of age, and an estimated 5.6 million people are expected to be diagnosed by the year 2050. The economic burden of AF is also significant. Annual healthcare costs exceed 5 times the normal healthcare costs of an average individual, with the majority of these costs driven by interventional procedures and inpatient care.2,3
AF is a complex disease that demands a high degree of individualized patient care. For physicians, this care requires keeping abreast of rapidly changing clinical practice guidelines and an expanding selection of available therapeutic agents. In addition, as the Centers for Medicare & Medicaid Services shifts toward a quality-centric approach to healthcare reimbursements, physician performance and quality patient care are becoming increasingly more important.4 Several definitive measures for quality AF patient care exist, including the assessment for thromboembolic risk factors as well as the provision and appropriate monitoring of anticoagulation therapy.5,6
Despite the existence of quality measures, many challenges remain in the management of this multifaceted disease. Although guidelines continually change to reflect the most recent evidence available, current guidelines do not provide definitive measures on how to provide individualized patient care. Furthermore, treatment challenges can be compounded when comorbid conditions are present.7 Taken together, these factors create a significant need for education on current evidence and best practices for the comprehensive management of AF.
To routinely update, improve, and reinforce practice behaviors, clinicians are required to regularly engage in continuing medical education (CME) activities. Typically, evaluation of CME efforts is limited to self-reporting of participant satisfaction and questions designed to assess the educational objectives of the activity. However, the ever-increasing focus on improving the quality of care demands more stringent and sophisticated methods for measuring changes in clinician performance associated with CME activity teachings. To this end, a new type of outcomes measure was adopted. Administrative claims data have long been used to evaluate the effects of various healthcare practices and interventions; however, the impact of CME teachings on physician behavior has not been commonly evaluated by these means. Here we describe a pilot study that used data from an administrative claims database to explore the potential connection between a CME-certified intervention and improvements in physician knowledge and competence in AF-related healthcare decisions and patient outcomes.
A 60-minute, CME-certified webcast activity was developed for clinicians who treat patients with AF. The activity incorporated interactive patient case–based questions and an expert panel discussion on current clinical data and guideline-recommended best practices for the optimal management of this patient population. Specific discussion topics included the clinical consequences of AF and the negative effects of the disease on quality of life; the use of risk assessment criteria to optimize antithrombotic treatment decisions for stroke prophylaxis; and the implementation of strategies to individualize care plans that incorporate specific patient needs along with clinical evidence for rate control, rhythm control, and thromboembolic prevention. In accordance with Accreditation Council for Continuing Medical Education standards for commercial support, the content of the webcast activity was examined by an independent, third-party review board; met criteria for objectivity, balance, and scientific rigor; and was determined to be free of commercial bias.8
To assess the impact of the CME activity on clinical practice, a retrospective cohort analysis of physician practices and AF patient outcomes was conducted. The study population consisted of cardiologists, electrophysiologists, and internal medicine physicians who participated in the AF CME activity between October 2009 and May 2010, and who were also identified as being contracted US-based physicians within the Humana, Inc health plan electronic data warehouse. A 12-month study period was identified for each physician participant based upon an index date (ie, the date the individual physician completed the specified CME activity); this period was defined as the 6 months prior to and following the index date (pre-CME period and post-CME period, respectively). Patients of these physicians who had at least 1 International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9- CM) coded claim for AF (427.3x) in the pre-CME period, who were 18 to 89 years of age, and who were enrolled in a Medicare Advantage or commercial full-insured health plan were also included in the analysis.
Physician and patient data were obtained from 5 electronic databases, including a provider file containing physician practice, specialty, and geographic information; a member file containing demographic and enrollment information for each patient per encounter (age, sex, type of insurance, and geographical region); a medical file containing up to 9 recorded ICD-9-CM codes per encounter and related payment information; a pharmacy file containing all Generic Product Identifier numbers of pharmacy-dispensed medications per claim and related payment information; and a lab file containing Logical Observation Identifiers Names and Codes and test results per encounter.
Administrative Claims Data
Therapeutic interventions and AF-related healthcare utilization and costs were obtained from the administrative claims databases for qualifying Humana patients treated by participating physicians. Specifically, AF-related healthcare costs and utilization, rate and rhythm control therapies, stroke prevention treatments and associated monitoring, medical devices and procedures related to AF, cardiovascular comorbidities, CHADS2 scores, Charlson Comorbidity Index scores, and patient demographic information were evaluated. All analyses were conducted using SAS 9.2/SAS Enterprise Guide 4.2 (SAS Institute Inc, Cary, North Carolina). Study exemption was provided by the University of Miami Institutional Review Board prior to data collection.
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