Jaeyong Bae1, Eric W Ford2, Hadi H K Kharrazi3, Timothy R Huerta4. 1. School of Nursing and Health Studies, Northern Illinois University, Wirtz Hall 257, Dekalb, IL 60115, United States. Electronic address: jaeyong.bae@niu.edu. 2. Health Care Organization and Policy, University of Alabama Birmingham, 1665 University Blvd., Birmingham, AL 35294, United States. Electronic address: ewford@uab.edu. 3. Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, 624 N. Broadway, Hampton House 606, Baltimore, MD 21205, United States. Electronic address: kharrazi@jhu.edu. 4. Department of Family Medicine, College of Medicine, The Ohio State University, 2231 North High Street, 265 Northwood and High Building, Columbus, OH 43201, United States. Electronic address: Timothy.Huerta@osumc.edu.
Abstract
PURPOSE: The purpose of this paper is to assess electronic medical record (EMR) automatic reminder use in relation to smoking cessation activities among primary-care providers. BACKGROUND: Primary-care physicians are in the frontline of efforts to promote smoking cessation. Moreover, doctors' prescribing privileges give them additional tools to help patients successfully quit smoking. New EMR functions can provide automated reminders for physicians to counsel smokers and provide prescriptions to support quit attempts. SAMPLE AND METHODS: Logit regression is used to analyze the 2012 National Ambulatory Medical Care Survey (NAMCS). Variables related to the EMR's clinical reminder capability, patient's smoking status, the provision of cessation counseling and the prescribing of drugs that support quitting are analyzed. RESULTS: For primary care visit documents, smoking status was recorded 77.7% of the time. Smoking cessation counseling was ordered/provided 16.4% of the time in physicians' offices using electronic reminders routinely compared to 9.1% in those lacking the functionality. Smoking cessation medication was ordered/prescribed for 3.7% of current smokers when reminders were routinely used versus 2.1% when no reminder was used. All the differences were statistically significant. CONCLUSIONS: The presence of an EMR equipped with automated clinical reminders is a valuable resource in efforts to promote smoking cessation. Insurers, regulators, and organizations promulgating clinical guidelines should include the use of EMR technology as part of their programs.
PURPOSE: The purpose of this paper is to assess electronic medical record (EMR) automatic reminder use in relation to smoking cessation activities among primary-care providers. BACKGROUND: Primary-care physicians are in the frontline of efforts to promote smoking cessation. Moreover, doctors' prescribing privileges give them additional tools to help patients successfully quit smoking. New EMR functions can provide automated reminders for physicians to counsel smokers and provide prescriptions to support quit attempts. SAMPLE AND METHODS: Logit regression is used to analyze the 2012 National Ambulatory Medical Care Survey (NAMCS). Variables related to the EMR's clinical reminder capability, patient's smoking status, the provision of cessation counseling and the prescribing of drugs that support quitting are analyzed. RESULTS: For primary care visit documents, smoking status was recorded 77.7% of the time. Smoking cessation counseling was ordered/provided 16.4% of the time in physicians' offices using electronic reminders routinely compared to 9.1% in those lacking the functionality. Smoking cessation medication was ordered/prescribed for 3.7% of current smokers when reminders were routinely used versus 2.1% when no reminder was used. All the differences were statistically significant. CONCLUSIONS: The presence of an EMR equipped with automated clinical reminders is a valuable resource in efforts to promote smoking cessation. Insurers, regulators, and organizations promulgating clinical guidelines should include the use of EMR technology as part of their programs.
Authors: Alex T Ramsey; Ami Chiu; Timothy Baker; Nina Smock; Jingling Chen; Tina Lester; Douglas E Jorenby; Graham A Colditz; Laura J Bierut; Li-Shiun Chen Journal: Transl Behav Med Date: 2020-12-31 Impact factor: 3.046
Authors: Jaana Takala; Iida Vähätalo; Leena E Tuomisto; Onni Niemelä; Pinja Ilmarinen; Hannu Kankaanranta Journal: NPJ Prim Care Respir Med Date: 2022-10-21 Impact factor: 3.289
Authors: Alice Guan; Jin E Kim-Mozeleski; Judy Y Tan; Stephen J McPhee; Nancy J Burke; Angela Sun; Joyce W Cheng; Janice Y Tsoh Journal: Addict Behav Date: 2019-09-11 Impact factor: 3.913
Authors: Michael S Amato; Sherine El-Toukhy; Lorien C Abroms; Henry Goodfellow; Alex T Ramsey; Tracey Brown; Helena Jopling; Zarnie Khadjesari Journal: JMIR Res Protoc Date: 2020-12-31
Authors: Polina V Kukhareva; Tanner J Caverly; Haojia Li; Hormuzd A Katki; Li C Cheung; Thomas J Reese; Guilherme Del Fiol; Rachel Hess; David W Wetter; Yue Zhang; Teresa Y Taft; Michael C Flynn; Kensaku Kawamoto Journal: J Am Med Inform Assoc Date: 2022-04-13 Impact factor: 7.942
Authors: Hadi Kharrazi; Claudia P Gonzalez; Kevin B Lowe; Timothy R Huerta; Eric W Ford Journal: J Med Internet Res Date: 2018-08-07 Impact factor: 5.428
Authors: Van C Willis; Kelly Jean Thomas Craig; Yalda Jabbarpour; Elisabeth L Scheufele; Yull E Arriaga; Monica Ajinkya; Kyu B Rhee; Andrew Bazemore Journal: JMIR Med Inform Date: 2022-01-21