Smoking prevalence among patients with psychiatric disorders in an integrated health care delivery system: A case-control study

Transcription

1 Smoking prevalence among patients with psychiatric disorders in an integrated health care delivery system: A case-control study Kelly C. Young-Wolff, PhD, MPH; Andrea H. Kline-Simon, MS; Constance Weisner, DrPH, MSW Drug and Alcohol Research Team, Division of Research, Kaiser Permanente HMORN Conference, 13 March 2015 Long Beach, CA Funded by Behavioral Health Research Initiative Kaiser Permanente Research

2 Background Adults with mental illness have higher smoking prevalence, greater nicotine dependence, and greater difficulty quitting Represent > 40% of current smokers, spend up to 25% of income on cigarettes; consume 45% of cigarettes sold in US 1,2 Greater smoking-related diseases, those with serious mental illness die 25 years prematurely 3 Despite declines in US smoking prevalence 4, less change in those with mental illness, suggests disparities increasing 5 1 Lasser et al., JAMA, 2000; 2 Steinberg et al. Tob Control, 2004; 3 Colton & Manderscheid, 2006; 4 CDC, 2010; 5 Cook et al.,

3 Background Smoking cessation treatments are well-established, costeffective, and reduce likelihood of relapse 1 Smokers with mental illness motivated to quit, and can quit with treatment, without aggravating psychiatric symptoms Elevated smoking partially due to lack of health insurance and reduced access to appropriate treatments 2-4 Longitudinal studies on smoking in adults with mental illness used data from US surveys and clinical samples 1 US Public Health Service Report, JAMA, 2000; 2 American Legacy Foundation, 2011; 3 Schroeder & Morris, 2010; 4 Williams et al.,

4 Research Aims Using secondary data from patients in a large, integrated healthcare delivery system, this observational case-control retrospective cohort study aimed to: 1) Describe and compare smoking prevalence over time ( ) in adults with 1+ of the 5 most prevalent psychiatric disorders and matched controls 2) Among smokers in 2010, compare smoking cessation medication use among cases with psychiatric disorders vs. matched controls 4

5 Integrated health care delivery system (medical, psychiatry & AOD services) 3.6+ million members (45% of market share, diversity increasing with ACA) Longitudinal data & long membership enrollment

6 Selection of the Analytical Sample Commercial adult patients, KPNC members at least 75% of the study period, with 1+ of the five most prevalent psychiatric disorders in 2010 Cases: Depression disorders, anxiety disorders, substance use disorders, bipolar disorder, ADHD; not mutually exclusive (N=155,733) Matched Controls: No psychiatric diagnoses created for each case matched 1-to-1 on sex, age, medical home facility (N=155,733) Aim 1: Sample Size = 311,466 Aim 2: Included subset of matched pairs where cases with psychiatric disorders and matched controls were smokers in 2010; N=5,716 6

7 Measures Smoking Status Obtained through standardized screening at all Adult Medicine appointments and recorded in EHR Smoking Cessation Medication Collection of any smoking cessation medication from a KPNC pharmacy in 2010 pulled from EHR Nicotine patches, lozenges, gums, inhalers, nasal spray, bupropion [Zyban], and varenicline [Chantix] Patient Characteristics Age, sex, race/ethnicity, median household income (geocoded based on address) pulled from EHR 7

8 Aim 1: Statistical Analyses Series of cross-sectional logistic regression analyses to test relation between cases (vs. control) and smoking at each year Repeated measures GEE models included time x case interactions to examine differences in smoking in cases vs. controls over time Multiple imputation used to address missing smoking data Analyses adjusted for age, sex, race/ethnicity, income, visit count (primary care, other outpatient, inpatient, ED) 8

9 Aim 2: Statistical Analyses Among smokers in 2010 Logistic regression analyses to test relation between cases (vs. control) and any use of tobacco cessation medication in 2010 Analyses adjusted for age, sex, race/ethnicity, income 9

10 Sample Demographics 54% Female 60% White, 16% Hispanic, 14% Asian, 7% black, 3% unknown Mean age = 50 (SD = 15) 32% Median household income < $50,000 Cases more likely to be White, less likely to be Asian, had lower annual income than controls* Women, older adults, and those with > income less likely to smoke* * p<

11 Results: Smoking (%) in Cases and Controls Substance Use Disorders (n=22,259 cases) Bipolar Disorder (n=8,357 cases) Depression Disorders (n=96,410 cases) Anxiety Disorders (n=69,928 cases) ADHD (n=6,611 cases) Cases % Controls % Cases % Controls % Cases % Controls % Cases % Controls % Cases % Controls %

12 12 Cross-Sectional Results: ORs of Smoking in Psychiatric Cases vs. Controls

13 Repeated Measures Logistic Regression Results Substance Use Disorders (n=22,259 cases) Bipolar Disorder (n=8,357 cases) Depression Disorders (n=96,410 cases) Anxiety Disorders (n=69,928 cases) ADHD (n=6,611 cases) Estimate SE Estimate SE Estimate SE Estimate SE Estimate SE Intercept -0.44* * * * * 0.10 Case (vs. Control) 0.87* * * * * 0.07 Time -0.21* * * * * 0.02 Time x Case Interaction 0.11* * * * p<.001, +p<.05 13

14 Smoking Cessation Medication Use: % of cases, 3.6% of controls used any cessation medication in 2010 Nicotine patch most commonly used (69%) White smokers and older smokers greater odds of use 14

15 Results from Logistic Regression Analyses * p< AOR = 1.82* (CI ) AOR = 1.68* (CI ) AOR = 1.73* (CI ) AOR = 2.21* (CI ) AOR = 2.04 (CI ) 15

16 Summary and Discussion Disparities in Smoking are Increasing Particularly for those with substance use disorders Need to imbed smoking treatment in chemical dependency and psychiatry Low Use of Cessation Medication Greater among those with psychiatric disorders Missed opportunity Research Needed to Understand Barriers Integrated health care systems important to connect vulnerable smokers with treatment Identify and address factors that contribute to low medication use 16

17 Limitations Smoking Status Relied on administrative databases; those who don t interact with KPNC will not have updated smoking status over time Self-report, no data on frequency/quantity of smoking Smoking Cessation Medication Utilization Limited to prescription fills in KPNC, any use vs. none Did not examine smoking cessation counseling 17

18 Drug and Alcohol Research Team, Division of Research Principal Investigators Cynthia Campbell, PhD Derek Satre, PhD Connie Weisner, DrPH, LCSW Kelly Young-Wolff, PhD, MPH Practice Leader Stacy Sterling, MSW, MPH Health Economist Sujaya Parthasarathy, PhD Senior Research Administrator Alison Truman, MA Analysts/Biostaticians Felicia Chi, MPH Andrea H Kline-Simon, MS Wendy Lu, MPH Tom Ray, MBA Postdoctoral Fellow Erik Storholm Interview Supervisor Gina Smith Anderson Project Coordinators Agatha Hinman, BA Kathleen Haley, MFT Sabrina Wood, BA Research Associates Georgina Berrios Diane Lott-Garcia Melanie Jackson Barbara Pichotto Lynda Tish Research Clinicians Thekla B Ross, PsyD Ashley Jones, PsyD Amy Leibowitz, PsyD Clinical Partners Anna Wong, PhD Charles Wibbelsman, MD David Pating, MD Barry Levine, MD Charles Moore, MD, MBA Don Mordecai, MD Murtuza Ghadiali, MD KPNC Members KPNC Primary Care KPNC Chemical Dependency Quality Improvement Committee KPNC Adolescent Medicine Specialists Committee KPNC Adolescent Chemical Dependency Coordinating Committee KPNC Oakland Pediatrics Department KPNC Regional Mental Health and Chemical Dependency

19 Thank you

20 Additional Slides

21 21 Visit Type Breakdown Substance Use Disorders Bipolar Disorder Depression Disorders Anxiety Disorders ADHD Cases Controls Cases Controls Cases Controls Cases Controls Cases Controls Any Mental Health Visits (%) Any Chemical Dependency Visits (%) Any Primary Care Visits (%)

22 Smoking Cessation Medication Utilization White smokers and older smokers more likely to use medications 22

23 23 Other Co-Occurring Psychiatric Disorders

24 Mechanisms Underlying Elevated Smoking Neurobiological, psychosocial, and systemic factors Reinforcing mood-altering effects of nicotine Shared environment of genetic factors Reduced ability to cope during cessation efforts Limited access to targeted, evidence-based tobacco cessation treatment Tobacco industry has designed products and marketing strategies to target consumer segments with mental illness 1 Dursun & Kutcher, 1999; 2 Kendler et al., 1993; 3 Ziedonis et al., 2008; 4 Schroder & Morris, 2010; 5 Cook et al., 2003; 6 Prochaska et al.,

25 Low Cessation Medication Utilization It is difficult to identify any other condition that presents such a mix of lethality, prevalence, and neglect, despite effective and readily available interventions 2008 clinical practice guideline of the US Public Health Service 25

26 Depression Disorders Anxiety Disorders Substance Use Disorders Bipolar Disorders ADHD Cases Control Cases Control Cases Control Cases Control Cases Control Female (%) Ethnicity (%) Asian Black Hispanic White Unknown Age m (SD) Household Income >= $50K

27 Psychiatric Comorbidities (%) Depression Disorders (n=96410) Anxiety Disorders (n=69928) Substance Use Disorders (n=22259) Bipolar Disorders (n=8357) ADHD (n=6611) Depression Anxiety Disorder Substance Use Bipolar Spectrum ADHD

28 Summary of Findings Smoking Prevalence Cases > likelihood of smoking Consistent with US and CA data: 2x increased odds of smoking Declines in smoking, but to a lesser extent than controls Differences across Psychiatric Diagnoses Substance use cases > % smokers and > odds of smoking relative to controls Disparities between cases and controls increasing fastest for substance use disorders Tobacco Cessation Medication Use Low utilization overall Cases higher odds of using medications (especially bipolar disorder) 28

29 Aim 1 QUESTION: Is smoking more prevalent within each year and over time ( ) among cases with psychiatric disorders vs. matched controls? 29

30 Aim 2 QUESTION: Of the smokers in 2010, were cases with psychiatric disorders or matched controls more likely to use tobacco cessation medication? Analysis Logistic regression analyses to test relation between cases (vs. control) and any use of tobacco cessation medication in 2010 Analyses adjusted for age, sex, race/ethnicity, income 30

31 Next Steps Funding to examine impact of ACA on smoking prevalence and use of tobacco cessation medications Cost-sharing reduced to $0 for tobacco cessation medications in 2015 Examine barriers, learn how to better link members to existing services Working to get a more in depth assessment of smoking in behavioral health treatment Future research needed to identify and address factors that contribute to the low quit rates, and better link KPNC patients to existing treatments 31

32 Summary and Discussion Disparities in smoking prevalence are increasing Particularly for those with substance use disorders Need to imbed treatment in chemical dependency clinics Medication use greater among cases, but low overall Greater contact with health care providers; missed opportunity With health reform, integrated health care systems will serve as increasingly important settings for connecting vulnerable smokers with effective treatments Research needed to identify factors that contribute to low use of cessation medication and better link to existing treatments 32

33 Strengths Large diverse sample of individuals with psychiatric disorders and matched controls over 4 years Psychiatric diagnoses and tobacco cessation medication use based on EHR rather than self-report Current study can inform future trends 33