Changing the default for tobacco-cessation treatment in an inpatient setting: study protocol of a randomized controlled trial

Babalola Faseru, Edward F Ellerbeck, Delwyn Catley, Byron J Gajewski, Taneisha S Scheuermann, Theresa I Shireman, Laura M Mussulman, Niaman Nazir, Terry Bush, Kimber P Richter, Babalola Faseru, Edward F Ellerbeck, Delwyn Catley, Byron J Gajewski, Taneisha S Scheuermann, Theresa I Shireman, Laura M Mussulman, Niaman Nazir, Terry Bush, Kimber P Richter

Abstract

Background: Most health care providers do not treat tobacco dependence routinely. This may in part be due to the treatment "default." Current treatment guidelines recommend that providers (1) ask patients if they are willing to quit and (2) provide cessation-focused medications and counseling only to smokers who state that they are willing to quit. The default is that patients have to "opt in" to receive cessation assistance: providers ask smokers if they are willing to quit, and only offer medications and cessation support to those who say "yes." This drastically limits the reach of cessation services because, at any given encounter, only one in three smokers say that they are ready to quit. The objective of this study is to determine the impact of providing all smokers with tobacco-cessation treatment unless they refuse it (OPT OUT) versus current practice-screening for readiness and only offering treatment to smokers who say they are ready to quit (OPT IN).

Methods: This individually randomized clinical trial is conducted in a tertiary-care hospital. We will conduct the trial among up to 1000 randomly selected hospitalized smokers to determine the population impact of changing the treatment default, identify mediators of outcome, and determine the cost-effectiveness of this new, highly proactive approach. This is a population-based study that targets an endpoint of vital interest; applies minimal eligibility criteria to broaden generalizability; and utilizes hospital staff for interventions to ensure long-term sustainability. The study employs delayed consent and an innovative Bayesian adaptive design to evaluate a major shift in our approach to care. If effective, this change would expand the reach of tobacco-cessation treatment from 30% to 100% of smokers.

Discussion: Regardless of outcome, the trial will provide a model of how to alter and evaluate the impact of health care defaults. If OPT OUT proves to be more effective, it will expand the population eligible for cessation treatment by over 300%. It will also simplify the tobacco-cessation treatment algorithm, and relieve busy health care providers of the burden of evaluating readiness to quit.

Trial registration: Clinical Trials Registration, ID: NCT02721082 . Registered on 22 March 2016.

Keywords: Hospital; Motivation; Randomized clinical trial; Smoking cessation; Tobacco use disorder; Treatment guidelines.

Conflict of interest statement

Authors’ information

BF, EFE, BG, TS, LMM, NN, and KP work for University of Kansas Medical Center and University of Kansas Cancer Center, Kansas City, KS, USA. DC works for Children’s Mercy Hospitals and Clinics, Center for Children’s Healthy Lifestyles and Nutrition, Kansas City, MO, USA. TIS works for Brown University, RI, USA, and TB works for Optum, Seattle, WA, USA.

Ethics approval and consent to participate

The study was approved by the University of Kansas Human Subjects Committee (IRB00006196; STUDY00001774). Consistent with the modified Zelen’s design, consent to participate is received at the 1-month follow-up.

Consent for publication

Not applicable

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Theoretical model

References

    1. Henningfield JE, Slade J. Tobacco-dependence medications: public health and regulatory issues. Food Drug Law J. 1998;53(Suppl):75–114.
    1. Pierce JP, Gilpin E. How long will today’s new adolescent smoker be addicted to cigarettes? Am J Public Health. 1996;86(2):253–6. doi: 10.2105/AJPH.86.2.253.
    1. Fiore MC, Jaen CR, Baker TB, et al. Treating tobacco use and dependence: 2008 update. Clinical practice guideline. Rockville: Department of Health and Human Services. Public Health Service; 2008.
    1. Miller WR, Rollnick S. Motivational interviewing: preparing people for change. 2. New York: Guilford Press; 2002.
    1. Mantler T, Irwin JD, Morrow D. Motivational interviewing and smoking behaviors: a critical appraisal and literature review of selected cessation initiatives. Psychol Rep. 2012;110(2):445–60. doi: 10.2466/02.06.13.18.PR0.110.2.445-460.
    1. Gonzales D, Rennard SI, Nides M, Oncken C, Azoulay S, Billing CB, Watsky EJ, Gong J, Williams KE, Reeves KR. Varenicline, an alpha4beta2 nicotinic acetylcholine receptor partial agonist, vs sustained-release bupropion and placebo for smoking cessation: a randomized controlled trial. JAMA. 2006;296(1):47–55. doi: 10.1001/jama.296.1.47.
    1. Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL, Jr, Jones DW, Materson BJ, Oparil S, Wright JT, Jr, et al. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA. 2003;289(19):2560–72. doi: 10.1001/jama.289.19.2560.
    1. Jamal A, Dube SR, Malarcher AM, Shaw L, Engstrom MC, Centers for Disease Control and Prevention Tobacco use screening and counseling during physician office visits among adults—National Ambulatory Medical Care Survey and National Health Interview Survey, United States, 2005–2009. MMWR Morb Mortal Wkly Rep. 2012;61 Suppl:38–45.
    1. Prochaska JO, DiClemente CC. Stages and processes of self-change of smoking: toward an integrative model of change. J Consult Clin Psychol. 1983;51(3):390–5. doi: 10.1037/0022-006X.51.3.390.
    1. Browning KK, Ferketich AK, Salsberry PJ, Wewers ME. Socioeconomic disparity in provider-delivered assistance to quit smoking. Nicotine Tob Res. 2008;10(1):55–61. doi: 10.1080/14622200701704905.
    1. Freund M, Campbell E, Paul C, McElduff P, Walsh RA, Sakrouge R, Wiggers J, Knight J. Smoking care provision in hospitals: a review of prevalence. Nicotine Tob Res. 2008;10(5):757–74. doi: 10.1080/14622200802027131.
    1. Centers for Disease C, Prevention. 44 Quitting smoking among adults—United States, 2001–2010. MMWR Morb Mortal Wkly Rep. 2011;60:1513–9.
    1. Johnson EJ, Steffel M, Goldstein DG. Making better decisions: from measuring to constructing preferences. Health Psychol. 2005;24(4 Suppl):S17–22. doi: 10.1037/0278-6133.24.4.S17.
    1. Richter KP, Ellerbeck EF. It’s time to change the default for tobacco treatment. Addiction. 2015;110(3):381–6. doi: 10.1111/add.12734.
    1. Van De Veer D. Paternalistic intervention: the moral bounds on benevolence. Princeton: Princeton University Press; 1986.
    1. Thaler RH, Sunstein CR. Nudge: improving decisions about health, wealth, and happiness. New Haven: Yale University Press; 2008.
    1. Zelen M. A new design for randomized clinical trials. N Engl J Med. 1979;300:1242–5. doi: 10.1056/NEJM197905313002203.
    1. Torgerson D. The use of Zelen’s design in randomised trials. BJOG. 2004;111(1):2. doi: 10.1111/j.1471-0528.2004.00033.x.
    1. Berry DA. Bayesian clinical trials. Nat Rev Drug Discov. 2006;5(1):27–36. doi: 10.1038/nrd1927.
    1. Faseru B, Turner M, Casey G, Ruder C, Befort CA, Ellerbeck EF, Richter KP. Evaluation of a hospital-based tobacco treatment services: Outcomes and lessons learned. J Hosp Med. 2011;6(4):143-50.
    1. Andrew M, Vegh P, Caco C, Kirpalani H, Jefferies A, Ohlsson A, Watts J, Saigal S, Milner R, Wang E. A randomized, controlled trial of platelet transfusions in thrombocytopenic premature infants. J Pediatr. 1993;123(2):285–91. doi: 10.1016/S0022-3476(05)81705-6.
    1. Adamson J, Cockayne S, Puffer S, Torgerson DJ. Review of randomised trials using the post-randomised consent (Zelen’s) design. Contemp Clin Trials. 2006;27(4):305–19. doi: 10.1016/j.cct.2005.11.003.
    1. McKenzie CR, Liersch MJ, Finkelstein SR. Recommendations implicit in policy defaults. Psychol Sci. 2006;17(5):414–20. doi: 10.1111/j.1467-9280.2006.01721.x.
    1. Faseru B, Yeh HW, Ellerbeck EE, Befort C, Richter KP. Prevalence and predictors of tobacco treatment in an academic medical center. Jt Comm J Qual Patient Saf. 2009;35(11):551–7. doi: 10.1016/S1553-7250(09)35075-8.
    1. Hughes JR, Keely J, Naud S. Shape of the relapse curve and long-term abstinence among untreated smokers. Addiction. 2004;99(1):29–38. doi: 10.1111/j.1360-0443.2004.00540.x.
    1. Garvey AJ, Bliss RE, Hitchcock JL, Heinold JW, Rosner B. Predictors of smoking relapse among self-quitters: a report from the Normative Aging Study. Addict Behav. 1992;17(4):367–77. doi: 10.1016/0306-4603(92)90042-T.
    1. Performance measurement initiatives: screening and treating tobacco and alcohol use. .
    1. Readmissions reduction program. .
    1. Hughes JR, Keely JP, Niaura RS, Ossip-Klein DJ, Richmond RL, Swan GE. Measures of abstinence in clinical trials: issues and recommendations. Nicotine Tob Res. 2003;5(1):13–25. doi: 10.1080/1462220031000070552.
    1. SRNT Subcommittee on Biochemical Verification. Biochemical verification of tobacco use and cessation. Nicotine Tob Res. 2002;4(2):149-159
    1. Williams GC, McGregor H, Sharp D, Kouides RW, Levesque CS, Ryan RM, Deci EL. A self-determination multiple risk intervention trial to improve smokers’ health. J Gen Intern Med. 2006;21(12):1288-94.
    1. Foulds J, Steinberg MB, Williams JM, Ziedonis DM. Developments in pharmacotherapy for tobacco dependence: past, present and future. Drug Alcohol Rev. 2006;25(1):59–71. doi: 10.1080/09595230500459529.
    1. Knoll MA. The role of behavioral economics and behavioral decision making in Americans’ retirement savings decisions. Soc Secur Bull. 2010;70(4):1–23.
    1. Berry SM, Carlin BP, Lee JJ, Muller P. Bayesian adaptive methods for clinical trials. New York: CRC Press; 2011.
    1. Rigotti NA, Clair C, Munafo MR, Stead LF. Interventions for smoking cessation in hospitalised patients. Cochrane Database Syst Rev. 2012;5:CD001837.
    1. Wadland WC, Holtrop JS, Weismantel D, Pathak PK, Fadel H, Powell J. Practice-based referrals to a tobacco cessation quit line: assessing the impact of comparative feedback vs general reminders. Ann Fam Med. 2007;5(2):135–42. doi: 10.1370/afm.650.
    1. Cupertino AP, Richter K, Cox LS, Garrett S, Ramirez R, Mujica F, Ellerbeck EF. Feasibility of a Spanish/English computerized decision aid to facilitate smoking cessation efforts in underserved communities. J Health Care Poor Underserved. 2010;21(2):504–17. doi: 10.1353/hpu.0.0307.
    1. Pisinger C, Vestbo J, Borch-Johnsen K, Jorgensen T. It is possible to help smokers in early motivational stages to quit. The Inter99 study. Prev Med. 2005;40(3):278–84.
    1. Stoltzfus K, Hunt S, Ayars C, Carlini B, Rabius V, Richter K. A pilot trial of proactive versus reactive referral to tobacco quitlines. J Smok Cessat. 2011;6(4):211–8.
    1. Schafer J. Analysis of incomplete multivariate data. Boca Raton: Chapman & Hall; 1997.
    1. Enders C. Applied missing data analysis. New York: The Guilford Press; 2010.
    1. Collins L, Schafer J, Kam C. A comparison of inclusive and restrictive strategies in modern missing data procedures. Psychol Methods. 2001;6:330–51. doi: 10.1037/1082-989X.6.4.330.
    1. Molenberghs G, Kenward M. Missing data in clinical studies. Chichester: Wiley; 2007.
    1. Enders C. Missing not at random models for latent growth curve analyses. Psychol Methods. 2011;16:1–16. doi: 10.1037/a0022640.
    1. Panel on Handling Missing Data in Clinical Trials CoNS, Division of Behavioral and Social Sciences and Education, National Research Council. Theprevention and treatment of missing data in clinical trials. Washington, DC: The National Academies Press; 2010
    1. Rosenberger W, Lachin J. Randomization in clinical trials: theory and practice. Hoboken: Wiley; 2015.
    1. The effect of population drift on adaptively randomized trials. .
    1. Hyland A, Li Q, Bauer JE, Giovino GA, Steger C, Cummings KM. Predictors of cessation in a cohort of current and former smokers followed over 13 years. Nicotine Tob Res. 2004;6(Suppl 3):S363–9. doi: 10.1080/14622200412331320761.
    1. MacKinnon DP, Lockwood CM, Hoffman JM, West SG, Sheets V. A comparison of methods to test mediation and other intervening variables. Psychol Methods. 2002;7:83–104. doi: 10.1037/1082-989X.7.1.83.
    1. Brown RL. Assessing specific mediational effects in complex theoretical models. Struct Equ Model. 1997;4:142–56. doi: 10.1080/10705519709540067.
    1. Shrout PE, Bolger N. Mediation in experimental and nonexperimental studies: new procedures and recommendations. Psychol Methods. 2002;7:422–35. doi: 10.1037/1082-989X.7.4.422.
    1. Gold MR, Siegel JE, Russell LB, Weinstein MC. Cost-effectiveness in health and medicine. New York: Oxford University Press; 1996.
    1. Phillips KA, Chen JL. Impact of the U.S. panel on cost-effectiveness in health and medicine. Am J Prev Med. 2002;22(2):98-105.
    1. Haddix AC, Teutsch SM, Corso PS. Prevention effectiveness: a guide to decision analysis and economic evaluation. 2. Oxford: Oxford University Press; 2003.
    1. Ellerbeck EF, Mahnken JD, Cupertino AP, Cox LS, Greiner KA, Mussulman LM, Nazir N, Shireman TI, Resnicow K, Ahluwalia JS. Effect of varying levels of disease management on smoking cessation: a randomized trial. Ann Intern Med. 2009;150(7):437–46. doi: 10.7326/0003-4819-150-7-200904070-00003.
    1. Richter KP, Faseru B, Mussulman LM, Ellerbeck EF, Shireman TI, Hunt JJ, Carlini BH, Preacher KJ, Ayars CL, Cook DJ. Using “warm handoffs” to link hospitalized smokers with tobacco treatment after discharge: study protocol of a randomized controlled trial. Trials. 2012;13:127. doi: 10.1186/1745-6215-13-127.
    1. Connor JT, Elm JJ, Broglio KR, ESETT and ADAPT-IT Investigators Bayesian adaptive trials offer advantages in comparative effectiveness trials: an example in status epilepticus. J Clin Epidemiol. 2013;66 8 Suppl:S130–7. doi: 10.1016/j.jclinepi.2013.02.015.
    1. Gajewski BJ, Berry SM, Quintana M, Pasnoor M, Dimachkie M, Herbelin L, Barohn R. Building efficient comparative effectiveness trials through adaptive designs, utility functions, and accrual rate optimization: finding the sweet spot. Stat Med. 2015;34(7):1134–49. doi: 10.1002/sim.6403.
    1. Centers for Disease C, Prevention, 35 Vital signs: current cigarette smoking among adults aged ≥ 18 years—United States, 2009. MMWR Morb Mortal Wkly Rep. 2010;59:1135–40.
    1. Ockene JK. Physician-delivered interventions for smoking cessation: strategies for increasing effectiveness. Prev Med. 1987;16(5):723–37. doi: 10.1016/0091-7435(87)90054-5.

Source: PubMed

3
Suscribir