Using Bioinformatics to Treat Hospitalized Smokers: Successes and Challenges of a Tobacco Treatment Service

Jt Comm J Qual Patient Saf. 2017 Dec;43(12):621-632. doi: 10.1016/j.jcjq.2017.06.010.

Abstract

Background: Hospitals face increasing regulations to provide and document inpatient tobacco treatment, yet few blueprint data exist to implement a tobacco treatment service (TTS).

Methods: A hospitalwide, opt-out TTS with three full-time certified counselors was developed in a large tertiary care hospital to proactively treat smokers according to Chronic Care Model principles and national treatment guidelines. A bioinformatics platform facilitated integration into the electronic health record to meet evolving Centers for Medicare & Medicaid Services meaningful use and Joint Commission standards. TTS counselors visited smokers at the bedside and offered counseling, recommended smoking cessation medication to be ordered by the primary clinical service, and arranged for postdischarge resources.

Results: During a 3.5-year span, 21,229 smokers (31,778 admissions) were identified; TTS specialists reached 37.4% (7,943), and 33.3% (5,888) of daily smokers received a smoking cessation medication order. Adjusted odds ratios (AORs) of receiving a chart order for smoking cessation medication during the hospital stay and at discharge were higher among patients the TTS counseled > 3 minutes and recommended medication: inpatient AOR = 7.15 (95% confidence interval [CI] = 6.59-7.75); discharge AOR = 5.3 (95% CI = 4.71-5.97). As implementation progressed, TTS counseling reach and medication orders increased. To assess smoking status ≤ 1 month postdischarge, three methods were piloted, all of which were limited by low follow-up rates (4.5%-28.6%).

Conclusion: The TTS counseled approximately 3,000 patients annually, with increases over time for reach and implementation. Remaining challenges include the development of strategies to engage inpatient care teams to follow TTS recommendations, and patients postdischarge in order to optimize postdischarge smoking cessation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Chronic Disease
  • Counseling / methods
  • Female
  • Hospital Information Systems / organization & administration*
  • Humans
  • Inpatients*
  • Male
  • Meaningful Use / organization & administration
  • Middle Aged
  • Program Development
  • Quality Improvement / organization & administration*
  • Self-Management / methods
  • Sex Factors
  • Smokers*
  • Smoking Cessation / methods*
  • Smoking Cessation Agents / administration & dosage
  • Socioeconomic Factors
  • Tertiary Care Centers

Substances

  • Smoking Cessation Agents