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Strengthen the Evidence for Maternal and Child Health Programs

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Evidence Tools
MCHbest. Smoking During Pregnancy.

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Strategy. Automatic Initiation of Smoking Cessation Program (Pregnancy)

Approach. Screen for tobacco use and automatically refer pregnant women who smoke to cessation services

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Overview. Pregnant women who are screened for tobacco use and automatically referred for cessation services are more likely to quit smoking. Integrating tobacco cessation into standard clinical practice through "opt-out" assessment and referral programs is one way to ensure that these services are built into the provision of care for perinatal smokers. These involve identifying pregnant smokers using carbon monoxide (CO) screening and automatically referring those who test positive for support. In opt-out programs, all patients receive services as part of routine standard of care unless they indicate refusal of services. Research indicates that "opt-out" referrals have the potential to improve engagement of pregnant smokers with smoking cessation support and to improve cessation outcomes.[1,2,3]

Evidence. Emerging Evidence. Strategies with this rating typically trend positive and have good potential to work...

Access the peer-reviewed evidence through the MCH Digital Library or related evidence source.

Potential Data Sources. Data to support this strategy can be accessed through:

  • Data on screening rates and documentation
  • Referral rates and timelines
  • Survey data on system-level factors supporting screening and referrals

Outcome Components. This strategy has shown to have impact on the following outcomes (Read more about these categories):

  • Health and Health Behaviors/Behavior Change. This strategy improves individuals' physical and mental health and their adoption of healthy behaviors (e.g., healthy eating, physical activity).
  • Access to/Receipt of Care. This strategy increases the ability for individuals to obtain healthcare services when needed, including preventive, diagnostic, and treatment services.
  • Timeliness of Care. This strategy promotes delivery of healthcare services in a timely manner to optimize benefits and prevent complications.

Detailed Outcomes. For specific outcomes related to each study supporting this strategy, access the peer-reviewed evidence and read the Intervention Results for each study.

Intervention Type. Screening (Read more about intervention types and levels as defined by the Public Health Intervention Wheel).

Intervention Level. Community-Focused

Examples from the Field. Access descriptions of ESMs that use this strategy or aligned components.

Sample ESMs. Here are sample ESMs to use as models for your own measures using the RBA framework (see The Role of Title V in Adapting Strategies).

Quadrant 1:
Measuring Quantity of Effort (“What/how much did we do?”)

  • Number of prenatal care sites implementing an automatic opt-out referral system for smoking cessation. (Measures adoption of intervention)
  • Number of electronic health records customized to support the opt-out referral workflow. (Measures systems-level implementation)

Quadrant 2:
Measuring Quality of Effort (“How well did we do it?”)

  • Percent of pregnant women screened for smoking at the first prenatal visit using a validated tool. (Measures consistency of screening)
  • Percent of automatic referrals that adhere to the protocol of directly connecting individuals to services. (Measures fidelity to intervention model)

Quadrant 3:
Measuring Quantity of Effect (“Is anyone better off?”)

  • Number of regional health systems that adopt the opt-out referral model as a standard of prenatal care. (Measures spread of intervention)
  • Number of state Medicaid programs that issue guidance promoting opt-out referral as a best practice. (Measures policy-level support)
  • Number of pregnant women who smoke who remain engaged in cessation treatment for at least 8 weeks after opt-out referral. (Measures sustained engagement)
  • Number of referred individuals who deliver infants with birth weights over 5.5 pounds, indicating mitigation of smoking risks. (Measures health impact)

Quadrant 4:
Measuring Quality of Effect (“How are they better off?”)

  • Percent of prenatal practices in areas with lower incomes that establish opt-out referral systems. (Measures reach of implementation)
  • Percent of referred individuals who can access cessation services within their own community. (Measures usability of services)
  • Percent decrease in adverse birth outcomes associated with smoking in communities with high rates of maternal smoking. (Measures impact on birth outcomes)
  • Percent of referred individuals who feel the opt-out process helped them recognize the importance of quitting smoking. (Measures impact on quit awareness)

Note. When looking at your ESMs, SPMs, or other strategies:

  1. Move from measuring quantity to quality.
  2. Move from measuring effort to effect.
  3. Quadrant 1 strategies should be used sparingly, when no other data exists.
  4. The most effective measurement combines strategies in all levels, with most in Quadrants 2 and 4.

Learn More. Read how to create stronger ESMs and how to measure ESM impact more meaningfully through Results-Based Accountability.

References

1 Roy K, Failla G, Dent H, et al. S78 Tobacco dependency in maternity: A novel service providing earlier in-hospital care for pregnant smokers. Thorax 2023; 78:A57-A-58.

2 Buchanan C, Nahhas GJ, Guille C, Cummings KM, Wheeler C, McClure EA. Tobacco use prevalence and outcomes among perinatal patients assessed through an "opt-out" cessation and follow-up clinical program. Maternal and Child Health Journal 2017;21:1790-7.

3 Campbell KA, Cooper S, Fahy SJ, Bowker K, LeonardiBee J, McEwen A et al. 'Opt-out' referrals after identifying pregnant smokers using exhaled air carbon monoxide: Impact on engagement with smoking cessation support. Tobacco Control: An International Journal 2017;26:300-6.

This project is supported by the Health Resources and Services Administration (HRSA) of the U.S. Department of Health and Human Services (HHS) under grant number U02MC31613, MCH Advanced Education Policy, $3.5 M. This information or content and conclusions are those of the author and should not be construed as the official position or policy of, nor should any endorsements be inferred by HRSA, HHS or the U.S. Government.