An Interview with Jen Marler, MD, Vice President, Clinical and Medical Affairs at Pivot.

What type of evidence should benefits leaders at corporations and health plans look for when selecting a tobacco cessation solution? Jen Marler, MD, Pivot’s in-house digital therapeutics expert, believes that evaluating scientific studies doesn’t require an advanced degree. Marler even has some best practices on how to “read” clinical studies, in the hopes that it helps verify which programs really work.

Question: What does “clinical data” mean when talking about tobacco cessation?

Jen Marler, MD: Clinical data comes from legitimate studies completed within a clinical setting that have a specific set of outcomes to be evaluated. Research is overseen by an external ethics committee, which signs off on the protocol and determines what data will be collected. Data is generated under rigorous conditions, with a high level of accountability and transparency. In some cases, HIPAA or a government agency like the FDA will specify how the study must be conducted.

Q: Why is clinical data important when selecting a tobacco cessation provider?

JM: Tobacco use is a chronic condition, like diabetes or hypertension. As with chronic conditions, you want to be sure that any program you utilize as a benefit offering has proven results – essentially, make sure that it’s not “snake oil.” After all, benefits enrollees – either with your company or health plan –  have placed their trust in you to select an effective program worth all of the efforts they’ll be putting into quitting. That’s why, as far as deal-breakers go, clinical data should be high on that list.

Q: How can you ensure that data and conclusions are trustworthy?

JM: Checking to see if the study was published in a relevant peer-reviewed publication is one of the best ways to do that. For example, Pivot has several publications in the Journal of Medical Internet Research (JMIR).

Look to see if the study was conducted under an ethics committee, or if there is an explanation as to why it was not. This information is usually found in the “Methods” section of a paper. Check if the study was registered in a trial registry (a website like clinicaltrials.gov, for example, can be a great resource). This is also typically mentioned in “Methods.” Finally, if you see multiple studies with similar results, that increases confidence too.

Q: Are there specific criteria to look for in tobacco cessation studies?

JM: When you talk about kicking habits like tobacco use, you must consider the potential for relapse. This is important when reviewing studies with short time spans. After about 6 months of being quit, the likelihood of relapse drops significantly, and quit rates stabilize. From a clinical data standpoint, it’s much easier to generate favorable results at 6 weeks than it is at 6 months. That’s why it’s important to approach studies that have short time spans with caution.

Another consideration is that only about 20% of tobacco users are ready to quit in the next 30 days. Part of a credible tobacco cessation program is nurturing readiness at the outset, and then assisting quitters over the long haul, even through setbacks. Therefore, you need to determine whether a study represents the general population of tobacco users with varying degrees of readiness (like your employees or plan members), or a cherry-picked group who are ready to quit immediately.

Q: How might an employer or health plan use data to select a tobacco cessation program?

JM: Three ways come to mind. First, recognize that by backing claims with credible data, a vendor proves that they’re a serious player in the game. Obtaining clinical data requires dedicating a considerable amount of time, discipline, and resources and it involves risk, because you may not like what the data reveals. So the mere offering of clinical evidence – rather than just marketing ploys – can be considered a litmus test of sorts.

Second, employers and health plans like yourself can leverage data to project likely outcomes, and estimate the probable bang for your buck. If you can predict how many in your tobacco-using population will quit smoking, vaping, or using other forms of tobacco, you can calculate improvements in enrollment, engagement, insurance claims, productivity, and more.

Finally, numeric evidence gives you a common-sense method for comparing vendors, so you can make an informed decision on which best meets your organization’s needs. It also gives you further detail oftentimes needed to justify your vendor selection to senior management.

Q: How can data be used to encourage trust in employers, health plans, and their member population?

JM: Everyone deserves to know what they are signing up for and what they can expect in terms of results – that’s what comes from quality data. Similarly, good data provides the opportunity to benchmark your outcomes. Are you overperforming, underperforming, or right where you’d expect to be? Knowing this lets you pat yourself on the back – or correct course as necessary.

In addition, a data-focused process enables transparency and collaboration, encouraging ongoing efforts to improve. That’s a big plus – when you have data to track and measure against, you can work to maintain or improve your results. And generally speaking, high-quality, transparent data can be viewed as a reliable proxy for the integrity of the overall tobacco cessation program.

Q: How does your organization ensure the integrity of clinical evidence?

JM: In one of Pivot’s most important clinical studies, published in the Journal of Medical Internet Research, data was collected in several ways. Some data was subjective, from participants self-reporting their tobacco usage directly in Pivot’s app on their cell phone. Other data was objective, including results from voluntary, self-guided breath samples taken on a breath sensor measuring carbon monoxide levels. The app data also included engagement metrics, such as the number of times the app was opened. This gave researchers a sense of how the program was being used.

Pivot also collects clinical data through secure online questionnaires and video conference bio-validation visits (a way of collecting breath samples electronically to confirm subjects are in fact tobacco-free). During interviews, carbon monoxide is quantified in exhaled breath using a special sensor. Studies are overseen by an external ethics committee, which approves data collection methods, and has the right to audit the anonymized, aggregated data. Moreover, medical products that are regulated by the FDA – such as Pivot – must follow rigorous data collection and reporting methods. This anonymized, aggregate data is subject to auditing to ensure quality and accuracy. Accordingly, there is a high level of accountability to ensure the data is trustworthy.

Q: What type of data does your organization give to employers and health plans, and how is it used?

JM: Pivot supplies employers and health plans with periodic reports providing aggregate data on multiple metrics. These include program enrollment, participant demographics, program engagement, cessation progress, cessation success, user satisfaction, and benchmark comparisons to other programs. Employers or health plans can then track the progress of their program over time, and work with Pivot as needed to optimize results.

Ultimately, reliable clinical evidence empowers employers and health plans to make informed decisions, ensuring that their partnership with Pivot is providing meaningful outcomes and value. In this way, clinical data puts the employer and health plan exactly where they need to be — in the driver’s seat.

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Jen Marler, M.D. is vice president of clinical and medical affairs at Pivot, a digital health company delivering clinically proven, behavioral science-based solutions that empower people to take control of their personal health.