Collaboration Is Key: Dr Matthew Smeltzer Explores Quality-of-Care Improvement in NSCLC

In a session concerned with the quality of care for patients with early-stage non–small cell lung cancer (NSCLC), Matthew Smeltzer, PhD, MStat, associate professor, Division of Epidemiology, Biostatistics, and Environmental Health, University of Memphis, spoke about the data he and his team have gathered regarding gaps in biomarker testing. This project represents an important venture in the efforts to improve patient outcomes and the lower overall survival numbers associated with NSCLC, which, Smeltzer et al argue, could be connected to inadequate implementation of evidence-based therapies and diagnostics.

Smeltzer discussed in more detail the quality improvement initiatives he and his team have implemented across 3 cancer centers in the US. In this interview, as he awaits 6-month follow-up data to reflect the impact of the initiative, Smeltzer spoke to the gaps in care that have been observed, their approach to addressing suboptimal care, and emphasized the value of collaborative efforts to make a difference in patient outcomes.

These topics, among other research developments and efforts, were explored at the 2024 World Conference on Lung Cancer (WCLC) meeting held in San Diego, California.

This transcript has been lightly edited for clarity and length.

Matthew Smeltzer, PhD | image credit: https://www.memphis.edu/publichealth/contact/faculty_profiles/smeltzer.php

The American Journal of Managed Care^® (AJMC^®): Can you contextualize the need for implementing quality improvement measures for the care of patients with NSCLC? How would you say these gaps impact the overall quality of care and treatment outcomes for patients?

This project is the second project of this sort that we've done. The Association of Cancer Care Centers does this work, and we did one in late-stage lung cancer where we noted some gaps in the quality of care, and in particular, guideline-concordant care delivery. We typically use a mixed methods and mixed modality approach with these projects, where we'll start with an assessment survey try to identify what gaps would be best to fill; we'll ask sites different topics about care delivery to see if optimal care delivery might be lacking in certain aspects.

While our previous project was on late-stage non–small cell lung cancer, this current project is on early-stage non–small cell lung cancer. We conducted the survey and identified that biomarker testing in early-stage non–small cell lung cancer was a big area that could use improvement, in access, delivery of the testing, and the processes around that. The first phase of the early-stage project taught us biomarker testing might be the place to focus on, so we ended up recruiting 3 sites to participate.

Then, we went into the sites to collect baseline data, look at their own data, and verify where their care /gaps were in each particular site. Was it concordant with our thoughts for the project? As it turns out, all 3 sites had suboptimal biomarker testing for patients with early-stage non–small cell lung cancer, so we chose that direction for their quality improvement.

Essentially, what the care pattern is now is not everyone is tested for guideline recommended biomarkers. And we wanted to understand what are the reasons that's not happening at their site, but more importantly, how can we facilitate better testing? So, we've measured their baseline testing rates, some process level things, information about their patients, and we will measure again in 6 months to see if we made any improvement with the initiative. We’ll try to build some type of data benchmarks into their long-term workflow so that they can monitor the quality over time and maintain that quality over time. Any change that we make will hopefully be sustainable.

AJMC: What are the specific strategies that were implemented as part of the quality improvement initiative? Can you share any examples of successful approaches?

In terms of our mixed modality approach, it starts with the broader assessment survey, then the baseline data at the specific sites, the group workshop—which is the qualitative time, where we all work together to brainstorm, find solutions, and implement them.

With the biomarker testing project right now—we've got 1 of those 3 in the intervention phase—the solution that they're implementing is reflex EGFR [epidermal growth factor receptor] testing for all patients with non-small cell, early-stage lung cancer. And the solution was to get the multidisciplinary team together along with the testing company, and coordinate: who's going to order the test? What process is going to go into the test ordering? Who's going to pay for it. How do we ensure that there's not unexpected costs coming back on the patients? And how do we make sure that it all gets ordered in a timely manner and in a way that's allowable? That took the clinicians, the administration and the payer all working together to come up with a protocol. We've implemented it, but we do not have to follow up data yet.

AJMC: Based on your findings, what key lessons can be learned by and applied to other cancer centers/health care settings?

A big key lesson is: if there's a willpower to make a change, and you can get people in a room, with a purpose, to sit down and find solutions, that we can solve a lot of these problems just by working together and getting innovative. So, when the people look for solutions together and are willing to be flexible, we can solve a lot of these problems; but it takes intentionality.

AJMC: What were the main challenges you encountered during this quality improvement initiative, how were they addressed, and are there any ongoing challenges that require more attention?

One challenge is data: data acquisition. Data analysis is always dependent on the infrastructure available at a cancer center. When you're working with community cancer centers, we have varying levels of ability to build more research-type or quality improvement–type data sets, So, we work with them to think about what metrics we really need to measure, how do we put that into place, and how do we get data that is meaningful but not overwhelming.

Another challenge is just getting the multidisciplinary team together and aligned to solve a problem. People’s clinicians have very busy schedules, and so, coordination and working together takes effort, as does getting calendars and schedules aligned to get everybody sitting down and working together. That's why we plan 3 months in advance—“Hey, we're going to be here for this half day workshop”—so everybody can clear their schedule to sit down and talk. And something that we've seen is, when you all sit down in a room and actually allocate time to solving a problem, you can really get a lot accomplished—but it is a barrier to get people together.