Analysis of MDS Data Deborah J. Ossip-Klein, Ph.D. University of Rochester Medical Center 2005 NAQC Annual Membership Meeting Chicago

Overview Benefits of MDS for Analyses Where to Start: Initial Common Questions to Address

Benefits of MDS for Analyses Consistent measures Comparability of measures across quitlines and over time Take advantage of natural experiments Can randomize quitlines to different treatment conditions (e.g., promotion, intervention)

MDS allows for at least 3 general types of analyses: Internal Tracking Within Quitlines Services delivered, caller characteristics, outcomes, other Benchmarking Across Quitlines Reach, outcomes, other Research Can answer research questions that are better addressed with multiple quitlines vs. a single site Reach and outcomes for populations whose numbers are too small at individual quitline sites for analysis (e.g., ethnic minority populations) How different environments and service delivery models relate to outcomes Others

Where to Start: Initial Common Questions to Address NAQC Research and Evaluation Workgroup identified a 2-part strategy for research: Begin with “Low Hanging Fruit” studies as a means of generating research data relatively quickly (building early success) and engaging/refining the research network based on lessons learned in working together Expand to Longer-Term research projects (projects that would take longer and more intense efforts to implement)

Low Hanging Fruit Pull from subsets of baseline MDS items that quitlines would feel comfortable sharing Descriptive Studies of North American Quitlines with Special Focus on Diversity and Reach Who calls (and who doesn’t call) quitlines in North America (e.g., ethnicity, age, gender, pregnancy)? What services do callers receive? Does this differ by population characteristics (e.g., ethnicity, gender, age, pregnancy)? NRT availability and use: What % request/ quitlines offer NRT? What is the range of services offered? Do callers who receive NRT differ from callers who do not (i.e, does NRT availability attract different types of callers – by ethnicity, gender, age, etc.)? What is the reach of quitlines? Does this differ by population characteristics (e.g., ethnicity, gender, age, pregnancy)? Concurrent Process Studies - with subsets of quitlines engaged in this research to identify barriers, facilitators, and lessons learned in using and sharing MDS data

Longer-Term Studies (partial listing – most frequently listed research topics) In general – how can quitlines improve quit rates? What is the relationship between baseline variables (e.g., population characteristics, referral source/media, quitline characteristics) and outcomes? Who does well with what kinds of interventions? How does this vary by gender, racial, ethnic, smoking characteristics? Does caller success vary by characteristics of counselors? What marketing/communication strategies can improve the reach and quit rates for quitlines? What are effective models for delivering NRT/medications through quitlines?

What is the impact of the context in which quitlines operate on process and outcomes? What is the impact of linking quitline services with other smoking cessation services and health systems (e.g., doctor offices) on utilization and outcomes? What effect does state/provincial legislation have on quitline utilization and outcomes, e.g. does a tax increase drive callers to quitlines? Do these callers have different quit rates? Operational Issues What is the optimal “packaging” of sessions (e.g., what is the optimal number of counseling sessions)? What are effective means of decreasing dropout from intervention and improving follow-up completion rates? How do variations in quitline services relate to outcomes?

The goal is for the MDS data to be useful Internally, to help each quitline track and maintain high quality services To provide helpful benchmarking across quitlines To answer research questions of value to quitlines and quitline funders

What is the Next Step? Your input is important What do you need to make this happen? What is missing? What looks right?