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Research ArticleOriginal Research

Improving Multiple Health Risk Behaviors in Primary Care: Lessons from the Prescription for Health COmmon Measures, Better Outcomes (COMBO) Study

Douglas H. Fernald, L. Miriam Dickinson, Desireé B. Froshaug, Bijal A. Balasubramanian, Jodi Summers Holtrop, Alex H. Krist, Russell E. Glasgow and Larry A. Green
The Journal of the American Board of Family Medicine September 2012, 25 (5) 701-711; DOI: https://doi.org/10.3122/jabfm.2012.03.110057
Douglas H. Fernald
From the Department of Family Medicine, University of Colorado, Aurora (DHF, LMD, LAG); the Colorado Foundation for Medical Care, Englewood (DBF); the University of Texas Southwestern Medical Center, Dallas (BAB); the Department of Family Medicine, Michigan State University, East Lansing (JSH); the Virginia Commonwealth University, Department of Family and Community Medicine, Richmond (AHK); and the Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD (REG).
MA
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L. Miriam Dickinson
From the Department of Family Medicine, University of Colorado, Aurora (DHF, LMD, LAG); the Colorado Foundation for Medical Care, Englewood (DBF); the University of Texas Southwestern Medical Center, Dallas (BAB); the Department of Family Medicine, Michigan State University, East Lansing (JSH); the Virginia Commonwealth University, Department of Family and Community Medicine, Richmond (AHK); and the Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD (REG).
PhD
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Desireé B. Froshaug
From the Department of Family Medicine, University of Colorado, Aurora (DHF, LMD, LAG); the Colorado Foundation for Medical Care, Englewood (DBF); the University of Texas Southwestern Medical Center, Dallas (BAB); the Department of Family Medicine, Michigan State University, East Lansing (JSH); the Virginia Commonwealth University, Department of Family and Community Medicine, Richmond (AHK); and the Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD (REG).
MS
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Bijal A. Balasubramanian
From the Department of Family Medicine, University of Colorado, Aurora (DHF, LMD, LAG); the Colorado Foundation for Medical Care, Englewood (DBF); the University of Texas Southwestern Medical Center, Dallas (BAB); the Department of Family Medicine, Michigan State University, East Lansing (JSH); the Virginia Commonwealth University, Department of Family and Community Medicine, Richmond (AHK); and the Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD (REG).
MBBS, PhD
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Jodi Summers Holtrop
From the Department of Family Medicine, University of Colorado, Aurora (DHF, LMD, LAG); the Colorado Foundation for Medical Care, Englewood (DBF); the University of Texas Southwestern Medical Center, Dallas (BAB); the Department of Family Medicine, Michigan State University, East Lansing (JSH); the Virginia Commonwealth University, Department of Family and Community Medicine, Richmond (AHK); and the Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD (REG).
PhD
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Alex H. Krist
From the Department of Family Medicine, University of Colorado, Aurora (DHF, LMD, LAG); the Colorado Foundation for Medical Care, Englewood (DBF); the University of Texas Southwestern Medical Center, Dallas (BAB); the Department of Family Medicine, Michigan State University, East Lansing (JSH); the Virginia Commonwealth University, Department of Family and Community Medicine, Richmond (AHK); and the Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD (REG).
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Russell E. Glasgow
From the Department of Family Medicine, University of Colorado, Aurora (DHF, LMD, LAG); the Colorado Foundation for Medical Care, Englewood (DBF); the University of Texas Southwestern Medical Center, Dallas (BAB); the Department of Family Medicine, Michigan State University, East Lansing (JSH); the Virginia Commonwealth University, Department of Family and Community Medicine, Richmond (AHK); and the Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD (REG).
PhD
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Larry A. Green
From the Department of Family Medicine, University of Colorado, Aurora (DHF, LMD, LAG); the Colorado Foundation for Medical Care, Englewood (DBF); the University of Texas Southwestern Medical Center, Dallas (BAB); the Department of Family Medicine, Michigan State University, East Lansing (JSH); the Virginia Commonwealth University, Department of Family and Community Medicine, Richmond (AHK); and the Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD (REG).
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Article Figures & Data

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    Figure 1.

    Change in diet scores among intervention patients. PBRN, practice-based research network.

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    Figure 2.

    Change in physical activity among intervention patients. MET, metabolic equivalent; PBRN, practice-based research network.

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    Figure 3.

    Change in proportion of current smokers in intervention patients. PBRN, practice-based research network.

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    Figure 4.

    Change in average drinks per day in intervention patients. PBRN, practice-based research network.

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    Figure 5.

    Change in number of unhealthy days in intervention patients. PBRN, practice-based research network.

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    Table 1. Summary Description of the Multiple Health Behavior Interventions, Health Risk Data Collection Methods, and Study Designs
    PBRN IDIntervention Description
    1Practices collaborated with a local health department to use an extension agent model to promote screening, counseling, and use of community resources.
    Intervention: used IT, new/modified staff roles, and counseling outside the practice
    HRA: self-administered by computer
    Design: longitudinal; no comparison group
    2A community health educator referral liaison was available to practices to provide patients with health behavior counseling, follow-up, and assistance in connecting to community resources.
    Intervention: used new/modified staff roles and counseling outside the practice
    HRA: administered by liaison
    Design: group (practice) randomized; control received physician referral only
    3Family screening assessments were conducted during modified well visits for children aged 2 years, and families were directed to health behavior counseling.
    Intervention: used new/modified staff roles and counseling outside the practice
    HRA: administered by nurse staff as part of screening tool
    Design: quasi-experimental; practices were assigned to groups
    4Patients were connected to web-based tools that promoted health behavior change accompanied by an IVR telephone system to prompt website use.
    Intervention: used IT, population screening/outreach, and counseling outside the practice
    HRA: self-administered by computer
    Design: patient randomized; control received usual care
    5Practice enhancement assistants provided performance feedback, training, practice change facilitation, and local quality improvement collaboratives for behavior change.
    Intervention: used new/modified staff roles, population screening/outreach, and counseling outside the practice
    HRA: self-administered by paper forms
    Design: practices randomized to receive different sets of health behavior-specific modules in time-ordered blocks
    8Existing medical assistants identified patients at risk for unhealthy behaviors then offered counseling and referred to community resources.
    Intervention: used new/modified staff roles, population screening/outreach, and counseling outside the practice
    HRA: self-administered by paper forms
    Design: patient randomized; control received usual care.
    9Patients connected to an IVR telephone system to promote health behavior change and deliver counseling.
    Intervention: used IT and counseling outside the practice
    HRA: self-administered via the IVR system
    Design: patient randomized; control received only printed educational materials
    • Adapted from Etz et al (2008)20 and Dodoo et al (2008).21

    • HRA, health risk assessment; IT, information technology; IVR, interactive voice recognition; PBRN, practice-based research network.

    • View popup
    Table 2. Comparison of Patient Characteristics at Baseline for Those With and Without Follow-up Observations
    Baseline Patient CharacteristicsFollow-Up (n = 2199)No Follow-Up (n = 2264)P
    Outcomes
        Diet score5.66 (2.57)5.58 (2.54).2854
        Physical activity (MET-minutes)2099 (2735)2131 (2672).7075
        Average drinks per day0.30030.3336.3175
        Current smokers26.232.0.0001
        Unhealthy days25.422.0.0810
            038.738.5
            1–1336.040.0
            ≥14
    Women74.374.1.8866
    Age (years)50.8 (15.8)44.2 (15.7)<.0001
    Race/ethnicity<.0001
        Non-Hispanic white62.456.7
        Non-Hispanic black11.619.2
        Hispanic/Latino20.918.9
        Other race5.15.2
    Education<.0001
        <HS14.012.3
        HS graduate/GED28.920.4
        >HS54.035.6
        Nonrespondent3.131.6
    Income ($)<.0001
         <25,00041.332.9
        25,000–49,99921.612.3
        ≥50,00022.213.5
        Nonrespondent14.941.3
    BMI31.6 (8.4)31.1 (8.2).0527
    • Values provided as mean (standard deviation) or %.

    • Data from Prescription for Health: COMBO study.

    • BMI, body mass index; HS, high school; MET, metabolic equivalent.

    • View popup
    Table 3. Analytical Sample Sizes for Each Outcome by Practice-Based Research Network (PBRN) (Baseline/Follow-Up) and Health Risk Assessment Follow-Up Intervals
    PBRN IDDietPhysical ActivitySmokingAlcoholQuality of LifeDays to Final Follow-Up Assessment*
    1848/174871/172873/173850/105233/164186 (43), 181
    2422/294421/294424/294421/292420/293177 (47), 188
    3157/79155/76155/780/0149/79292 (70), 282
    488/3987/3988/3988/3988/39158 (44), 181
    51573/8721514/8491568/8491512/8691237/69531 (0), 31
    8386/236363/237405/236112/27344/231349 (84), 359
    988/4588/46†87/4586/13199 (62), 196
    • ↵* Values shown as mean (standard deviation), median.

    • ↵† Smoking calculations for PBRN 9 were attempted but there were too few patients at follow-up.

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The Journal of the American Board of Family     Medicine: 25 (5)
The Journal of the American Board of Family Medicine
Vol. 25, Issue 5
September-October 2012
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Improving Multiple Health Risk Behaviors in Primary Care: Lessons from the Prescription for Health COmmon Measures, Better Outcomes (COMBO) Study
Douglas H. Fernald, L. Miriam Dickinson, Desireé B. Froshaug, Bijal A. Balasubramanian, Jodi Summers Holtrop, Alex H. Krist, Russell E. Glasgow, Larry A. Green
The Journal of the American Board of Family Medicine Sep 2012, 25 (5) 701-711; DOI: 10.3122/jabfm.2012.03.110057

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Improving Multiple Health Risk Behaviors in Primary Care: Lessons from the Prescription for Health COmmon Measures, Better Outcomes (COMBO) Study
Douglas H. Fernald, L. Miriam Dickinson, Desireé B. Froshaug, Bijal A. Balasubramanian, Jodi Summers Holtrop, Alex H. Krist, Russell E. Glasgow, Larry A. Green
The Journal of the American Board of Family Medicine Sep 2012, 25 (5) 701-711; DOI: 10.3122/jabfm.2012.03.110057
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