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Research ArticleOriginal Research

Real-World Implementation and Outcomes of Health Behavior and Mental Health Assessment

Hector P. Rodriguez, Beth A. Glenn, Tanya T. Olmos, Alex H. Krist, Stephanie L. Shimada, Rodger Kessler, Suzanne Heurtin-Roberts and Roshan Bastani
The Journal of the American Board of Family Medicine May 2014, 27 (3) 356-366; DOI: https://doi.org/10.3122/jabfm.2014.03.130264
Hector P. Rodriguez
From the Department of Health Policy and Management, Fielding School of Public Health, University of California, Los Angeles (HPR, BAG, TTO, RB); the Division of Cancer Prevention and Control, Jonsson Comprehensive Cancer Center, Los Angeles, CA (BAG, RB); the Department of Family Medicine and Population Health, Virginia Commonwealth University, Richmond (AHK); The Center for Health Quality, Outcomes and Economic Research, VA Healthcare System, Bedford, MA (SLS); the Department of Family Medicine, University of Vermont, Burlington (RK); and the Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD (SH-R).
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Beth A. Glenn
From the Department of Health Policy and Management, Fielding School of Public Health, University of California, Los Angeles (HPR, BAG, TTO, RB); the Division of Cancer Prevention and Control, Jonsson Comprehensive Cancer Center, Los Angeles, CA (BAG, RB); the Department of Family Medicine and Population Health, Virginia Commonwealth University, Richmond (AHK); The Center for Health Quality, Outcomes and Economic Research, VA Healthcare System, Bedford, MA (SLS); the Department of Family Medicine, University of Vermont, Burlington (RK); and the Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD (SH-R).
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Tanya T. Olmos
From the Department of Health Policy and Management, Fielding School of Public Health, University of California, Los Angeles (HPR, BAG, TTO, RB); the Division of Cancer Prevention and Control, Jonsson Comprehensive Cancer Center, Los Angeles, CA (BAG, RB); the Department of Family Medicine and Population Health, Virginia Commonwealth University, Richmond (AHK); The Center for Health Quality, Outcomes and Economic Research, VA Healthcare System, Bedford, MA (SLS); the Department of Family Medicine, University of Vermont, Burlington (RK); and the Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD (SH-R).
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Alex H. Krist
From the Department of Health Policy and Management, Fielding School of Public Health, University of California, Los Angeles (HPR, BAG, TTO, RB); the Division of Cancer Prevention and Control, Jonsson Comprehensive Cancer Center, Los Angeles, CA (BAG, RB); the Department of Family Medicine and Population Health, Virginia Commonwealth University, Richmond (AHK); The Center for Health Quality, Outcomes and Economic Research, VA Healthcare System, Bedford, MA (SLS); the Department of Family Medicine, University of Vermont, Burlington (RK); and the Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD (SH-R).
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Stephanie L. Shimada
From the Department of Health Policy and Management, Fielding School of Public Health, University of California, Los Angeles (HPR, BAG, TTO, RB); the Division of Cancer Prevention and Control, Jonsson Comprehensive Cancer Center, Los Angeles, CA (BAG, RB); the Department of Family Medicine and Population Health, Virginia Commonwealth University, Richmond (AHK); The Center for Health Quality, Outcomes and Economic Research, VA Healthcare System, Bedford, MA (SLS); the Department of Family Medicine, University of Vermont, Burlington (RK); and the Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD (SH-R).
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Rodger Kessler
From the Department of Health Policy and Management, Fielding School of Public Health, University of California, Los Angeles (HPR, BAG, TTO, RB); the Division of Cancer Prevention and Control, Jonsson Comprehensive Cancer Center, Los Angeles, CA (BAG, RB); the Department of Family Medicine and Population Health, Virginia Commonwealth University, Richmond (AHK); The Center for Health Quality, Outcomes and Economic Research, VA Healthcare System, Bedford, MA (SLS); the Department of Family Medicine, University of Vermont, Burlington (RK); and the Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD (SH-R).
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Suzanne Heurtin-Roberts
From the Department of Health Policy and Management, Fielding School of Public Health, University of California, Los Angeles (HPR, BAG, TTO, RB); the Division of Cancer Prevention and Control, Jonsson Comprehensive Cancer Center, Los Angeles, CA (BAG, RB); the Department of Family Medicine and Population Health, Virginia Commonwealth University, Richmond (AHK); The Center for Health Quality, Outcomes and Economic Research, VA Healthcare System, Bedford, MA (SLS); the Department of Family Medicine, University of Vermont, Burlington (RK); and the Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD (SH-R).
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Roshan Bastani
From the Department of Health Policy and Management, Fielding School of Public Health, University of California, Los Angeles (HPR, BAG, TTO, RB); the Division of Cancer Prevention and Control, Jonsson Comprehensive Cancer Center, Los Angeles, CA (BAG, RB); the Department of Family Medicine and Population Health, Virginia Commonwealth University, Richmond (AHK); The Center for Health Quality, Outcomes and Economic Research, VA Healthcare System, Bedford, MA (SLS); the Department of Family Medicine, University of Vermont, Burlington (RK); and the Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD (SH-R).
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Article Figures & Data

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    Figure 1.

    Proportion of respondents screening “positive” for intervention for each health behavior and mental health measure

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    Table 1. Participating Primary Care Practice Characteristics
    Practice SiteLocationPractice TypePrimary Patient DemographicsHistory of Implementing Behavioral Health AssessmentsElectronic Health RecordDuration (days)Total Assessments Completed, n (% reach)Patients Providing Feedback (%)
    ALos Angeles, CAFQHCLow-income, Chinese-American (85%)Registered nurse administered behavioral health assessment during initial intake appointmentsYes666 (79)*94.0
    BSanta Ana, CAFQHCLow-income, Mexican-American (76%)Prior use of depression screening (PHQ-9)No559 (74)*59.3
    CEagle Rock, CAFQHCLow-income, Filipino-American (58%) and Mexican-American (27%)No routine collection of behavioral health dataYes1065 (65)*93.8
    DLos Angeles, CAFQHCLow-income, Mexican-Americans (51%) and Central-Americans (31%)No routine collection of behavioral health dataYes493 (85)*95.7
    EMontpelier, VTPBRNLower-middle income, white (90%)Intermittent use of depression (PHQ-9), anxiety (GAD), and alcohol use (Audit-C)Yes322 (64)*95.5
    FFront Royal, VAPBRNLower-middle income, white (85%)Routinely assessed multiple health behaviors through personal health recordYes345 (73)†88.9
    GBon Secours, VAPBRNLower-middle income, African American (85%)Routinely assessed multiple health behaviors through personal health recordYes220 (88)†85.0
    HRichmond, VAPBRNLower-middle income, African American (60%) and white (30%)Routinely assessed smoking status but no other behavioral or mental health assessmentYes435 (59)†100
    IBedford, MAVALower-middle income, white veterans (90%)Intermittent collection of behavioral health data but no comprehensive behavioral health assessment in placeYes457 (60)*91.2
    • ↵* For 6 practices, reach was calculated using administrative reports (no. of completed surveys / no. number of nonurgent patient visits).

    • ↵† For 4 practices, reach was calculated using tallies by the research team (no. of completed surveys / no. of nonurgent patients offered the survey).

    • AUDIT-C, Alcohol Use Disorders Identification Test; FQHC, federally qualified health center; GAD, generalized anxiety disorder; PBRN, practice-based research network; PHQ-9, 9-item Patient Health Questionnaire; VA, Veterans Health Administration.

    • View popup
    Table 2. Respondent Characteristics by Primary Care Setting
    Patient CharacteristicsOverall (n = 463)FQHCs (n = 284)PBRNs (n = 122)VA (n = 57)P Value
    Female sex61.270.265.33.8< .001
    Age, years< .001
        <305.05.44.33.9
        30–397.667.610.31.9
        40–4915.817.415.57.7
        50–5932.237.724.121.2
        60–6928.426.529.336.5
        70–797.45.111.211.5
        ≥803.60.45.217.3
    Education< .001
        Less than high school34.650.411.23.9
        High school graduate or GED25.321.733.625.5
        Some college14.811.019.025.5
        Associates degree/technical training10.78.112.121.6
        4-Year college degree or more14.68.824.123.5
    Race/ethnicity< .001
        Non-Hispanic white29.06.769.682.9
        Black/African American7.81.923.99.8
        Mexican-American24.836.32.20.0
        Other Hispanic13.819.52.22.4
        Chinese14.321.40.00.0
        Filipino6.810.10.00.0
        Other3.84.12.24.9
    Born in the United States45.314.294.695.7< .001
    Survey language< .001
        English56.428.9100.0100.0
        Spanish31.150.70.00.0
        Chinese12.520.40.00.0
    English literacy< .001
        Very good/good56.831.899.1100.0
        Not good20.933.20.00.0
        Not at all22.335.00.90.0
    Needs interpreter< .001
        No64.744.897.4100.0
        Yes22.034.31.80.0
        Sometimes13.420.90.90.0
    Employment< .01
        Full time21.114.437.719.2
        Part time12.818.13.55.8
        Unemployed16.721.09.79.6
        Homemaker15.323.33.50.0
        Disabled10.15.518.415.4
        Other24.017.727.250.0
    Marital statusN/S
        Married48.550.049.638.5
        Single, never married17.316.918.317.3
        Divorced12.410.410.426.9
        Other21.822.721.717.3
    • Data are percentages.

    • FQHC, federally qualified health center; N/S, no statistically significant differences between primary care practice type; PBRN, practice-based research network; VA, Veterans Health Administration.

    • View popup
    Table 3. The Relation of Primary Care Practice Type and Screening Positive, Unadjusted vs. Adjusted Analyses
    Health Behavior MeasureFQHC (vs PBRN)VA (vs PBRN)
    Unadjusted ORP ValueAdjusted ORP ValueUnadjusted ORP ValueAdjusted ORP Value
    Fast food0.22< .0010.16< .050.441.06
    Fruits/vegetables0.778.8< .050.931.26
    Soda0.740.760.81.87
    Exercise1.781.140.890.54
    Stress1.45< .051.251.662.1
    Anxiety/worry0.860.651.041.46
    Depression/interest1.061.181.891.14
    Sleep0.640.821.011.19
    Smoking0.36P < .010.521.70.87
    Smokeless tobacco0.31< .0547.81.641.75
    Alcohol1.15.01< .051.81< .052.47
    Drug use1.590.688.44P < .017.34< .05
    Self-rated health1.69< .051.660.770.77
    Total positive screens*−0.050.20.370.6
    • P values are compared to practice-based research network (PBRN) practices. The adjusted analyses control for patient sex, age, education, race/ethnicity, nativity, employment status, and marital status. Bold values indicate statistically significant results at P < .05.

    • ↵* Coefficient is interpreted as the odds of primary care practice type [federally qualified health center (FQHC) or Veterans Affairs (VA)] patients screening positive for the measure compared to PBRN patients.

    • OR, odds ratio.

    • View popup
    Table 4. The Use of the Behavioral Health Assessment during the Clinical Encounter, by Primary Care Practice Type
    Overall (n = 408)FQHC (n = 241)PBRN (n = 115)VA (n = 52)P Value*
    Patient felt comfortable answering the questions85.691.776.377.5< .001
    Provider showed patients the results of the behavioral health assessment58.553.767.7—< .05
    Patients received a copy of results to take home36.028.450.041.0< .01
    Provider asked patient about their concerns about the results54.146.767.064.3< .01
    Provider asked which health concerns patient would like to work on60.248.781.371.4< .001
    Provider helped identify specific steps patient can take to address concerns72.164.685.681.5< .01
    Patient plans to follow up with provider about health concerns from the behavioral health assessment83.277.591.193.2< .01
    • Data are percentages.

    • ↵* P values indicate the overall differences across primary care practice types.

    • FQHC, federally qualified health center; PBRN, practice-based research network; VA, Veterans Health Administration.

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The Journal of the American Board of Family     Medicine: 27 (3)
The Journal of the American Board of Family Medicine
Vol. 27, Issue 3
May-June 2014
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Real-World Implementation and Outcomes of Health Behavior and Mental Health Assessment
Hector P. Rodriguez, Beth A. Glenn, Tanya T. Olmos, Alex H. Krist, Stephanie L. Shimada, Rodger Kessler, Suzanne Heurtin-Roberts, Roshan Bastani
The Journal of the American Board of Family Medicine May 2014, 27 (3) 356-366; DOI: 10.3122/jabfm.2014.03.130264

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Real-World Implementation and Outcomes of Health Behavior and Mental Health Assessment
Hector P. Rodriguez, Beth A. Glenn, Tanya T. Olmos, Alex H. Krist, Stephanie L. Shimada, Rodger Kessler, Suzanne Heurtin-Roberts, Roshan Bastani
The Journal of the American Board of Family Medicine May 2014, 27 (3) 356-366; DOI: 10.3122/jabfm.2014.03.130264
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