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Research ArticleOriginal Research

Impact of Social Determinants of Health on Patients with Complex Diabetes Who Are Served by National Safety-Net Health Centers

Vivian Li, Mary Ann McBurnie, Melissa Simon, Phil Crawford, Michael Leo, Fred Rachman, Erika Cottrell, Lydia Dant, Mary Oneha and Rosy Chang Weir
The Journal of the American Board of Family Medicine May 2016, 29 (3) 356-370; DOI: https://doi.org/10.3122/jabfm.2016.03.150226
Vivian Li
From the Association of Asian Pacific Community Health Organizations, San Leandro CA (VL, RCW); Kaiser Permanente Center for Health Research, Portland OR (MAB, PC, ML); Northwestern University, Feinberg School of Medicine, Chicago IL (MS); Alliance of Chicago Community Health Services, Chicago IL (FR); OCHIN, Inc., Portland OR (EC); The Fenway Institute, Boston, MA (LD); and the Waimanalo Health Center, Waimanalo, HI (MO).
MS
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Mary Ann McBurnie
From the Association of Asian Pacific Community Health Organizations, San Leandro CA (VL, RCW); Kaiser Permanente Center for Health Research, Portland OR (MAB, PC, ML); Northwestern University, Feinberg School of Medicine, Chicago IL (MS); Alliance of Chicago Community Health Services, Chicago IL (FR); OCHIN, Inc., Portland OR (EC); The Fenway Institute, Boston, MA (LD); and the Waimanalo Health Center, Waimanalo, HI (MO).
PhD
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Melissa Simon
From the Association of Asian Pacific Community Health Organizations, San Leandro CA (VL, RCW); Kaiser Permanente Center for Health Research, Portland OR (MAB, PC, ML); Northwestern University, Feinberg School of Medicine, Chicago IL (MS); Alliance of Chicago Community Health Services, Chicago IL (FR); OCHIN, Inc., Portland OR (EC); The Fenway Institute, Boston, MA (LD); and the Waimanalo Health Center, Waimanalo, HI (MO).
MD, MPH
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Phil Crawford
From the Association of Asian Pacific Community Health Organizations, San Leandro CA (VL, RCW); Kaiser Permanente Center for Health Research, Portland OR (MAB, PC, ML); Northwestern University, Feinberg School of Medicine, Chicago IL (MS); Alliance of Chicago Community Health Services, Chicago IL (FR); OCHIN, Inc., Portland OR (EC); The Fenway Institute, Boston, MA (LD); and the Waimanalo Health Center, Waimanalo, HI (MO).
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Michael Leo
From the Association of Asian Pacific Community Health Organizations, San Leandro CA (VL, RCW); Kaiser Permanente Center for Health Research, Portland OR (MAB, PC, ML); Northwestern University, Feinberg School of Medicine, Chicago IL (MS); Alliance of Chicago Community Health Services, Chicago IL (FR); OCHIN, Inc., Portland OR (EC); The Fenway Institute, Boston, MA (LD); and the Waimanalo Health Center, Waimanalo, HI (MO).
PhD
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Fred Rachman
From the Association of Asian Pacific Community Health Organizations, San Leandro CA (VL, RCW); Kaiser Permanente Center for Health Research, Portland OR (MAB, PC, ML); Northwestern University, Feinberg School of Medicine, Chicago IL (MS); Alliance of Chicago Community Health Services, Chicago IL (FR); OCHIN, Inc., Portland OR (EC); The Fenway Institute, Boston, MA (LD); and the Waimanalo Health Center, Waimanalo, HI (MO).
MD
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Erika Cottrell
From the Association of Asian Pacific Community Health Organizations, San Leandro CA (VL, RCW); Kaiser Permanente Center for Health Research, Portland OR (MAB, PC, ML); Northwestern University, Feinberg School of Medicine, Chicago IL (MS); Alliance of Chicago Community Health Services, Chicago IL (FR); OCHIN, Inc., Portland OR (EC); The Fenway Institute, Boston, MA (LD); and the Waimanalo Health Center, Waimanalo, HI (MO).
PhD, MPP
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Lydia Dant
From the Association of Asian Pacific Community Health Organizations, San Leandro CA (VL, RCW); Kaiser Permanente Center for Health Research, Portland OR (MAB, PC, ML); Northwestern University, Feinberg School of Medicine, Chicago IL (MS); Alliance of Chicago Community Health Services, Chicago IL (FR); OCHIN, Inc., Portland OR (EC); The Fenway Institute, Boston, MA (LD); and the Waimanalo Health Center, Waimanalo, HI (MO).
MPH
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Mary Oneha
From the Association of Asian Pacific Community Health Organizations, San Leandro CA (VL, RCW); Kaiser Permanente Center for Health Research, Portland OR (MAB, PC, ML); Northwestern University, Feinberg School of Medicine, Chicago IL (MS); Alliance of Chicago Community Health Services, Chicago IL (FR); OCHIN, Inc., Portland OR (EC); The Fenway Institute, Boston, MA (LD); and the Waimanalo Health Center, Waimanalo, HI (MO).
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Rosy Chang Weir
From the Association of Asian Pacific Community Health Organizations, San Leandro CA (VL, RCW); Kaiser Permanente Center for Health Research, Portland OR (MAB, PC, ML); Northwestern University, Feinberg School of Medicine, Chicago IL (MS); Alliance of Chicago Community Health Services, Chicago IL (FR); OCHIN, Inc., Portland OR (EC); The Fenway Institute, Boston, MA (LD); and the Waimanalo Health Center, Waimanalo, HI (MO).
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Article Figures & Data

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    Figure 1.

    Structure of the Community Health Applied Research Network (CHARN).22 *Overall governance of the network is the responsibility of the CHARN Steering Committee (SC). The SC is responsible for approving final decisions, establishing subcommittees, affirming their charters, and appointing subcommittee chairs. †Asian Health Services, CA; Charles B. Wang Community Health Center, NY; Waianae Coast Comprehensive Health Center, HI; Waimanalo Health Center, HI. ‡Erie Family Health Center, IL; Glide Health Services, CA; Heartland Health Outreach, IL; Howard Brown Health Center, IL; Near North, IL; North Country Health Care, AZ; PCC Community Wellness Center, IL. §Beaufort Jasper Hampton Comprehensive Health Services, SC; Chase Brexton Health Services, MD; Fenway Health, MA. ¶Multnomah County Health Department, OR; Richmond Clinic, OR; Open Door Community Health Center, CA; Virginia Garcia Memorial Health Center, OR. AAPCHO, Association of Asian Pacific Community Health Organizations; DCC, Data Coordinating Center at the Kaiser Permanente Center for Health Research, Portland, Oregon; UCLA, University of California, Los Angeles.

  • Figure 2.
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    Figure 2.

    Insurance status. Baseline interaction of HbA1c with insurance status and diabetes status in the diabetes mellitus [DM] + cardiovascular disease [CVD] + depression [DEP] group (A) compared with DM-only group (B). For the DM + CVD + DEP group, baseline HbA1c did not differ among insurance groups, whereas for those with DM only, uninsured patients had higher baseline HbA1c.

  • Figure 3.
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    Figure 3.

    Interactions of HbA1c with primary language and diabetes status in the diabetes mellitus [DM]–only group (A), the DM + cardiovascular disease [CVD] group (B), and the DM + CVD + depression [DEP] group (C). Among those for whom Spanish was the primary language, HbA1c declined over time to a greater degree in the DM + CVD (B) group compared to the DM-only group (A). For the DM + CVD + DEP group (C), Spanish speakers had lower baseline HbA1c than English speakers compared with the DM-only group (A), in which a baseline difference was not detected between English and Spanish speakers.

Tables

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    Table 1.

    International Classification of Diseases, 9th Revision Codes of Diabetes, Cardiovascular Disease, and Depression

    Diagnosed ConditionPrimary Care Visit/Problem ListICD-9 Codes
    DiabetesDiabetes mellitus250.xx
    Polyneuropathy in diabetes357.2
    Diabetic retinopathy362.0
    Background diabetic retinopathy362.01
    Proliferative diabetic retinopathy362.02
    Nonproliferative diabetic retinopathy NOS362.03
    Mild nonproliferative diabetic retinopathy362.04
    Moderate nonproliferative diabetic retinopathy362.05
    Severe nonproliferative diabetic retinopathy362.06
    Diabetic macular edema362.07
    Cardiovascular DiseaseMyocardial infarction410.x, 412.x
    Congestive heart failure428.x
    Peripheral vascular disease443.9, 441.x, 785.4, V43.4
    Cerebrovascular disease430.x to 438.x
    DepressionMajor depressive affective disorder, single episode296.2x
    Major depressive affective disorder, recurrent episode296.3x
    Atypical depressive disorder296.82
    Depressive type psychosis298.0
    Dysthymic disorder300.4
    Chronic depressive personality disorder301.12
    Adjustment disorder with depressed mood309.0
    Prolonged depressive reaction309.1
    Adjustment disorder with mixed anxiety and depressed mood309.28
    Depressive disorder, not elsewhere classified311
    • ICD-9, International Classification of Diseases, 9th Revision; NOS, not otherwise specified.

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    Table 2.

    Characteristics of Adult Community Health Applied Research Network Patients with at Least One Primary Care Visit per Year, for at Least 3 Consecutive Years, between January 1, 2006, and December 31, 2013 (N = 114,845)

    Patients with DiabetesPatients without DiabetesTotal
    nCol %nCol %nCol %
    Sex
        Male7,42642.833,94334.841,36936.0
        Female9,91457.163,10764.773,02163.6
        Transgender200.14300.44500.4
        Missing or unknown00.050.050.0
    Race/ethnicity
        Hispanic3,21218.517,26317.720,47517.8
        Non-Hispanic white4,37825.229,10329.933,48129.2
        Non-Hispanic black1,74010.011,36811.713,10811.4
        Non-Hispanic Asian or Pacific Islander7,44442.934,80235.742,24636.8
        Other*5022.94,2614.34,7634.1
        Missing or unknown840.56880.77720.7
    Primary language
        English8,28447.748,87750.157,16149.8
        Spanish2,72815.712,53212.915,26013.3
        Cantonese or Mandarin3,89122.422,09022.725,98122.7
        Other1,6899.86,2466.47,9356.9
        Missing or unknown7684.47,7407.98,5087.4
    • ↵* Includes American Indian and multiracial. Col %, column percentages.

    • View popup
    Table 3.

    Characteristics of Adult Patients with Diabetes in the Community Health Applied Research Network Who Had at Least One Primary Care Visit over at Least 3 Consecutive Years

    DM Only (n = 13,790)DM + CVD (n = 817)DM + DEP (n = 2,495)DM + CVD + DEP (n = 258)
    Age in 2013 (years), mean (SD)54.7 (13.4)61.9 (12.5)50.7 (12.2)58.2 (10.7)
    Sex
        Male6156 (45)402 (49)763 (31)105 (41)
        Female7624 (55)415 (51)1722 (69)153 (59)
        Transgender10 (<1)0 (0)10 (<1)0< (0)
        Missing/unknown0 (0)0 (0)0 (0)0 (0)
    Race/ethnicity
        Hispanic2682 (19)63 (8)453 (18)14 (5)
        Non-Hispanic white2912 (21)246 (30)1104 (44)116 (45)
        Non-Hispanic black1419 (10)90 (11)197 (8)34 (13)
        Non-Hispanic Asian/Pacific Islander6314 (46)391 (48)656 (26)83 (32)
        Other*289 (2)13 (2)39 (2)4 (2)
        Missing/unknown64 (1)7 (1)11 (0)2 (1)
    Primary language
        English5919 (43)494 (61)1677 (67)194 (75)
        Spanish2308 (17)49 (6)358 (14)13 (5)
        Cantonese/Mandarin3514 (26)158 (19)196 (8)23 (9)
        Other1395 (10)71 (9)203 (8)20 (8)
        Missing/unknown654 (5)45 (6)61 (2)8 (3)
    Insurance status
        Continuously insured7656 (56)614 (75)1478 (59)195 (76)
        Continuously uninsured2174 (16)41 (5)251 (10)7 (3)
        Insurance gaps†3476 (25)145 (18)747 (30)55 (21)
        Missing or unknown484 (4)17 (2)19 (1)1 (0)
    Charlson index, mean (SD)1.2 (0.8)2.4 (1.0)1.5 (1.1)2.6 (1.4)
    Number of annual visits
        1 or 21775 (13)51 (6)181 (7)12 (5)
        3 or 44902 (36)207 (25)565 (23)40 (16)
        ≥57113 (52)559 (68)1749 (70)206 (80)
    • Data are n (%) unless otherwise indicated.

    • ↵* Includes American Indian and multiracial.

    • ↵† Includes a single encounter.

    • CVD, cardiovascular disease; DEP, depression; DM, diabetes mellitus; SD, standard deviation.

    • View popup
    Table 4.

    Intercept Coefficients: Estimated Marginal Mean Differences in Average HbA1c Level at the Index Date*

    Category for Intercept Differences for Mean HbA1cFixed Effectsβ CoefficientSE (β)P ValueLinear Contrast P Values
    NodeGrand mean at baseline (intercept)†7.7680.172<.001<.001
        Mean HbA1c level difference, node 2 vs node 1−0.5770.113<.001
        Mean HbA1c level difference, node 3 vs node 1−0.3910.232.123
        Mean HbA1c level difference, node 4 vs node 1−0.3870.083<.001
    Age (at baseline)Each additional year of age−0.0140.002.001NA
    Charlson index scoreEach additional Charlson index score point−0.0910.031.011NA
    SexFemale vs male−0.2310.040<.001NA
    Race/ethnicityHispanic vs non-Hispanic white0.1370.112.243<.001
    Non-Hispanic black vs non-Hispanic white0.3140.090.004
    Non-Hispanic Asian or Pacific Islander vs non-Hispanic white0.0150.087.865
    Non-Hispanic other vs non-Hispanic white0.3930.128.009
    Insurance statusContinually uninsured vs continually insured0.3750.125.010.002
    Insurance gaps vs continually insured0.1330.051.022
    Primary languageSpanish vs English0.0350.145.812.009
    Cantonese or Mandarin vs English−0.2130.086.028
    Other language vs English0.0790.104.457
    Health care use‡3 or 4 Visits vs 1 or 2 visits0.0120.081.889.296
    ≥5 Visits vs 1 or 2 visits0.0920.101.383
    • ↵* This multilevel model predicted mean HbA1c level as a function of diabetes status, primary language, and insurance status, adjusting for age, Charlson index score, sex, race/ethnicity, and node.

    • ↵† Assuming all other covariates equal zero.

    • ↵‡ Average number of annual primary care visits.

    • NA, not available; SE, standard error.

    • View popup
    Table 5.

    Slope Coefficients: Estimated Marginal Mean Differences in Average Change or Slope (Trajectory) of HbA1c Level for Every Unit Change in the Variable*

    Category for Slope differences for mean HbA1cFixed Effectsβ CoefficientSE (β)P ValueLinear Contrast P Values
    NodeGrand mean at baseline†0.0330.0270.241>.500
        Mean HbA1c level difference, node 2 vs node 1−0.0060.0210.795
        Mean HbA1c level difference, node 3 vs node 10.0150.0400.723
        Mean HbA1c level difference, node 4 vs node 10.0060.0170.711
    Age (at baseline)Each additional year of age−0.0030.000<0.001NA
    Charlson index scoreEach additional Charlson index score point−0.0020.0060.796NA
    SexFemale vs male0.0160.0090.075NA
    Race/ethnicityHispanic vs non-Hispanic white0.0520.0280.087.22
    Non-Hispanic black vs non-Hispanic white−0.0050.0300.858
    Non-Hispanic Asian or Pacific Islander vs non-Hispanic white−0.0140.0230.559
    Non-Hispanic other vs non-Hispanic white−0.0520.0470.284
    Insurance statusContinually uninsured vs continually insured0.0540.0210.024.014
    Insurance gaps vs continually insured−0.0020.0100.833
    Primary languageSpanish vs English−0.0600.0340.101.052
    Cantonese or Mandarin vs English0.0390.0180.051
    Other language vs English0.0190.0270.479
    Health care use‡3 or 4 Visits vs 1 or 2 visits−0.0200.0200.333>.500
    ≥5 Visits vs 1 or 2 visits−0.0240.0210.280
    • ↵* This multilevel model predicted mean HbA1c level as a function of diabetes status, primary language, and insurance status, adjusting for age, Charlson index score, sex, race/ethnicity, and node.

    • ↵† Assuming all other covariates equal zero.

    • ↵‡ Average number of annual primary care visits.

    • NA, not available; SE, standard error.

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The Journal of the American Board of Family     Medicine: 29 (3)
The Journal of the American Board of Family Medicine
Vol. 29, Issue 3
May-June 2016
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Impact of Social Determinants of Health on Patients with Complex Diabetes Who Are Served by National Safety-Net Health Centers
Vivian Li, Mary Ann McBurnie, Melissa Simon, Phil Crawford, Michael Leo, Fred Rachman, Erika Cottrell, Lydia Dant, Mary Oneha, Rosy Chang Weir
The Journal of the American Board of Family Medicine May 2016, 29 (3) 356-370; DOI: 10.3122/jabfm.2016.03.150226

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Impact of Social Determinants of Health on Patients with Complex Diabetes Who Are Served by National Safety-Net Health Centers
Vivian Li, Mary Ann McBurnie, Melissa Simon, Phil Crawford, Michael Leo, Fred Rachman, Erika Cottrell, Lydia Dant, Mary Oneha, Rosy Chang Weir
The Journal of the American Board of Family Medicine May 2016, 29 (3) 356-370; DOI: 10.3122/jabfm.2016.03.150226
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