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Research ArticleOriginal Articles

Spreading a Medical Home Redesign: Effects on Emergency Department Use and Hospital Admissions

Robert J. Reid, Eric A. Johnson, Clarissa Hsu, Kelly Ehrlich, Katie Coleman, Claire Trescott, Michael Erikson, Tyler R. Ross, David T. Liss, DeAnn Cromp and Paul A. Fishman
The Annals of Family Medicine May 2013, 11 (Suppl 1) S19-S26; DOI: https://doi.org/10.1370/afm.1476
Robert J. Reid
1Group Health Physicians, Seattle, Washington
2School of Public Health, University of Washington, Seattle, Washington
MD, PhD
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  • For correspondence: reid.rj@ghc.org
Eric A. Johnson
3Group Health Research Institute, Seattle, Washington
MA
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Clarissa Hsu
2School of Public Health, University of Washington, Seattle, Washington
3Group Health Research Institute, Seattle, Washington
PhD
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Kelly Ehrlich
3Group Health Research Institute, Seattle, Washington
MS
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Katie Coleman
3Group Health Research Institute, Seattle, Washington
MSPH
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Claire Trescott
1Group Health Physicians, Seattle, Washington
MD
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Michael Erikson
4Group Health Cooperative, Seattle, Washington
MSW
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Tyler R. Ross
3Group Health Research Institute, Seattle, Washington
MA
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David T. Liss
2School of Public Health, University of Washington, Seattle, Washington
3Group Health Research Institute, Seattle, Washington
5Division of General Internal Medicine & Geriatrics, Northwestern University Fein-berg School of Medicine, Chicago, Illinois
PhD, MA
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DeAnn Cromp
3Group Health Research Institute, Seattle, Washington
MPH
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Paul A. Fishman
2School of Public Health, University of Washington, Seattle, Washington
3Group Health Research Institute, Seattle, Washington
PhD
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  • Figure 1
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    Figure 1

    Use of in-person office visits, secure electronic message threads, and telephone encounters over time, 2008–2012.

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    Table 1

    Baseline Characteristics of the Study Populations, 2009

    CharacteristicGroup Health Practices (n=305,578)Network Practices (n=107,365)Total (N=412,943)
    Age, mean (SD), y43.5 (22.6)40.4 (21.9)42.7 (22.5)
    Age-group, No. (%)
     1–5 years12,889 (4.2)5,104 (4.9)17,993 (4.4)
     6–11 years18,307 (5.9)8,050 (7.7)26,357 (6.4)
     12–16 years19,156 (6.2)8,283 (7.9)27,439 (6.6)
     17–34 years57,226 (18.5)18,328 (17.5)75,554 (18.3)
     35–44 years37,959 (12.3)13,556 (13.0)51,525 (12.5)
     45–64 years109,707 (35.6)38,753 (37.1)148,461 (36.0)
     65–74 years26,836 (8.7)6,644 (6.4)33,480 (8.1)
     75–84 years17,860 (5.8)4,300 (4.1)22,160 (5.4)
     ≥85 years8,563 (2.8)1,411 (1.4)9,974 (2.4)
    Education, neighborhood level, No. (%)
     High13,679 (40.1)37,118 (35.5)160,797 (39.0)
     Medium152,462 (49.4)53,327 (51.1)205,789 (49.8)
     Low32,331 (10.5)13,985 (13.4)46,316 (11.2)
    Family income, neighborhood level, median (SD), $59,882 (19,833)51,909 (15,122)57,787 (19,037)
    Residence location, RUCA, No. (%)
     Urban269,515 (96.1)75,241 (72.0)371,756 (90.0)
     Metropolitan/large rural5,868 (1.9)19,598 (18.8)25,466 (6.2)
     Small rural/isolated areas2,811 (0.9)7,472 (7.2)10,283 (2.5)
     Not mapped3,309 (1.1)2,129 (2.0)5,438 (1.3)
    Insurance segment, No. (%)
     Medicare55,435 (18.0)13,038 (12.5)68,473 (16.6)
     Medicaid9,196 (3.0)838 (0.8)10,034 (2.4)
     Commercial/self-pay221,190 (71.7)86,904 (83.2)308,064 (74.6)
     Individual or family plan22,682 (7.4)3,660 (3.5)26,342 (6.4)
    Health plan product, No. (%)
     HMO257,466 (83.5)73,383 (70.3)330,849 (80.1)
     PPO/POS51,037 (16.5)31,057 (29.7)82,094 (19.9)
    Insurance benefit design, No. (%)
     Well-care waiver203,166 (66.0)65,949 (63.0)269,115 (65.2)
     High-deductible plan3,157 (1.0)997 (1.0)4,154 (1.0)
     Drug coverage267,857 (87.0)95,880 (92.0)363,737 (88.1)
    Morbidity, ACG RUB category, No. (%)
     0 (nonusers)37,417 (7.1)11,134 (6.0)48,551 (6.8)
     1 (low morbidity)36,332 (6.9)12,414 (6.7)48,746 (6.8)
     253,530 (10.1)19,901 (10.7)73,431 (10.3)
     3133,188 (25.2)45,905 (24.8)179,093 (25.1)
     431,992 (6.0)10,613 (5.7)42,535 (6.0)
     5 (high morbidity)14,142 (2.7)4,026 (2.2)18,168 (2.5)
    • HMO = health maintenance organization; POS = point of service; PPO = preferred provider organization; ACG = adjusted clinical group; RUB = Resource Utilization Band; RUCA = rural urban commuting area.

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    Table 2

    Adjusted Changes in Use for PCMH Patients Relative to Nonequivalent Control Patients

    Measure of Use and PeriodChangea (95% CI)P Value
    Monthly primary care office visits per 1,000 enrollees
    Implementation (year 1)
     Q17.54 (6.22 to 8.85)<.001
     Q25.32 (3.84 to 6.80)<.001
     Q3−1.18 (−2.87 to 0.51).17
     Q4−10.93 (−12.74 to −9.13)<.001
    Early stabilization (year 2)−9.65 (−11.82 to −8.07)<.001
    Late stabilization (year 3)−12.62 (−14.46 to −10.79)<.001
    Monthly ED visits per 1,000 enrollees
    Implementation (year 1)
     Q1−0.02 (−0.38 to 0.35).93
     Q2−0.59 (−1.00 to −0.18).005
     Q3−0.86 (−1.33 to −0.38).000
     Q4−1.43 (−1.94 to −0.92)<.001
    Early stabilization (year 2)−1.73 (−2.17 to −1.28)<.001
    Late stabilization (year 3)−2.31 (−2.82 to −1.80)<.001
    Monthly inpatient admissions (total) per 1,000 enrollees
    Implementation (year 1)
     Q10.55 (0.30 to 0.80)<.001
     Q20.63 (0.36 to 0.91)<.001
     Q30.27 (−0.04 to 0.57).09
     Q40.07 (−0.25 to 0.40).66
    Early stabilization (year 2)−0.01 (−0.28 to 0.25).93
    Late stabilization (year 3)0.05 (−0.25 to 0.35).74
    Inpatient admissions (total; ACS conditions) per 1,000 enrollees
    Implementation (year 1)
     Q10.03 (−0.04 to 0.10).45
     Q20.04 (−0.03 to 0.12).25
     Q30.02 (−0.06 to 0.10).65
     Q4−0.04 (−0.12 to 0.05).38
    Early stabilization (year 2)−0.02 (−0.09 to 0.05).61
    Late stabilization (year 3)0.03 (−0.05 to 0.11).49
    • ED = emergency department; PCMH = patient-centered medical home; ACS = ambulatory care sensitive; ADG = adjusted diagnosis group.

    • ↵a Estimated differences derived from regression models in the change in use for PCMH patients compared with nonequivalent control patients adjusted for age, sex, education, family income, residence location, insurance segment, health plan product, insurance benefit design, ADG mix, and calendar month.

Additional Files

  • Figures
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  • Supplemental Appendix

    Supplemental Appendix. Contextual Factors at Group Health

    Files in this Data Supplement:

    • Supplemental data: Appendix - PDF file, 5 pages, 217 KB
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The Annals of Family Medicine: 11 (Suppl 1)
The Annals of Family Medicine: 11 (Suppl 1)
Vol. 11, Issue Suppl 1
May/June 2013
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Spreading a Medical Home Redesign: Effects on Emergency Department Use and Hospital Admissions
Robert J. Reid, Eric A. Johnson, Clarissa Hsu, Kelly Ehrlich, Katie Coleman, Claire Trescott, Michael Erikson, Tyler R. Ross, David T. Liss, DeAnn Cromp, Paul A. Fishman
The Annals of Family Medicine May 2013, 11 (Suppl 1) S19-S26; DOI: 10.1370/afm.1476

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Spreading a Medical Home Redesign: Effects on Emergency Department Use and Hospital Admissions
Robert J. Reid, Eric A. Johnson, Clarissa Hsu, Kelly Ehrlich, Katie Coleman, Claire Trescott, Michael Erikson, Tyler R. Ross, David T. Liss, DeAnn Cromp, Paul A. Fishman
The Annals of Family Medicine May 2013, 11 (Suppl 1) S19-S26; DOI: 10.1370/afm.1476
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