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Research ArticleOriginal Research

The Effects of Major Disruptions on Practice Participation in Facilitation During a Primary Care Quality Improvement Initiative

Jennifer R. Hemler, Samuel T. Edwards, Steele Valenzuela, Andrea Baron, Jennifer D. Hall, Cynthia K. Perry, Bijal A. Balasubramanian, Laura Damschroder, Leif I. Solberg, Benjamin F. Crabtree and Deborah J. Cohen
The Journal of the American Board of Family Medicine January 2022, 35 (1) 124-139; DOI: https://doi.org/10.3122/jabfm.2022.01.210205
Jennifer R. Hemler
From the Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (JRH, BFC); Section of General Internal Medicine, Veterans Affairs (VA) Portland Health Care System, Portland, OR (STE); Division of General Internal Medicine and Geriatrics, Oregon Health & Science University, Portland, OR (STE); Department of Family Medicine, Oregon Health & Science University, Portland, OR (STE, SV, AB, JDH, DJC); School of Nursing, Oregon Health & Science University, Portland, OR (CKP); Department of Epidemiology, Human Genetics, and Environmental Science, UTHealth School of Public Health, Dallas, TX (BAB); Implementation Pathways, LLC and VA Center for Clinical Management Research, Ann Arbor, MI (LD); HealthPartners Institute, Minneapolis, MN (LIS).
PhD
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Samuel T. Edwards
From the Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (JRH, BFC); Section of General Internal Medicine, Veterans Affairs (VA) Portland Health Care System, Portland, OR (STE); Division of General Internal Medicine and Geriatrics, Oregon Health & Science University, Portland, OR (STE); Department of Family Medicine, Oregon Health & Science University, Portland, OR (STE, SV, AB, JDH, DJC); School of Nursing, Oregon Health & Science University, Portland, OR (CKP); Department of Epidemiology, Human Genetics, and Environmental Science, UTHealth School of Public Health, Dallas, TX (BAB); Implementation Pathways, LLC and VA Center for Clinical Management Research, Ann Arbor, MI (LD); HealthPartners Institute, Minneapolis, MN (LIS).
MD, MPH
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Steele Valenzuela
From the Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (JRH, BFC); Section of General Internal Medicine, Veterans Affairs (VA) Portland Health Care System, Portland, OR (STE); Division of General Internal Medicine and Geriatrics, Oregon Health & Science University, Portland, OR (STE); Department of Family Medicine, Oregon Health & Science University, Portland, OR (STE, SV, AB, JDH, DJC); School of Nursing, Oregon Health & Science University, Portland, OR (CKP); Department of Epidemiology, Human Genetics, and Environmental Science, UTHealth School of Public Health, Dallas, TX (BAB); Implementation Pathways, LLC and VA Center for Clinical Management Research, Ann Arbor, MI (LD); HealthPartners Institute, Minneapolis, MN (LIS).
MS
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Andrea Baron
From the Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (JRH, BFC); Section of General Internal Medicine, Veterans Affairs (VA) Portland Health Care System, Portland, OR (STE); Division of General Internal Medicine and Geriatrics, Oregon Health & Science University, Portland, OR (STE); Department of Family Medicine, Oregon Health & Science University, Portland, OR (STE, SV, AB, JDH, DJC); School of Nursing, Oregon Health & Science University, Portland, OR (CKP); Department of Epidemiology, Human Genetics, and Environmental Science, UTHealth School of Public Health, Dallas, TX (BAB); Implementation Pathways, LLC and VA Center for Clinical Management Research, Ann Arbor, MI (LD); HealthPartners Institute, Minneapolis, MN (LIS).
MPH
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Jennifer D. Hall
From the Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (JRH, BFC); Section of General Internal Medicine, Veterans Affairs (VA) Portland Health Care System, Portland, OR (STE); Division of General Internal Medicine and Geriatrics, Oregon Health & Science University, Portland, OR (STE); Department of Family Medicine, Oregon Health & Science University, Portland, OR (STE, SV, AB, JDH, DJC); School of Nursing, Oregon Health & Science University, Portland, OR (CKP); Department of Epidemiology, Human Genetics, and Environmental Science, UTHealth School of Public Health, Dallas, TX (BAB); Implementation Pathways, LLC and VA Center for Clinical Management Research, Ann Arbor, MI (LD); HealthPartners Institute, Minneapolis, MN (LIS).
MPH
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Cynthia K. Perry
From the Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (JRH, BFC); Section of General Internal Medicine, Veterans Affairs (VA) Portland Health Care System, Portland, OR (STE); Division of General Internal Medicine and Geriatrics, Oregon Health & Science University, Portland, OR (STE); Department of Family Medicine, Oregon Health & Science University, Portland, OR (STE, SV, AB, JDH, DJC); School of Nursing, Oregon Health & Science University, Portland, OR (CKP); Department of Epidemiology, Human Genetics, and Environmental Science, UTHealth School of Public Health, Dallas, TX (BAB); Implementation Pathways, LLC and VA Center for Clinical Management Research, Ann Arbor, MI (LD); HealthPartners Institute, Minneapolis, MN (LIS).
PhD, FNP-BC
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Bijal A. Balasubramanian
From the Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (JRH, BFC); Section of General Internal Medicine, Veterans Affairs (VA) Portland Health Care System, Portland, OR (STE); Division of General Internal Medicine and Geriatrics, Oregon Health & Science University, Portland, OR (STE); Department of Family Medicine, Oregon Health & Science University, Portland, OR (STE, SV, AB, JDH, DJC); School of Nursing, Oregon Health & Science University, Portland, OR (CKP); Department of Epidemiology, Human Genetics, and Environmental Science, UTHealth School of Public Health, Dallas, TX (BAB); Implementation Pathways, LLC and VA Center for Clinical Management Research, Ann Arbor, MI (LD); HealthPartners Institute, Minneapolis, MN (LIS).
MBBS, PhD
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Laura Damschroder
From the Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (JRH, BFC); Section of General Internal Medicine, Veterans Affairs (VA) Portland Health Care System, Portland, OR (STE); Division of General Internal Medicine and Geriatrics, Oregon Health & Science University, Portland, OR (STE); Department of Family Medicine, Oregon Health & Science University, Portland, OR (STE, SV, AB, JDH, DJC); School of Nursing, Oregon Health & Science University, Portland, OR (CKP); Department of Epidemiology, Human Genetics, and Environmental Science, UTHealth School of Public Health, Dallas, TX (BAB); Implementation Pathways, LLC and VA Center for Clinical Management Research, Ann Arbor, MI (LD); HealthPartners Institute, Minneapolis, MN (LIS).
MPH, MS
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Leif I. Solberg
From the Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (JRH, BFC); Section of General Internal Medicine, Veterans Affairs (VA) Portland Health Care System, Portland, OR (STE); Division of General Internal Medicine and Geriatrics, Oregon Health & Science University, Portland, OR (STE); Department of Family Medicine, Oregon Health & Science University, Portland, OR (STE, SV, AB, JDH, DJC); School of Nursing, Oregon Health & Science University, Portland, OR (CKP); Department of Epidemiology, Human Genetics, and Environmental Science, UTHealth School of Public Health, Dallas, TX (BAB); Implementation Pathways, LLC and VA Center for Clinical Management Research, Ann Arbor, MI (LD); HealthPartners Institute, Minneapolis, MN (LIS).
MD
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Benjamin F. Crabtree
From the Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (JRH, BFC); Section of General Internal Medicine, Veterans Affairs (VA) Portland Health Care System, Portland, OR (STE); Division of General Internal Medicine and Geriatrics, Oregon Health & Science University, Portland, OR (STE); Department of Family Medicine, Oregon Health & Science University, Portland, OR (STE, SV, AB, JDH, DJC); School of Nursing, Oregon Health & Science University, Portland, OR (CKP); Department of Epidemiology, Human Genetics, and Environmental Science, UTHealth School of Public Health, Dallas, TX (BAB); Implementation Pathways, LLC and VA Center for Clinical Management Research, Ann Arbor, MI (LD); HealthPartners Institute, Minneapolis, MN (LIS).
PhD
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Deborah J. Cohen
From the Department of Family Medicine and Community Health, Research Division, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (JRH, BFC); Section of General Internal Medicine, Veterans Affairs (VA) Portland Health Care System, Portland, OR (STE); Division of General Internal Medicine and Geriatrics, Oregon Health & Science University, Portland, OR (STE); Department of Family Medicine, Oregon Health & Science University, Portland, OR (STE, SV, AB, JDH, DJC); School of Nursing, Oregon Health & Science University, Portland, OR (CKP); Department of Epidemiology, Human Genetics, and Environmental Science, UTHealth School of Public Health, Dallas, TX (BAB); Implementation Pathways, LLC and VA Center for Clinical Management Research, Ann Arbor, MI (LD); HealthPartners Institute, Minneapolis, MN (LIS).
PhD
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    Figure 1.

    Practice Survey Question About Disruptions.

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    Appendix Figure 1.

    Variation in facilitation hours by practice

Tables

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    Table 1.

    Practice Characteristics

    Characteristics
    Practice Facilitation (Mean hours [SD])18.2 (16.7)
    Practice Size/Ownership, n (%)
        Group clinician-owned248 (25.1)
        Solo clinician-owned174 (17.6)
        Hospital/HS/HMO266 (27.0)
        Safety net243 (24.6)
        Other23 (2.3)
        Missing33 (3.3)
    Practice Location, n (%)
        Large town152 (15.4)
        Rural area175 (17.7)
        Suburban72 (7.3)
        Urban588 (59.6)
    Participation in Other Demonstration Projects, n (%)
        No619 (62.7)
        Yes316 (32.0)
        Missing52 (5.3)
    Cooperative, n (%)
        Midwest136 (13.8)
        North Carolina134 (13.6)
        Northwest175 (17.7)
        New York City90 (9.1)
        Oklahoma196 (19.9)
        Southwest181 (18.3)
        Virginia75 (7.6)
    • Abbreviations: HS, Health System; HMO, Health Maintenance Organization; SD, standard deviation.

    • View popup
    Table 2.

    Disruptive Events Reported by Practices Before and During EvidenceNOW Interventions

    Before InterventionDuring Intervention
    N (%)N (%)
    Number of Disruption Types
        0485 (49.1)476 (48.2)
        1329 (33.3)318 (32.2)
        2125 (12.7)146 (14.8)
        3+48 (4.9)47 (4.8)
    Disruption Type
        Lost clinician279 (28.3)318 (32.2)
        Lost office manager/head nurse164 (16.6)212 (21.5)
        Organizational*52 (5.3)59 (6.0)
        Information system†142 (14.4)75 (7.6)
    • ↵* Includes “been purchased by or affiliated with a larger entity”; “moved to a new location”.

    • ↵† Includes “implemented a new or different electronic health record”; “changed to a new billing system”.

    • View popup
    Table 3.

    Association of Disruptive Events During Intervention with Participation in Facilitation

    Facilitation Participation (hours, 95% CI)*Difference (hours, 95% CI)P value
    One or More Disruptions PresentYesNo
    14.9 (8.3, 21.6)14.5 (9.0, 20.1)0.39 (−1.18, 1.96)0.630
    Disruption Type PresentYesNo
    Lost clinician16.4 (8.5, 24.3)15.1 (8.9, 21.6)1.28 (−1.00, 3.56)0.388
    Lost office manager/head nurse15.9 (8.7, 23.2)15.3 (8.5, 22.2)0.60 (−1.51, 2.70)0.786
    Organizational14.5 (7.1, 21.9)15.5 (8.7, 22.3)−1.01 (−2.58, 0.57)0.293
    Information system14.4 (7.1, 21.8)15.6 (8.6, 22.6)−1.17 (−3.26, 0.93)0.393
    • Abbreviation: CI, confidence interval.

    • ↵* Participation in facilitation shown as estimated mean hours, adjusted for events at baseline, practice size/ownership, practice location, participation in other demonstration projects, and Adaptive Reserve. Type III test utilized, testing if all 6 comparisons are equivalent to zero. Statistical significance defined as p-value < 0.05.

    • View popup
    Appendix Table 1.

    Descriptions of “Other” Responses to Post-Intervention Practice Survey Question About Disruptions

    “Other” Write-in Responses as CategorizedBaseline Survey (n)Post-Intervention Survey (n)Methodological Treatment
    Implemented a new or different EHR20Recoded to existing question response
    Lost one or more clinicians23Recoded to existing question response
    Lost one or more office managers or head nurses01Recoded to existing question response
    Moved to a new location02Recoded to existing question response
    New billing system22Recoded to existing question response
    Ownership change11Recoded to existing question response
    New staff2441Excluded because of varied and ambiguous nature of “staff” and lack of clarity if new staff were additions or replacements to existing staff
    Lost staff223Excluded because of varied and ambiguous nature of “staff”
    New EHR features and EHR challenges56Excluded because of small n
    Practice expansion/merger not involving ownership change1110Excluded because of small n; unclear if these are the same as existing question response
    Practice/site closed01Excluded because of small n
    Miscellaneous1517Excluded because of small n and heterogeneity of responses
    Total responses excluded from analysis64106
    • Abbreviation: EHR, electronic health record.

    • View popup
    Appendix Table 2.

    Estimated Marginal Hours and Difference in Hours (95% CI) of Participation in Practice Facilitation by Occurrence of Disruption*

    DifferenceP value
    Disruption TypesNoYes
    Lost clinician15.1 (8.9, 21.6)16.4 (8.5, 24.3)1.28 (−1.00, 3.56)0.388
    Lost office manager15.3 (8.5, 22.2)15.9 (8.7, 23.2)0.60 (−1.51, 2.70)0.786
    Purchased/new affiliation/new location15.5 (8.7, 22.3)14.5 (7.1, 21.9)−1.01 (−2.58, 0.57)0.293
    New EHR or billing software15.6 (8.6, 22.6)14.4 (7.1, 21.8)−1.17 (−3.26, 0.93)0.393
    0 events1+ events
    One or More Disruptions14.5 (9.0, 20.1)14.9 (8.3, 21.6)0.39 (−1.18, 1.96)0.630
    Number of Disruptions†0 events1 event
    15.2 (8.9, 21.5)15.5 (7.7, 23.3)0.32 (−1.93, 2.58)0.983
    0 events2 events
    15.2 (8.9, 21.5)15.7 (8.8, 22.7)0.57 (−2.35, 3.50)0.958
    0 events3+ events
    15.2 (8.9, 21.5)15.2 (8.3, 22.2)0.07 (−1.93, 2.07)1.000
    1 event2 events
    15.5 (7.7, 23.3)15.7 (8.8, 22.7)0.25 (−2.72, 3.22)0.996
    1 event3+ events
    15.5 (7.7, 23.3)15.2 (8.3, 22.2)−0.26 (−2.00, 1.48)0.981
    2 events3+ events
    15.7 (8.8, 22.7)15.2 (8.3, 22.2)−0.51 (−2.82, 1.81)0.943
    • Abbreviation: CI, confidence interval; EHR, electronic health record.

    • ↵* Estimated marginal hours are adjusted over the levels of the following variables: baseline disruptions, practice size ownership, practice location, other demonstration projects, and Adaptive Reserve.

    • ↵† Difference not included for all 6 comparisons. Also, Type III test utilized, testing if all 6 comparisons are equivalent to zero.

    • View popup
    Appendix Table 3.

    Association of Disruptions During Intervention with Participation in Practice Facilitation: Complete Model, with Imputed and Non-Imputed Results.*

    Estimate (95% CI)Imputed Estimates (95% CI)
    Intercept17.76 (13.04, 24.20)17.52 (12.50, 24.56)
    Events During Intervention
        0 eventsReferenceReference
        1 + event1.03 (0.93, 1.13)1.03 (0.92, 1.15)
    Events Before Intervention
        0 eventsReferenceReference
        1 + event before intervention1.12 (1.03, 1.22)1.12 (1.03, 1.22)
    Practice Size/Ownership
        Group clinician-ownedReferenceReference
        Solo clinician-owned0.92 (0.76, 1.12)0.92 (0.76, 1.12)
        Hospital/HS/HMO0.83 (0.71, 0.97)0.84 (0.71, 0.98)
        Safety net0.77 (0.54, 1.09)0.77 (0.53, 1.12)
        Other0.74 (0.63, 0.87)0.75 (0.62, 0.90)
        Missing0.90 (0.68, 1.19)-
    Practice Location
        Large townReferenceReference
        Rural area0.96 (0.84, 1.11)0.96 (0.83, 1.12)
        Suburban0.73 (0.54, 0.97)0.73 (0.53, 0.99)
        Urban1.10 (0.79, 1.54)1.10 (0.77, 1.58)
    Participate in Other Initiatives
        NoReferenceReference
        Yes0.99 (0.87, 1.11)0.99 (0.88, 1.13)
        Missing0.99 (0.80, 1.23)-
    Adaptive Reserve
        LowReferenceReference
        High0.99 (0.89, 1.10)1.00 (0.89, 1.12)
        Missing0.87 (0.78, 0.97)-
    • Abbreviations: CI, confidence interval; HMO, Health Maintenance Organization; HS, Health System.

    • ↵* Reference groups (the intercept) include zero follow-up disruptions, zero baseline disruptions, group clinician-owned, large town, no other demonstration projects, and low Adaptive Reserve.

    • View popup
    Appendix Table 4.

    Alternative Definitions of Participation in Practice Facilitation: Summary and Association with Any Disruption

    NameDefinitionSummaryAssociation With Practice Event* (95% CI)
    Consistency of Facilitation Visits, Mean (SD)Months during intervention period with an in-person PF visit7.61 (3.22)0.86 (0.59, 1.31)
    Length of Facilitation Visit, Mean (SD)Total hours of facilitation/total number of in-person PF visits1.63 (0.89)1.00 (0.94, 1.08)
    Dose Categories, N (%)0.94 (0.74, 1.18)
    Low: <10 hours384 (38.9)
    Short: ≥10 -<50 hours, <10 months188 (19.0)
    Consistent: ≥10-<50 hours, ≥10 months351 (35.6)
    High: ≥50 hours64 (6.5)
    • Abbreviations: CI, confidence interval; PF, practice facilitation; SD, standard deviation.

    • ↵* For the participation in practice facilitation outcomes, consistency of practice facilitation and length of practice facilitation visit, a Poisson regression and Gamma regression models were implemented, exploring the effect of any disruption against no disruptions. For dose categories, we used a multinomial logistic regression. Incident rate/odds ratios (exponentiated coefficients) and 95% CIs were reported.

    • For months with an in-person encounter, we see a 14% decrease in practice facilitation if a practice had a disruption versus no disruptions. For length of practice facilitation, we see no effect if a practice had a disruption versus no disruptions. For the pooled dose, there is a 6% decrease in the odds of a disruption occurring for a Low, Short, or Consistent dose versus a High dose.

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The Effects of Major Disruptions on Practice Participation in Facilitation During a Primary Care Quality Improvement Initiative
Jennifer R. Hemler, Samuel T. Edwards, Steele Valenzuela, Andrea Baron, Jennifer D. Hall, Cynthia K. Perry, Bijal A. Balasubramanian, Laura Damschroder, Leif I. Solberg, Benjamin F. Crabtree, Deborah J. Cohen
The Journal of the American Board of Family Medicine Jan 2022, 35 (1) 124-139; DOI: 10.3122/jabfm.2022.01.210205

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The Effects of Major Disruptions on Practice Participation in Facilitation During a Primary Care Quality Improvement Initiative
Jennifer R. Hemler, Samuel T. Edwards, Steele Valenzuela, Andrea Baron, Jennifer D. Hall, Cynthia K. Perry, Bijal A. Balasubramanian, Laura Damschroder, Leif I. Solberg, Benjamin F. Crabtree, Deborah J. Cohen
The Journal of the American Board of Family Medicine Jan 2022, 35 (1) 124-139; DOI: 10.3122/jabfm.2022.01.210205
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