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Research ArticleOriginal Research

Does Ownership Make a Difference in Primary Care Practice?

Stephan Lindner, Leif I. Solberg, William L. Miller, Bijal A. Balasubramanian, Miguel Marino, K. John McConnell, Samuel T. Edwards, Kurt C. Stange, Rachel J. Springer and Deborah J. Cohen
The Journal of the American Board of Family Medicine May 2019, 32 (3) 398-407; DOI: https://doi.org/10.3122/jabfm.2019.03.180271
Stephan Lindner
From Center for Health Systems Effectiveness & Department of Emergency Medicine, Oregon Health & Science University, Portland, (SL, KJM); School of Public Health, Oregon Health & Science University, Portland State University, Portland (SL, MM, KJM); Department of Emergency Medicine, Oregon Health & Science University, Portland (SL, KJM); HealthPartners Institute, Minneapolis, Minnesota (LIS); Department of Family Medicine, Lehigh Valley Health Network, Allentown, PA (WLM); Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (BAB); Department of Family Medicine, Oregon Health & Science University, Portland, (MM STE, RJS, DJC); Section of General Internal Medicine, Veterans Affairs Portland Health Care System, Portland, OR (STE); Center for Community Health Integration, Departments of Family Medicine & Community Health, Population & Quantitative Health Sciences, and Sociology, Case Western Reserve University, Cleveland, OH (KCS).
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Leif I. Solberg
From Center for Health Systems Effectiveness & Department of Emergency Medicine, Oregon Health & Science University, Portland, (SL, KJM); School of Public Health, Oregon Health & Science University, Portland State University, Portland (SL, MM, KJM); Department of Emergency Medicine, Oregon Health & Science University, Portland (SL, KJM); HealthPartners Institute, Minneapolis, Minnesota (LIS); Department of Family Medicine, Lehigh Valley Health Network, Allentown, PA (WLM); Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (BAB); Department of Family Medicine, Oregon Health & Science University, Portland, (MM STE, RJS, DJC); Section of General Internal Medicine, Veterans Affairs Portland Health Care System, Portland, OR (STE); Center for Community Health Integration, Departments of Family Medicine & Community Health, Population & Quantitative Health Sciences, and Sociology, Case Western Reserve University, Cleveland, OH (KCS).
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William L. Miller
From Center for Health Systems Effectiveness & Department of Emergency Medicine, Oregon Health & Science University, Portland, (SL, KJM); School of Public Health, Oregon Health & Science University, Portland State University, Portland (SL, MM, KJM); Department of Emergency Medicine, Oregon Health & Science University, Portland (SL, KJM); HealthPartners Institute, Minneapolis, Minnesota (LIS); Department of Family Medicine, Lehigh Valley Health Network, Allentown, PA (WLM); Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (BAB); Department of Family Medicine, Oregon Health & Science University, Portland, (MM STE, RJS, DJC); Section of General Internal Medicine, Veterans Affairs Portland Health Care System, Portland, OR (STE); Center for Community Health Integration, Departments of Family Medicine & Community Health, Population & Quantitative Health Sciences, and Sociology, Case Western Reserve University, Cleveland, OH (KCS).
MD, MA
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Bijal A. Balasubramanian
From Center for Health Systems Effectiveness & Department of Emergency Medicine, Oregon Health & Science University, Portland, (SL, KJM); School of Public Health, Oregon Health & Science University, Portland State University, Portland (SL, MM, KJM); Department of Emergency Medicine, Oregon Health & Science University, Portland (SL, KJM); HealthPartners Institute, Minneapolis, Minnesota (LIS); Department of Family Medicine, Lehigh Valley Health Network, Allentown, PA (WLM); Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (BAB); Department of Family Medicine, Oregon Health & Science University, Portland, (MM STE, RJS, DJC); Section of General Internal Medicine, Veterans Affairs Portland Health Care System, Portland, OR (STE); Center for Community Health Integration, Departments of Family Medicine & Community Health, Population & Quantitative Health Sciences, and Sociology, Case Western Reserve University, Cleveland, OH (KCS).
MBBS, PhD
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Miguel Marino
From Center for Health Systems Effectiveness & Department of Emergency Medicine, Oregon Health & Science University, Portland, (SL, KJM); School of Public Health, Oregon Health & Science University, Portland State University, Portland (SL, MM, KJM); Department of Emergency Medicine, Oregon Health & Science University, Portland (SL, KJM); HealthPartners Institute, Minneapolis, Minnesota (LIS); Department of Family Medicine, Lehigh Valley Health Network, Allentown, PA (WLM); Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (BAB); Department of Family Medicine, Oregon Health & Science University, Portland, (MM STE, RJS, DJC); Section of General Internal Medicine, Veterans Affairs Portland Health Care System, Portland, OR (STE); Center for Community Health Integration, Departments of Family Medicine & Community Health, Population & Quantitative Health Sciences, and Sociology, Case Western Reserve University, Cleveland, OH (KCS).
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K. John McConnell
From Center for Health Systems Effectiveness & Department of Emergency Medicine, Oregon Health & Science University, Portland, (SL, KJM); School of Public Health, Oregon Health & Science University, Portland State University, Portland (SL, MM, KJM); Department of Emergency Medicine, Oregon Health & Science University, Portland (SL, KJM); HealthPartners Institute, Minneapolis, Minnesota (LIS); Department of Family Medicine, Lehigh Valley Health Network, Allentown, PA (WLM); Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (BAB); Department of Family Medicine, Oregon Health & Science University, Portland, (MM STE, RJS, DJC); Section of General Internal Medicine, Veterans Affairs Portland Health Care System, Portland, OR (STE); Center for Community Health Integration, Departments of Family Medicine & Community Health, Population & Quantitative Health Sciences, and Sociology, Case Western Reserve University, Cleveland, OH (KCS).
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Samuel T. Edwards
From Center for Health Systems Effectiveness & Department of Emergency Medicine, Oregon Health & Science University, Portland, (SL, KJM); School of Public Health, Oregon Health & Science University, Portland State University, Portland (SL, MM, KJM); Department of Emergency Medicine, Oregon Health & Science University, Portland (SL, KJM); HealthPartners Institute, Minneapolis, Minnesota (LIS); Department of Family Medicine, Lehigh Valley Health Network, Allentown, PA (WLM); Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (BAB); Department of Family Medicine, Oregon Health & Science University, Portland, (MM STE, RJS, DJC); Section of General Internal Medicine, Veterans Affairs Portland Health Care System, Portland, OR (STE); Center for Community Health Integration, Departments of Family Medicine & Community Health, Population & Quantitative Health Sciences, and Sociology, Case Western Reserve University, Cleveland, OH (KCS).
MD
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Kurt C. Stange
From Center for Health Systems Effectiveness & Department of Emergency Medicine, Oregon Health & Science University, Portland, (SL, KJM); School of Public Health, Oregon Health & Science University, Portland State University, Portland (SL, MM, KJM); Department of Emergency Medicine, Oregon Health & Science University, Portland (SL, KJM); HealthPartners Institute, Minneapolis, Minnesota (LIS); Department of Family Medicine, Lehigh Valley Health Network, Allentown, PA (WLM); Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (BAB); Department of Family Medicine, Oregon Health & Science University, Portland, (MM STE, RJS, DJC); Section of General Internal Medicine, Veterans Affairs Portland Health Care System, Portland, OR (STE); Center for Community Health Integration, Departments of Family Medicine & Community Health, Population & Quantitative Health Sciences, and Sociology, Case Western Reserve University, Cleveland, OH (KCS).
MD, PhD
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Rachel J. Springer
From Center for Health Systems Effectiveness & Department of Emergency Medicine, Oregon Health & Science University, Portland, (SL, KJM); School of Public Health, Oregon Health & Science University, Portland State University, Portland (SL, MM, KJM); Department of Emergency Medicine, Oregon Health & Science University, Portland (SL, KJM); HealthPartners Institute, Minneapolis, Minnesota (LIS); Department of Family Medicine, Lehigh Valley Health Network, Allentown, PA (WLM); Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (BAB); Department of Family Medicine, Oregon Health & Science University, Portland, (MM STE, RJS, DJC); Section of General Internal Medicine, Veterans Affairs Portland Health Care System, Portland, OR (STE); Center for Community Health Integration, Departments of Family Medicine & Community Health, Population & Quantitative Health Sciences, and Sociology, Case Western Reserve University, Cleveland, OH (KCS).
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Deborah J. Cohen
From Center for Health Systems Effectiveness & Department of Emergency Medicine, Oregon Health & Science University, Portland, (SL, KJM); School of Public Health, Oregon Health & Science University, Portland State University, Portland (SL, MM, KJM); Department of Emergency Medicine, Oregon Health & Science University, Portland (SL, KJM); HealthPartners Institute, Minneapolis, Minnesota (LIS); Department of Family Medicine, Lehigh Valley Health Network, Allentown, PA (WLM); Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health in Dallas, Dallas, TX (BAB); Department of Family Medicine, Oregon Health & Science University, Portland, (MM STE, RJS, DJC); Section of General Internal Medicine, Veterans Affairs Portland Health Care System, Portland, OR (STE); Center for Community Health Integration, Departments of Family Medicine & Community Health, Population & Quantitative Health Sciences, and Sociology, Case Western Reserve University, Cleveland, OH (KCS).
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Article Figures & Data

Tables

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    Table 1.

    Practice and Patient Characteristics by Ownership Type*

    MeasureObservations†Physician-Owned PracticesHealth System/Medical Group PracticesFQHC Practices
    ValueValueDifference (95% CI)P ValueValueDifference (95% CI)P Value
    Practice demographics
        Ownership (Values showing %)98953.225.621.2
        Solo practice (Values showing %)96645.08.136.9 (−54.4 to −16.1)<.00112.8−32.2 (−56.4 to −9.1).009
        Urban practice location (Values showing %)98974.957.317.6 (−48.9 to 1.0).1646.7−28.2 (−43.3 to −9.0).002
        Multispecialty practice (Values showing %)95717.632.414.6 (10.2 to 21.1)<.00156.338.7 (28.3 to 53.0)<.001
        Less than 5 years under current ownership (Values showing %)88412.441.028.6 (21.1 to 37.1)<.00116.94.5 (−4.9 to 17.3).45
        At least one major change in last year (Values showing %)94943.165.422.3 (6.0 to 39.4).0172.129.0 (13.3 to 47.6).001
        Less than 5 years of EHR experience (Values showing %)86933.346.313.0 (−4.1 to 36.7).2325.47.9 (−24.2 to 19.1).47
    Practice patient demographics
        Patients receiving Medicaid (Values showing %)88428.220.28.0 (−15.9 to 1.6).0840.412.2 (0.8 to 22.9).03
        Patients receiving Medicare (Values showing %)88523.028.75.7 (1.4 to 11.2).0215.37.7 (−12.9 to −4.0)<.001
        Non-white patients (Values showing %)85145.242.42.8 (−26.5 to 13.0).7735.010.2 (−24.1 to 7.0).2
        Hispanic/Latino patients (Values showing %)82514.39.35.0 (−13.1 to 22.).2431.817.5 (1.2 to 30.3).04
    Other external and internal factors
        Have PCMH recognition (Values showing %)92639.342.22.9 (−17.0 to 16.7).7366.527.2 (4.0 to 46.0).01
        Participate in other demonstration programs (Values showing %)90833.623.310.3 (−29.3 to 4.4).2235.21.6 (−14.3 to 23.2).87
        Part of an ACO (Values showing %)93741.756.614.9 (−13.1 to 32.6).2137.2−4.5 (−25.6 to 14.8).66
        Have stage 1 and 2 certified EHR MU (Values showing %)87472.966.86.1 (−22.4 to 9.5).4862.3−4.5 (−25.6 to 14.8).66
        Burnout‡ (Values showing %)93014.719.64.9 (−0.1 to 11.9).1119.44.7 (−4.2 to 10.1).19
        No. of practices (Values showing numbers)989526253210
    • ↵* Based on practice surveys and practice member surveys of practices participating in EvidenceNOW, collected between October 2015 and April 2017.

    • ↵† The column “Observations” shows the number of practices with an observed value for the respective measure. Urban practice location is defined as percent of practices in urban locations based on Rural-Urban Commuting Areas using 2010 Census data. A major change includes the following: have moved to a new location, lost one or more clinicians, lost one or more office managers or head nurses, been purchased by or affiliated with a larger organization, new billing system, or another change specified by the practice. Demonstration programs include State Innovation Models Initiative, Comprehensive Primary Care Initiative, Transforming Clinical Practice Initiative—Support and Alignment Network, Community Health Worker training program, Blue Cross/Blue Shield patient-centered medical home program, Association of State and Territorial Health Officials's Million Hearts State Learning Collaborative; Million Hearts: Cardiovascular Disease Risk Reduction Model, or another program identified by the practice.

    • ↵‡ The percent burned out denotes the percent of practice members who responded affirmative to one of the following items: level 3, I am definitely burning out and have one or more symptoms of burnout, such as physical and emotional exhaustion; level 4, the symptoms of burnout that I'm experiencing won't go away; I think about frustrations at work a lot; level 5, I feel completely burned out and often wonder if I can go on practicing; I am at the point where I may need some changes.

    • CI, confidential interval; FQHC, Federally Qualified Health Center; EHR, electronic health records; PCMH, patient-centered medical home; MU, meaningful use; ACO, Accountable Care Organization.

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    Table 2.

    Quality Improvement Process Measures by Ownership Type*

    MeasureObservations†Physician-Owned PracticesHealth System/Medical Group PracticesFQHC Practices
    ValueValueDifference (95% CI)P ValueValueDifference (95% CI)P Value
    Quality-aligned care delivery processes
        Discuss clinical quality data (Values showing %)98927.944.316.4 (4.2 to 24.6).00156.728.8 (16.0 to 41.6)<.001
        Have someone configuring/writing quality reports (Values showing %)86864.279.114.9 (2.7 to 25.4).0191.527.3 (14.2 to 38.9)<.001
        Produced CQM reports in last six months‡ (Values showing %)83269.477.88.4 (−15.9 to 22.4).4394.324.9 (9.3 to 40.0).002
        Use at least one registry§ (Values showing %)94061.167.56.4 (−16.5 to 25.1).5983.122.0 (14.2 to 32.9)<.001
        Use of empanelment (Values showing %)92973.188.014.9 (6.2 to 20.8)<.00181.88.7 (1.6 to 18.9).04
        CVD prevention guidelines included in EHR prompts or standing orders (Values showing %)94660.265.35.1 (−14.3 to 21.9).6176.616.4 (7.7 to 28.0).002
        CVD management guidelines included in EHR prompts or standing orders (Values showing %)94657.061.54.5 (−15.4 to 21.5).6670.713.7 (3.3 to 27.3).03
        Score for CVD improvement being a priority is 8 to 10 out of 10 (Values showing %)92965.256.78.5 (−20.2 to 3.8).1660.25.0 (−22.9 to 12.0).57
    Change management processes
        CPCQ strategies score‖ (Values showing mean)78510.28.61.6 (−8.5 to 2.8)>.998.91.3 (−4.1 to 1.4)>.99
        Number of practices (Values showing numbers)989526253210
    • ↵* Based on practice surveys and practice members surveys of practices participating in EvidenceNOW, collected between October 2015 and April 2017).

    • ↵† The column “Observations” shows the number of practices with an observed value for the respective measure.

    • ↵‡ CQM reports refers to the following clinical quality measures: percentage of patients aged 18 years and older with ischemic vascular disease with documented use of aspirin or other antithrombotic (NQF 0068), percentage of patients aged 18 through 85 years of age who had a diagnosis of hypertension and whose blood pressure was adequately controlled (<140/90) during the measurement year (NQF 0018), and percentage of patients aged 18 years or older who were screened about tobacco use one or more times within 24 months and who received cessation counseling intervention if identified as a tobacco user (NQF 0028).

    • ↵§ Use of registry refers to the following patients: ischemic vascular disease, hypertension, high cholesterol, diabetes, prevention services, and high risk (high use) patients.

    • ↵‖ The CPCQ score is based on fourteen measures of strategies to improve cardiovascular preventive care; see text and Appendix A for details.

    • FQHC, federally qualified health center; CI, confidential interval; CQM, clinical quality measures; CVD, cardiovascular disease; EHR, electronic health records; CPCQ, Change Process Capability questionnaire.

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    Table 3.

    Cardiovascular Disease Prevention Clinical Quality Measures by Ownership Type*

    MeasureObservations†Physician-Owned PracticesHealth System/Medical Group PracticesFQHC Practices
    ValueValueDifference (95% CI)P valueValueDifference (95% CI)P value
    Aspirin (Values showing %)88657.567.510.0 (0.2 to 21.5).0859.11.6 (−8.2 to 10.5).73
    Blood pressure (Values showing %)89264.060.63.4 (−7.3 to 2.0).1564.30.3 (−6.4 to 9.2).94
    Cholesterol (Values showing %)67958.258.20.1 (−8.7 to 14.3).9955.23.0 (−7.9 to 4.7).38
    Smoking (Values showing %)86951.067.316.3 (1.8 to 24.2).00469.318.3 (1.1 to 26.7).004
    Number of practices (Values showing numbers)989526253210
    • ↵* Based on practice surveys of practices participating in EvidenceNOW, collected between October 2015 and April 2017. See Appendix A for a definition of the four cardiovascular disease prevention clinical quality measures.

    • ↵† The column “Observations” shows the number of practices with an observed value for the respective measure.

    • CI, confidential interval; FQHC, federally qualified health center.

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    Appendix A:

    Description and Number of Missing Values for Variables Used in this Analysis

    MeasureDescriptionMissing Values*
    Practice characteristics
        OwnershipThe survey question was “Which of the following best describes your practice's ownership? (Check all that apply)” The following categories were possible responses: clinician-owned solo or group practice; hospital/health system owned; Health Maintenance Organization (e.g., Kaiser Permanente); Federally Qualified Health Center or look-alike; non-federal-government clinic (e.g., state, county, city, public health clinic, etc.); academic health center/faculty practice; federal (military, Veterans Administration, Department of Defense); Rural Health Clinic; Indian Health Service; other (please specify).0 (526)/0 (253)/0 (210)
        Solo practice (%)Percent of practices with one clinician.10 (526)/6 (253)/7 (210)
        Urban practice location (%)Percent of practices in urban locations based on Rural-Urban Commuting Areas using 2010 Census data.0 (526)/0 (253)/0 (210)
        Multispecialty practice (%)Percent of practices with multispecialty.19 (526)/9 (253)/4(210)
        Less than 5 years under current ownership (%)Percent of practices with less than 5 years under current ownership.43 (526)/41 (253)/21 (210)
        At least one major change in last year (%)Percent of practices with at least one major change in the last year. A major change includes the following: have moved to a new location; lost one or more clinicians; lost one or more office managers or head nurses; been purchased by or affiliated with a larger organization; new billing system; or another change specified by the practice.15 (526)/19 (253)/6 (21
        Have PCMH recognition (%)Percent of practices recognized or accredited as patient-centered medical home.40 (526)/16 (253)/7 (210)
        Participate in other demonstration programs (%)Percent of practices that participated in the past 12 months in one of the following payment or quality demonstration programs: State Innovation Models Initiative, Comprehensive Primary Care Initiative, Transforming Clinical Practice Initiative—Support and Alignment Network, Community Health Worker training program, BC/BS PCMH.38 (526)/26 (253)/17 (210)
    Collaborative; Million Hearts: Cardiovascular Disease Risk Reduction Model; or another program identified by the practice.
        Part of an ACO (%)Percent of practices that are part of an ACO.23 (526)/18 (253)/11 (210)
        Burnout (%)Percent of practice members burned out. Practice member with a score of 3 or higher for the following question are considered burned out: Using your own definition of burnout—please indicate which of the following statements best describes how you feel about your situation at work (select only one response): 1: I enjoy my work. I have no symptoms of burnout.; 2: Occasionally I am under stress, and I don't always have as much energy as I once did, but I don't feel burned out.; 3: I am definitely burning out and have one or more symptoms of burnout, such as physical and emotional exhaustion.; 4: The symptoms of burnout that I'm experiencing won't go away. I think about frustrations at work a lot.; 5: I feel completely burned out and often wonder if I can go on practicing. I am at the point where I may need some changes.29 (526)/7 (253)/23 (210)
        Less than 5 years if EHR experience (%)Average number of years of years a practice has used an EHR.41 (526)/48 (253)/21 (210)
        Have stage 1 and 2 certified EHR MU (%)Percent of practices those EHR is stage 1 and 2 certified meaningful use.43 (526)/45 (253)/27 (210)
        Patients receiving Medicaid (%)Percent of patients receiving Medicaid, including those eligible for both Medicaid and Medicare.48 (526)/37 (253)/20 (210)
        Patients receiving Medicare (%)Percent of patients receiving Medicare.48 (523)/37 (253)/17 (210)
        Non-white patients (%)Percent of patients classified as non-white, which includes black/African-American; American Indian or Alaska Native; Asian; Native Hawaiian or other Pacific Islander; some other race/mixed race.78 (526)/43 (253)/19 (210)
    Hispanic/Latino patients (%)Percent of patients classified as Hispanic or Latino.100 (526)/45 (253)/19 (210)
    Quality improvement process measures
        Discuss clinical quality data (%)Percent of practices where people discuss data or reports about clinical quality from health plans or other external entities during meetings. Possible responses include: never, infrequently, often, not applicable/solo practice, don't know.0 (526)/0 (253)/0 (210)
        Have someone configuring/writing quality reports (%)Percent of practices that have someone who can configure or write quality reports from the EHR.57 (526) 42 / (253)/22 (210)
        Produced CQM reports in last 6 months (%)Percent of practices that produced any CQM report in the last 6 months regarding the following clinical quality measures: percentage of patients aged 18 years and older with ischemic vascular disease with documented use of aspirin or other antithrombotic (NQF 0068); percentage of patients aged 18 through 85 years of age who had a diagnosis of hypertension and whose blood pressure was adequately controlled (<140/90) during the measurement year (NQF 0018); percentage of patients aged 18 years or older who were screened about tobacco use one or more times within 24 months AND who received cessation counseling intervention if identified as a tobacco user (NQF 0028).91 (526)/50 (253)/16 (210)
        Use at least one registry (%)Percent of practices using at least one registry for the following categories of patients: ischemic vascular disease, hypertension, high cholesterol, diabetes, prevention services, and high risk (high use) patients.27 (526)/13 (253)/9 (210)
        Use of empanelment (%)Percent of practices for which clinicians have their own panel of patients for whom they are responsible.36 (526)/12 (253)/12 (210)
        CVD prevention guidelines included in EHR prompts or standing orders (%)Percent of practices using level 3 or 4 of cardiovascular disease prevention guidelines. Levels are as follows: practice does not follow specific guidelines (level 1), guidelines are posted or clinicians have agreed to use them (level 2), practice uses EHR provider guideline-based prompts and reminders (level 3), and practice uses standing orders (level 4).24 (526)/14 (253)/5 (210)
        CVD management guidelines included in EHR prompts or standing orders (%)Percent of practices using level 3 or 4 of cardiovascular disease management guidelines. Levels are as follows: practice does not follow specific guidelines (level 1), guidelines are posted or clinicians have agreed to use them (level 2), practice uses EHR provider guideline-based prompts and reminders (level 3), and practice uses standing orders (level 4).24 (526)/14 (253)/5 (210)
        Score for CVD improvement being a priority is 8 to 10 out of 10 (%)Percent of practices reporting that improving cardiovascular disease preventing care over the next year is a priority of 8 or higher on a scale of 1 to 10, with 0 = no priority and 10 = highest priority.43 (526)/8 (253)/9 (210)
        CPCQ strategies score (mean)Mean CPCQ score. The score is based on fourteen measures of strategies to improve cardiovascular preventive care. A practice can provide the following answers to each of these measures: strongly disagree (−2 points), somewhat disagree (−1), neither agree nor disagree (0 points), somewhat agree (1 point), strongly agree (2 points), and NA. The points are summed up, for a range from −28 to 28. The 14 measures are (1) providing information and skills-training; (2) using opinion leaders, role modeling, or other vehicles to encourage support for changes; (3) changing or creating systems in the practice that make it easier to provide high quality care; (4) removal or reduction of barriers to better quality of care; (5) using teams focused on accomplishing the change process for improved care; (6) delegating to non-clinician staff the responsibility to carry out aspects of care that are normally the responsibility of physicians; (7) providing to those who are charged with implementing improved care the power to authorize and make the desired changes; (8) periodic measurement of care quality for assessing compliance with any new approach to care; (9) reporting measurements of practice performance on cardiovascular disease prevention measures (such as aspirin for patients at risk for ischemic vascular disease) for comparison with their peers; (10) setting goals and benchmarking rates of performance quality on cardiovascular disease prevention measures at least yearly; (11) customizing the implementation of cardiovascular disease prevention care changes to the practice; (12) using rapid cycling, piloting, pre-testing, or other vehicles for reducing the risk of negative results for introducing organization-wide change in care; (13) deliberately designing care improvements so as to make clinician participation less work than before; (14) and deliberately designing care improvements to make the care process more beneficial to the patient.132 (526)/48 (253)/24 (210)
    Cardiovascular disease prevention clinical quality measures
        Aspirin (%)Percentage of patients 18 years of age and older who were discharged alive for acute myocardial infarction, coronary artery bypass graft, or percutaneous coronary interventions in the 12 months prior to the measurement period, or who had an active diagnosis of ischemic vascular disease during the measurement period, and who had documentation of use of aspirin or another antithrombotic during the measurement period.55 (526)/33 (253)/15 (210)
        Blood pressure (%)Percentage of patients 18 to 85 years of age who had a diagnosis of hypertension and whose blood pressure was adequately controlled (<140/90 mm Hg) during the measurement period.54 (526)/30 (253)/13 (210)
        Cholesterol (%)Percentage of high-risk adult patients aged [mteq]21 years who were previously diagnosed with or currently have an active diagnosis of clinical atherosclerotic cardiovascular disease; OR adult patients aged [mteq]21 years with a fasting or direct low-density lipoprotein cholesterol level [mteq]190 mg/dL; OR patients aged 40 to 75 years with a diagnosis of diabetes with a fasting or direct low-density lipoprotein cholesterol level of 70 to 189 mg/dL; who were prescribed or are already on statin medication therapy during the measurement year.134 (526)/93 (253)/83 (210)
        Smoking (%)Percentage of patients aged 18 years and older who were screened for tobacco use one or more times within 24 months AND who received cessation counseling intervention if identified as a tobacco user.61 (526)/44 (253)/15 (210)
    • ↵* The numbers show missing values and, in parentheses, number of practices, for physician-owned/health system and medical group/federally qualified health center practices, respectively. For instance, 10 out of 526 physician-owned, 6 out of 253 health system and 7 out of 210 Federally Qualified Health Centers (FQHC) practices had missing values regarding their solo practice status.

    • CQM, clinical quality measures; CVD, cardiovascular disease; EHR, electronic health records; CPCQ, Change Process Capability questionnaire; BC/BS PCMH, Blue Cross/Blue Shield patient-centered medical home; MU, meaningful use; ACO, Accountable Care Organization; NA, Not applicable.

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The Journal of the American Board of Family     Medicine: 32 (3)
The Journal of the American Board of Family Medicine
Vol. 32, Issue 3
May-June 2019
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Does Ownership Make a Difference in Primary Care Practice?
Stephan Lindner, Leif I. Solberg, William L. Miller, Bijal A. Balasubramanian, Miguel Marino, K. John McConnell, Samuel T. Edwards, Kurt C. Stange, Rachel J. Springer, Deborah J. Cohen
The Journal of the American Board of Family Medicine May 2019, 32 (3) 398-407; DOI: 10.3122/jabfm.2019.03.180271

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Does Ownership Make a Difference in Primary Care Practice?
Stephan Lindner, Leif I. Solberg, William L. Miller, Bijal A. Balasubramanian, Miguel Marino, K. John McConnell, Samuel T. Edwards, Kurt C. Stange, Rachel J. Springer, Deborah J. Cohen
The Journal of the American Board of Family Medicine May 2019, 32 (3) 398-407; DOI: 10.3122/jabfm.2019.03.180271
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More in this TOC Section

  • Identifying and Addressing Social Determinants of Health with an Electronic Health Record
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  • A Pilot Comparison of Clinical Data Collection Methods Using Paper, Electronic Health Record Prompt, and a Smartphone Application
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Keywords

  • Cardiovascular Diseases
  • Cross Sectional Analysis
  • Delivery of Health Care
  • Group Practice
  • Ownership
  • Primary Health Care
  • Process Measures
  • Quality Improvement

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