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Research ArticleOriginal Research

Impact of Electronic Health Record Clinical Decision Support on Diabetes Care: A Randomized Trial

Patrick J. O’Connor, JoAnn M. Sperl-Hillen, William A. Rush, Paul E. Johnson, Gerald H. Amundson, Stephen E. Asche, Heidi L. Ekstrom and Todd P. Gilmer
The Annals of Family Medicine January 2011, 9 (1) 12-21; DOI: https://doi.org/10.1370/afm.1196
Patrick J. O’Connor
MD, MPH
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JoAnn M. Sperl-Hillen
MD
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William A. Rush
PhD
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Paul E. Johnson
PhD
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Gerald H. Amundson
BS
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Stephen E. Asche
MA
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Heidi L. Ekstrom
MA
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Todd P. Gilmer
PhD
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  • Figure 1.
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    Figure 1.

    Example of Diabetes Wizard.

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    Figure 2.

    Diagram illustrating randomization and disposition of clinics, primary care physicians, and diabetes patients.

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    Figure 3.

    Diabetes Wizard use during and after intervention for the intervention group only.

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    Table 1.

    Characteristics of Study Physicians and Diabetes Patients Linked to Those Study Physicians at Intervention and Control Clinics

    VariableIntervention ClinicControl ClinicP Valuea
    a P value derived from independent samples t test or Pearson χ2.
    Patients
    Total No.1,1941,362
        Mean age (SD), y57.0 (10.7)57.5 (10.1).23
        Female, %46.754.5<.001
        White race, %82.870.6<.001
        Coronary heart disease preintervention, %12.112.6.75
        Congestive heart failure preintervention, %2.93.6.35
        Preintervention first glycated A1c, mean (SD) [median], %7.4 (1.68) [7.0]7.4 (1.67) [7.0].47
        Preintervention first systolic blood pressure, mean (SD) [median], mm Hg127.3 (17.4) [126]126.8 (17.1) [125].40
        Preintervention first diastolic blood pressure, mean (SD) [median], mm Hg74.5 (10.9) [74]73.5 (10.5) [74].023
        Preintervention first LDL cholesterol value, mean (SD) [median], mg/dL99.4 (34.5) [94]95.9 (33.8) [90].019
    Primary care physicians
    Total No.2020
        Age, mean (SD), y49.2 (9.9)50.2 (7.3).71
        Family physician,%80.045.0.02
        Female physician, %55.050.0.75
        Diabetes patients per physician, mean (SD), No.43.7 (17.3)55.8 (30.2).13
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    Table 2.

    Rates and Counts of Diabetes Encounters, Glycated Hemoglobin Tests, Low-Density Lipoprotein Cholesterol Tests, and Blood Pressure Measures, Comparing Intervention and Control Clinics in the Preintervention and Postintervention Periods

    Intervention ClinicControl Clinic
    VariablePre-intervention 12 moPost-intervention 12 moChangePre-intervention 12 moPost-intervention 12 moChangeIntervention EffectaP Valueb
    Hemoglobin A1c=glycated hemoglobin; CI=confidence interval; LDL = low-density lipoprotein.
    a The intervention effect column illustrates the differential amount of change in the intervention arm relative to the control arm comparing pre- with postintervention.
    b P value associated with the time × condition term in a generalized linear mixed model with repeated time measurements, study arm, and their interaction.
    c P <.001.
    d P <.01.
    e P <.05.
    Patients with 1 or more encounters or tests, proportion (95% CI)
        Diabetes encounters.850 (.820–.876).949 (.932–.962).099c.875 (.849–.897).956 (.941–.967).081c.018.78
        Hemoglobin A1c tests.829 (.788–.864).940 (.919–.956).112c.858 (.822–.888).929 (.906–.947).071c.041.045
        Blood pressure measurements.986 (.977–.991).988 (.980–.993).003.986 (.978–.991).981 (.971–.987)−.005.008.28
        LDL cholesterol tests.819 (.779–.854).871 (.838–.899).052d.846 (.809–.876).865 (.831–.892).019.033.14
    Encounters or tests done per patient, mean (95% CI), No.
        Diabetes encounters3.9 (3.6–4.4)4.5 (4.1–4.9)0.49d4.4 (4.1–4.8)5.1 (4.7–5.5)0.68c−0.20.33
        Hemoglobin A1c tests2.0 (1.8–2.1)2.4 (2.2–2.5)0.41c2.0 (1.8–2.2)2.3 (2.2–2.5)0.31c0.11.09
        LDL tests1.4 (1.2–1.5)1.5 (1.4–1.7)0.17d1.4 (1.3–1.6)1.5 (1.4–1.6)0.080.09.09
    • View popup
    Table 3.

    Changes and Proportion of Adult Diabetes Patients at Goal on Glycated Hemoglobin, Blood Pressure, and LDL Cholesterol Measures Among Intervention and Control Group Primary Care Physicians and Clinics in the Preintervention (Baseline) and Postintervention Periods

    Intervention ClinicControl Clinic
    VariableNo.BaselinePost-interventionChangeBaselinePost-interventionChangeIntervention EffectaP Valueb
    DBP = diastolic blood pressure; hemoglobin A1c=glycated hemoglobin; LDL=low-density lipoprotein; SBP=systolic blood pressure; SE=standard error.
    a The intervention effect column illustrates the differential amount of change in the intervention arm relative to the control arm comparing before and after the intervention.
    b For mean value analysis, P value associated with the time × condition term in a general linear mixed model with repeated time measurements, study arm, and their interaction. For proportion at goal analysis, P value associated with study arm.
    c P <.001.
    Hemoglobin A1c, mean (SE), %1,0928.5 (0.09)7.9 (0.09)−0.58c8.4 (0.08)8.1 (0.08)−0.32c−0.26.01
    Hemoglobin A1c <7%, % (SE)1,14478.4 (2.0)79.2 (2.0)−0.8.80
    SBP, mean (SE), mm Hg894141.3 (0.70)130.5 (0.70)−10.8c141.6 (0.69)131.5 (0.69)−10.1c−0.70.56
    SBP <130 mm Hg, % (SE)1,50680.2 (1.6)75.1 (1.6)5.1.03
    DBP, mean (SE), mm Hg73185.1 (0.52)76.8 (0.52)−8.3c84.6 (0.51)77.1 (0.51)−7.5c−0.82.38
    DBP <80 mm Hg, % (SE)1,66985.6 (1.4)81.7 (1.5)3.9.07
    LDL cholesterol, mean (SE), mg/dL868122.3 (1.7)97.9 (1.8)−24.4c124.1 (1.7)98.3 (1.8)−25.8c1.37.62
    LDL cholesterol <100 mg/dL (or <70 mg/dL if heart disease), % (SE)1,36285.2 (1.6)83.9 (1.5)1.4.53

Additional Files

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  • The Article in Brief

    Impact of Electronic Health Record Clinical Decision Support on Diabetes Care: A Randomized Trial

    Patrick J. O'Connor , and colleagues

    Background This study tests a diabetes decision support tool embedded in an electronic health record. The tool offers doctors drug-specific treatment suggestions based on the patient�s current treatment, clinical goals, other medical conditions, and kidney and liver functions.

    What This Study Found Compared with patients in the control group, patients in the intervention group had significantly better hemoglobin A1c values, better maintenance of systolic blood pressure control, and borderline better maintenance of diastolic blood pressure control. Participating doctors were highly satisfied with the intervention, and many continued using the technology after the study ended.

    Implications

    • The authors conclude that, in the coming era of genomic medicine and personalized chronic disease care, clinical support decision strategies like the one tested in this trial, capable of simultaneously standardizing and personalizing clinical care, will become essential to effective primary care.
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The Annals of Family Medicine: 9 (1)
The Annals of Family Medicine: 9 (1)
Vol. 9, Issue 1
1 Jan 2011
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Impact of Electronic Health Record Clinical Decision Support on Diabetes Care: A Randomized Trial
Patrick J. O’Connor, JoAnn M. Sperl-Hillen, William A. Rush, Paul E. Johnson, Gerald H. Amundson, Stephen E. Asche, Heidi L. Ekstrom, Todd P. Gilmer
The Annals of Family Medicine Jan 2011, 9 (1) 12-21; DOI: 10.1370/afm.1196

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Impact of Electronic Health Record Clinical Decision Support on Diabetes Care: A Randomized Trial
Patrick J. O’Connor, JoAnn M. Sperl-Hillen, William A. Rush, Paul E. Johnson, Gerald H. Amundson, Stephen E. Asche, Heidi L. Ekstrom, Todd P. Gilmer
The Annals of Family Medicine Jan 2011, 9 (1) 12-21; DOI: 10.1370/afm.1196
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