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Research ArticleOriginal Research

Accelerated Adoption of Advanced Health Information Technology in Beacon Community Health Centers

Emily Jones and Michael Wittie
The Journal of the American Board of Family Medicine September 2015, 28 (5) 565-575; DOI: https://doi.org/10.3122/jabfm.2015.05.150034
Emily Jones
From the Division of Behavioral Health and Intellectual Disabilities Policy, Office of Disability, Aging, and Long-Term Care Policy, Office of the Assistant Secretary for Planning and Evaluation, US Department of Health and Human Services, Washington, DC (EJ); Department of Health Policy and Management, The Milken Institute School of Public Health and Health Services, The George Washington University, Washington, DC (EJ); the Office of Clinical Safety and Quality, Office of the National Coordinator for Health Information Technology, US Department of Health and Human Services, Washington, DC (MW).
PhD, MPP
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Michael Wittie
From the Division of Behavioral Health and Intellectual Disabilities Policy, Office of Disability, Aging, and Long-Term Care Policy, Office of the Assistant Secretary for Planning and Evaluation, US Department of Health and Human Services, Washington, DC (EJ); Department of Health Policy and Management, The Milken Institute School of Public Health and Health Services, The George Washington University, Washington, DC (EJ); the Office of Clinical Safety and Quality, Office of the National Coordinator for Health Information Technology, US Department of Health and Human Services, Washington, DC (MW).
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Article Figures & Data

Tables

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    Table 1. Key Features of the Beacon Communities Program
    Program FeatureDescription
    FundingSeventeen communities each received approximately $11–16 million each to build and strengthen the health information technology infrastructure in each community, use health information technology to drive quality improvement, and test innovative practices.
    Community-level focusOf the 17 Beacon communities, 1 was urban, 7 were predominantly rural, and 7 were a mix of both urban and rural localities. Different communities defined themselves in various ways; some Beacon communities attempted to change the entire delivery system in their community, whereas others focused more narrowly.
    Collaborative governanceTo ensure that each Beacon was responsive to the needs of the community, Beacon grantees were required to engage multiple stakeholders in decision-making regarding the goals and interventions that were pursued. Partnerships within the communities were forged and strengthened during the Beacon program.
    Specific objectivesEach community honed the objectives from their funding proposal into specific, measurable goals that could be achieved during the 2-year project period.
    Interventions tied to the objectives of each communityOnce each community winnowed their objectives down to specific, measurable goals, they received technical assistance to design and implement interventions to work toward those goals.
    Measuring and reporting performanceBeacon communities were required to report, on a quarterly basis, performance measures of their choosing. The measures were selected to reflect improvements on the objectives of each community. Technical assistance for extracting, aggregating, and reporting the data was provided.
    Data feedback for quality improvementEach quarter, the Beacon communities received a feedback report that was based on analysis of Medicare claims data. The feedback report highlighted patterns in utilization and costs, and communities received technical assistance with interpreting the feedback reports and changing their approaches to pursuing their objectives based on the feedback reports.
    • View popup
    Table 2. Health Center and Patient Characteristics, by Beacon Community Status, 2010–2012
    CharacteristicsOverallNon–Beacon CommunityBeacon Community
    Health centers
        Patients served annually at each health center (mean no.)17,646.6017,417.2320,516.00*
        Rural47.5247.9641.96
        Region
            South34.5135.4922.35†
            Northeast17.6517.4620.00
            Midwest18.9018.5323.53‡
            West28.9428.5334.12
        Receive funding to target services to special populations
            Homeless19.5919.8116.86
            Migrant and seasonal farm workers13.9913.8915.29
        Accreditation or patient-centered medical home recognition (mean %)32.9732.6137.65
    Patient demographics
         <100% FPL68.5868.5968.47
        Insurance status and type
            Uninsured39.2939.2839.40
            Medicaid34.0033.8336.14*
            Other public1.831.831.81
            Private16.1116.2114.86
            Medicare7.998.067.02‡
        Race/ethnicity
            Hispanic25.2225.4222.73
            Black19.6619.4322.44
            Other race12.3312.3511.98
            White42.6842.6742.85
        Male sex42.6042.6541.86
        Age (years)
            0–1930.7730.6032.90‡
            20–6461.4261.5160.28
            ≥657.747.826.81‡
    • Data are mean percentages unless otherwise indicated. PCMH information was available in 2012 only.

    • Source: Uniform Data System, 2010–2012.

    • ↵* P < .05.

    • ↵† P < .001.

    • ↵‡ P < .01.

    • FPL, federal poverty level.

    • View popup
    Table 3. Electronic Health Record Adoption Among Health Centers, 2010–2012
    201020112012
    Health Centers (mean %)Percentage Point DifferenceHealth Centers (mean %)Percentage Point Difference (P Value)Health Centers (mean %)Percentage Point Difference (P Value)
    OverallNon-BeaconBeaconOverallNon-BeaconBeaconOverallNon-BeaconBeacon
    Any EHR64.8263.9775.2911.32*79.6179.1085.886.7889.9889.4097.658.25*
    EHR at all sites50.6750.0957.657.5665.1664.4374.129.6979.3078.7187.068.35
    Basic EHR29.7429.3834.124.7440.3439.9844.714.7349.7548.5265.8817.36†
    • Source: Uniform Data System, 2010–2012.

    • P values are from independent samples differences in means tests comparing Beacon and non–Beacon health centers:

    • ↵* P < .05,

    • ↵† P < .01.

    • EHR, electronic health record.

    • View popup
    Table 4. Factors Associated With Gaining Basic Electronic Health Record Capability Between 2010 and 2012
    CovariateAdjusted Odds Ratio (95% CI)P Value
    Beacon
        Yes1.71 (1.31–2.24)*.00
        No (reference)1
    Rural
        Yes0.90 (0.74–1.09).27
        No (reference)1
    Region
        South (reference)1
        Northeast1.26 (0.99–1.61).06
        Midwest1.23 (0.98–1.54).07
        West0.83 (0.66–1.04).11
    Size (patients served annually/1000)1.00 (0.99–1.00).07
    Poverty (<100% FPL)1.01 (1.00–1.01)*.00
    Insurance status and type
        Lacking health insurance0.99 (0.98–1.00)*.00
        Covered by Medicaid0.99 (0.98–1.00)†.01
        Other types of insurance (reference)1
    Race/ethnicity
        Hispanic1.00 (1.00–1.00).91
        Black1.00 (0.99–1.00).23
        Other race1.00 (0.99–1.00).25
        White, non-Hispanic (reference)1
    Year
        20100.92 (0.77–1.11).39
        20110.95 (0.80–1.14).61
        2012 (reference)1
    • Source: Uniform Data System, 2010–2012.

    • ↵* P < .001.

    • ↵† P < .01.

    • CI, confidence interval; FPL, federal poverty level.

    • View popup
    Table 5. Use of Health Information Technology Functionalities, 2010 and 2012
    Health Centers Using Each Functionality (%)Percentage Point Difference Between Beacon and Non-Beacon
    2010201220102012
    OverallNon-BeaconBeaconOverallNon-BeaconBeacon
    Structured data capture
        Patient history and demographic information63.9463.0175.2989.5788.9597.6512.28*8.70*
    Electronic order transmission
        Prescriptions50.4049.6160.0086.3185.6295.2910.399.67*
        Lab orders49.9649.3357.6574.4673.8582.358.328.50
        Radiology orders21.7321.3925.8834.8935.4927.064.49−8.43
    Clinical decision support
        Guideline-based reminders for interventions or tests51.1150.1962.3580.0578.8995.2912.16*16.40†
        Prompt for and record of tobacco cessation intervention34.9134.1044.7167.2066.4976.4710.61‡9.98
    Engaging patients and families
        Capability to provide patients with an electronic copy of their health information upon request41.1440.2751.7670.9570.9770.5911.49*−0.38
        Capacity to give clinical summaries to patients after visits52.0951.1663.5385.0684.2895.2912.37*11.01‡
    Care coordination and performance measurement
        Capability to exchange key clinical information32.5031.9838.8255.0954.0069.416.8415.41‡
        Electronically submit clinical measures49.8749.3356.4770.7870.1778.827.148.65
    Public health
        Disease notifications sent electronically11.5811.4612.9418.6118.6917.651.48−1.04
        Electronic reporting to immunization registries21.3721.0025.8836.1435.7641.184.885.42
    • Source: 2010 and 2012 Uniform Data System.

    • The significance between Beacon and non-Beacon usage rates for each functionality was tested using independent samples differences in means t tests:

    • ↵* P < .05,

    • ↵† P < .001,

    • ↵‡ P < .01.

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The Journal of the American Board of Family     Medicine: 28 (5)
The Journal of the American Board of Family Medicine
Vol. 28, Issue 5
September-October 2015
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Accelerated Adoption of Advanced Health Information Technology in Beacon Community Health Centers
Emily Jones, Michael Wittie
The Journal of the American Board of Family Medicine Sep 2015, 28 (5) 565-575; DOI: 10.3122/jabfm.2015.05.150034

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Accelerated Adoption of Advanced Health Information Technology in Beacon Community Health Centers
Emily Jones, Michael Wittie
The Journal of the American Board of Family Medicine Sep 2015, 28 (5) 565-575; DOI: 10.3122/jabfm.2015.05.150034
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