Journal of Medical Systems

, 37:9922 | Cite as

A Randomized Trial of Population-Based Clinical Decision Support to Manage Health and Resource Use for Medicaid Beneficiaries

  • David F. Lobach
  • Kensaku Kawamoto
  • Kevin J. Anstrom
  • Garry M. Silvey
  • Janese M. Willis
  • Fred S. Johnson
  • Rex Edwards
  • Jessica Simo
  • Pam Phillips
  • David R. Crosslin
  • Eric L. Eisenstein
Original Paper

Abstract

To determine whether a clinical decision support system can favorably impact the delivery of emergency department and hospital services. Randomized clinical trial of three clinical decision support delivery modalities: email messages to care managers (email), printed reports to clinic administrators (report) and letters to patients (letter) conducted among 20,180 Medicaid beneficiaries in Durham County, North Carolina with follow-up through 9 months. Patients in the email group had fewer low-severity emergency department encounters vs. controls (8.1 vs. 10.6/100 enrollees, p < 0.001) with no increase in outpatient encounters or medical costs. Patients in the letter group had more outpatient encounters and greater outpatient and total medical costs. There were no treatment-related differences for patients in the reports group. Among patients <18 years, those in the email group had fewer low severity (7.6 vs. 10.6/100 enrollees, p < 0.001) and total emergency department encounters (18.3 vs. 23.5/100 enrollees, p < 0.001), and lower emergency department ($63 vs. $89, p = 0.002) and total medical costs ($1,736 vs. $2,207, p = 0.009). Patients who were ≥18 years in the letter group had greater outpatient medical costs. There were no intervention-related differences in patient-reported assessments of quality of life and medical care received. The effectiveness of clinical decision support messaging depended upon the delivery modality and patient age. Health IT interventions must be carefully evaluated to ensure that the resultant outcomes are aligned with expectations as interventions can have differing effects on clinical and economic outcomes.

Keywords

Clinical decision support Population health Care coordination Medical resource use Medical costs 

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • David F. Lobach
    • 1
  • Kensaku Kawamoto
    • 1
  • Kevin J. Anstrom
    • 2
  • Garry M. Silvey
    • 1
  • Janese M. Willis
    • 1
  • Fred S. Johnson
    • 3
  • Rex Edwards
    • 2
  • Jessica Simo
    • 3
  • Pam Phillips
    • 3
  • David R. Crosslin
    • 4
  • Eric L. Eisenstein
    • 1
    • 2
  1. 1.Division of Clinical Informatics, Department of Community and Family MedicineDuke University Medical CenterDurhamUSA
  2. 2.Duke Clinical Research InstituteDurhamUSA
  3. 3.Division of Community Health, Department of Community and Family MedicineDuke University Medical CenterDurhamUSA
  4. 4.Department of BiostatisticsUniversity of WashingtonSeattleUSA

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