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Research

Current use and costs of electronic health records for clinical trial research: a descriptive study

Kimberly A. Mc Cord, Hannah Ewald, Aviv Ladanie, Matthias Briel, Benjamin Speich, Heiner C. Bucher and Lars G. Hemkens; for the RCD for RCTs initiative and the Making Randomized Trials More Affordable Group
February 03, 2019 7 (1) E23-E32; DOI: https://doi.org/10.9778/cmajo.20180096
Kimberly A. Mc Cord
Basel Institute for Clinical Epidemiology and Biostatistics (Mc Cord, Ewald, Ladanie, Briel, Speich, Bucher, Hemkens), Department of Clinical Research, University Hospital Basel, University of Basel; University Medical Library (Ewald), University of Basel; Swiss Tropical and Public Health Institute (Ladanie), University of Basel, Basel, Switzerland; Department of Health Research Methods, Evidence, and Impact (Briel), McMaster University, Hamilton, Ont.
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Hannah Ewald
Basel Institute for Clinical Epidemiology and Biostatistics (Mc Cord, Ewald, Ladanie, Briel, Speich, Bucher, Hemkens), Department of Clinical Research, University Hospital Basel, University of Basel; University Medical Library (Ewald), University of Basel; Swiss Tropical and Public Health Institute (Ladanie), University of Basel, Basel, Switzerland; Department of Health Research Methods, Evidence, and Impact (Briel), McMaster University, Hamilton, Ont.
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Aviv Ladanie
Basel Institute for Clinical Epidemiology and Biostatistics (Mc Cord, Ewald, Ladanie, Briel, Speich, Bucher, Hemkens), Department of Clinical Research, University Hospital Basel, University of Basel; University Medical Library (Ewald), University of Basel; Swiss Tropical and Public Health Institute (Ladanie), University of Basel, Basel, Switzerland; Department of Health Research Methods, Evidence, and Impact (Briel), McMaster University, Hamilton, Ont.
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Matthias Briel
Basel Institute for Clinical Epidemiology and Biostatistics (Mc Cord, Ewald, Ladanie, Briel, Speich, Bucher, Hemkens), Department of Clinical Research, University Hospital Basel, University of Basel; University Medical Library (Ewald), University of Basel; Swiss Tropical and Public Health Institute (Ladanie), University of Basel, Basel, Switzerland; Department of Health Research Methods, Evidence, and Impact (Briel), McMaster University, Hamilton, Ont.
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Benjamin Speich
Basel Institute for Clinical Epidemiology and Biostatistics (Mc Cord, Ewald, Ladanie, Briel, Speich, Bucher, Hemkens), Department of Clinical Research, University Hospital Basel, University of Basel; University Medical Library (Ewald), University of Basel; Swiss Tropical and Public Health Institute (Ladanie), University of Basel, Basel, Switzerland; Department of Health Research Methods, Evidence, and Impact (Briel), McMaster University, Hamilton, Ont.
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Heiner C. Bucher
Basel Institute for Clinical Epidemiology and Biostatistics (Mc Cord, Ewald, Ladanie, Briel, Speich, Bucher, Hemkens), Department of Clinical Research, University Hospital Basel, University of Basel; University Medical Library (Ewald), University of Basel; Swiss Tropical and Public Health Institute (Ladanie), University of Basel, Basel, Switzerland; Department of Health Research Methods, Evidence, and Impact (Briel), McMaster University, Hamilton, Ont.
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Lars G. Hemkens
Basel Institute for Clinical Epidemiology and Biostatistics (Mc Cord, Ewald, Ladanie, Briel, Speich, Bucher, Hemkens), Department of Clinical Research, University Hospital Basel, University of Basel; University Medical Library (Ewald), University of Basel; Swiss Tropical and Public Health Institute (Ladanie), University of Basel, Basel, Switzerland; Department of Health Research Methods, Evidence, and Impact (Briel), McMaster University, Hamilton, Ont.
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    Figure 1:

    Flow chart showing trial selection. Note: EHR = electronic health record, RCT = randomized controlled trial.

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    Table 1:

    Characteristics of randomized controlled trials published in English between January 2000 and Sept. 13, 2017 that used electronic health records

    CharacteristicNo. (%) of trials*
    Overall
    n = 189
    EHR-evaluating
    n = 172
    EHR-supported
    n = 17
    EHR for intervention172 (91.0)172 (100.0)–
     Computerized physician order entry system or clinical decision-support system128 (67.7)128 (74.4)–
     Telehealth14 (7.4)14 (8.1)–
     Personal health record26 (13.8)26 (15.1)–
     Electronic patient-reported outcomes4 (2.1)4 (2.3)–
    EHR for outcome measurement158 (83.6)143 (83.1)15 (88)
    EHR for patient recruitment105 (55.6)91 (52.9)14 (82)
    Country/region
     North America153 (81.0)140 (81.4)13 (76)
     United Kingdom9 (4.8)7 (4.1)2 (12)
     Continental Europe15 (7.9)14 (8.1)1 (6)
     Other†12 (6.3)11 (6.4)1 (6)
    Cluster RCT64 (33.9)61 (35.5)3 (18)
    Unit of randomization
     Clinician49 (25.9)46 (26.7)3 (18)
     Patient76 (40.2)65 (37.8)11 (65)
     Pharmacy1 (0.5)1 (0.6)0 (0)
     Practice/clinic54 (28.6)51 (29.6)3 (18)
     Unit/floor9 (4.8)9 (5.2)0 (0)
    Publication year, median (IQR)2012 (2009–2014)2012 (2009–2014)2013 (2010–2013)
    Sample size, median (IQR)
     Total89 (24–732)80 (22–513)732 (73–2513)
     Cluster RCTs excluded239 (57–1187)254 (60–1187)900 (111–3075)
     Cluster RCTs only24 (12–47)24 (12–52)18 (12–24)
    Blinding
     Open label27 (14.3)23 (13.4)4 (24)
     Single-blinded19 (10.0)18 (10.5)1 (6)
     Double-blinded7 (3.7)6 (3.5)1 (6)
     Outcome assessment blinding35 (18.5)30 (17.4)5 (29)
     Not reported101 (53.4)95 (55.2)6 (35)
    • Note: EHR = electronic health record, IQR = interquartile range, RCT = randomized controlled trial.

    • ↵* Except where noted otherwise.

    • ↵† Includes China, Japan, Taiwan, Iran, India, Pakistan, Lebanon, Australia and Kenya.

    • View popup
    Table 2:

    Characteristics of randomized controlled trials supported by electronic health records

    InvestigatorCountry; sample sizeEHR use for recruitment; study typeEHR use for outcome assessment; extent of use of routinely collected dataPatient population/ indicationIntervention and control*Primary outcome; length of follow-up; amount of missing dataSetting
    Bereznicki et al.,18 2008Australia; 1551 patientsYes; retrospectiveYes; EHR aloneUncontrolled asthmaIntervention: contact by community pharmacist plus educational material and referral to general practitioner for asthma managementRatio of dispensed preventer and reliever medication; 6 mo; NRCommunity pharmacy network
    Corson et al.,19 2011US; 42 caregivers (randomly allocated), 365 patientsNo; prospectiveYes; hybrid, primary outcome EHR aloneMusculoskeletal painIntervention: patient and clinician education, symptom monitoring and feedback to cliniciansGuideline-concordant care; 12 mo; NRPrimary care clinics associated with Department of Veterans Affairs medical centre and urban hospital
    de Jong et al.,20 2013Netherlands; 73 general practitioner trainees (randomly allocated)†Yes; retrospectiveYes; hybrid, primary outcome EHR aloneSkin and psychosocial conditionsSteering patient mix of general practitioner traineesTrainee exposure to specific field, and knowledge and self-efficacy; 6 mo; 5%–10%Practice network with general practitioner training program
    Fu et al.,21 2014US; 6400 patientsYes; retrospectiveYes, hybrid; primary outcome active data collection aloneCurrent smokersProactive outreach plus choice of smoking cessation services6-mo prolonged smoking abstinence at 1 yr; 12 mo; 48.3% (but 0% for EHR outcome)Department of Veterans Affairs medical centre
    Galbreath et al.,22 2004US; 1069 patientsYes; retrospectiveYes, hybrid; primary outcome active data collection aloneSymptomatic congestive heart failureCongestive heart failure management program (plus at-home scale)All-cause mortality and use of health care services; NR (time to event); NRVarious health care networks‡ and Medicare/ Medicaid participants
    Gerber et al.,23 2013US; 18 practices, 170 caregivers (randomly allocated), 185 212 patientsYes; retrospectiveYes, hybrid; primary outcome active data collection aloneClinical practice groups with primary care pediatricians (children with acute respiratory tract infections)Antibiotic stewardship programChange in broad-spectrum antibiotics prescribed for bacterial infections or in antibiotic prescribed for viral infections; 12 mo; 5% of caregiversPediatric primary care network
    Green et al.,24 2013US; 4675 patientsYes; retrospectiveYes; EHR alonePrevention of colorectal cancerAutomated interventions v. assisted care v. navigated care v. usual careReceiving any colorectal cancer test and being current for colorectal cancer testing in years 1 and 2; 24 mo; 0.2%Primary care practice network
    Hoffman et al.,25 2010US; 404 patientsYes; retrospectiveNo; active data collection alonePrevention of colorectal cancerFecal immunochemical test (v. guaiac-based occult blood test)Screening adherence; 3 mo; NRDepartment of Veterans Affairs network (primary care clinics and laboratory)
    Israel et al.,26 2013US; 732 patientsYes, retrospectiveNo; active data collection aloneAdult inpatients with at least 1 of several cardiovascular disease diagnoses in EHRMinimal intervention (medication reconciliation), enhanced intervention (minimal intervention plus pharmacist) or usual careRate of underuse of cardiovascular drugs; 3 mo; NRUniversity hospital (orthopedic, internal medicine, family medicine and cardiology wards)
    McCarren et al.,27 2013US; 12 practices (randomly allocated), 220 patientsYes; retrospectiveYes; EHR aloneHeart failure and guideline-nonconcordant β-blocker prescriptionInformation to pharmacy about prescription nonconcordanceGuideline-concordant prescriptions; 6 mo; 0%Veterans Health Administration facilities and pharmacies
    Phillips et al.,29 2011US; 3895 patientsYes; retrospectiveYes; EHR alonePrevention of breast cancerTelephone calls and reminder letters from patient navigatorsAdherence to biennial mammography; 9 mo; NRHospital-based internal medicine practices
    Piazza et al.,30 2013US; 2513 patientsYes; retrospectiveYes; EHR aloneMedical service inpatients at risk for venous thromboembolism with planned discharge within 48 hAlert for physicianSymptomatic deep vein thrombosis or pulmonary embolism; 3 mo; < 0.1%Inpatient medical unit
    Qureshi et al.,31 2012UK; 24 caregivers (randomly allocated), 748 patientsNo; prospectiveYes; hybrid, primary outcome EHR aloneAdult primary care patients with no previously diagnosed cardiovascular riskFamily history questionnaire (in addition to Framingham risk score)Proportion of identified participants with high cardiovascular risk scores; NA; 1.7%Family practices in research network
    Skinner et al.,32 2015US; 1032 patientsYes; retrospectiveYes; EHR alonePrevention of colorectal cancerTablet-based Cancer Risk Intake System assessment before appointment and control groupReceived risk-appropriate colorectal cancer testing and any type of colorectal cancer testing; 12 mo; 0%Family practices affiliated with university medical centre
    Stewart et al.,28 2014US; 235 patientsYes; retrospectiveYes; hybrid, primary outcome EHR aloneDysthymia or major depressive disorderCollaborative care program with psychotherapy and antidepressant drugsCardiovascular events; 96 mo; 0%Academic group practice
    Vestbo et al.,33 2016UK; 2802 patientsNo; prospectiveYes; hybrid, primary outcome active data collection aloneCOPD and regular maintenance inhaler therapyFluticasone furoate + vilanterol (100 μg/ 25 μg) once a day via inhalation v. usual careModerate or severe COPD exacerbation; 12 mo; 24.8%Health care network in and around Salford, hospitals, general practitioners, pharmacies
    Wolf et al.,34 2005US; 113 health care providers (randomly allocated), 1978 patientsYes; retrospectiveYes; EHR alonePrevention of colorectal cancerEducation session plus performance feedbackCompletion of colorectal cancer screening; NA; NRDepartment of Veterans Affairs primary care clinics
    • Note: COPD = chronic obstructive pulmonary disease, EHR = electronic health record, NA = not applicable, NR = not reported.

    • ↵* All comparisons are “usual care” unless otherwise specified.

    • ↵† Number of patients not reported.

    • ↵‡ University of Texas Health Science Center at San Antonio, in partnership with Wilford Hall Medical Center, Brooke Army Medical Center, South Texas Veterans Health Care System, TRICARE Region 6 and University Health System.

    • View popup
    Table 3:

    Costs of randomized controlled trials supported by electronic health records*

    Type of data extraction from EHR source; investigatorEHR source preexistingIntervention integrated during routine care (no additional staff needed)Total trial cost, US$No. of patients†Cost per patient, US$
    Automatic
    Bereznicki et al.,18 2008YesYes67 750††155144
    Manual
    Green et al.,24 2013YesNo2 800 000§5000560
    Piazza et al.,30 2013UnclearNo5 026 000¶25132000
    Wolf et al.,34 2005YesYes86 753**197844
    Unclear whether automatic or manual
    McCarren et al.,27 2013YesYes69 300††220315
    • Note: EHR = electronic health record.

    • ↵* In all trials, the EHR was used for recruitment (retrospective) and outcome assessment (all with EHR alone).

    • ↵† As reported by authors for these costs data.

    • ‡ Total received funding, including $42 157 for staff costs for the duration of the project, $6132 for a consultant programmer (for software development), $15 330 for pharmacy payments and $6132 for nonsalary costs such as printing, postage and travel.

    • ↵§ Total received funding.

    • ↵¶ Study costs were $2000 per patient and included costs of the trial start-up and close out.

    • ↵** Total cost of the colorectal cancer screening promotional effort (intervention only).

    • ↵†† Total received funding. “Most of the [working] time was donated.”

    • View popup
    Table 4:

    Risk of bias assessment with the Cochrane risk of bias tool15

    InvestigatorRandom sequence generationAllocation concealmentBlinding of participants and personnelBlinding of outcome assessmentIncomplete outcome data (> 10%)Selective outcome reporting*
    Bereznicki et al.18?−−−?NA
    Corson et al.19??+−?NA
    de Jong et al.20−?+?−NA
    Fu et al.21??+−+†NA
    Galbreath et al.22??++?NA
    Gerber et al.23?−+?−NA
    Green et al.24−−+−−NA
    Hoffman et al.25−????NA
    Israel et al.26−?−−?NA
    McCarren et al.27−?++−NA
    Phillips et al.29??+??NA
    Piazza et al.30−−+?−NA
    Qureshi et al.31−−+?−NA
    Skinner et al.32??+?−NA
    Stewart et al.28−−+−−NA
    Vestbo et al.33−−+?+NA
    Wolf et al.34??+??NA
    • Note: EHR = electronic health record, NA = nonapplicable, − = low risk of bias, ? = unclear risk of bias, + = high risk of bias.

    • ↵* Since only the publication identified in our literature search was assessed (there was no systematic protocol search and no searching for further manuscripts related to that study), we did not consider this item.

    • ↵† The completeness of outcome data based on the electronic health record (secondary study outcome) was perfect (0% missing data).

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Current use and costs of electronic health records for clinical trial research: a descriptive study
Kimberly A. Mc Cord, Hannah Ewald, Aviv Ladanie, Matthias Briel, Benjamin Speich, Heiner C. Bucher, Lars G. Hemkens
Jan 2019, 7 (1) E23-E32; DOI: 10.9778/cmajo.20180096

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Current use and costs of electronic health records for clinical trial research: a descriptive study
Kimberly A. Mc Cord, Hannah Ewald, Aviv Ladanie, Matthias Briel, Benjamin Speich, Heiner C. Bucher, Lars G. Hemkens
Jan 2019, 7 (1) E23-E32; DOI: 10.9778/cmajo.20180096
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