Ignite Creation Date:
2025-12-25 @ 3:08 AM
Ignite Modification Date:
2026-01-22 @ 9:47 PM
Study NCT ID:
NCT03244033
Status:
COMPLETED
Last Update Posted:
2023-01-10
First Post:
2017-07-31
Is NOT Gene Therapy:
True
Has Adverse Events:
True
Brief Title:
Integrating Contextual Factors Into Clinical Decision Support
Sponsor:
Organization:
Raw JSON
{'hasResults': True, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}}, 'resultsSection': {'moreInfoModule': {'pointOfContact': {'email': 'sweiner@uic.edu', 'phone': '312-355-1700', 'title': 'Dr. Saul Weiner', 'organization': 'University of Illinois at Chicago'}, 'certainAgreement': {'piSponsorEmployee': False, 'restrictiveAgreement': False}}, 'adverseEventsModule': {'timeFrame': 'At index visit for each patient during the study period.', 'eventGroups': [{'id': 'EG000', 'title': 'Contextual Survey + Contextual CDS', 'description': 'Contextual factors obtained from patients in the Contextual Survey along with contextual red flags already stored in the EHR will produce a variety of Contextual Clinical Decision Support, both passive and interruptive alerts.\n\nContextual clinical decision support: Incorporation of contextual data into EHR clinical decision support alerts\n\nContextual survey: Patients complete a survey asking about red flags that could signal contextual factors relevant to their care', 'otherNumAtRisk': 177, 'deathsNumAtRisk': 177, 'otherNumAffected': 0, 'seriousNumAtRisk': 177, 'deathsNumAffected': 0, 'seriousNumAffected': 0}, {'id': 'EG001', 'title': 'Contextual Survey Only', 'description': 'Contextual factors obtained from patients in the Contextual Survey along with contextual red flags already stored in the EHR will not be used for CDS or to produce alerts.\n\nContextual survey: Patients complete a survey asking about red flags that could signal contextual factors relevant to their care', 'otherNumAtRisk': 275, 'deathsNumAtRisk': 275, 'otherNumAffected': 0, 'seriousNumAtRisk': 275, 'deathsNumAffected': 0, 'seriousNumAffected': 0}], 'frequencyThreshold': '5'}, 'outcomeMeasuresModule': {'outcomeMeasures': [{'type': 'PRIMARY', 'title': 'Resolution of Contextual Red Flags', 'denoms': [{'units': 'Participants', 'counts': [{'value': '177', 'groupId': 'OG000'}, {'value': '275', 'groupId': 'OG001'}]}, {'units': 'Red flags', 'counts': [{'value': '362', 'groupId': 'OG000'}, {'value': '540', 'groupId': 'OG001'}]}], 'groups': [{'id': 'OG000', 'title': 'Contextual Survey + Contextual CDS', 'description': 'Contextual factors obtained from patients in the Contextual Survey along with contextual red flags already stored in the EHR will produce a variety of Contextual Clinical Decision Support, both passive and interruptive alerts.\n\nContextual clinical decision support: Incorporation of contextual data into EHR clinical decision support alerts\n\nContextual survey: Patients complete a survey asking about red flags that could signal contextual factors relevant to their care'}, {'id': 'OG001', 'title': 'Contextual Survey Only', 'description': 'Contextual factors obtained from patients in the Contextual Survey along with contextual red flags already stored in the EHR will not be used for CDS or to produce alerts.\n\nContextual survey: Patients complete a survey asking about red flags that could signal contextual factors relevant to their care'}], 'classes': [{'categories': [{'title': 'Red flag improved/resolved', 'measurements': [{'value': '116', 'groupId': 'OG000'}, {'value': '240', 'groupId': 'OG001'}]}, {'title': 'Red flag worsened', 'measurements': [{'value': '83', 'groupId': 'OG000'}, {'value': '99', 'groupId': 'OG001'}]}, {'title': 'Red flag unchanged or mixed', 'measurements': [{'value': '163', 'groupId': 'OG000'}, {'value': '201', 'groupId': 'OG001'}]}]}], 'analyses': [{'pValue': '.91', 'groupIds': ['OG000', 'OG001'], 'paramType': 'Odds Ratio (OR)', 'ciNumSides': 'TWO_SIDED', 'ciPctValue': '96', 'paramValue': '.97', 'ciLowerLimit': '.57', 'ciUpperLimit': '1.64', 'groupDescription': 'Logistic mixed effects regression modeling likelihood of red flag improved/resolved (vs. not) during outcome period with fixed effects of intervention, site, and whether contextual factor was incorporated into care plan, and random effects of patient and provider. Red flags may be clustered in patients; patients are clustered in providers.', 'statisticalMethod': 'Mixed Models Analysis', 'nonInferiorityType': 'SUPERIORITY', 'statisticalComment': 'Adjusted for site (p\\<.001) and for whether physician contextualized plan (AOR 2.14, p=.001), and random effects of physician and patient.'}], 'paramType': 'COUNT_OF_UNITS', 'timeFrame': '6-9 months following index visit', 'description': 'Proportion of red flags noted at index visit that have resolved', 'calculatePct': False, 'unitOfMeasure': 'Red flags', 'reportingStatus': 'POSTED', 'typeUnitsAnalyzed': 'Red flags', 'denomUnitsSelected': 'Red flags', 'populationDescription': 'Red flags identified in visits of participants.'}, {'type': 'SECONDARY', 'title': 'Probing of Contextual Red Flags', 'denoms': [{'units': 'Participants', 'counts': [{'value': '177', 'groupId': 'OG000'}, {'value': '275', 'groupId': 'OG001'}]}, {'units': 'Red flags', 'counts': [{'value': '362', 'groupId': 'OG000'}, {'value': '540', 'groupId': 'OG001'}]}], 'groups': [{'id': 'OG000', 'title': 'Contextual Survey + Contextual CDS', 'description': 'Contextual factors obtained from patients in the Contextual Survey along with contextual red flags already stored in the EHR will produce a variety of Contextual Clinical Decision Support, both passive and interruptive alerts.\n\nContextual clinical decision support: Incorporation of contextual data into EHR clinical decision support alerts\n\nContextual survey: Patients complete a survey asking about red flags that could signal contextual factors relevant to their care'}, {'id': 'OG001', 'title': 'Contextual Survey Only', 'description': 'Contextual factors obtained from patients in the Contextual Survey along with contextual red flags already stored in the EHR will not be used for CDS or to produce alerts.\n\nContextual survey: Patients complete a survey asking about red flags that could signal contextual factors relevant to their care'}], 'classes': [{'categories': [{'title': 'Probed', 'measurements': [{'value': '215', 'groupId': 'OG000'}, {'value': '271', 'groupId': 'OG001'}]}, {'title': 'Not probed', 'measurements': [{'value': '147', 'groupId': 'OG000'}, {'value': '269', 'groupId': 'OG001'}]}]}], 'analyses': [{'pValue': '0.02', 'groupIds': ['OG000', 'OG001'], 'paramType': 'Odds Ratio (OR)', 'ciNumSides': 'TWO_SIDED', 'ciPctValue': '95', 'paramValue': '2.09', 'ciLowerLimit': '1.13', 'ciUpperLimit': '3.86', 'estimateComment': 'OR\\>1 indicates greater likelihood in intervention group vs. control.', 'groupDescription': 'Logistic mixed effects regression modeling likelihood of provider probing red flag (vs. not) during visit with fixed effects of intervention, site, \\\\whether red flag was select on pre-visit questionnaire, and whether audiorecorder was visible to provider, and random effects of patient and provider. Red flags may be clustered in patients; patients are clustered in providers.', 'statisticalMethod': 'Mixed Models Analysis', 'nonInferiorityType': 'SUPERIORITY', 'statisticalComment': 'Adjusted for site, source of red flag, visible/concealed recorder, and random effects of physician and patient.'}], 'paramType': 'COUNT_OF_UNITS', 'timeFrame': 'At index visit', 'description': 'Proportion of red flags which the examining physician probes', 'calculatePct': False, 'unitOfMeasure': 'Red flags', 'reportingStatus': 'POSTED', 'typeUnitsAnalyzed': 'Red flags', 'denomUnitsSelected': 'Red flags'}, {'type': 'SECONDARY', 'title': 'Planning for Contextual Factors', 'denoms': [{'units': 'Participants', 'counts': [{'value': '177', 'groupId': 'OG000'}, {'value': '275', 'groupId': 'OG001'}]}, {'units': 'Contextual factors', 'counts': [{'value': '383', 'groupId': 'OG000'}, {'value': '509', 'groupId': 'OG001'}]}], 'groups': [{'id': 'OG000', 'title': 'Contextual Survey + Contextual CDS', 'description': 'Contextual factors obtained from patients in the Contextual Survey along with contextual red flags already stored in the EHR will produce a variety of Contextual Clinical Decision Support, both passive and interruptive alerts.\n\nContextual clinical decision support: Incorporation of contextual data into EHR clinical decision support alerts\n\nContextual survey: Patients complete a survey asking about red flags that could signal contextual factors relevant to their care'}, {'id': 'OG001', 'title': 'Contextual Survey Only', 'description': 'Contextual factors obtained from patients in the Contextual Survey along with contextual red flags already stored in the EHR will not be used for CDS or to produce alerts.\n\nContextual survey: Patients complete a survey asking about red flags that could signal contextual factors relevant to their care'}], 'classes': [{'categories': [{'title': 'Plan contextualized for factor', 'measurements': [{'value': '221', 'groupId': 'OG000'}, {'value': '255', 'groupId': 'OG001'}]}, {'title': 'Plan not contextualized for factor', 'measurements': [{'value': '162', 'groupId': 'OG000'}, {'value': '254', 'groupId': 'OG001'}]}]}], 'analyses': [{'pValue': '.006', 'groupIds': ['OG000', 'OG001'], 'paramType': 'Odds Ratio (OR)', 'ciNumSides': 'TWO_SIDED', 'ciPctValue': '95', 'paramValue': '2.67', 'ciLowerLimit': '1.32', 'ciUpperLimit': '5.41', 'estimateComment': 'OR \\> 1 indicates greater likelihood in intervention group vs. control.', 'groupDescription': 'Logistic mixed effects regression modeling likelihood of provider incorporating contextual factor into care plan (vs. not) at visit with fixed effects of intervention, site, whether red flag was select on pre-visit questionnaire, whether audiorecorder was visible to provider, whether factor was identified by provider probe, whether factor was revealed by patient, and random effects of patient and provider. Red flags may be clustered in patients; patients are clustered in providers.', 'statisticalMethod': 'Mixed Models Analysis', 'nonInferiorityType': 'SUPERIORITY', 'statisticalComment': 'Adjusted for site, source of factor, recorder visible/concealed, and random effects of physician and patient.'}], 'paramType': 'COUNT_OF_UNITS', 'timeFrame': 'At index visit', 'description': 'Proportion of contextual factors identified during visit that are incorporated into care plan', 'calculatePct': False, 'unitOfMeasure': 'Contextual factors', 'reportingStatus': 'POSTED', 'typeUnitsAnalyzed': 'Contextual factors', 'denomUnitsSelected': 'Contextual factors'}]}, 'participantFlowModule': {'groups': [{'id': 'FG000', 'title': 'Contextual Survey + Contextual CDS', 'description': 'Contextual factors obtained from patients in the Contextual Survey along with contextual red flags already stored in the EHR will produce a variety of Contextual Clinical Decision Support, both passive and interruptive alerts.\n\nContextual clinical decision support: Incorporation of contextual data into EHR clinical decision support alerts\n\nContextual survey: Patients complete a survey asking about red flags that could signal contextual factors relevant to their care'}, {'id': 'FG001', 'title': 'Contextual Survey Only', 'description': 'Contextual factors obtained from patients in the Contextual Survey along with contextual red flags already stored in the EHR will not be used for CDS or to produce alerts.\n\nContextual survey: Patients complete a survey asking about red flags that could signal contextual factors relevant to their care'}], 'periods': [{'title': 'Overall Study', 'milestones': [{'type': 'STARTED', 'achievements': [{'groupId': 'FG000', 'numSubjects': '177'}, {'groupId': 'FG001', 'numSubjects': '275'}]}, {'type': 'COMPLETED', 'achievements': [{'groupId': 'FG000', 'numSubjects': '177'}, {'groupId': 'FG001', 'numSubjects': '275'}]}, {'type': 'NOT COMPLETED', 'achievements': [{'groupId': 'FG000', 'numSubjects': '0'}, {'groupId': 'FG001', 'numSubjects': '0'}]}]}], 'recruitmentDetails': '570 patients were assessed for eligibility to participate across the clinics at the two sites. 118 declined to participate and were not randomized.'}, 'baselineCharacteristicsModule': {'denoms': [{'units': 'Participants', 'counts': [{'value': '177', 'groupId': 'BG000'}, {'value': '275', 'groupId': 'BG001'}, {'value': '452', 'groupId': 'BG002'}]}], 'groups': [{'id': 'BG000', 'title': 'Contextual Survey + Contextual CDS', 'description': 'Contextual factors obtained from patients in the Contextual Survey along with contextual red flags already stored in the EHR will produce a variety of Contextual Clinical Decision Support, both passive and interruptive alerts.\n\nContextual clinical decision support: Incorporation of contextual data into EHR clinical decision support alerts\n\nContextual survey: Patients complete a survey asking about red flags that could signal contextual factors relevant to their care'}, {'id': 'BG001', 'title': 'Contextual Survey Only', 'description': 'Contextual factors obtained from patients in the Contextual Survey along with contextual red flags already stored in the EHR will not be used for CDS or to produce alerts.\n\nContextual survey: Patients complete a survey asking about red flags that could signal contextual factors relevant to their care'}, {'id': 'BG002', 'title': 'Total', 'description': 'Total of all reporting groups'}], 'measures': [{'title': 'Age, Customized', 'classes': [{'title': 'Adult (18 and older)', 'denoms': [{'units': 'Participants', 'counts': [{'value': '177', 'groupId': 'BG000'}, {'value': '275', 'groupId': 'BG001'}, {'value': '452', 'groupId': 'BG002'}]}], 'categories': [{'measurements': [{'value': '177', 'groupId': 'BG000'}, {'value': '275', 'groupId': 'BG001'}, {'value': '452', 'groupId': 'BG002'}]}]}], 'paramType': 'COUNT_OF_PARTICIPANTS', 'unitOfMeasure': 'Participants'}, {'title': 'Sex: Female, Male', 'classes': [{'denoms': [{'units': 'Participants', 'counts': [{'value': '177', 'groupId': 'BG000'}, {'value': '275', 'groupId': 'BG001'}, {'value': '452', 'groupId': 'BG002'}]}], 'categories': [{'title': 'Female', 'measurements': [{'value': '111', 'groupId': 'BG000'}, {'value': '182', 'groupId': 'BG001'}, {'value': '293', 'groupId': 'BG002'}]}, {'title': 'Male', 'measurements': [{'value': '66', 'groupId': 'BG000'}, {'value': '93', 'groupId': 'BG001'}, {'value': '159', 'groupId': 'BG002'}]}]}], 'paramType': 'COUNT_OF_PARTICIPANTS', 'unitOfMeasure': 'Participants'}, {'title': 'Race and Ethnicity Not Collected', 'classes': [{'denoms': [{'units': 'Participants', 'counts': [{'value': '0', 'groupId': 'BG000'}, {'value': '0', 'groupId': 'BG001'}, {'value': '0', 'groupId': 'BG002'}]}], 'categories': [{'measurements': [{'value': '0', 'groupId': 'BG002'}]}]}], 'paramType': 'COUNT_OF_PARTICIPANTS', 'unitOfMeasure': 'Participants', 'populationDescription': 'Race and Ethnicity were not collected from any participant.'}, {'title': 'Region of Enrollment', 'classes': [{'title': 'United States', 'denoms': [{'units': 'Participants', 'counts': [{'value': '177', 'groupId': 'BG000'}, {'value': '275', 'groupId': 'BG001'}, {'value': '452', 'groupId': 'BG002'}]}], 'categories': [{'measurements': [{'value': '177', 'groupId': 'BG000'}, {'value': '275', 'groupId': 'BG001'}, {'value': '452', 'groupId': 'BG002'}]}]}], 'paramType': 'NUMBER', 'unitOfMeasure': 'participants'}, {'title': 'Clinic Site', 'classes': [{'denoms': [{'units': 'Participants', 'counts': [{'value': '177', 'groupId': 'BG000'}, {'value': '275', 'groupId': 'BG001'}, {'value': '452', 'groupId': 'BG002'}]}], 'categories': [{'title': 'Site 1', 'measurements': [{'value': '118', 'groupId': 'BG000'}, {'value': '160', 'groupId': 'BG001'}, {'value': '278', 'groupId': 'BG002'}]}, {'title': 'Site 2', 'measurements': [{'value': '59', 'groupId': 'BG000'}, {'value': '115', 'groupId': 'BG001'}, {'value': '174', 'groupId': 'BG002'}]}]}], 'paramType': 'COUNT_OF_PARTICIPANTS', 'unitOfMeasure': 'Participants'}], 'populationDescription': '(As in participant flow diagram)'}}, 'documentSection': {'largeDocumentModule': {'largeDocs': [{'date': '2017-06-08', 'size': 338238, 'label': 'Study Protocol and Statistical Analysis Plan', 'hasIcf': False, 'hasSap': True, 'filename': 'Prot_SAP_000.pdf', 'typeAbbrev': 'Prot_SAP', 'uploadDate': '2022-02-04T10:55', 'hasProtocol': True}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'SINGLE', 'whoMasked': ['OUTCOMES_ASSESSOR']}, 'primaryPurpose': 'HEALTH_SERVICES_RESEARCH', 'interventionModel': 'PARALLEL'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 452}}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2018-09-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2022-04', 'completionDateStruct': {'date': '2021-11-12', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2022-04-12', 'studyFirstSubmitDate': '2017-07-31', 'resultsFirstSubmitDate': '2022-02-04', 'studyFirstSubmitQcDate': '2017-08-04', 'lastUpdatePostDateStruct': {'date': '2023-01-10', 'type': 'ACTUAL'}, 'resultsFirstSubmitQcDate': '2022-04-12', 'studyFirstPostDateStruct': {'date': '2017-08-09', 'type': 'ACTUAL'}, 'resultsFirstPostDateStruct': {'date': '2023-01-10', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2021-11-12', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Resolution of Contextual Red Flags', 'timeFrame': '6-9 months following index visit', 'description': 'Proportion of red flags noted at index visit that have resolved'}], 'secondaryOutcomes': [{'measure': 'Probing of Contextual Red Flags', 'timeFrame': 'At index visit', 'description': 'Proportion of red flags which the examining physician probes'}, {'measure': 'Planning for Contextual Factors', 'timeFrame': 'At index visit', 'description': 'Proportion of contextual factors identified during visit that are incorporated into care plan'}]}, 'oversightModule': {'oversightHasDmc': True, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['context', 'contextual error', 'contextual care', 'electronic medical record', 'clinical decision support'], 'conditions': ['Medical Errors', 'Decision Support Systems, Clinical', 'Diagnostic Errors']}, 'referencesModule': {'references': [{'pmid': '36279133', 'type': 'DERIVED', 'citation': 'Weiner SJ, Schwartz A, Weaver F, Galanter W, Olender S, Kochendorfer K, Binns-Calvey A, Saini R, Iqbal S, Diaz M, Michelfelder A, Varkey A. Effect of Electronic Health Record Clinical Decision Support on Contextualization of Care: A Randomized Clinical Trial. JAMA Netw Open. 2022 Oct 3;5(10):e2238231. doi: 10.1001/jamanetworkopen.2022.38231.'}]}, 'descriptionModule': {'briefSummary': 'Preventing contextual errors requires heightening clinician responsiveness to clues that there are contextual factors during the clinical encounter, in real time. These clues, termed contextual red flags are evident in two sources: the medical record and from patients directly. An effective intervention would prompt clinicians to determine whether there are underlying contextual factors that could be addressed in the care plan, averting contextual error. This desirable process is termed contextual probing.\n\nWhile clinical decision support (CDS) has been used to provide physicians with timely biomedical information at the point of care to prevent errors and promote appropriate care, this technology also affords an opportunity to draw physician attention to both contextual red flags and contextual factors in order to avert contextual errors. This study assesses the potential of "contextualized CDS" to improve contextualization of care through a randomized controlled intervention trial, with assessment measures of both patient health care outcomes and averted costs associated with overuse and misuse of medical services. The three hypotheses are that CDS:\n\n1. Reduces contextual error: CDS tools that inform clinicians of contextual factors and prompt them to explore contextual red flags should result in a reduction in contextual error.\n2. Improve health care outcomes: Contextualized CDS predicts improved health care outcomes defined as a partial or full resolution of the contextual red flag (e.g. elevated HgB A1c) after the index visit.\n3. Reduces avoidable health care costs: Contextualized CDS is associated with a reduction in misuse and overuse of inappropriate or unnecessary medical services.', 'detailedDescription': 'The term patient context refers to the myriad contextual factors in patients\' lives that complicate the application of research evidence to patient care. For instance, the inability of a patient to afford a medication for a particular condition is a contextual factor. Contextual factors can be addressed when correctly identified. Substituting a low cost generic for a high cost brand name medication may enable a patient to afford a medication. Addressing contextual factors in a care plan is termed contextualizing care. Conversely, the failure to address a contextual factor when it is feasible to so is a contextual error, because it results in an inappropriate plan of care. In sum, contextual errors are medical errors caused by inattention to patient context. They are common and linked to both diminished health care outcomes and an increase in health care costs related to overuse and misuse of medical services. These findings were determined using a validated method for coding audio recorded data called Content Coding for Contextualization of Care ("4C") collected during the encounters by both real patients, and by unannounced standardized patients (USPs) employing checklists.\n\nPreventing contextual errors requires heightening clinician responsiveness to clues that there are contextual factors during the clinical encounter, in real time. These clues, termed contextual red flags are evident in two sources: the medical record and from patients directly. An effective intervention would prompt clinicians to determine whether there are underlying contextual factors that could be addressed in the care plan, averting contextual error. This desirable process is termed contextual probing.\n\nWhile clinical decision support (CDS) has been used to provide physicians with timely biomedical information at the point of care to prevent errors and promote appropriate care, this technology also affords an opportunity to draw physician attention to both contextual red flags and contextual factors in order to avert contextual errors. This study assesses the potential of "contextualized CDS" to improve contextualization of care through a randomized controlled intervention trial, with assessment measures of both patient health care outcomes and averted costs associated with overuse and misuse of medical services. The three hypotheses are that CDS:\n\n1. Reduces contextual error: CDS tools that inform clinicians of contextual factors and prompt them to explore contextual red flags should result in a reduction in contextual error.\n2. Improve health care outcomes: Contextualized CDS predicts improved health care outcomes defined as a partial or full resolution of the contextual red flag (e.g. elevated HgB A1c) after the index visit.\n3. Reduces avoidable health care costs: Contextualized CDS is associated with a reduction in misuse and overuse of inappropriate or unnecessary medical services.\n\nTo test the hypotheses, patients who consent to participate will be randomized to usual care or care enhanced with contextualized CDS. Participants will audio record their visits, and the data will be coded using 4C. They will be followed several months after the index visit for assessment of outcomes by blinded assessors using an established tracking method. In addition, USPs presenting with cases containing complicating contextual factors that if overlooked result in overuse and misuse of medical services, will be employed to assess the third hypothesis, and to supplement the data obtained by observing the effects of contextual alerts on the care of real patients for the first hypothesis.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* English-speaking adult patients presenting to outpatient primary care clinics for scheduled appointments who can be contacted in advance of their appointment and the clinicians (physicians or nurse practitioners) seeing those patients at those visits.\n\nExclusion Criteria:\n\n* • Patients with emergent or unscheduled visits or who do not speak English.'}, 'identificationModule': {'nctId': 'NCT03244033', 'briefTitle': 'Integrating Contextual Factors Into Clinical Decision Support', 'organization': {'class': 'OTHER', 'fullName': 'University of Illinois at Chicago'}, 'officialTitle': 'Integrating Contextual Factors Into Clinical Decision Support to Reduce Contextual Error and Improve Outcomes in Ambulatory Care', 'orgStudyIdInfo': {'id': '2017-0555'}, 'secondaryIdInfos': [{'id': 'R01HS025374', 'link': 'https://reporter.nih.gov/quickSearch/R01HS025374', 'type': 'AHRQ'}]}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'Contextual Survey + Contextual CDS', 'description': 'Contextual factors obtained from patients in the Contextual Survey along with contextual red flags already stored in the EHR will produce a variety of Contextual Clinical Decision Support, both passive and interruptive alerts.', 'interventionNames': ['Other: Contextual clinical decision support', 'Behavioral: Contextual survey']}, {'type': 'ACTIVE_COMPARATOR', 'label': 'Contextual Survey Only', 'description': 'Contextual factors obtained from patients in the Contextual Survey along with contextual red flags already stored in the EHR will not be used for CDS or to produce alerts.', 'interventionNames': ['Behavioral: Contextual survey']}], 'interventions': [{'name': 'Contextual clinical decision support', 'type': 'OTHER', 'description': 'Incorporation of contextual data into EHR clinical decision support alerts', 'armGroupLabels': ['Contextual Survey + Contextual CDS']}, {'name': 'Contextual survey', 'type': 'BEHAVIORAL', 'description': 'Patients complete a survey asking about red flags that could signal contextual factors relevant to their care', 'armGroupLabels': ['Contextual Survey + Contextual CDS', 'Contextual Survey Only']}]}, 'contactsLocationsModule': {'locations': [{'zip': '60612', 'city': 'Chicago', 'state': 'Illinois', 'country': 'United States', 'facility': 'University of Illinois at Chicago', 'geoPoint': {'lat': 41.85003, 'lon': -87.65005}}, {'zip': '60153', 'city': 'Maywood', 'state': 'Illinois', 'country': 'United States', 'facility': 'Loyola University Medical Center', 'geoPoint': {'lat': 41.8792, 'lon': -87.84312}}], 'overallOfficials': [{'name': 'Saul J Weiner, MD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'University of Illinois at Chicago'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'University of Illinois at Chicago', 'class': 'OTHER'}, 'collaborators': [{'name': 'Agency for Healthcare Research and Quality (AHRQ)', 'class': 'FED'}, {'name': 'Loyola University', 'class': 'OTHER'}], 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Professor', 'investigatorFullName': 'Alan Schwartz', 'investigatorAffiliation': 'University of Illinois at Chicago'}}}}