Ignite Creation Date:
2025-12-24 @ 7:02 PM
Ignite Modification Date:
2026-01-27 @ 7:18 AM
Study NCT ID:
NCT02645357
Status:
COMPLETED
Last Update Posted:
2017-02-09
First Post:
2015-12-31
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Implementing an Evidence-based Computerized Decision Support System Linked to Electronic Health Records to Improve Care for Cancer Patients
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'interventionBrowseModule': {'meshes': [{'id': 'D035061', 'term': 'Control Groups'}], 'ancestors': [{'id': 'D015340', 'term': 'Epidemiologic Research Design'}, {'id': 'D004812', 'term': 'Epidemiologic Methods'}, {'id': 'D008919', 'term': 'Investigative Techniques'}, {'id': 'D012107', 'term': 'Research Design'}, {'id': 'D008722', 'term': 'Methods'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'NONE'}, 'primaryPurpose': 'HEALTH_SERVICES_RESEARCH', 'interventionModel': 'PARALLEL'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 15431}}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2015-11'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2017-02', 'completionDateStruct': {'date': '2017-01', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2017-02-08', 'studyFirstSubmitDate': '2015-12-31', 'studyFirstSubmitQcDate': '2015-12-31', 'lastUpdatePostDateStruct': {'date': '2017-02-09', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2016-01-01', 'type': 'ESTIMATED'}, 'primaryCompletionDateStruct': {'date': '2016-12', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'resolution rates', 'timeFrame': '12 months', 'description': 'the rate at which the issues reported by the reminders are resolved'}]}, 'oversightModule': {'oversightHasDmc': False}, 'conditionsModule': {'keywords': ['Oncology Patients', 'evidence-based', 'computerized', 'decision', 'support system', 'linked', 'electronic health records'], 'conditions': ['Medical Oncology']}, 'referencesModule': {'references': [{'pmid': '27884165', 'type': 'DERIVED', 'citation': 'Moja L, Passardi A, Capobussi M, Banzi R, Ruggiero F, Kwag K, Liberati EG, Mangia M, Kunnamo I, Cinquini M, Vespignani R, Colamartini A, Di Iorio V, Massa I, Gonzalez-Lorenzo M, Bertizzolo L, Nyberg P, Grimshaw J, Bonovas S, Nanni O. Implementing an evidence-based computerized decision support system linked to electronic health records to improve care for cancer patients: the ONCO-CODES study protocol for a randomized controlled trial. Implement Sci. 2016 Nov 25;11(1):153. doi: 10.1186/s13012-016-0514-3.'}]}, 'descriptionModule': {'briefSummary': 'Implementing an evidence-based computerized decision support system linked to electronic health records to improve care for cancer patients.\n\nThe ONCO-CODES (Computerized DEcision Support in ONCOlogy) trial is a pragmatic, parallel group, randomized controlled study with 1:1 allocation ratio Study Duration 12 month Study Center(s) Single-center\n\nObjectives:\n\nThe primary outcome of this trial is a process outcome. i.e. the rate at which the issues reported by the reminders are resolved (resolution rates).', 'detailedDescription': 'Implementing an evidence-based computerized decision support system linked to electronic health records to improve care for cancer patients.\n\nShort Title/Acronym ONCO-CODES Protocol Code IRST100.23\n\nRationale:\n\nComputerized decision support systems (CDSSs) are computer programs that provide clinicians, staff, patients, or other individuals with person-specific, actionable recommendations or management options that are intelligently filtered or presented at appropriate times to enhance health and health care. CDSSs might be integrated with patient electronic health records (EHRs) and evidence-based knowledge. The Investigators designed a pragmatic randomized controlled trial to evaluate the effectiveness of patient-specific, point-of-care reminders generated by the Medilogy Decision Support System (MediDSS) on clinical practice and the quality of care in the Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS. The Investigators hypothesize that MediDSS reminders can increase clinician adherence to guidelines and, eventually, improve the quality of care offered to hospitalized patient. The adoption of CDSSs is likely to increase across healthcare systems due to growing concerns about the quality of medical care and discrepancy between real and ideal practice, continuous calls for a meaningful use of health information technology, and the increasing use of and familiarity with advanced technology among new generations of physicians.\n\nStudy Design:\n\nThe ONCO-CODES (Computerized DEcision Support in ONCOlogy) trial is a pragmatic, parallel group, randomized controlled study with 1:1 allocation ratio Study Duration 12 month Study Center(s) Single-center\n\nObjectives:\n\nThe primary outcome of this trial is a process outcome. i.e. the rate at which the issues reported by the reminders are resolved (resolution rates).\n\nNumber of Subjects:\n\nThe investigators calculated the sample size on the basis of the primary outcome. A sample of 1,704 reminders will be necessary to detect the difference between the two groups (power = 0.90; α =0.05, two-sided; 1:1 allocation). Since estimates for intracluster correlation are not available, Implementing an evidence-based computerized decision support system linked to electronic health records to improve care for cancer patients.\n\nDiagnosis and Main Inclusion Criteria:\n\nThe investigators will include all the patients admitted to the facilities of the IRST IRCCS. There are no exclusion criteria\n\nStatistical Methodology:\n\nAll analyses will follow the intention-to-treat principle: patients will be analyzed in the group to which they have been randomized. Descriptive statistics will be presented.\n\nAll statistical tests will be two-sided. The investigators will use the Stata software to perform all statistical analyses (Stata Corp., College Station, TX, USA).The investigators increased the required sample size (by 20%) to 2,046 reminders to account for clustering by patient.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* The Investigators will include all the EHRs of patients admitted to the facilities of the IRST IRCCS.\n\nExclusion Criteria:\n\n* There are no exclusion criteria.'}, 'identificationModule': {'nctId': 'NCT02645357', 'acronym': 'ONCO-CODES', 'briefTitle': 'Implementing an Evidence-based Computerized Decision Support System Linked to Electronic Health Records to Improve Care for Cancer Patients', 'organization': {'class': 'OTHER', 'fullName': 'Istituto Romagnolo per lo Studio dei Tumori Dino Amadori IRST S.r.l. IRCCS'}, 'officialTitle': 'Effect on Professional Practice and Health Care Outcomes of Computerized Evidence-based Information System and Clinical Decision Support: A Randomized Controlled Trial in Orthopaedics (GR-2009-1606736)', 'orgStudyIdInfo': {'id': 'IRST100.23'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'computer reminders on clinical practice', 'description': 'on-screen, point-of-care computer reminders on clinical practice.', 'interventionNames': ['Other: computer reminders on clinical practice']}, {'type': 'OTHER', 'label': 'Control group', 'description': 'No on-screen, point-of-care computer reminders on clinical practice.', 'interventionNames': ['Other: Control group']}], 'interventions': [{'name': 'computer reminders on clinical practice', 'type': 'OTHER', 'description': 'on-screen, point-of-care computer reminders on clinical practice.', 'armGroupLabels': ['computer reminders on clinical practice']}, {'name': 'Control group', 'type': 'OTHER', 'description': 'control group', 'armGroupLabels': ['Control group']}]}, 'contactsLocationsModule': {'locations': [{'zip': '47014', 'city': 'Meldola', 'country': 'Italy', 'facility': 'Oncologia Medica, IRST IRCCS, Meldola', 'geoPoint': {'lat': 44.12775, 'lon': 12.0626}}], 'overallOfficials': [{'name': 'Alessandro Passardi, MD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'IRST IRCCS'}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Istituto Romagnolo per lo Studio dei Tumori Dino Amadori IRST S.r.l. IRCCS', 'class': 'OTHER'}, 'collaborators': [{'name': 'Ministry of Health, Italy', 'class': 'OTHER_GOV'}, {'name': 'University of Milan', 'class': 'OTHER'}, {'name': "I.R.C.C.S Ospedale Galeazzi-Sant'Ambrogio", 'class': 'OTHER'}, {'name': 'Catholic University of the Sacred Heart', 'class': 'OTHER'}, {'name': 'Duodecim, Finnish Medical Association, Helsinki', 'class': 'UNKNOWN'}, {'name': 'Mario Negri Institute for Pharmacological Research', 'class': 'OTHER'}, {'name': 'Ottawa Hospital Research Institute', 'class': 'OTHER'}], 'responsibleParty': {'type': 'SPONSOR'}}}}