Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'SINGLE', 'whoMasked': ['OUTCOMES_ASSESSOR']}, 'primaryPurpose': 'PREVENTION', 'interventionModel': 'PARALLEL'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 719}}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2013-04'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2015-03', 'completionDateStruct': {'date': '2013-06', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2015-03-07', 'studyFirstSubmitDate': '2009-12-15', 'studyFirstSubmitQcDate': '2009-12-16', 'lastUpdatePostDateStruct': {'date': '2015-03-10', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2009-12-17', 'type': 'ESTIMATED'}, 'primaryCompletionDateStruct': {'date': '2013-06', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': "The percentage of elderly patients who receive a specified high-risk medication from the Beer's list.", 'timeFrame': 'Earlier of hospital stay or end of study'}], 'secondaryOutcomes': [{'measure': 'The average number of specified high risk medications prescribed per patient.', 'timeFrame': 'Earlier of hospital stay or end of study'}, {'measure': 'Restraint use', 'timeFrame': 'Earlier of hospital stay or end of study'}, {'measure': 'Falls', 'timeFrame': 'Earlier of hospital stay or end of study'}, {'measure': 'Length of stay', 'timeFrame': 'Earlier of hospital stay or end of study'}, {'measure': 'Total Cost', 'timeFrame': 'Earlier of hospital stay or end of study'}, {'measure': 'Discharge status', 'timeFrame': '6 months'}]}, 'oversightModule': {'oversightHasDmc': False}, 'conditionsModule': {'keywords': ['Electronic prescribing', 'Inappropriate medications', 'Patient safety', 'Elderly patients in the hospital'], 'conditions': ['Elderly']}, 'referencesModule': {'references': [{'pmid': '37818791', 'type': 'DERIVED', 'citation': 'Cole JA, Goncalves-Bradley DC, Alqahtani M, Barry HE, Cadogan C, Rankin A, Patterson SM, Kerse N, Cardwell CR, Ryan C, Hughes C. Interventions to improve the appropriate use of polypharmacy for older people. Cochrane Database Syst Rev. 2023 Oct 11;10(10):CD008165. doi: 10.1002/14651858.CD008165.pub5.'}]}, 'descriptionModule': {'briefSummary': 'Introduction:\n\nThe Beers list identifies medications that should be avoided in persons 65 years or older because they are ineffective, pose an unnecessarily high risk, or a safer alternative is available. In a recent study, we found a high rate of prescribing of Beers list medications to hospitalized patients. At Baystate, 41% of medical patients received at least one Beers list drug classified as "high severity," meaning it carried a high risk for an adverse drug reaction, while 5% received 3 or more. Some Beers drugs have been associated with delirium and falls. When compared to Baystate patients who did not receive a high severity medication, those who did had an increased risk of mortality (7.8% vs. 5.2%), longer length of stay (5.5 days vs. 3.9 days) and higher costs ($11,240 vs. 6243).\n\nSpecific Aims:\n\n1. Quantify the impact of synchronous electronic alerts on physician prescribing of high-severity Beers\' list drugs to hospitalized patients over the age of 65 years.\n2. Compare physician reactions to each drug-specific alert\n\nProject Description:\n\nWe will develop a series of clinical alerts in CIS, Baystate\'s computerized provider order entry system, to reduce the use of potentially inappropriate medications among hospitalized elders. We will randomize providers to electronic alerts or usual care. Whenever a provider randomized to alerts attempts to place an order for a high-risk medication on the Beers list and the intended recipient is over 65 years of age, a synchronous alert (i.e. a "pop-up") will inform the physician about the risks associated with the medication and will propose safer alternatives.\n\nWe will collect data on physician ordering and patient outcomes comparing the number of Beers list prescriptions from providers receiving electronic alerts to those not receiving alerts. Our anticipated outcome is a decrease in inappropriate prescribing during the period when the electronic alerts are activated. Other potential outcomes include decrease in length of stay and a decrease in falls.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['OLDER_ADULT'], 'minimumAge': '65 Years', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Hospitalized patients with Age \\> 65\n\nExclusion Criteria:\n\n* None'}, 'identificationModule': {'nctId': 'NCT01034761', 'briefTitle': 'Using Clinical Alerts to Decrease Inappropriate Medication Prescribing', 'organization': {'class': 'OTHER', 'fullName': 'Baystate Medical Center'}, 'officialTitle': 'Using Clinical Alerts in a Computerized Provider Order Entry System to Decrease Inappropriate Medication Prescribing Among Hospitalized Elders', 'orgStudyIdInfo': {'id': '132454'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'Pop-up alerts', 'description': 'Providers will receive pop-up alerts in the electronic medical record when prescribing one of the specified medications from the Beers list.', 'interventionNames': ['Behavioral: Pop-up alert']}, {'type': 'NO_INTERVENTION', 'label': 'Usual care'}], 'interventions': [{'name': 'Pop-up alert', 'type': 'BEHAVIORAL', 'description': 'Pop-up alert in the electronic medical record whenever the provider enters an order for a specified high risk medication from the Beers list.', 'armGroupLabels': ['Pop-up alerts']}]}, 'contactsLocationsModule': {'locations': [{'zip': '01199', 'city': 'Springfield', 'state': 'Massachusetts', 'country': 'United States', 'facility': 'Baystate Medical Center', 'geoPoint': {'lat': 42.10148, 'lon': -72.58981}}], 'overallOfficials': [{'name': 'Linda J Canty, MD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Baystate Medical Center'}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Baystate Medical Center', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Assistant Clinical Professor of Medine', 'investigatorFullName': 'Linda Canty, MD', 'investigatorAffiliation': 'Baystate Medical Center'}}}}