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The clinical research management information system: An institutional database for tracking clinical trials
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Abstracts Using a Simple Computer Database to Enhance Clinic Visit Management Philip H. Frost, Jacqueline M. Smith, Eve Gray
Medical Research Institute of San Francisco, San Francisco, California (P-20) Chnical centers with distributed data entry systems often underuse their computers by limiting use to predesigned forms entry data packages. Clinical staff often perceive the system to be of little value for local clinic activities. Using a simple non-relational database software our staff designed a patient tracking system which serves many clinic management needs. Using PFS: File and it's Report, a patient profile template was designed. The first section contains basic demographic and baseline randomization categories with data fairly constant. Later sections include visit information categories and are updated at each visit. Following each patient contact a new patient profile is generated. The computerized patient profile is useful in many ways. It eliminates need for hand-kept logs such as drug assignments, protocol deviations and morbid events. It provides updated patient information such as address, age, sex, personal M.D. data and baseline data "flags" for required visit procedures; birthday lists; and, tracks other clinic data. This poster will describe the software and process, and display sample forms.
The Clinical Research Management Information System: An Institutional Database for Tracking Clinical Trials E p h r a i m S. Casper, Elinor Miller, S t e p h e n B. Ellis, M a r t h a Z.
Stalker Memorial Sloan-Kettering Cancer Center, New York, New York (P-21) Maximizing research opportunities and monitoring the progress of ongoing trials are responsibilities of large research institutions. A unique database, the Clinical Research Management Information S~,'stem (CRMIS), was developed to track clinical research at Memorial Hospital. Data are collected for every protocol and include: type of research, disease under study, investigator(s), eligibility criteria, study drugs, resources required, and sources of funding. Confidential patient accrual lists are maintained as an institutional record. CRMIS records IRB actions, and serves IRB needs by automatically generating requests for annual progress reports as they become due. CRMIS also interfaces with other institutional data bases. Over the past five years an average of 136 new protocols have been opened annually; over 500 are open at any time. CRMIS reports are useful to investigators and administrators in monitoring and planning clinical research. Data about current studies has facilitated identification of unrecognized research opport-unities, stimulated collaborative research, and is essential for optimal allocation of resources.
Data Editing and Updating Under Centralized and Distributed Systems Walter W. O w e n , Peter R. Gilbert
George Washington University, Rockville, Maryland (P-22) Drawing on our Data Coordinating Center experience in two major, NIH-sponsored, multicenter clinical trials, we address important issues in data editing and updating under centralized and distributed data entry systems. Should intra-form editing be complete or selective? Are the edit checks, performed interactively during distributed data entry sufficient or should there be an additional central editing? What impact does data set size have on the extent and types of edit checking? How can edit programs be written to simplify changes? Should questionable data be retained on the masterirfles while under investigation? How are questionable items flagged? How often should edit messages be sent tc clinics for correction to maximize response and mLnimize turnaround time, and how can outstanding edit messages be tracked? How does a clinic respond if a data item flagged as out-of-range is really accurate? How can audit trials be maintained? Should data be re-edited after correction? Should inter-form edits be performed and, if so, what is the timetable and appropriate format for distributing followup queries to the clinics? What additional checks should be performed on data sets frozen for analysis purposes?
Distributed Data Entry and Electronic Mail in the ONTT, A Multicenter Clinical Trial S t e v e n T. C a m p b e l l , Peter R. Gilbert
George Washington University, Rockville, Maryland (P-23) Patients entering the Optic Neuritis Treatment Trial (ON'I'I'), a major medical investigation sponsored by the National Eye Institute, must be randomized within eight days of the onset of visual symptoms. This motivated the Data Coordinating Center (DCC) to develop user-friendly
Abstracts Using a Simple Computer Database to Enhance Clinic Visit Management Philip H. Frost, Jacqueline M. Smith, Eve Gray
Medical Research Institute of San Francisco, San Francisco, California (P-20) Chnical centers with distributed data entry systems often underuse their computers by limiting use to predesigned forms entry data packages. Clinical staff often perceive the system to be of little value for local clinic activities. Using a simple non-relational database software our staff designed a patient tracking system which serves many clinic management needs. Using PFS: File and it's Report, a patient profile template was designed. The first section contains basic demographic and baseline randomization categories with data fairly constant. Later sections include visit information categories and are updated at each visit. Following each patient contact a new patient profile is generated. The computerized patient profile is useful in many ways. It eliminates need for hand-kept logs such as drug assignments, protocol deviations and morbid events. It provides updated patient information such as address, age, sex, personal M.D. data and baseline data "flags" for required visit procedures; birthday lists; and, tracks other clinic data. This poster will describe the software and process, and display sample forms.
The Clinical Research Management Information System: An Institutional Database for Tracking Clinical Trials E p h r a i m S. Casper, Elinor Miller, S t e p h e n B. Ellis, M a r t h a Z.
Stalker Memorial Sloan-Kettering Cancer Center, New York, New York (P-21) Maximizing research opportunities and monitoring the progress of ongoing trials are responsibilities of large research institutions. A unique database, the Clinical Research Management Information S~,'stem (CRMIS), was developed to track clinical research at Memorial Hospital. Data are collected for every protocol and include: type of research, disease under study, investigator(s), eligibility criteria, study drugs, resources required, and sources of funding. Confidential patient accrual lists are maintained as an institutional record. CRMIS records IRB actions, and serves IRB needs by automatically generating requests for annual progress reports as they become due. CRMIS also interfaces with other institutional data bases. Over the past five years an average of 136 new protocols have been opened annually; over 500 are open at any time. CRMIS reports are useful to investigators and administrators in monitoring and planning clinical research. Data about current studies has facilitated identification of unrecognized research opport-unities, stimulated collaborative research, and is essential for optimal allocation of resources.
Data Editing and Updating Under Centralized and Distributed Systems Walter W. O w e n , Peter R. Gilbert
George Washington University, Rockville, Maryland (P-22) Drawing on our Data Coordinating Center experience in two major, NIH-sponsored, multicenter clinical trials, we address important issues in data editing and updating under centralized and distributed data entry systems. Should intra-form editing be complete or selective? Are the edit checks, performed interactively during distributed data entry sufficient or should there be an additional central editing? What impact does data set size have on the extent and types of edit checking? How can edit programs be written to simplify changes? Should questionable data be retained on the masterirfles while under investigation? How are questionable items flagged? How often should edit messages be sent tc clinics for correction to maximize response and mLnimize turnaround time, and how can outstanding edit messages be tracked? How does a clinic respond if a data item flagged as out-of-range is really accurate? How can audit trials be maintained? Should data be re-edited after correction? Should inter-form edits be performed and, if so, what is the timetable and appropriate format for distributing followup queries to the clinics? What additional checks should be performed on data sets frozen for analysis purposes?
Distributed Data Entry and Electronic Mail in the ONTT, A Multicenter Clinical Trial S t e v e n T. C a m p b e l l , Peter R. Gilbert
George Washington University, Rockville, Maryland (P-23) Patients entering the Optic Neuritis Treatment Trial (ON'I'I'), a major medical investigation sponsored by the National Eye Institute, must be randomized within eight days of the onset of visual symptoms. This motivated the Data Coordinating Center (DCC) to develop user-friendly