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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
Integrating data to facilitate clinical research: a case study
Ilana N Ackerman1, Richard H Osborne
1Centre for Health, Exercise and Sports Medicine, School of Physiotherapy, University of Melbourne and Centre for Rheumatic Diseases, Royal Melbourne Hospital, Parkville, Victoria, Australia. i.ackerman@pgrad.unime.b.edu.au
Abstract:
The integration of routine clinical administrative activities into ongoing rigorous clinical research poses challenges for both clinicians and researchers. This case study describes the development of a responsive database system used to facilitate comprehensive longitudinal research into the outcomes of patients waiting for hip and knee replacement surgery in a large public teaching hospital. The initial research procedure was paper-based, with manual patient matching and data entry. This process was time-consuming and associated with substantial risk of error and omissions, necessitating the design of a better system. An integrated database system was designed to receive daily electronic updates of the orthopaedic waiting-list and scheduled clinic and surgery dates. Using readily available software (Microsoft Access), new patients were identified through specifying inclusion and exclusion criteria which allowed rapid and complete recruitment at time of entry to the waiting-list. The integrated system specified the appropriate timing of multiple follow-up assessments, provided prompt information on recruitment for reporting purposes and integrated multiple linked research projects within one database. Seamless exporting of data to statistical programs for analysis was also enabled. This simple integrated approach facilitated efficient execution of a longitudinal study from recruitment to statistical analysis while maximising confidentiality and minimising resources required. This case study describes the development and design of a simple system which could be easily adapted for database management in hospital or clinic-based settings according to local requirements.
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