title: Consolidating CCDs from multiple data sources: a modular approach.
abstract: BACKGROUND
  Healthcare providers sometimes receive multiple continuity of care documents (CCDs) for a single patient encompassing the patient's various encounters and medical history recorded in different information systems. It is cumbersome for providers to explore different pages of CCDs to find specific data which can be duplicated or even conflicted. This study describes initial steps toward a modular system that integrates and de-duplicates multiple CCDs into one consolidated document for viewing or processing patient-level data.
  
  
  METHODS
  The authors developed a prototype system to consolidate and de-duplicate CCDs. The system is engineered to be scalable, extensible, and open source. Using a corpus of 150 de-identified CCDs synthetically generated from a single data source with a common vocabulary to represent 50 unique patients, the authors tested the system's performance and output. Performance was measured based on document throughput and reduction in file size and volume of data. The authors further compared the output of the system with manual consolidation and de-duplication. Testing across multiple vendor systems or implementations was not performed.
  
  
  RESULTS
  All of the input CCDs was successfully consolidated, and no data were lost. De-duplication significantly reduced the number of entries in different sections (49% in Problems, 60.6% in Medications, and 79% in Allergies) and reduced the size of the documents (57.5%) as well as the number of lines in each document (58%). The system executed at a rate of approximately 0.009-0.03 s per rule depending on the complexity of the rule.
  
  
  CONCLUSIONS
  Given increasing adoption and use of health information exchange (HIE) to share data and information across the care continuum, duplication of information is inevitable. A novel system designed to support automated consolidation and de-duplication of information across clinical documents as they are exchanged shows promise. Future work is needed to expand the capabilities of the system and further test it using heterogeneous vocabularies across multiple HIE scenarios.
authors.affiliation: School of Informatics and Computing, Department of BioHealth Informatics, Indiana University Regenstrief Institute, Inc. hosseini@umail.iu.edu.
authors.forename: Masoud
authors.initials: M
authors.lastname: Hosseini
authors.affiliation: CreateIT, Inc., Richmond, Indiana, USA.
authors.forename: Jonathan
authors.initials: J
authors.lastname: Meade
authors.affiliation: CreateIT, Inc., Richmond, Indiana, USA.
authors.forename: Jamie
authors.initials: J
authors.lastname: Schnitzius
authors.affiliation: Regenstrief Institute, Inc. Richard M. Fairbanks School of Public Health at IUPUI, Indiana University Center for Health Information and Communication, Department of Veterans Affairs, Veterans Health Administration, Health Services Research and Development Service CIN 13-416, Richard L. Roudebush VA Medical Center.
authors.forename: Brian E
authors.initials: BE
authors.lastname: Dixon
mesh_terms: D003266:Continuity of Patient Care; D057286:Electronic Health Records; D066275:Health Information Exchange; D057208:Health Level Seven; D006801:Humans; D020407:Internet; D062527:Meaningful Use; D008498:Medical Record Linkage
keywords: Health Level Seven (HL7); consolidation; continuity of care document (CCD); de-duplication; health information exchange (HIE); meaningful use; medical informatics