Indiana University-Purdue University Indianapolis (IUPUI) / Physicians receive multiple CCDs for a single patient encompassing 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 the steps towards a system that integrates multiple CCDs into one
consolidated document for viewing or processing patient-level data. Also, the impact of the
system on healthcare providers’ perceived workload is evaluated.
A modular system is developed to consolidate and de-duplicate CDA-based documents.
The system is engineered to be scalable, extensible and open source. The system’s performance
and output has evaluated first based on synthesized data and later based on real-world CCDs
obtained from INPC database. The accuracy of the consolidation system along with the gaps in
identification of the duplications were assessed. Finally, the impact of the system on healthcare
providers’ workload is evaluated using NASA TLX tool.
All of the synthesized CCDs were successfully consolidated, and no data were lost. The
de-duplication accuracy was 100% based on synthesized data and the processing time for each
document was 1.12 seconds. For real-world CCDs, our system de-duplicated 99.1% of the
problems, 87.0% of allergies, and 91.7% of medications. Although the accuracy of the system is
still very promising, however, there is a minor inaccuracy. Due to system improvements, the
processing time for each document is reduced to average 0.38 seconds for each CCD.
The result of NASA TLX evaluation shows that the system significantly decreases
healthcare providers’ perceived workload. Also, it is observed that information reconciliation
reduces the medical errors. The time for review of medical documents review time is significantly
reduced after CCD consolidation.
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.
| Identifer | oai:union.ndltd.org:IUPUI/oai:scholarworks.iupui.edu:1805/11262 |
| Date | 09 1900 |
| Creators | Hosseini Asanjan, Seyed Masoud |
| Contributors | Jones, Josette F., Dixon, Brian E., Vreeman, Daniel J., Faiola, Anthony, Wu, Huanmei |
| Source Sets | Indiana University-Purdue University Indianapolis |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
Page generated in 0.0019 seconds