Indiana University-Purdue University Indianapolis (IUPUI) / Community Health Centers (CHCs) play a pivotal role in delivery of primary healthcare to
the underserved, yet have not benefited from a modern data analytics platform that can support
clinical, operational and financial decision making across the continuum of care. This research is
based on a systems redesign collaborative of seven CHC organizations spread across Indiana to
improve efficiency and access to care.
Three research questions (RQs) formed the basis of this research, each of which seeks to
address known knowledge gaps in the literature and identify areas for future research in health
informatics. The first RQ seeks to understand the information needs to support operations at
CHCs and implement an information architecture to support those needs. The second RQ
leverages the implemented data infrastructure to evaluate how advanced analytics can guide
open access scheduling – a specific use case of this research. Finally, the third RQ seeks to
understand how the data can be visualized to support decision making among varying roles in
CHCs.
Based on the unique work and information flow needs uncovered at these CHCs, an end
to-end analytics solution was designed, developed and validated within the framework of a rapid
learning health system. The solution comprised of a novel heterogeneous longitudinal clinic data
warehouse augmented with big data technologies and dashboard visualizations to inform CHCs
regarding operational priorities and to support engagement in the systems redesign initiative.
Application of predictive analytics on the health center data guided the implementation of open
access scheduling and up to a 15% reduction in the missed appointment rates. Performance
measures of importance to specific job profiles within the CHCs were uncovered. This was
followed by a user-centered design of an online interactive dashboard to support rapid
assessments of care delivery. The impact of the dashboard was assessed over time and formally
validated through a usability study involving cognitive task analysis and a system usability scale
questionnaire. Wider scale implementation of the data aggregation and analytics platform through
regional health information networks could better support a range of health system redesign
initiatives in order to address the national ‘triple aim’ of healthcare.
| Identifer | oai:union.ndltd.org:IUPUI/oai:scholarworks.iupui.edu:1805/13388 |
| Date | 15 April 2016 |
| Creators | Kunjan, Kislaya |
| Contributors | Jones, Josette F., Toscos, Tammy, Wu, Huanmei, Holden, Richard |
| Source Sets | Indiana University-Purdue University Indianapolis |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
Page generated in 0.0023 seconds