Healthcare utilizations are typically measured independently of each other; neglecting the interdependencies between services. An episode of care is suitable for measuring healthcare utilizations of patients with complex health conditions because it tracks all contacts throughout the healthcare system. The overall goal of this research was to construct an episode of care data system to study healthcare utilizations and costs of chronic obstructive pulmonary disease (COPD) exacerbations. To achieve this goal, four related studies were undertaken.
The first study (Chapter 2) evaluated the agreement between emergency department (ED) data and hospital records for capturing transitions between the two care settings. Using the κ statistic as a measure of concordance, we found good agreement between the two data sources for intra-facility transfers; but only fair agreement for inter-facility transfers. The results show that linking multiple data sources would be important to identify all related healthcare utilization across care settings.
The second study (Chapter 3) linked hospital data, ED data, physician billing claims, and outpatient drug records to construct an episode of care data system for COPD patients. Latent class analysis was used to identify COPD patient groups with distinct healthcare pathways. Pathways were associated with outcomes such as mortality and costs. A few individuals followed complex pathways and incurred high costs.
Building on the previous study, the next one (Chapter 4) predicted whether high-cost patients in one episode also incurred high costs in subsequent episodes. Using logistic regression models, we found that patient information routinely collected in administrative health data could satisfactorily predict those who become persistent high users.
The final study (Chapter 5) used a cross-validation approach to compare the performance of eight alternative linear regression models for predicting costs of episodes of COPD exacerbations. The results indicate that the robust regression model, a model not often considered for cost prediction, was among the best models for predicting episode-based costs.
Overall, this research demonstrated how population-based administrative health databases could be linked to construct an episode of care data system for a chronic health condition. The resulting data system supported novel investigations of healthcare system-wide utilizations and costs. / May 2016
| Identifer | oai:union.ndltd.org:MANITOBA/oai:mspace.lib.umanitoba.ca:1993/31226 |
| Date | 07 January 2016 |
| Creators | Kuwornu, John Paul |
| Contributors | Lix, Lisa (Community Health Sciences), Forget, Evelyn (Community Health Sciences) Muthukumarana, Saman (Statistics) Teare, Gary (Community Health Sciences) Quail, Jacqueline (Community Health Sciences) |
| Publisher | Springer, Wolters Kluwer Health |
| Source Sets | University of Manitoba Canada |
| Detected Language | English |
Page generated in 0.0072 seconds