Name
Title | ||
|---|---|---|
Evaluating the relative value of care interventions based on clinical pathway variation detection and propensity score. |
Abstract | ||
|---|---|---|
Value-based healthcare (VBHC) aims to increase the value derived from resources available for a population. Identifying the value of care interventions is significant for improving medical quality and reduce costs. With the increase of electronic medical record (EMR), process mining technology provides the possibility to this goal. We proposed a complete framework range from discovering to evaluating the relative value of care interventions, which integrates clinical pathway variation detection algorithm to align event logs with process models, propensity score method to decrease confounding bias in observational studies, and value function based on cost-utility analysis for quantifying the result of interventions. To verify our method, a real-life data set of ischemic stroke treatment from one hospital was checked with the process model of clinical pathways (CPs). We found that neuroprotective drugs were the most frequent activity with effectiveness not fully demonstrated in the CP after detecting the variation. Experimental tests showed the outcome measure and their relative values for the commonly applied neuroprotective drugs in stroke treatment. It is the first EMR-based work for assessing the value of activities computably and uniformly in the clinical process, offering a pragmatic way for VBHC. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/BIBM49941.2020.9313546 | BIBM |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Haifeng Xu | 1 | 0 | 4.06 |
| Hui Yan | 2 | 0 | 0.34 |
| Jianfei Pang | 3 | 0 | 3.04 |
| Shan Nan | 4 | 0 | 0.34 |
| Xi Yang | 5 | 0 | 1.69 |
| Zhao Dongsheng | 6 | 0 | 6.42 |