Variance analysis in task-time matrix clinical pathways

H. Yan; P. van Gorp; U. Kaymak; L. Ji; X. Lu; C.C. Chiau; H.H.M. Korsten; H. Duan

doi:10.1109/BHI.2017.7897253

Variance analysis in task-time matrix clinical pathways

H. Yan, P. van Gorp, U. Kaymak, L. Ji, X. Lu, C.C. Chiau, H.H.M. Korsten, H. Duan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

5 Citations (Scopus)

Abstract

Clinical pathways are popular healthcare management tools to standardise care and ensure quality. Measuring pathway conformance and analysing variances gives valuable feedback in the context of care improvement trajectories. The Business Process Model and Notation (BPMN) language and Task-Time matrices are popular ways to model clinical pathways. A key step in variance analysis involves the computation of optimal alignments between the pathway model and patient-specific traces. This paper presents for this step a new algorithm which reduces the time for finding deviations from hours to minutes. A case study on variance analysis is undertaken, where a clinical pathway from the practice and a large set of patients data from an EMR database are used. The results demonstrate that automated variance analysis between BPMN Task-Time models and real-life EMR data is feasible. We also provide meaningful insights for further improvement.

Original language	English
Title of host publication	2017 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2017, 16-19 February 2017, Orlando, Florida
Place of Publication	Piscataway
Publisher	Institute of Electrical and Electronics Engineers
Pages	253-256
Number of pages	4
ISBN (Electronic)	978-1-5090-4179-4
ISBN (Print)	978-1-5090-4180-0
DOIs	https://doi.org/10.1109/BHI.2017.7897253
Publication status	Published - 11 Apr 2017
Event	International Conference on Biomedical and Health Informatics (BHI 2017), 16-19 February 2017, Orlando, Florida: Integrative Informatics for Precision and Preventive Medicine - Orlando, United States Duration: 17 Feb 2017 → 19 Feb 2017 Conference number: 2017 http://bhi.embs.org/2017/

Conference

Conference	International Conference on Biomedical and Health Informatics (BHI 2017), 16-19 February 2017, Orlando, Florida
Abbreviated title	BHI 2017
Country/Territory	United States
City	Orlando
Period	17/02/17 → 19/02/17
Internet address	http://bhi.embs.org/2017/

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10.1109/BHI.2017.7897253

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Yan, H., van Gorp, P., Kaymak, U., Ji, L., Lu, X., Chiau, C. C., Korsten, H. H. M., & Duan, H. (2017). Variance analysis in task-time matrix clinical pathways. In 2017 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2017, 16-19 February 2017, Orlando, Florida (pp. 253-256). Article 7897253 Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/BHI.2017.7897253

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abstract = "Clinical pathways are popular healthcare management tools to standardise care and ensure quality. Measuring pathway conformance and analysing variances gives valuable feedback in the context of care improvement trajectories. The Business Process Model and Notation (BPMN) language and Task-Time matrices are popular ways to model clinical pathways. A key step in variance analysis involves the computation of optimal alignments between the pathway model and patient-specific traces. This paper presents for this step a new algorithm which reduces the time for finding deviations from hours to minutes. A case study on variance analysis is undertaken, where a clinical pathway from the practice and a large set of patients data from an EMR database are used. The results demonstrate that automated variance analysis between BPMN Task-Time models and real-life EMR data is feasible. We also provide meaningful insights for further improvement.",

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Yan, H, van Gorp, P , Kaymak, U, Ji, L, Lu, X, Chiau, CC, Korsten, HHM & Duan, H 2017, Variance analysis in task-time matrix clinical pathways. in 2017 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2017, 16-19 February 2017, Orlando, Florida., 7897253, Institute of Electrical and Electronics Engineers, Piscataway, pp. 253-256, International Conference on Biomedical and Health Informatics (BHI 2017), 16-19 February 2017, Orlando, Florida, Orlando, Florida, United States, 17/02/17. https://doi.org/10.1109/BHI.2017.7897253

Variance analysis in task-time matrix clinical pathways. / Yan, H.; van Gorp, P.; Kaymak, U. et al.
2017 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2017, 16-19 February 2017, Orlando, Florida. Piscataway: Institute of Electrical and Electronics Engineers, 2017. p. 253-256 7897253.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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T1 - Variance analysis in task-time matrix clinical pathways

AU - Yan, H.

AU - van Gorp, P.

AU - Kaymak, U.

AU - Ji, L.

AU - Lu, X.

AU - Chiau, C.C.

AU - Korsten, H.H.M.

AU - Duan, H.

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AB - Clinical pathways are popular healthcare management tools to standardise care and ensure quality. Measuring pathway conformance and analysing variances gives valuable feedback in the context of care improvement trajectories. The Business Process Model and Notation (BPMN) language and Task-Time matrices are popular ways to model clinical pathways. A key step in variance analysis involves the computation of optimal alignments between the pathway model and patient-specific traces. This paper presents for this step a new algorithm which reduces the time for finding deviations from hours to minutes. A case study on variance analysis is undertaken, where a clinical pathway from the practice and a large set of patients data from an EMR database are used. The results demonstrate that automated variance analysis between BPMN Task-Time models and real-life EMR data is feasible. We also provide meaningful insights for further improvement.

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ER -

Variance analysis in task-time matrix clinical pathways

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