- Abstract:
-
There is growing interest in the use of routinely collected electronic health records to enhance service delivery and facilitate clinical research. It should be possible to detect and measure patterns of care and use the data to monitor improvements but there are methodological and data quality challenges. Driven by the desire to model the impact of a patient self-test blood count monitoring service in patients on chemotherapy, we aimed to (i) establish reproducible methods of process-mining ...
Expand abstract - Publication status:
- Published
- Peer review status:
- Peer reviewed
- Version:
- Accepted Manuscript
- Files:
-
-
(pdf, 470.4kb)
-
- Publisher copy:
- 10.1016/j.ijmedinf.2017.03.011
-
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- Grant:
- Diagnostic Evidence Co-operatives
- Publisher:
- Elsevier Publisher's website
- Journal:
- International Journal of Medical Informatics Journal website
- Volume:
- 103
- Pages:
- 32-41
- Publication date:
- 2017-04-08
- DOI:
- EISSN:
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1872-8243
- ISSN:
-
1386-5056
- Pubs id:
-
pubs:691477
- URN:
-
uri:73faad28-ccfe-436f-88b6-2cc8e8569cc2
- UUID:
-
uuid:73faad28-ccfe-436f-88b6-2cc8e8569cc2
- Local pid:
- pubs:691477
- Language:
- English
- Keywords:
- Copyright holder:
- Elsevier B.V.
- Copyright date:
- 2017
- Notes:
-
Copyright © 2017 Elsevier B.V. This is the accepted manuscript version of the article. The final version is available online from Elsevier at: https://doi.org/10.1016/j.ijmedinf.2017.03.011
Journal article
Process mining routinely collected electronic health records to define real-life clinical pathways during chemotherapy
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