Risk-Adjusted Monitoring Method for Surgical Data: Methodology for Data Analytics (Work in Progress)
Refereed conference paper presented and published in conference proceedings


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AbstractHospital Authority (HA) has launched a Surgical Outcome Monitoring and Improvement Program (SOMIP), which is used to audit the surgical performance of all public hospitals in Hong Kong. One of the most important information provided by the annual SOMIP report is the changes of 30-day mortality and identify whether and when there is a significant deterioration for each hospital. However, the routine monitoring method used such as Variable Life-adjusted Display (VLAD) and Cumulative Sum Charting (CUSUM) may not be able to detect the change of surgical performance efficiently. Expected improvement or deterioration in surgical outcome may not be exactly the same as the truth. In this paper, we develop a more effective risk-adjusted monitoring method to detect the change in surgical performance. By adapting this method to SOMIP, the proposed monitoring procedure is expected to not only benefit frontline surgeons, anaesthetists and intensivists when they decide on the operations for patients, but also help managers in HA to evaluate the surgical performance and further improve surgical quality.
All Author(s) ListLai X., Liu L., Lai P.B.S., Tsoi K., Wang H., Chong K.C., Zee B.
Name of Conference4th IEEE International Congress on Big Data, BigData Congress 2015
Start Date of Conference27/06/2015
End Date of Conference02/07/2015
Place of ConferenceNew York City
Country/Region of ConferenceUnited States of America
Detailed descriptionorganized by IEEE Computer Society, 27 June – 2 July 2015,
Year2015
Month8
Day17
Pages317 - 319
ISBN9781467372787
ISSN2379-7703
LanguagesEnglish-United Kingdom
KeywordsEWMA, monitoring performance, risk adjustment, Surgical big data

Last updated on 2020-08-07 at 03:07