Validation of an algorithm using inpatient electronic health records to determine the presence and severity of cirrhosis in patients with hepatocellular carcinoma in England: an observational study. Issue 7 (9th July 2019)
- Record Type:
- Journal Article
- Title:
- Validation of an algorithm using inpatient electronic health records to determine the presence and severity of cirrhosis in patients with hepatocellular carcinoma in England: an observational study. Issue 7 (9th July 2019)
- Main Title:
- Validation of an algorithm using inpatient electronic health records to determine the presence and severity of cirrhosis in patients with hepatocellular carcinoma in England: an observational study
- Authors:
- Driver, Robert J
Balachandrakumar, Vinay
Burton, Anya
Shearer, Jessica
Downing, Amy
Cross, Tim
Morris, Eva
Rowe, Ian A - Abstract:
- Abstract : Objectives: Outcomes in hepatocellular carcinoma (HCC) are determined by both cancer characteristics and liver disease severity. This study aims to validate the use of inpatient electronic health records to determine liver disease severity from treatment and procedure codes. Design: Retrospective observational study. Setting: Two National Health Service (NHS) cancer centres in England. Participants: 339 patients with a new diagnosis of HCC between 2007 and 2016. Main outcome: Using inpatient electronic health records, we have developed an optimised algorithm to identify cirrhosis and determine liver disease severity in a population with HCC. The diagnostic accuracy of the algorithm was optimised using clinical records from one NHS Trust and it was externally validated using anonymised data from another centre. Results: The optimised algorithm has a positive predictive value (PPV) of 99% for identifying cirrhosis in the derivation cohort, with a sensitivity of 86% (95% CI 82% to 90%) and a specificity of 98% (95% CI 96% to 100%). The sensitivity for detecting advanced stage cirrhosis is 80% (95% CI 75% to 87%) and specificity is 98% (95% CI 96% to 100%), with a PPV of 89%. Conclusions: Our optimised algorithm, based on inpatient electronic health records, reliably identifies and stages cirrhosis in patients with HCC. This highlights the potential of routine health data in population studies to stratify patients with HCC according to liver disease severity.
- Is Part Of:
- BMJ open. Volume 9:Issue 7(2019)
- Journal:
- BMJ open
- Issue:
- Volume 9:Issue 7(2019)
- Issue Display:
- Volume 9, Issue 7 (2019)
- Year:
- 2019
- Volume:
- 9
- Issue:
- 7
- Issue Sort Value:
- 2019-0009-0007-0000
- Page Start:
- Page End:
- Publication Date:
- 2019-07-09
- Subjects:
- hepatology -- hepatobiliary tumours -- epidemiology
Medicine -- Research -- Periodicals
610.72 - Journal URLs:
- http://www.bmj.com/archive ↗
http://bmjopen.bmj.com/ ↗ - DOI:
- 10.1136/bmjopen-2018-028571 ↗
- Languages:
- English
- ISSNs:
- 2044-6055
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
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- 20622.xml