A methodology to extract outcomes from routine healthcare data for patients with locally advanced non-small cell lung cancer

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Title: A methodology to extract outcomes from routine healthcare data for patients with locally advanced non-small cell lung cancer
Author(s): Wong, S-L
Ricketts, K
Royle, G
Williams, M
Mendes, R
Item Type: Journal Article
Abstract: BACKGROUND: Outcomes for patients in UK with locally advanced non-small cell lung cancer (LA NSCLC) are amongst the worst in Europe. Assessing outcomes is important for analysing the effectiveness of current practice. However, data quality is inconsistent and regular large scale analysis is challenging. This project investigates the use of routine healthcare datasets to determine progression free survival (PFS) and overall survival (OS) of patients treated with primary radical radiotherapy for LA NSCLC. METHODS: All LA NSCLC patients treated with primary radical radiotherapy in a 2 year period were identified and paired manual and routine data generated for an initial pilot study. Manual data was extracted information from hospital records and considered the gold standard. Key time points were date of diagnosis, recurrence, death or last clinical encounter. Routine data was collected from various data sources including, Hospital Episode Statistics, Personal Demographic Service, chemotherapy data, and radiotherapy datasets. Relevant event dates were defined by proxy time points and refined using backdating and time interval optimization. Dataset correlations were then tested on key clinical outcome indicators to establish if routine data could be used as a reliable proxy measure for manual data. RESULTS: Forty-three patients were identified for the pilot study. The manual data showed a median age of 67 years (range 46- 89 years) and all patients had stage IIIA/B disease. Using the manual data, the median PFS was 10.78 months (range 1.58-37.49 months) and median OS was 16.36 months (range 2.69-37.49 months). Based on routine data, using proxy measures, the estimated median PFS was 10.68 months (range 1.61-31.93 months) and estimated median OS was 15.38 months (range 2.14-33.71 months). Overall, the routine data underestimated the PFS and OS of the manual data but there was good correlation with a Pearson correlation coefficient of 0.94 for PFS and 0.97 for OS. CONCLUSIONS: This is a novel approach to use routine datasets to determine outcome indicators in patients with LA NSCLC that will be a surrogate to analysing manual data. The ability to enable efficient and large scale analysis of current lung cancer strategies has a huge potential impact on the healthcare system.
Publication Date: 11-Apr-2018
Date of Acceptance: 16-Mar-2018
URI: http://hdl.handle.net/10044/1/58701
DOI: https://dx.doi.org/10.1186/s12913-018-3029-6
ISSN: 1472-6963
Publisher: BioMed Central
Journal / Book Title: BMC Health Services Research
Volume: 18
Issue: 1
Sponsor/Funder: Imperial College Healthcare NHS Trust- BRC Funding
Funder's Grant Number: RDB01 79560
Copyright Statement: © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/ ), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated.
Keywords: LA NSCLC
Routine datasets
Routine datasets
1117 Public Health And Health Services
0807 Library And Information Studies
Health Policy & Services
Publication Status: Published
Conference Place: England
Article Number: ARTN 278
Appears in Collections:Division of Surgery
Division of Cancer
Faculty of Medicine

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