Estimating the Burden of Alcohol on Ambulance Callouts through Development and Validation of an Algorithm Using Electronic Patient Records

Background: Alcohol consumption places a significant burden on emergency services, including ambulance services, which often represent patients’ first, and sometimes only, contact with health services. We aimed to (1) improve the assessment of this burden on ambulance services in Scotland using a lo...

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Main Authors: Francesco Manca, Jim Lewsey, Ryan Waterson, Sarah M. Kernaghan, David Fitzpatrick, Daniel Mackay, Colin Angus, Niamh Fitzgerald
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:International Journal of Environmental Research and Public Health
Subjects:
Online Access:https://www.mdpi.com/1660-4601/18/12/6363
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spelling doaj-3b30a9ce170c49fc87531df3a6dc6e2f2021-06-30T23:59:06ZengMDPI AGInternational Journal of Environmental Research and Public Health1661-78271660-46012021-06-01186363636310.3390/ijerph18126363Estimating the Burden of Alcohol on Ambulance Callouts through Development and Validation of an Algorithm Using Electronic Patient RecordsFrancesco Manca0Jim Lewsey1Ryan Waterson2Sarah M. Kernaghan3David Fitzpatrick4Daniel Mackay5Colin Angus6Niamh Fitzgerald7Institute of Health and Wellbeing, University of Glasgow, Glasgow G12 8QQ, UKInstitute of Health and Wellbeing, University of Glasgow, Glasgow G12 8QQ, UKBusiness Intelligence Department, Scottish Ambulance Service, Edinburgh EH12 9EB, UKBusiness Intelligence Department, Scottish Ambulance Service, Edinburgh EH12 9EB, UKFaculty of Health Sciences & Sport, University of Stirling, Stirling FK9 4LA, UKInstitute of Health and Wellbeing, University of Glasgow, Glasgow G12 8QQ, UKSchool of Health and Related Research, University of Sheffield, Sheffield S10 2TN, UKFaculty of Health Sciences & Sport, University of Stirling, Stirling FK9 4LA, UKBackground: Alcohol consumption places a significant burden on emergency services, including ambulance services, which often represent patients’ first, and sometimes only, contact with health services. We aimed to (1) improve the assessment of this burden on ambulance services in Scotland using a low-cost and easy to implement algorithm to screen free-text in electronic patient record forms (ePRFs), and (2) present estimates on the burden of alcohol on ambulance callouts in Scotland. Methods: Two paramedics manually reviewed 5416 ePRFs to make a professional judgement of whether they were alcohol-related, establishing a gold standard for assessing our algorithm performance. They also extracted all words or phrases relating to alcohol. An automatic algorithm to identify alcohol-related callouts using free-text in EPRs was developed using these extracts. Results: Our algorithm had a specificity of 0.941 and a sensitivity of 0.996 in detecting alcohol-related callouts. Applying the algorithm to all callout records in Scotland in 2019, we identified 86,780 (16.2%) as alcohol-related. At weekends, this percentage was 18.5%. Conclusions: Alcohol-related callouts constitute a significant burden on the Scottish Ambulance Service. Our algorithm is significantly more sensitive than previous methods used to identify alcohol-related ambulance callouts. This approach and the resulting data have potential for the evaluation of alcohol policy interventions as well as for conducting wider epidemiological research.https://www.mdpi.com/1660-4601/18/12/6363ambulance calloutsburden of alcoholalgorithm developmentroutine health recordsparamedicsScotland
collection DOAJ
language English
format Article
sources DOAJ
author Francesco Manca
Jim Lewsey
Ryan Waterson
Sarah M. Kernaghan
David Fitzpatrick
Daniel Mackay
Colin Angus
Niamh Fitzgerald
spellingShingle Francesco Manca
Jim Lewsey
Ryan Waterson
Sarah M. Kernaghan
David Fitzpatrick
Daniel Mackay
Colin Angus
Niamh Fitzgerald
Estimating the Burden of Alcohol on Ambulance Callouts through Development and Validation of an Algorithm Using Electronic Patient Records
International Journal of Environmental Research and Public Health
ambulance callouts
burden of alcohol
algorithm development
routine health records
paramedics
Scotland
author_facet Francesco Manca
Jim Lewsey
Ryan Waterson
Sarah M. Kernaghan
David Fitzpatrick
Daniel Mackay
Colin Angus
Niamh Fitzgerald
author_sort Francesco Manca
title Estimating the Burden of Alcohol on Ambulance Callouts through Development and Validation of an Algorithm Using Electronic Patient Records
title_short Estimating the Burden of Alcohol on Ambulance Callouts through Development and Validation of an Algorithm Using Electronic Patient Records
title_full Estimating the Burden of Alcohol on Ambulance Callouts through Development and Validation of an Algorithm Using Electronic Patient Records
title_fullStr Estimating the Burden of Alcohol on Ambulance Callouts through Development and Validation of an Algorithm Using Electronic Patient Records
title_full_unstemmed Estimating the Burden of Alcohol on Ambulance Callouts through Development and Validation of an Algorithm Using Electronic Patient Records
title_sort estimating the burden of alcohol on ambulance callouts through development and validation of an algorithm using electronic patient records
publisher MDPI AG
series International Journal of Environmental Research and Public Health
issn 1661-7827
1660-4601
publishDate 2021-06-01
description Background: Alcohol consumption places a significant burden on emergency services, including ambulance services, which often represent patients’ first, and sometimes only, contact with health services. We aimed to (1) improve the assessment of this burden on ambulance services in Scotland using a low-cost and easy to implement algorithm to screen free-text in electronic patient record forms (ePRFs), and (2) present estimates on the burden of alcohol on ambulance callouts in Scotland. Methods: Two paramedics manually reviewed 5416 ePRFs to make a professional judgement of whether they were alcohol-related, establishing a gold standard for assessing our algorithm performance. They also extracted all words or phrases relating to alcohol. An automatic algorithm to identify alcohol-related callouts using free-text in EPRs was developed using these extracts. Results: Our algorithm had a specificity of 0.941 and a sensitivity of 0.996 in detecting alcohol-related callouts. Applying the algorithm to all callout records in Scotland in 2019, we identified 86,780 (16.2%) as alcohol-related. At weekends, this percentage was 18.5%. Conclusions: Alcohol-related callouts constitute a significant burden on the Scottish Ambulance Service. Our algorithm is significantly more sensitive than previous methods used to identify alcohol-related ambulance callouts. This approach and the resulting data have potential for the evaluation of alcohol policy interventions as well as for conducting wider epidemiological research.
topic ambulance callouts
burden of alcohol
algorithm development
routine health records
paramedics
Scotland
url https://www.mdpi.com/1660-4601/18/12/6363
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