ArticleInternational journal of population data science2019
Using deterministic record linkage to link ambulance and emergency department data: is it possible without patient identifiers? A case study from the UK.
Article in International journal of population data science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 8 citations in OpenAlex.
- Observational
- Natural language processing-driven knowledge graphs for transformative public health intelligence and research datasets in urgent and emergency care.Frontiers in public health · 2026Article
- Ascertaining injury risk issues through big data analysis: text-mining based analysis of national emergency response data.Frontiers in public health · 2024Article
- Linking Ambulance Records with Hospital and Death Index Data to Evaluate Patient Outcomes.International journal of general medicine · 2022Article
- Lessons in Linkage: combining administrative data using deterministic linkage for surveillance of sports and recreation injuries in Florida, United States.International journal of population data science · 2022Article
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Authors and funding
9 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionRoutine linkage of emergency ambulance records with those from the emergency department is uncommon in the UK. Our study, known as the Pre-Hospital Emergency Department Data Linking Project (PHED Data), aimed to link records of all patients conveyed by a single emergency ambulance service to thirteen emergency departments in the UK from 2012-2016.
objectivesWe aimed to examine the feasibility and resource requirements of collecting de-identified emergency department patient record data and, using a deterministic matching algorithm, linking it to ambulance service data.
methodsWe used a learning log to record contacts and activities undertaken by the research team to achieve data linkage. We also conducted semi-structured interviews with information management/governance staff involved in the process.
resultsWe found that five steps were required for successful data linkage for each hospital trust. The total time taken to achieve linkage was a mean of 65 weeks. A total of 958,057 emergency department records were obtained and, of these, 81% were linked to a corresponding ambulance record. The match rate varied between hospital trusts (50%-94%). Staff expressed strong enthusiasm for data linkage. Barriers to successful linkage were mainly due to inconsistencies between and within acute trusts in the recording of two ambulance event identifiers (CAD and call sign). Further data cleaning was required on emergency department fields before full analysis could be conducted. Ensuring the data was not re-identifiable limited validation of the matching method.
conclusionWe conclude that deterministic record linkage based on the combination of two event identifiers (CAD and call sign) is possible. There is an appetite for data linkage in healthcare organisations but it is a slow process. Developments in standardising the recording of emergency department data are likely to improve the quality of the resultant linked dataset. This would further increase its value for providing evidence to support improvements in health care delivery. HIGHLIGHTS: Ambulance records are rarely linked to other datasets; this study looks at the feasibility and resource requirement to use deterministic matching to link ambulance and emergency department data for patients conveyed by ambulance to the emergency department.It is possible to link these data, with an average match rate of 81% across 13 emergency departments and one large ambulance trust.All trusts approached provided match-able data and there was an appetite for data linkage; however, it was a long process taking an average of 65 weeks.We conclude that deterministic matching using no patient identifiers can be used in this setting.
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