Our findings suggest that the NEWS could successfully be used by ambulance services to identify patients most at risk from subsequent deterioration. The implementation of this early warning system has the potential to support ambulance clinician decision making, providing an additional tool to identify and appropriately escalate care for acutely unwell patients.
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. Objectives We 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. Methods We 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. Results We 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. Conclusion We 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.
SummaryObjective: Georgetown University has a student run Emergency Medical Services (EMS) organization with over 100 emergency medical technicians (EMTs). We set out to determine whether implementing an electronic patient care report (ePCR) system was associated with improved physical exam documentation. Methods: This study evaluated documentation of the physical exam on prehospital patient care reports (PCRs). An ePCR system was implemented. ePCR documentation was compared to that of the previously used paper PCRs. This study looked retrospectively at 154 PCRs. 77 were hand written PCRs from before the electronic system. The PCRs involved chief complaints that were primarily respiratory, neurologic, or both. 77 ePCRs of matching chief complaint categories were used for comparison. Each chart was reviewed for completion of certain physical exam findings. The mean percentage of documented components from the ePCRs was compared to that of the hand written PCRs. The null hypothesis was that the absolute increase in the mean was not more than 20 percent. The two exclusion criteria were PCRs completed by study investigators after the design of the project and partially or completely missing PCRs. Results: The absolute increase in mean physical exam component documentation was 36% (95% CI = 29-43%). A weighted kappa of 0.894 showed very good agreement between chart reviewers. Conclusions: This study rejected the null hypothesis that the ePCR system was associated with a mean increase of no more than 20%. It observed increase in physical exam documentation. Limitations of this study included the inability to determine whether documentation of physical exam findings reflected performance of the physical exam, and what components of the ePCR system bundle were responsible for the increase in physical exam component documentation.
BackgroundMost callers to 999 ambulance services are transported to hospital emergency departments (EDs), but ambulance services receive no information on patient outcomes. PHED Data is a two-year mixed-methods observational study of the process and potential benefits of linking data from EDs with ambulance service data to allow analysis of patient outcomes. We report on our first aim, to examine the potential opportunities and challenges to routinely linking these data.MethodsWe approached six acute trusts, selected to give a range of performance, location and size, from an English metropolitan area. We used a structured learning log to collect data on the process, time input and reflections. We analysed these data with descriptive statistics, and qualitatively for themes.ResultsAll six trusts we approached agreed to participate. Data were linked using an algorithm based on date, time and patient demographics. We achieved a dataset of 7 75 018 records covering 2012–2016, and a linkage rate of 81%.We identified five stages of the process: senior approval; exploring data availability; information governance agreement; data transfer and linking.The most intensive phases were; negotiating senior approval (mean research team input per trust of 8 hours 5 min [SD 8 hours 3 min] plus additional time from acute trusts), and data linkage (mean research team input per trust 12 hours 40 min [SD 7 hours 4 min]).The stage which took the longest was information governance (mean 19 weeks).Key themes included the positive attitudes of trusts to participating, the range of decision-makers involved, and the need for sustained input from the research team.ConclusionsWe have found the process of data linkage to be feasible, but requires dedicated time from research and trust staff, over a prolonged period, in order to achieve initial set up. Linked data are now being analysed.
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