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amber contains records of published research authored by staff working in NHS ambulance services in England and Scotland. amber is managed by the Library and Knowledge Services for NHS Ambulance Services in England [LKS ASE]. For more information see the About pages or contact LKS ASE.

UPDATE: amber is evolving to include the published output of the Scottish Ambulance Service.  Starting in July 2021 colleagues at Manchester University NHS Trust Library Service will be adding publications from 2006 – to date. 

We are committed to delivering and maintaining a high quality of data.  If you are aware of any inaccuracies in the data on amber do contact us and we will correct it.  If you believe your work should be included in amber and it is currently not there please let us know.

  • Initial prehospital vital signs to predict subsequent adverse hospital outcomes

    Williams, T.A.; Ho, K.M.; Tohira, H.; Fatovich, D.M.; Bailey, P.; Brink, D.; Gowens, Paul; Perkins, Gavin; Finn, Judith (2017-05-21)
    There is growing interest to improve identification of the critically ill patient in the prehospital setting.1–3 We aimed to assess whether initial vital physiological signs in the prehospital setting can predict subsequent adverse hospital outcomes, defined as intensive care (ICU) admission or death in the emergency department (ED). https://bmjopen.bmj.com/content/7/Suppl_3/A5.3 This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. http://creativecommons.org/licenses/by-nc/4.0/ DOI http://dx.doi.org/10.1136/bmjopen-2017-EMSabstracts.14
  • Investigating the population characteristics, processes and outcomes of pre-hospital psychiatric and self-harm emergencies in Scotland: a national record linkage study

    Duncan, E.; Best, C.; Dougall, N.; Skor, S.; Fitzpatrick, David; Evans, J.; Corfield, Alasdair; Goldie, I.; Maxwell, M.; Snooks, Helen; et al. (2017-05-21)
    To investigate the demographic characteristics, care pathways, and clinical and service outcomes of people who present to ambulance services with a psychiatric or self-harm emergency. https://bmjopen.bmj.com/content/7/Suppl_3/A11.3 This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. http://creativecommons.org/licenses/by-nc/4.0/ DOI http://dx.doi.org/10.1136/bmjopen-2017-EMSabstracts.29
  • Use of a modified Delphi process to develop research priorities in major trauma

    McElroy, Luke; Robinson, Lisa; Battle, Ceri; Laidlow, Lynn; Teager, Alistair; de Bernard, Louis; McGillvray, Jack; Tsang, Kevin; Bell, Steve; Leech, Caroline; et al. (2021-06-16)
  • Frontiers of performance: using a mathematical model to discover unobservable performance limits in a pre-hospital and retrieval service

    Moultrie, Chris; Corfield, Alasdair; Pell, J.; Mackay, Daniel (2017-05-21)
    We aimed to establish if a validated computer model could derive otherwise unobservable performance limits for a physician-led pre-hospital and retrieval service. https://bmjopen.bmj.com/content/7/Suppl_3/A18.1 This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. http://creativecommons.org/licenses/by-nc/4.0/ DOI http://dx.doi.org/10.1136/bmjopen-2017-EMSabstracts.45
  • Forecasting the demand profile for a physician-led pre-hospital care service using a mathematical model

    Moultrie, Chris; Corfield, Alasdair; Pell, J.; Mackay, Daniel (2017-05-21)
    We aimed to investigate if a queueing-theory derived, stochastic, computerised mathematical model could accurately predict the number and seasonal pattern of primary pre-hospital missions undertaken by a physician-led pre-hospital and retrieval service in 2016. https://bmjopen.bmj.com/content/7/Suppl_3/A18.2.info This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. http://creativecommons.org/licenses/by-nc/4.0/ DOI http://dx.doi.org/10.1136/bmjopen-2017-EMSabstracts.46

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