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Abstract
Objective To assess the performance of the pandemic medical early warning score (PMEWS) in a cohort of adult patients seen in the community by emergency care practitioners (ECP) and its correlation with ECP decision-making to either ‘treat and leave’ or transfer for hospital assessment.
Methods Cases attended by ECP in South Yorkshire in 2007 in which the final ECP working diagnosis was a respiratory condition were retrospectively identified from the Yorkshire Ambulance Service database. The patient report forms were reviewed for the PMEWS variables and scores calculated using the PMEWS system. The outcome measure was management in the community versus transport to hospital. Receiver operating characteristics (ROC) curves were calculated to assess the discrimination of PMEWS.
Results A cohort of 300 patients was assessed. 217 (72%) were aged 65 years or over, and 272 (91%) had either comorbid disease or impaired functional status. 98 (33%) were deemed to need hospital assessment or admission. The ROC curves suggested that there is good correlation between the PMEWS score and the decision to discharge.
Conclusions PMEWS correlates well with decisions to admit to hospital or leave at home made by extended role practitioners in the patient group studied; however, further prospective work is required to further validate early warning scoring systems in prehospital care.
- Advanced practitioner
- clinical assessment
- clinical management
- emergency ambulance systems
- emergency care practitioners
- emergency care systems
- emergency medical services
- prehospital emergency care
- transportation of patients
- triage
Statistics from Altmetric.com
- Advanced practitioner
- clinical assessment
- clinical management
- emergency ambulance systems
- emergency care practitioners
- emergency care systems
- emergency medical services
- prehospital emergency care
- transportation of patients
- triage
Early warning scores (EWS) have evolved within secondary care to provide early indicators that a patient's condition has deteriorated and may require a higher level of care, usually within an intensive care unit. Their use as ‘track and trigger’ systems has been advocated nationally for patients admitted to hospital.1 Research within the emergency department (ED) has examined the application of a modified version, the pandemic medical early warning score (PMEWS), to adult patients with community-acquired pneumonia and found it to out-perform CURB-65 in predicting hospital admission and requirement for critical care.2
We aimed to assess the performance of the PMEWS score in a cohort of patients seen in the community by emergency care practitioners (ECP) and its correlation with ECP decision-making either to ‘treat and leave’ or transfer for hospital assessment.
Methods
Yorkshire Ambulance Service (YAS) provides emergency medical services to a population of approximately 6.5 million in a large mixed urban and rural area of northern England. The South Yorkshire region includes four major population centres and serves a population of approximately 1.2 million. ECP have been functioning in YAS since 2005. They are a mixture of paramedics and nurses who have undertaken 12 months of additional training at diploma or degree level, and are dispatched single-handed by an ECP in the ambulance control room who uses clinical judgement to select the most suitable calls for attendance regardless of prioritisation code.
Cases attended by ECP in South Yorkshire in 2007, in which the final ECP working diagnosis was a respiratory condition were retrospectively identified from the YAS database. Respiratory cases were chosen for comparability with previous work. The clinical documentation was reviewed for the PMEWS variables and scores calculated (as in figure 1). For consistency with previous work, and to assess the performance of the score in a ‘real world’ pragmatic way, if one or two variables were missing they were assumed to be normal. If three or more were missing the patient was excluded. The outcome measure was management in the community versus transport to hospital. Receiver operating characteristics (ROC) curves were calculated to assess the discrimination of PMEWS.
Pandemic medical early warning score (PMEWS). BP, blood pressure; MEWS, medical early warning score.
A statistical power calculation indicated that 300 cases would be required to achieve statistical significance. Ethical approval was not deemed necessary as the study constituted a review of current practice.
Results
Three hundred and eighty-seven patients were initially identified. Eighty-seven were excluded (56 for incomplete data, 12 for missing records, 11 aged under 16 years, seven not admitted at patient request and one admitted at patient request), leaving a cohort of 300. Two hundred and seventeen (72%) were aged 65 years or over, and 272 (91%) had either comorbid disease or impaired functional status. Ninety-eight (33%) were deemed to need hospital assessment or admission.
Distribution of scores in the physiological component of PMEWS is shown in figure 2 and in the full PMEWS in figure 3. Correlation of scores with need for hospital attendance is shown in figures 4 and 5. ROC curves for both the physiological component and the full score are shown in figure 6. The area under the ROC curves demonstrates there is good discrimination in the scoring system with PMEWS, both with or without social components, for the likelihood of a decision to admit the patient.
Distribution of scores: physiological component only.
Distribution of scores: complete pandemic medical early warning score (PMEWS) scoring.
Correlation of scores with need for hospital attendance: physiological component only.
Correlation of scores with need for hospital attendance: full pandemic medical early warning score (PMEWS).
Receiver operator characteristic curves.
Discussion
Only small amounts of evidence exist to support the use of EWS in any form in the prehospital environment, although it was discussed as an important potential development in work from 2006 on ambulance pre-alert guidance,3 and early small studies appear promising.4
With the Taking Healthcare to the Patient agenda5 in ambulance services, as well as the overall aim of delivering care closer to home for patients, there is an increasing move towards assessment and referral at the first point of contact with unscheduled care services (the front end model). This model carries higher clinical risk than the traditional ambulance service model of ‘treat and convey’. Previous work has shown that community assessment by ambulance staff with extended training can lead to improved 28-day outcomes6 and risk managing these decisions is becoming increasingly important. Studies that have looked at ‘treat and release’ protocols by paramedics trained to a standard level have shown an increased risk of inappropriate decision-making7 and inappropriate use of the protocols provided.8 While various prehospital trauma stratification tools exist, little has been done to assess the use of medical EWS in this environment. A study from South Africa showed patients with low physiological EWS had significantly lower rates of admission.9 Recent work from Ireland used EWS at point of attendance at the ED and found that it had the potential to be used as a triage tool to identify ‘at-risk’ patients from initial contact.10
We aimed to establish whether the PMEWS correlated with decisions made by autonomous practitioners to assess its potential suitability for use as a decision support tool in the prehospital environment. Our results would suggest there is significant potential for the use of a physiologically based score in this role, in line with previous findings in an unselected patient population within the ED.
One of the main modifications within PMEWS is the inclusion of functional status, comorbidities and social factors, elements that are particularly pertinent when assessing patients in the community regarding their safety to remain in their current environment. In our sample both the physiological score alone and the physiological–social score perform well in predicting ability to discharge. The physiological score alone performs marginally (although not statistically significantly) better in pure terms, but as a pragmatic tool the inclusion of social factors adds an area of ‘absolute’ (as much as there ever is) safety; no patient with a physiological–social score of under 2 in our sample was considered to require transport to hospital.
The authors acknowledge that there is a risk of generalising the results given that a large proportion of the cases were elderly patients; however, most patients with respiratory problems seen in the community would be expected to be older. Children under 16 years were excluded as the physiological variables in PMEWS would be inaccurate, with specific paediatric scoring being required, such work still being developed nationally.11
We would suggest that a further prospective ‘shadow’ trial should evaluate in more detail the relative contributions of physiological and social factors to transport and admission decision-making. In the meantime, PMEWS appears to have value as a decision support and risk management tool within the increasing structure of ‘treat and leave’ protocols in UK ambulance services.
Conclusion
PMEWS provides a tool by which the risk associated with managing a patient in a prehospital setting may be managed more effectively. This work shows it correlates well with decisions to admit to hospital or leave at home made by ECP. Prospective studies are now required with long-term outcomes to assess its practicality for use across a range of medical presentations.
Footnotes
Competing interests None.
Provenance and peer review Not commissioned; externally peer reviewed.