In this observational study of people aged ≥ 50 using an ambulance service, a large proportion of patients (58.7%) were frail (CFS ≥ 5). Frailty prevalence increased with advancing age and deprivation. Ambulance crews spent more time attending to people who were frail compared to people who were not. However, frail people were less likely to be conveyed to hospital.
Frailty is not well described in older populations using the ambulance service, and to our knowledge there are no published studies reporting frailty in this setting. Published estimates of community frailty prevalence vary, reflecting heterogeneity in clinical settings, population characteristics and frailty measures.
The English Longitudinal Study of Ageing (ELSA) provides data for several frailty metrics. Analyses of ELSA data have generated estimates of frailty prevalence ranging from 14% of adults aged ≥ 606 to 8% among adults aged ≥ 50 . The latter study also found higher prevalence of frailty in both the most deprived areas and urban areas of England. An analysis using primary care data, restricted to people aged ≥ 65, found 12% were moderately frail and 3% severely frail .
We did not observe the expected higher prevalence of frailty amongst women [37, 38] suggesting that older people who use the ambulance service are not representative of the older population in general.
On average, paramedics spent eight minutes longer on-scene when attending frail patients compared to those who were not frail. Frailty is associated with medical complexity and instability , so a prolonged assessment may be justified. Furthermore, any additional community care for people not conveyed to hospital is likely to involve multiple providers and may be time consuming to arrange. In our study, frailty was associated with higher average NEWS2. However, frail patients were also more likely to be managed in the community or discharged on scene. Our data do not offer detailed insights into why patients with frailty were less likely to be conveyed to hospital. Possible influences on the paramedics’ clinical decision-making include advance care plans, availability of support from community services, or patients’ reluctance to go to hospital, particularly during the Covid-19 pandemic. Nevertheless, our study suggests a significant proportion of ambulance service time is spent attending frail patients who ultimately do not require conveyance to hospital.
This study used a pragmatic design to collect information on patient frailty in the ambulance setting, and is amongst the first to measure frailty and its association with key outcomes in this setting. Paramedic allocation to calls was random, but decisions to record frailty were not, as paramedics volunteered to enrol in the study.
To address the potential for selection bias, we reweighted our sample of callouts to match the population of eligible callouts on factors known to be associated with frailty. Future studies in this setting should utilise systematic random sampling strategies to ensure accurate estimates of frailty prevalence.
When a patient is acutely unwell, knowledge of usual levels of functional ability and daily activities helps clinical decision-making. Information from the patient, family or care records can be used to allocate a baseline CFS reflecting the patient’s status two weeks before the current clinical episode . We were missing a proportion of these data (42% across all callouts), which suggests that generating this assessment is challenging in the ambulance setting.
The non-missing baseline scores may be subject to recall bias as patients (especially those requiring attendance by a paramedic) may not accurately recall health and status information over this time frame, and cognitive and hearing impairment are common in this population.
Further research is needed to understand the barriers to obtaining these data in clinical practice. Additional training for ambulance clinicians (to assess frailty over time) and enhancing access to primary care records (which are likely to hold data sufficient to generate historical or longitudinal frailty status) are possible solutions.
Study paramedics received training on how to use the CFS online, rather than face to face due to the coronavirus pandemic. There are limitations associated with online training; study paramedics had no opportunity to discuss any aspect of their learning, or clarify potential misunderstandings regarding the CFS. We were unable to judge the study paramedics knowledge of the CFS following completion of the training package, nor determine their competency to apply it in clinical practice. However, similar online frailty training packages have been rated as effective, feasible, and met with high satisfaction from users .
COVID-19 is likely to have influenced decisions on conveyance to hospital, particularly with older patients involved in the study. Ambulance conveyance rates to ED’s varied significantly early in the pandemic . However, given the high conveyance rate observed in this study any change in patient or clinician behaviour due to the pandemic appears limited.
Study data were collected during a six-month period. We did not observe any meaningful or systematic variations in frailty scores over this time in our sensitivity analyses. However, it is important to acknowledge that some of the seasonal effects associated with variation in ambulance call patterns  may have influenced the characteristics of the study participants.
In the future, paramedics are likely to have increasing involvement with a growing population of older people living with frailty. Enhancing clinical understanding and recognition of frailty improves patient outcomes and patient-centred care in acute settings .
Routine frailty assessment by the ambulance service could support clinical decision making and provision of appropriate community care for those not conveyed to hospital. This study suggests that paramedics would require more training to be confident in frailty assessment. Improved record sharing between different care settings could allow access to automatically generated frailty scores such as the hospital frailty index  or electronic frailty index  and support routine collection of frailty data in the ambulance setting. Longitudinal profiles of frailty at individual and population level could enable ambulance services to be more responsive to the demands of an ageing population.