Principal findings
The research questions addressed are discussed below.
What models are in place? How and on what scale are they delivered? (CONTEXT)
This study showed that while GPs are commonly working in EDs (66% of respondents to our initial survey used some form of GP-ED model), delivery models vary widely in scope of the GP role and scale of the GP service. Service objectives most frequently included reducing waiting times, reducing ED patient volume and making better use of available ED resources.
After developing a taxonomy to classify the ways in which GPs work in and alongside EDs, we identified three main models of working which were explored in depth (see Chapter 4). We found sites where GPs were working within the ED in a fully integrated fashion, sites where GPs worked in the ED providing a parallel service alongside the ED team and sites where the GP service was provided outside the ED but still within the same hospital location.5 Significant variation within models was also identified, in relation to (inter alia): streaming systems; level of oversight of the GP model; remit of the GP; access to investigations; level of integration and communication; and IT system compatibility (see Chapter 4).19 Models of GP employment varied but could broadly be divided into: ‘in-house’ by the NHS Trust or by a separate primary care provider (which could result in a stable workforce) or by external providers sometimes with unstable locum staffed services.150 While our focus was on GPs in EDs, several of our case study sites also used wider primary care teams involving a range of professionals to meet the needs of patients attending the ED.
While variation within models was observed, there were however key features identified and commonly associated with each of the three service designs. Integrated models were typically used at sites with lower levels of ‘primary care demand’ at the ED, often funded from within the same NHS Trust as the ED. GPs were fully integrated members of the ED team with access to the same IT system and investigations as other ED staff and viewed and valued as members of the ED team but acting in extended GP roles.
At the other end of the spectrum, outside–onsite models typically aimed to deal specifically with primary care demand and had a clearly defined identity in a separate physical location. As a result, there were usually agreed criteria and pathways for accessing the service and GPs’ remit generally remained similar to that of community primary care (without access to ED investigations).
The inside–parallel models were the most varied and sometimes had features from each of the other two models. For example, at these sites, the level of primary care demand (and aim of addressing this) varied. While streaming guidelines often existed, there was sometimes flexibility for GPs to take on a wider role, with variable access to ED level investigations and differing perceptions about how integrated the GP service and the ED were intended to be at different sites.
How do the models work (in comparison with standard practice)? Does the way they work align with the intentions of those who set them up? (MECHANISM)
In our refined programme theory (see Chapter 7), we identified pathways through which GP models were observed to operate. The first step in all models related to the decisions taken about which patients would be directed to the GPs within the ED (often through a formal streaming system, but sometimes based on individual clinicians’ preferences).156 We identified settings where high-quality streaming decisions were facilitated by experienced staff (usually nurses), adequately detailed guidelines, the streamer’s understanding of GP skills, communication between the streamer and the GP service and oversight and active quality improvement of the streaming set-up.146 When such contextual factors were lacking, there were risks of patients being streamed either inappropriately to GPs (risking redirection back to ED after review) or inappropriately to the ED (meaning the GP model made less impact). The system for streaming was more influential at inside–parallel and outside–onsite models where GPs acted differently to ED doctors, than in the inside–integrated models where more overlap in approach was expected.
The second step in our theory discussed how GPs worked within the deployed model to deliver patient care. We observed that GPs used a variety of different approaches, sometimes working in very similar manner to community primary care, sometimes taking on an ED clinician role and sometimes working flexibly using different approaches for different patients.32 Role boundaries were generally clearer in the outside–onsite models. The GP role could be restricted or expanded due to the level of resources available within the model (e.g. access to ED level investigations) and for personal characteristics of individual clinicians, including preferred ways of working, confidence levels and medicolegal concerns. Techniques described by GPs (see Chapter 4) as ways to mitigate risks of ED working included longer appointments, different thresholds for investigation or admission and developing supplementary ED skills.32
The third stage of our theory refers to the end outcomes for both patients and the wider ED. While our patient data were limited, we identified how patients’ expectations of an ED visit, and whether these were met or exceeded appeared linked to subsequent satisfaction.20 In addition to patient-level factors influencing these expectations, the visibility and accessibility of the GP-ED model also shaped expectations.157 Reports from staff indicated that models where patients were redirected to the GP-ED model but could not then receive definitive care (observed in outside–onsite models) were frustrating for patients and staff alike.146
Our theory also highlighted the importance of culture in underpinning successful GP-ED models, with strong clinical leadership aiding the development of a culture which encourages interprofessional communication and mutual respect to enabling safe care provision.
What are the outcomes of each model in terms of: percentages of emergency department attendances seen; admissions; reattendance rates; waiting times; costs; patient safety; patient experience; team impact and sustainability? (OUTCOMES)
Effectiveness
Routine data quality across sites was variable. Our marker conditions analysis at a single inside–parallel site with strict primary care streaming criteria showed that when treating the least unwell patients (those requiring no investigations or treatment at the ED) those seeing GPs generally spent less overall time in the department than those seeing an ED clinician. The routine data identified only two sites with statistically significant evidence of reversal in the existing upwards trends in time spent in the ED.
The routine data indicated that in general, at the GP-ED model sites, attendances increased over time. Reattendances within 28 days in the post-intervention period increased over that in the pre-intervention period in 8/9 sites assessed. Data on investigation use at intervention sites demonstrated a mixed picture which was difficult to interpret. This complexity was also identified in the data relating to treatments delivered although overall there was a pattern of increasing treatments delivered pre intervention, followed by decreasing treatments delivered post intervention, but the significance of this is uncertain. A mixed picture was seen in relation to hospital admissions in the Integrated and Parallel sites, with data quality issues at the Outside sites, with examples of both increases and decreases both pre and post intervention. Similarly, average length of hospital stay showed a mixed picture both over all intervention sites and within models with some trendlines remaining essentially flat.
Patient experience
In many instances, we found descriptions of how GP-ED models could meet or exceed patients’ expectations about the level and timeliness of care provided in the ED. Our qualitative data identified the potential for patient dissatisfaction with GP-ED models that redirected patients elsewhere after they had waited to be seen rather than providing definitive treatment. Given the small numbers of patients participating in the study, we were not able to identify a single GP model most likely to improve patient experience.20
Safety
Clinical directors, from 11 of the 13 case study sites visited, had no patient safety concerns and did not describe any patient safety experiences related to GP-ED service models. The CD of a parallel service (Parallel-1) had concerns about which organisation held governance responsibilities and the skillset of GPs working in the ED following two local patient safety incidents. Two CDs perceived that since GPs had been working in the department, overall patient safety had improved because the experienced, permanent GPs could also give advice to other staff members (Integrated-1, Integrated-2). Small numbers of local patient safety incident reports regarding the GP-ED services were identified (n = 14 from all case study sites). The qualitative data provided examples of departmental and organisational factors that were identified to improve the safety of care delivered notably: appropriate streaming processes, led by an experienced nurse; communication and teamwork between the services; and clear governance processes for the GP-ED service. We described how individual GPs attempted to mitigate the risks of ED work in their clinical decision-making.32
Marker conditions data analysis suggested that there was no increase in reattendances within 7 days seen among patients treated at one site (Parallel-2), which we used as a marker of the safety of the care provided. Routine data analysis indicated upward trends in reattendances within 28 days at most intervention sites.
Resource use
When looking at ED visits by individual models, the inside–integrated model saw a small cost saving (£8.73), but small cost increases were seen in the inside–parallel model (£9.51) and the outside–onsite model (£16.30). With respect to inpatient admissions, all models saw small cost savings (£25–215) with the outside–onsite model seeing the largest saving (£215). While each model type had reduced admission LOS and costs compared to the controls, this assumes that case mix for each model type was the same, though it is possible that the type of patients seen and admitted are different thus resulting in different lengths of stay and costs. There is also considerable variation in approaches to financing GP services.146 In addition to negligible cost differences in the ED, there were also small time savings (range 3.5–23.5 minutes) compared to the controls.
Our CCA to investigate the economic impact of GPs working in a ‘parallel’ service model at Parallel-2 study site (see Chapter 6) suggested that GPs could provide a time and investigation sparing service to the patients with selected ‘marker conditions’ and who required the lowest levels of intervention, without increasing admission or reattendance rates.
What are the relationships between context, mechanism and outcomes, and is the evidence base transferable to commissioning, service improvement and cost-effective delivery in other settings?
Our refined programme theory aims to summarise our findings, highlighting the mechanisms acting in the three different models and how these may produce differing results. When reviewing each of the models they each have strengths and weaknesses, a single ‘best’ model for every site cannot be identified, and will depend on the local context and priorities of the service, which should be examined and clarified,5 as discussed in our implementation toolkit (see Project web page). We have noted that a clearer ED identity (inside–integrated) or GP identity (outside–onsite) generally meant service design aligned with aims, whereas there was more scope for variation and possible confusion at the Integrated-Parallel models.
We recognise that we have a large body of qualitative evidence describing mechanisms at the level of individual clinicians and teams, and the contexts in which these mechanisms are likely to occur (see Chapter 4). We have not demonstrated that these mechanisms lead to outcomes visible at the department level in routinely collected data (see Chapter 5).
Complex data and temporal variation, local variation in service provision and general lack of clarity regarding funding of GP-ED models meant that the relative balance between costs and effects is unclear. The analysis of the management of marker conditions using data provided by a single site cannot be generalised to all parallel sites but indicates potentially how GPs can make a difference in some EDs.
Toolkit development
Our research teamworked with study co-applicants and a stakeholder group of CDs to translate the research findings into actionable findings to be included in a ‘toolkit’ (see Project web page). This seeks to support ED CDs to appraise and reflect on how their GP-ED service functions and make operational plans for practice improvements in four key areas:
- Managing patient demand – including understanding patient-level, department-level and wider system-level influences on demand, information and education strategies for addressing demand and recommendations for evaluating demand.
- Improving patient flow – including strategic plans for improving nurses’ knowledge of primary care-type conditions (for streaming), training GPs to work in an ED, implementing streaming guidance; and operationally managing streaming and redirection to primary care.
- Improving patients’ experiences (and expectation) of accessing urgent care –including education and information to improve understanding and acceptability of streaming, considerations in redirecting patients to community primary care and suggestions for patient surveys to help inform service improvements.
- Improving patient safety – including supporting streaming to an appropriate clinician, clinical decision-making and communication between GP and ED teams.
The toolkit enables directors to identify what strategies they can implement in their service and provides a quality improvement tool and action plan to support service improvements in the four key areas.
Comparison with existing literature
Our RRR of 96 articles (see Chapter 3) developed candidate theories under five key themes: streaming and flow, the GP role, patient satisfaction, patient safety implications and wider system implications (including cost effectiveness).15
Streaming and flow
Our review findings (see Chapter 3) emphasised the importance of effective streaming, identifying influences including levels of available guidance, understanding GPs’ remit and effective interprofessional communication. These aligned both with our own findings146 from case study sites (see Chapter 4) and with the findings from another recent qualitative exploration of GP-ED streaming.158 However, our quantitative data did not demonstrate relationships between the quality of the streaming process and the rate of flow of patients through the department at our case study sites. Similarly, another NIHR-funded GP-ED study recently published findings from a 1-year analysis of HES data from 40 sites with GP-ED models and detected no statistically significant effect on the 4-hour wait target.159
The general practitioner role
Our initial review identified the concept of ‘the GP role’, which was particularly associated with the use of fewer investigations and admissions. Although GPs working in an ‘ED clinician’ role has also been identified, this was explored in a more limited way. Our qualitative data, particularly from inside–integrated sites, provide a fuller description of the range of tasks additional to the ‘usual’ GP role that GPs may undertake in EDs. We also identified descriptions of how GPs adapt their approach to meet the needs of the patient they are seeing. Potential barriers to maintaining the ‘GP role’ in ED were also described. In keeping with our findings, the recent large qualitative study described by Scantelbury et al.160 described how GPs are more ‘risk tolerant’ as a key premise of GP ED models, but that this was contested by some staff and service leaders. They also identified differing views on what level of access to investigations would make a GP-ED model most effective, with some services feeling access was essential, while others remained concerned about the risk of ‘GPs going native’ and consequently limiting access. Our marker conditions analysis (see Chapter 6) suggested that those GPs may use a different approach to ED clinicians when both groups treated patients who required the lowest level of investigation or treatment. However, our routine data analysis failed to demonstrate this impact at the department level. This is consistent with Gaughan et al.159 who found no statistically significant effects of GP-ED services on 4-hour waits, patients leaving without being seen or hospital admissions.
Patient satisfaction
Our initial review findings suggested that any improved satisfaction from seeing a GP in the ED would likely be derived from care exceeding initial expectations, particularly in relation to waiting time. It also highlighted that patients in more integrated models may be unaware they have seen a GP, without any resultant impact on satisfaction. Our qualitative data supported this, describing that people were often unaware they had seen a GP, were broadly supportive of the idea of GP-ED models and satisfied with timely care.20 Access to timely care is one key reason that patients choose to attend the ED for more minor problems.161,162 Our marker conditions analysis suggested that people most likely to have minor problems (requiring no investigations or treatment) would be seen in a more timely fashion by GPs than by ED clinicians. However, this impact did not extend beyond this small proportion of overall ED attendances to influence LOS in the ED for the whole department.
Patient safety implications
There was no evidence in our initial RRR15 (see Chapter 3) that GP-ED service models improved care of the sickest patients by freeing up ED staff. This is in keeping with our quantitative findings that there were no reductions in average patient time in the department, as found also by Gaughan et al. with no impact on 4-hour waits.159
Using reattendance as a marker of safety, there was no evidence in the review15 of more reattendances for GPs than for ED staff. This was reflected in our marker condition analysis at a single site and again in keeping with Gaughan et al.159 who found GPs working in/alongside the ED was associated with a small reduction in unplanned reattendances within 7 days. Our routine data indicated upward trends across intervention sites for reattendance within 28 days, largely irrespective of GP-ED model intervention, although this is outside the usual timescale for assessing safety.163
There were some anecdotal reports in the review about poor communication impacting quality of care – also a theme in the small number of Coroners’ reports, NRLS and local patient safety incident reports identified.14,164 GPs are recognised as low patient safety incident reporters, which may have contributed to the low number of reports identified.146 Communication failures, exacerbated by hierarchical differences and conflicting roles and role ambiguity, are known to be associated with patient safety incidents,165,166 while interventions to improve communication between healthcare professionals such as briefings, or ‘huddles’, are associated with improved patient safety outcomes.167,168 Our qualitative data identified factors that inhibited and facilitated communication between the GP-ED and ED services. Strong clinical leadership was observed at the sites with a stronger sense of professional respect, teamworking and collaboration. Clinician involvement in leadership positions in hospitals is associated with improved quality of patient care.169
The patient safety incident reports described how high-risk patients could be incorrectly streamed to the GP service and that GPs may mismanage conditions outside of their usual skillset.14 There is little national guidance on which ED patients should be streamed to GP services.170 This study’s work supports an experienced senior nurse over algorithmic methods.14,171 There is little national guidance on which ED patients should be streamed to GP services.170 This study’s work supports an experienced senior nurse over algorithmic methods.171 Our qualitative data improved our understanding of the strategies GPs in EDs used to try to ensure quality and safety of the care they provided, with findings structured around Croskerry’s dual-process model of reasoning (see Chapter 4).31,32
Wider system implications – cost effectiveness and provider-induced demand
Our RRR did not identify any research reporting an economic assessment, whether CCA, a full economic evaluation or a detailed analysis of GP activity and outcomes where the presenting complaint is a typical primary care problem, but seen in an ED.
In broad terms, our findings from the single-site marker conditions analysis support the existing UK-based research56,61 and other research that has not included an economic assessment,72,73,76–78,96,172 suggesting that GPs do have a role in managing some patients attending ED and they may admit fewer patients, take less time and use fewer investigations and treatments compared with ED clinicians, particularly for lower acuity presentations. This saving, however, may be offset against the GP higher employment costs compared with ED clinicians seeing equivalent patients. Nonetheless, releasing ED clinicians to see patients that they are more skilled at managing has potential value for the EDs. Our qualitative data provide additional detail to the current literature about the influence of context, and how this strongly influences how GP may practice compared with ED clinicians.
Our CCA using routine data suggests all models saw small cost savings, largely driven by reductions in hospital admissions (largest savings in the outside–onsite group). This conflicts with the data from Gaughan et al.,159 which did not identify reductions in admissions at sites using GP-ED models. However, the savings identified should be interpreted with caution as the cost of employing GPs may vary considerably compared with the cost of employing GPs that we used.143
Our RRR identified studies suggesting that visible services may create their own demand, rather than relieving ED pressures, while this was not reported at sites where an integrated model was ‘invisible’.15 This fitted with our qualitative findings, with staff describing examples of what they perceived to be provider-induced demand at more ‘visible’ sites.157 However, our routine data analysis found that demand increased over time at all study sites including controls regardless of the visibility of services. The wider literature highlights other drivers of demand at the ED, in particular identifying the attractiveness of promptly available tests.162 While patient-reported reasons for attending EDs are often related to limited or poor access to primary care, an analysis of routine data found that there was no statistically significant relationship between the number of GPs in a primary care trust area and the number of emergency admissions.162,173 While patient-reported reasons for attending EDs are often related to limited or poor access to primary care, an analysis of routine data found that there was no statistically significant relationship between the number of GPs in a primary care trust area and the number of emergency admissions.173 However, in deprived areas, a higher number of GPs was associated with reduced emergency admission.
Strengths and limitations identified
From the outset, our realist approach focused the study on understanding not just the outcomes of GP-ED models, but also the reasons why different models may lead to different outcome patterns. The use of mixed methods in both data collection and analysis has strengthened our ability to investigate and demonstrate the true complexity of current GP-ED models in operation (see Figure 1 for study summary). The taxonomy developed in Phase 1 provided an easily applied method for classifying GP-ED models while also recognising the variability seen within models and how they function.5 We gathered data from a wide variety of services across the two study phases, adding breadth to our descriptions of how these models operate. We have engaged regularly and meaningfully with both public contributors and wider stakeholders and ED staff to ensure the relevance of our findings to policy and practice. We identified key actionable findings (see below) along with a toolkit (see Project web page) to help those working in EDs to develop or improve their GP-ED models based on the evidence gathered.
Several key limitations were identified. Firstly, study recruitment was challenging at various levels. Our narrow recruitment criteria both for case study sites (due to the requirements for our Interrupted Time Series Analysis) and individual patients (due to attempting to identify patients with the chosen ‘marker conditions’) limited the potential pool of participants. While we reached our target number of case study sites, we did not recruit as many patients as intended.18 Governance issues at two sites prevented us recruiting patients. We have published our reflections on the challenges of patient recruitment in ED research for wider learning (see Project web page).18 Additionally, recruitment of staff participants was particularly challenging at some of the busiest sites. We recognise that those services under the most pressure may not have been well represented in our sample.
Our second major challenge related to the quality of the routinely collected data available. This is a recognised issue in emergency care research.174 Accessing the available data from NHS Digital involved lengthy delays (including pre pandemic), meaning the qualitative and quantitative data analysis did not run concurrently as intended. Thus, we did not have the opportunity to collect further explanatory (and contemporaneous) qualitative data to explain patterns identified from the quantitative analysis. The quality of the data was also often concerning, with some data, such as those on time-to-treatment and investigation use, being particularly unreliable. Some of our remaining uncertainty about the potential role of GPs in EDs exists due to these data quality issues.
We were also limited in the data we could collect from local sites for our marker conditions analysis, successfully gathering data from just 1 of our 10 intervention sites. The pragmatic approach used in this analysis was also shaped by the limitations of the data, particularly around assessing acuity of presenting condition. We relied on investigations and treatments received as a proxy for severity of condition but recognise that this makes it problematic to assess appropriateness of treatment and investigation for patients at different severity levels.
Our third concern related to how well the data allowed us to refine our initial theories. Our qualitative data relied heavily on self-report from clinicians and patients, and no GP consultations were observed. Further triangulation of these data with observed encounters would have been useful. Our quantitative data were largely limited to whole department-level statistics, which made it difficult to be confident of potential links to reasoning at the individual level, that we had identified through our fieldwork. Our refined programme theory diagrams highlight these areas of uncertainty.
Finally, it is important to acknowledge the shifting ED landscape over the period of the study. There has been a rapid evolution of models of UEC with further disruptive innovation during and after the COVID-19 pandemic. We identified huge complexities in service models, with every case site having set up their service somewhat differently, and in several settings the services were continually evolving. Furthermore, the COVID-19 pandemic impacted both how individuals access health care and how services design their systems. New approaches such as ‘telephone first’ and ‘total triage’ approaches in both EDs and community primary care were much less widespread at the time of data collection and their relevance to our findings remains unexplored.
Equality, diversity and inclusion
Chapter 1 describes the role of our public contributors throughout the study in ensuring inclusivity and accessibility at all stages. While our use of routinely collected data from sites across England and Wales should represent all ED attenders, we faced challenges with patient recruitment for our qualitative work and our small sample is unlikely to be fully representative. We reflected on these recruitment difficulties and suggested possible mitigations (e.g. amended recruitment materials and the provision of incentives) in a published paper.18 Our research team brought a range of expertise and levels of experience. More junior team members were provided with training opportunities and encouraged to take the lead in specific areas of work, resulting in a large number of peer-reviewed publications and several new first authors.
Implications for policy and practice/key actionable findings
We have not identified a single GP-ED model that appears to represent ‘best practice’. Rather, we emphasise the need to understand individual patient-level, department-level and wider system-level influences on demand for service design features (including signage, layout, resources, staffing streaming/redirection policies), developing patient education materials, managing public awareness and working with community-based primary care to ensure patients seek care from the most appropriate service for their need.
To manage their expectations, patients need to be kept informed of which type of clinician they are being streamed to and why they are being streamed to primary care clinicians or redirected to another service, along with reassurance of primary care clinicians’ expertise and role in the ED. Decisions to stream patients to a clinician should also be collaborative, with patients feeling involved in this decision. Patient surveys would be helpful to gather service-user feedback and provide insights into what makes primary care streaming or redirection to community primary care more or less acceptable to patients.
To ensure that patients are efficiently and safely streamed to an appropriate clinician for their needs, nurses should be trained and experienced, and streaming pathways/protocols need to be co-produced by primary care and ED teams and clearly defined. To support this, there also need to be governance processes in place that reflect the aim of the service and how primary care clinicians are expected to work. A strong teamworking and communication culture can support clinicians develop an understanding of how individual clinicians and teams work. Operationally managing streaming can help monitor attendances and capacity and deploy staff to manage peaks in demand.
General practitioners should be recruited in line with the intended role of the service (and skillset required) with ongoing reflective training with a senior GP or ED clinician. GPs working in a role where they are seeing mostly primary care patients need to consider that they are seeing higher-risk patients and patients may require additional clinical skills (e.g. history taking, examination, safety netting) to ensure serious illness is excluded.32 GPs seeing emergency care patients require tailored professional developmental opportunities relevant to their role.
Adding GPs to the skill mix in EDs increases processing capacity in the department. However, if the ED’s main challenge is exit block, as frequently reported currently, then the effectiveness at resolving the overall problem of patient flow will be limited. Potential locality-based opportunity costs of using GPs in EDs must also be considered.
While our marker conditions analysis did show some promise that the single GP-ED model explored (inside–parallel) could result in the least sick patients being seen more efficiently, we recognise that for this to have an impact at a department level, there need to be enough patients needing this level of care. This was not the case at all case study sites (e.g. where GP remit was narrow) and we saw GPs extending their role seeing sicker patients, but benefits of this at the ED level were not demonstrated from the routinely collected data.
Further work needed
Routine data collection and quality
The quality and extent of routine ED data collection during the study period limited the conclusions we could draw. The ECDS has since been introduced across England to standardise data collection and this should facilitate further research in this area. Patient experience data were notably very limited in this study (mainly in relation to experience of streaming) and we would advocate for the systematic capture of patient experience measures (PREM) as part of routine care. However, we also recognise that there is currently no agreed patient-reported outcome measure (PROM)175 for use in the ED and further work on the development of relevant PROMs and PREMs would be valuable. The relationships between patients’ expectations and those experience and outcome measures are also important to examine further. We recognise the tension that exists between maximising patient satisfaction and managing demand appropriately in a system under pressure.
To improve our understanding of the safety of GP ED models, there would be benefits for linking data between primary and secondary care to understand the whole patient journey. Currently it remains challenging to understand how attendances at ED relate to use of primary care and other elements of the urgent care system. It would be helpful to understand how frequently patients attending one service reattend elsewhere, and whether patients who are redirected from a service do go on to access appropriate care in another service.
With better quality data from EDs and other secondary care or primary care domains, it is important to conduct well-designed comparative effectiveness and cost-effectiveness studies based upon more rigorous quantitative epidemiological and statistical methods than has been possible with the data available to date. Such research is essential to guide future policy regarding GPs in EDs.
Workforce
It was beyond the scope of this study to explore the impact of GP-ED models on local community primary care. Potential effects might include EDs competing for primary care staff from an already limited pool,176 with a potential increase in workload for the remaining community workforce. They might also see their workload increased by redirection policies. Exploring these issues from the perspective of community primary care and the whole system would be helpful.
This study focused specifically on the role of GPs in EDs; however, we recognise that often GPs are working as part of wider primary care teams staffed by professionals from a variety of backgrounds. While some of the insights we have gained will be transferrable to other professional groups, there is a need to further explore how these multidisciplinary teams may operate differently. We note the ongoing NIHR-funded study177 (NIHR131356) which addresses this topic for non-medical practitioners. Teamworking across the ED is an important dimension to that evaluation.
Specific to the role of GPs in EDs, more could be done to support (and evaluate) the development of the GP with a special interest in ED role, including the development of a core set of competencies for ED work, and as adapted for different GP-ED models. Standardised minimum requirements could support training programme design, continuing professional development and governance of these services.
Similarly, we suggested that basic minimum requirements for the assessments made during the process of streaming to a GP (e.g. recording of observations) could be considered, recognising again that more robust streaming systems will be required for models operating outside the ED. Finally, we recognise that our qualitative data about what GPs do in consultations are based on self-report. Other methods such as consultation observations and activity tracking could provide helpful additional evidence about differences in practice.
Conclusion
As supported by national policy, GPs commonly work in emergency care, within or alongside emergency medicine doctors. A range of GP-ED models exist, with varying levels of integration, communication and training. We developed a taxonomy to describe GP service models (integrated with the ED service, parallel within the ED, outside the ED on the hospital site) and present a programme theory that describes how these service models were observed to operate. Routine data were of variable quality, limiting our analysis. We did not find clear or consistent effects on processes or outcomes of care although findings were mixed – this precludes definitive evidence about clinical or operational benefits. Time series analysis demonstrated trends across intervention sites for increased time spent in the ED, increased ED attendances and reattendances and mixed findings for hospital admissions. Findings suggest that GP-ED models do not meet the aim of reducing ED waiting times and improving patient flow with limited evidence of cost savings. Evidence on patient experience was limited but broadly supportive; we identified department-level processes to optimise the safety of GP-ED models. Qualitative data indicated GPs were often valued members of the wider ED team, with significant appetite at some sites to use their specific skillset to provide care in the ED. We developed a toolkit, based on our findings, to provide guidance for implementing and delivering GP-ED services. Better-quality routine data from EDs are needed to conduct well-designed comparative effectiveness and cost-effectiveness studies and to guide future policy regarding GPs in EDs.