Introduction
The experience and training that a qualified GP brings to an ED are seen as strengths in terms of patient management. When appropriately used, a GP within the ED could potentially enable prudent use of investigations and lower inappropriate admissions. As described in Chapter 3, two studies from the UK56 and Ireland,70 published in 1996 and a later Dutch study77 suggest that GPs working within the ED managing patients with primary care type problems leads to cost savings from the hospital perspective. In these studies, patients were allocated to the GP by an ED triage nurse, compared with ‘business as usual’ – that is, no GP care. The costs savings were due to fewer referrals and admissions and lower investigation rates by the GPs, assumed due to a different approach to patient management. Cost savings were noted despite the GPs giving longer consultation times, and having higher salaries compared with ED clinicians. The key driver of the cost reduction was identified as reduction in admission to hospital by the GPs, compared with an ED clinician.56 Other studies without economic evaluations reported that GPs had reduced ‘process times’ in the ED for patients with primary care type problems.56,73,74,76–78 None of the studies identified in our RRR were full economic evaluations and may not be representative of current ways of working, financing models or current service pressures.
In Chapter 3, we described an initial theory explaining how engaging GPs to work in EDs to see patients with primary care problems might be a cost-effective option. However, as the research progressed it became clearer that there was no single outcome for a cost-effectiveness analysis that would be of greatest relevance for the stakeholders of this research. The health economic analysis was therefore reframed to be a CCA, with the following refinement to our initial theory.
If there is demand for patients with primary care type problems (C), GPs can see these patients in the ED (M), which is economically attractive (O) compared with patients being seen by ED clinicians, due to fewer referrals and admissions and lower investigation rates by the GPs despite the GPs having higher salary costs (M).
During the analysis, we were also mindful of an additional candidate theory which had suggested that GP-ED models might help to free up ED staff for more seriously ill patients. Our RRR suggested this might not occur in settings where there are delays in transferring patients to wards or inadequate staffing.
Aim
We aimed to investigate the economic impact of GPs on ED resource use and the related costs of clinical management when a GP within the ED treats a patient with primary care problems compared with an ED clinician.
Methods
To support the testing of the theories developed by the realist review, the methodological approach used for the economic analyses was CCA.151 CCA considers the costs and resource consequences resulting from, or associated with, the use of an intervention (in this case GPs managing patients) and its alternative (ED clinicians managing the patient). The range of costs and resource consequences to be included in the analysis depends on the characteristics of interventions and their comparators. Generally, the estimates of resource use and of benefits are separate domains of the evaluation. Estimates of resource use may also include the comparative value of healthcare service use outcomes (such as length of hospital stay, or number of hospitalisations, outpatient or primary care consultations) associated with the intervention or its comparators. The analysis plan was incorporated into the combined statistical and health economics plan (see Report Supplementary Material 2). The perspective taken for the CCA is an NHS perspective and the time horizon was 1 year.
Marker condition selection
Testing our theories required that we have a clear concept of which ‘primary care problems’ could potentially be managed by either a GP or an ED clinician. As described in Chapter 3, six representative (‘marker’) conditions were identified to inform sampling for both the qualitative and quantitative data collection.
For the analyses described in this chapter, marker conditions were defined using the coded presenting complaint (Table 16).
| Marker condition | Presenting complaint as coded |
|---|---|
| 1. Abdominal pain | 1. Abdomen pain non-trauma |
| 2. Back pain | 2. Back pain non-trauma |
| 3. Chest pain | 3. Chest pain non-trauma |
| 4. Headache | 4. Headache/head pain non-trauma |
| 5. Cough and shortness of breath | 5. Cough; short of breath; noisy breathing; difficulty breathing |
| 6. Child under 10 years with fever | 6. Child < 10 years of age with a fever |
Site availability
All 13 research sites were invited to contribute to the quantitative investigation of the management of marker conditions in the ED. Most agreed to support this aspect of the research and investigate how to undertake the extraction of the data from their ED databases, using a ‘trial extraction’ based on the local activity variables available for the back pain marker condition. Unfortunately, some EDs found it difficult to devote staff time to support provision of data or did not have access to data of sufficient quality at this stage in the research (October 2019–January 2020). Subsequently, the COVID-19 pandemic profoundly affected the ability of most EDs to support the research. This left only one centre – Parallel-2 – able to provide a full data set for analysis.
Data collection and processing
Anonymised patient-level data extracts from the Parallel-2 ED database were obtained. The data extracts included information on presenting complaint and final diagnosis and whether a GP or ED clinician was responsible for management of the patients. As the data are based on HRG codes, specific information on diagnostic tests and treatments was not available. Data were cleaned to ensure standardisation of each marker condition data set.
The time in ED was categorised into three distinct periods and extracted in line with these periods:
- arrival (T1) to treatment (T2)
- treatment (T2) to discharge (T3)
- overall time in ED (T1–T3).
The HRG codes were used to determine investigation and treatment categories as proxies for severity and complexity. Table 17 provides examples of the investigations and treatments included in each category. Table 18 shows the HRG codes and their associated treatment and investigation combinations.152
| Investigation category level | Example investigations | Treatment category level | Example treatments |
|---|---|---|---|
| 1 | Urinalysis, electrocardiogram, pregnancy test, some blood tests (e.g. biochemistry) | 1 | Observations, IV cannula |
| 2 | Plain film X-ray, some blood tests (e.g. haematology, blood cultures) | 2 | Local anaesthesia, physiotherapy |
| 3 | CT scan, MRI scan, ultrasound scan | 3 | Urinary catheter, incision and drainage. |
| 4 | Chest drain, intubation |
| HRG code | Definition | Severity/complexity |
|---|---|---|
| VB02Z | Investigation category 3 and treatment category 4 | Most |
| VB03Z | Investigation category 3 and treatment category 1–3 | Most |
| VB04Z | Investigation category 2 and treatment category 4 | Most |
| VB05Z | Investigation category 2 and treatment category 3 | Most |
| VB06Z | Investigation category 1 and treatment category 3–4 | Most |
| VB07Z | Investigation category 2 and treatment category 2 | Medium |
| VB08Z | Investigation category 2 and treatment category 1 | Medium |
| VB09Z | Investigation category 1 and treatment category 1–2 | Least |
| VB11Z | No investigations of treatment | Least |
Analysis
For each marker condition, descriptive analyses were undertaken, reporting frequencies and percentages for categorical data, and measures of central tendency for numerical data. Pearson’s chi-squared test was used to compare proportions of patients admitted to hospital and discharged home, while the non-parametric Mann–Whitney U-test was used to compare time. Data were stratified by whether the patient had been seen by ED clinician or by a GP. Generalised linear regression models (GLM) were then used to investigate the effect of clinician seen on patient time within the ED (see Report Supplementary Material 4). Time was included as the dependent variable; categorical variables, such as marker condition, gender or being seen by a GP or ED clinician, were included as fixed variables; and continuous variables, such as age, were included as covariates. A backward enter stepwise approach was taken with non-statistically significant variables (p > 0.05) removed.
We undertook both base-case analysis and sensitivity analysis, in order to investigate the influence of how GPs impact the time spent by patients in the ED.
- Base case. The base-case analysis was obtained from running the economic analysis with assumptions and inputs that represents the most usual circumstances in the ED setting and is analogous to an ‘intention-to-treat’ approach. In practice, this included all patients who attended with one of the relevant identified presenting complaints, representing ‘real life’ ED as the diagnosis is not known at the time of arrival.
- Sensitivity analysis: The purpose of undertaking this analysis was to understand whether and how effective streaming might influence the CCA. Of all patients with one of the selected presenting complaints, the subsequent diagnostic code recorded was reviewed by an ED clinician/co-investigator supporting the research. For this analysis, patients with a diagnosis that would not be expected to be managed by a GP in ED, and should not have been streamed to a GP, were excluded. For example, this excludes patients presenting with chest pain and subsequently diagnosed with conditions including myocardial infarction, supraventricular tachycardia and tension pneumothorax (see Report Supplementary Material 3).
Consequences
The ‘consequences’ of interest for this analysis of management of patients with the marker conditions, using their ED data, are the relative differences observed in:
For each marker condition:
- Numbers (%) treated by GP versus ED clinician.
- Severity/complexity (derived from HRG investigation and treatment categories).
- Admission (to inpatient care) rate.
- Overall mean time in ED (arrival to discharge): T-overall.
- Mean waiting time from arrival (booking in at reception) to being seen by a treating clinician (treatment): T-1.
- Mean time from treatment (seen by treating clinician) to discharge: T-2.
For all marker conditions:
- Discharge destination.
- Reattendance at ED with same complaint.
Costs
At the Parallel-2 site, the costs of the GP sessions or service were not available as the CCG paid the local provider for the service delivery. The cost of a GP delivering ED sessions was provided by Integrated-2 (a different site) with information about funding sources and strategies from other sites also providing context. NHS Reference costs 2019153 were used to provide costs for the investigations and treatment categories.
The CCA has a 12-month time horizon and so no discounting was applied to either costs or consequences.
Results
Parallel-2 site, setting and context
At the time of the case site visits (between June 2018 and July 2019), Parallel-2 had an Emergency Care Centre, comprising the ED, Emergency Admissions Unit and an Urgent Care Centre (see Chapter 4, Table 4 for further site characteristics). The urgent care centre and the ED are adjacent to each other but are separate work areas (corridors known as ‘pods’). Streaming to each service is undertaken by the triage nursing team. The GPs do not provide a service overnight – all patients will be seen by ED staff during this period and in daytime hours the service was not always fully staffed. The GPs were encouraged to act as GPs and deal with primary care problems streamed to them.
Marker conditions analysis
Below we present brief summaries of the base-case and sensitivity analyses undertaken for all six marker conditions. Tables presenting the full results are available in Report Supplementary Material 4. Table 19 summarises the number of patients with each marker condition through the 12-month period (1 July 2018 through 30 June 2019).
| Marker condition | Total patients, N | Male (%) | Female (%) | Mean age (SD) | Median age (IQR) | Age range (minimum–maximum) |
|---|---|---|---|---|---|---|
| Back pain | 1929 | 847 (43.9) | 1082 (56.1) | 45.7 (18.6) | 45 (31–59) | 2–98 |
| Chest pain | 4747 | 2339 (49.3) | 2407 (50.7) | 47.0 (19.4) | 47 (31–61) | 0–96 |
| Cough and breathlessness | 7485 | 3505 (46.8) | 3979 (53.2) | 35.5 (28.8) | 33 (4–61) | 0–100 |
| Fever (< 10s) | 2528 | 1305 (51.6) | 1223 (48.4) | 2.1 (2.1) | 1 (1–3) | 0–9 |
| Abdominal pain | 7824 | 2891 (37.0) | 4931 (63.0) | 39.1 (21.0) | 35 (24–54) | 0–98 |
| Headache | 1907 | 784 (41.1) | 1122 (58.8) | 37.0 (21.5) | 33 (21–53) | 0–96 |
Back pain
Of the 1929 patients presenting with back pain with a median age 45 years of age, 56% were female, 44% male and most (78%) were seen by ED clinicians, the rest (22%) by GPs.
Using the HRG investigations and treatment category groupings (see Table 17) as a proxy for severity, the more severe patients were more often seen by ED clinicians with the proportion of patients being seen by GPs increasing as severity decreased. While inpatient admission rates were higher when the patients were seen by ED clinicians, this aligned with severity. For patients who were least severe (and seen by ED clinicians (69%), inpatient admissions were higher (p = 0.047) when the patient was seen by ED clinicians, compared with GPs.
Once registered, for patients who were put into the GP stream on arrival to the ED, the average overall time (T1–T3) spent in the ED was shorter than if they were streamed to the ED clinician (a difference of 47 minutes, p < 0.001). The driver of that difference was the time between initiation of treatment and departure (T2–T3) from the ED (a difference of 45 minutes, p < 0.001). The less severe patients spent less time in the period between treatment to departure but a difference in duration between ED clinicians and GPs was maintained (13 minutes, p < 0.001 shorter time if seen by GPs).
Sensitivity analysis
The population used in the sensitivity analysis was 1339 (69.4%) of the base-case population. For those patients with a presenting complaint of back pain (non-trauma), categorised as likely to have been suitable for streaming to a GP based on their subsequent diagnosis, the average age was similar (45 years of age, 54% female). Most (77%) were seen by ED clinicians, the rest (23%) treated by GPs.
Using the HRG category groupings (see Table 17), the more severe patients were more often seen by an ED clinician with the proportion of patients being seen by GPs increasing as severity decreased. While inpatient admission rates were higher when the patients were seen by ED clinicians, this aligned with severity. For patients who were least severe and seen by ED clinicians (57.9%), inpatient admissions were higher for ED clinicians compared with GPs, although the difference was not statistically significant (p = 0.091).
For the patients allocated to the GP stream on arrival at the ED, the time (T1–T3) spent in the ED was shorter than if they were streamed to the ED clinician (a difference of 46 minutes, p < 0.001). The driver of that difference was the time (T2–T3) between initiating treatment and departure from the ED (a difference of 46 minutes, p < 0.001). The less severe patients spent less time in the period between treatment to departure but a difference in duration between ED clinicians and GPs was maintained (16 minutes shorter time if seen by the GP vs. ED clinician, p < 0.001).
Chest pain
Of the 4747 patients attending the ED with a presenting complaint of chest pain, 50.7% were female and 49.3% male. Most (93.5%) patients were treated by an ED clinician and 6.5% treated by a GP. Patients seen by the ED clinicians were significantly older than those seen by the GP (median age 48 vs. 31, p < 0.001) which may reflect some age-related selection bias.
Using HRG investigation and treatment categories as proxies for severity, most severe patients (see Table 17) were more often seen and treated by the ED clinicians (99.4% vs. 0.6%), with the proportion of patients seen by GPs increasing as severity decreased.
Overall, the ED clinicians admitted a significantly higher proportion of patients to hospital than GPs (27.1% vs. 3.6%, χ² = 83.9, p < 0.001), consistent with seeing more severe and complicated patients than the GPs. Of the less severe patients, inpatient admissions were higher when the patient was seen by the ED clinician compared with the GP (3.0% vs. 0.7%, χ² = 4.4, p = 0.043). Emergency department clinicians treated the majority of severe patients, where most hospital admissions originated, and there were not enough patients in the GP group to test the difference in the proportions of inpatient admissions.
Once booked in, patients who were treated by GPs spent less time (T-overall 61 minutes less) before discharge than those treated by ED clinicians (mean 2 hours 4 minutes vs. 3 hours 5 minutes, p < 0.001). This time includes the waiting time to be seen before treatment (T1–T3). There was no significant difference in the waiting time (mean 1 hour 26 minutes vs. 1 hour 29 minutes, p = 0.317) before being treated; the significant time difference was between treatment and discharge (T2–T3) (1 hour 38 minutes vs. 35 minutes, p < 0.001) indicating that, once seen by a doctor, the GPs’ patients took less time before discharge.
The main time difference between initial treatment and discharge (T2–T3) was in the least severe patients (43 minutes for ED clinicians and 29 minutes for GPs, p < 0.001) and the medium severity patients (1 hour 45 minutes for ED clinicians and 1 hour 18 minutes for GPs, p = 0.016).
Sensitivity analysis
The matched population for the sensitivity analysis was 3915 (82.5% of base-case population). For patients with a presenting complaint of chest pain and subsequent diagnosis indicating likely suitability for streaming to a GP, the median age was 47 years of age though, again, the ED clinicians saw significantly older patients than GPs (median age 48 vs. 30 years, p < 0.001). Most patients (92.9%) were seen by ED clinicians, and 7.1% were treated by GPs.
Using the HRG category groupings (see Table 17), the more severe patients were more often seen by an ED clinician with the proportion of patients being seen by GPs increasing as severity decreased. Inpatient admissions were only significantly different between ED clinicians and GPs for the least severe patients (3.5% vs. 0.8%, χ² = 4.9, p = 0.027).
For patients streamed to GPs on arrival to the ED, the overall time (T1–T3) spent in the ED was shorter if they were streamed to the GP (a difference of 64 minutes, p < 0.001). The driver of that difference was the time between initiating treatment and departure (T2–T3) from the ED (a difference of 65 minutes, p < 0.001). The less severe patients spent less time from treatment to departure (T2–T3) but a difference in duration between ED clinicians and GPs was maintained (21 minutes shorter time if seen by GPs, p < 0.001).
Cough and breathlessness
Of the 7485 patients with a presenting complaint of cough or breathlessness, 53.2% were female and 46.8% were male. Most (81.2%) patients were treated by an ED clinician and 18.8% treated by a GP. The median age of those treated by ED clinicians compared with those treated by GPs was 34 years of age compared with 32 years of age.
Using HRG investigation and treatment categories as proxies for severity (see Table 17), most severe patients were more often seen and treated by the ED clinicians (96.5% vs. 3.5%), with the proportion of patients seen by GPs increasing as severity decreased.
Overall, the ED clinicians admitted a significantly higher proportion of patients to hospital than GPs (29.0% vs. 2.8%, χ² = 429.0, p < 0.001), consistent with seeing more severe and complicated patients than GPs. A significant difference in the proportions of patient admissions existed in the least severe patients (admissions 5.9% vs. 1.8%, χ² = 32.4 p < 0.001) and the most severe patients (admissions 64.6% vs. 8.3%, χ² = 94.2 p < 0.001), while in the middle group no difference was observed (p = 0.229).
Once booked in, patients seeing a GP spent less time (T1–T3) (47 minutes) than those treated by ED clinicians (mean 2 hours 5 minutes vs. 2 hours 52 minutes, p < 0.001). Comparing the time between initial treatment and discharge, there was a small but significant difference in the waiting time (mean 1 hour 16 minutes vs. 1 hour 26 minutes, p < 0.001) in favour of seeing ED clinicians (T1–T2), but a larger, significant, time difference between treatment and discharge (T2–T3) (mean 1 hour 36 minutes vs. 38 minutes, p < 0.001) in favour (shorter time) of seeing GPs.
When stratified by severity, again there was no difference in waiting times between ED clinicians and GPs (T1–T2) for the most severe and the medium severity cough and breathlessness patients (p = 0.053 and p = 0.178, respectively) though for the least severe patients there was a small, but significant, difference in wait time (T1–T2) (1 hour 13 minutes vs. 1 hour 26 minutes, p < 0.001) favouring those seen by an ED clinician (shorter time). For each severity category, the time between initial treatment and discharge (T2–T3) was significantly shorter for patients seeing a GP compared with an ED clinician, with the time difference ranging from 16 minutes (least severe, p < 0.001) to 1 hour and 35 minutes (most severe, p < 0.001).
Sensitivity analysis
The matched population for the sensitivity analysis was 7001 (93.5% of the base-case population). When the patients had both a presenting complaint of breathlessness and a subsequent diagnosis suggesting they were suitable for streaming to a GP, the median age was 33 years (median age 34 years ED clinicians vs. 32 years GPs, p = 0.033). Most patients (80.9%) were seen by ED clinicians and 19.1% were treated by GPs.
Using the HRG category groupings (see Table 17), the more severe patients were more often seen by an ED clinician with the proportion of patients being seen by GPs increasing as severity decreased. Inpatient admissions were higher among ED clinicians than GPs for the most severe (65.0% vs. 9.1%, χ² = 85.9, p < 0.001) and the least severe patients (6.3% vs. 1.6%, χ² = 38.7, p < 0.001), though no difference was observed in the medium severity patients (p = 0.067).
For patients streamed to GPs on arrival to the ED, the time (T1–T3) spent in the ED was shorter than if they were streamed to the ED clinician (a difference of 52 minutes, p < 0.001). The driver of that difference was the time between initiating treatment and departure (T2–T3) from the ED (a difference of 61 minutes, p < 0.001). The least severe patients spent less time between arrival and treatment (T1–T2) (10 minutes shorter, p < 0.001) when seen by the ED staff, but less time between treatment to departure (T2–T3) (21 minutes shorter, p < 0.001) when seen by a GP. Significantly shorter times were observed between treatment and discharge (T2–T3) for both the most severe (1 hour 35 minutes shorter (p < 0.001) and the medium severe patients (35 minutes shorter, p < 0.001) when seen by GPs compared with ED clinicians.
Fever in children under 10 years of age
Of the 2528 children with a presenting complaint of fever, 48.4% were female and 51.6% were male. Most (71.7%) patients were treated by an ED clinician and 28.3% treated by a GP. No statistically significant difference in age was observed between those seen by ED clinicians (median age 1 year) and those seen by GPs (2 years of age) (p = 0.057), respectively.
Using HRG investigation and treatment categories as proxies for severity, most severe patients (see Table 17) were more often seen and treated by the ED clinicians (98.6% vs. 1.4%), with the proportion of patients seen by GPs increasing as severity decreased.
Overall, the ED clinicians admitted a significantly higher proportion of patients to hospital than GPs (13.8% vs. 2.4%, χ² = 71.1, p < 0.001), though the significant difference in the proportion of admissions was most evident in the least severe patients (admissions 9.0% vs. 2.4%, χ² = 31.6, p < 0.001) and the medium severity patients (admissions 30.1% vs. 2.7%, χ² = 12.5, p = 0.001).
Once booked in, patients treated by GPs spent less time (19 minutes) in ED (T1–T3) than those treated by ED clinicians (mean 2 hours 16 minutes vs. 2 hours 35 minutes, p < 0.001). However, this time includes the waiting time to be seen before treatment (T1–T2). The significant differences in time were those between the initial arrival and treatment (T1–T2) (mean 1 hour 37 minutes vs. 1 hour 19 minutes, p < 0.001) – shorter for those seen by ED clinician than GPs, and the time between treatment and departure (T2–T3) (mean 38 minutes vs. 1 hour 16 minutes, p < 0.001), which was shorter for those seen by GPs.
When stratified by severity, the time between initial treatment and discharge (T2–T3) was significantly shorter for those treated by GPs, in both the least severe patients (1 hour 9 minutes vs. 38 minutes, p < 0.001) and the medium severity patients (1 hour 43 minutes vs. 49 minutes, p < 0.001).
Sensitivity analysis
The matched population for the sensitivity analysis was 2405 (95.1% of the base-case population). When the patients, aged under 10 years, had both a presenting complaint of fever and a subsequent diagnosis indicating that they were likely to have been suitable for streaming to a GP, the median age was 1 year for those seen by the ED clinicians compared with median age 2 years for GPs (p = 0.074). Most patients (71.7%) were seen by ED clinicians and 28.3% treated by GPs.
Using the HRG category groupings (see Table 17), the more severe patients were more often seen by an ED clinician with the proportions of patients being seen by GPs increasing as severity decreased, though the vast majority of patients were of the least severe category. Inpatient admissions were higher between ED clinicians and GPs only for the least severe patients (9.1% vs. 2.2%, χ² = 33.3, p < 0.001).
For the patients who were streamed to GPs on arrival to the ED, the overall time (T1–T3) spent in the ED was shorter than if they were streamed to ED clinicians (a difference of 23 minutes, p < 0.001). The driver of that difference was the time between initiating treatment and discharge (T2–T3) from the ED (a difference of 40 minutes, p < 0.001). The least severe patients spent less time between arrival and treatment (T1–T2, 15 minutes shorter, p < 0.001) when seen by the ED staff, but less time between treatment to departure (T2–T3, 34 minutes shorter, p < 0.001) when seen by a GP. Significantly shorter times were observed between arrival and treatment (T1–T2, 31 minutes shorter, p < 0.001) if seen by ED clinicians, though shorter times between treatment and discharge (T2–T3), for the medium severe patients, (61 minutes shorter, p < 0.001) when seen by GPs compared with ED clinicians.
Abdominal pain
Of the 7824 patients attending the ED with a presenting complaint of abdominal pain, 63.0% were female and 37.0% were male. Most patients (85.8%) were treated by an ED clinician and 14.2% by a GP. There was a statistically significant difference in age of 7 years between those seen by the ED clinician and those seen by the GP (median age 36 vs. 29 years, p < 0.001) with the ED clinician seeing older patients which suggests some selection bias.
Using HRG investigation and treatment categories as proxies for severity, the most severe patients (see Table 17) were more often seen and treated by the ED clinicians (99.4% vs. 0.6%), with the proportion of patients seen by GPs increasing as severity decreased.
Overall, ED clinicians admitted a significantly higher proportion of patients to hospital than GPs (30.2% vs. 4.8%, χ² = 315.0, p < 0.001). This was driven by significant differences in the proportions of patient admissions among medium severity patients (admissions 17.3% vs. 9.0%, χ² = 6.2, p = 0.013), with the difference in admissions between ED clinicians and GPs for the least severe patients showing no significant difference (5.4% vs. 3.9%, χ² = 2.5, p = 0.116).
Most severe patients, where most hospital admissions originated, were seen and treated by the ED clinicians and there were not enough patients in the GP group to test the difference in proportions of patients admitted.
Once booked in, patients treated by GPs with a presenting complaint of abdominal pain experienced a shorter overall time (T1–T3) before discharge than those treated by ED clinicians (mean 2 hour 6 minutes vs. 3 hours 14 minutes, p < 0.001). This was most evident between treatment and discharge (T2–T3) (mean 37 minutes for GPs vs. 1 hour 45 minutes for ED clinicians, p < 0.001).
When stratified by severity, there was a small, but significant, difference in overall waiting times (T1–T3) between ED clinicians and GPs for the least severe patients (1 hour 18 minutes vs. 1 hour 28 minutes, p < 0.001), while there was no difference between ED clinicians and GPs seeing the medium severity and most severe abdominal pain patients (p = 0.588 and 0.315, respectively). Time between initial treatment and discharge (T2–T3) was significantly shorter for all patients of all severities who saw GPs with differences ranging from 15 minutes (p < 0.001) for the least severe patients to 49 minutes (p = 0.030) for the most severe patients.
Sensitivity analysis
The matched population for the sensitivity analysis was 6967 (89.0% of the base-case population). When the patients had both a presenting complaint of abdominal pain and a subsequent diagnosis likely to have been suitable for streaming to GPs, the median age was 35 years with a significant difference between those seen by ED clinicians compared to GPs (median age 36 vs. 29 years, p < 0.001). Most patients (85.3%) were seen by ED clinicians and 14.7% by GPs.
Using the HRG category groupings (see Table 17), the more severe patients were more often seen by an ED clinician with the proportions of patients being seen by GPs increasing as severity decreased. Inpatient admissions were significantly higher between ED clinicians and GPs for all patient severities (most severe: 62.4% vs. 25.0%, χ² = 7.1, p = 0.008; medium severe: 16.3% vs. 7.9%, χ² = 6.3, p = 0.012; and least severe: 5.8% vs. 3.4%, χ² = 6.3, p = 0.012).
The overall time (T1–T3) spent in the ED was shorter for patients streamed to the GPs (a difference of 1 hour 10 minutes, p < 0.001). The driver of that difference was the time between initiating treatment and discharge (T2–T3) from the ED (a difference of 1 hour 9 minutes, p < 0.001). The least severe patients spent less time between arrival and treatment (T1, 8 minutes shorter, p = 0.001) when seen by the ED staff, but less time between treatment to discharge (T2–T3, 23 minutes shorter, p < 0.001) when seen by a GP. Significantly shorter times were only otherwise observed between treatment and discharge (T2–T3) for the medium severity patients (32 minutes shorter, p < 0.001) when seen by GPs compared with ED clinicians.
Headache
Of the 1907 patients attending the ED with a presenting complaint of headache, 59% were female and 41% were male. Most patients (82%) were treated by an ED clinician and 18% by a GP. Those seen by the ED clinician were older than those seen by the GP (median age 34 vs. 31 years, p = 0.002), respectively, which suggests some selection bias.
Using HRG investigation and treatment categories as proxies for severity, most severe patients (see Table 17) were more often seen and treated by the ED clinicians (99.3% vs. 0.7%), with the proportion of patients seen by GPs increasing as severity decreased.
Overall, the ED clinicians admitted a significantly higher proportion of patients to hospital than GPs (18.1% vs. 2.7%, χ² = 50.5, p < 0.001). When patients were stratified by severity, there were no significant differences in the proportion of patient admissions between GPs and ED clinicians, but sample sizes limited power of analysis.
Once booked in, patients treated by GPs with a primary complaint of headache spent a shorter (T1–T3) time (48 minutes) before discharge than those treated by ED clinicians (2 hours 9 minutes vs. mean 2 hours 57 minutes, p < 0.001). The time between treatment and discharge (T2–T3) (mean 33 minutes vs. 1 hour 26 minutes, p < 0.001) was also shorter when the patient was treated by GPs.
When stratified by severity, there was a small, significant difference in waiting times (T1–T2) between ED clinicians and GPs for the least severe patients (1 hour 24 minutes vs. 1 hour 35 minutes, p = 0.010), but no difference for the medium or severe patients (p = 0.435 and p = 0.894, respectively). Time between initial treatment and discharge (T2–T3) was significantly shorter in both the least severe (43 vs. 31 minutes, p < 0.001) and medium severity patients (1 hour 13 minutes vs. 34 minutes, p < 0.001) if seen by GPs compared with ED clinicians.
Sensitivity analysis
The matched population for the sensitivity analysis was 1361 (71.4% of the base-case population). When the patients had both a presenting complaint of headache and a subsequent diagnosis categorised as likely to have been suitable for GP streaming, the median age was 34 years with a significant difference between those seen by the ED clinicians compared to GPs (median age 35 vs. 30 years, p < 0.001). Most patients (81.1%) were seen by an ED clinician and 18.9% by a GP.
Using the HRG category groupings (see Table 17), the more severe patients were more often seen by an ED clinician with the proportion of patients being seen by GPs increasing as severity decreased. No differences in inpatient admissions were observed between ED clinicians and GPs for any patient severity (most severe, p = 0.852; medium severe, p = 0.157 and least severe, p = 0.117).
The overall time (T1–T3) spent in the ED was shorter for patients streamed to GPs (difference 1 hour 1 minute, p < 0.001). The driver of that difference was the time between initiating treatment and departure (T2–T3) from the ED (1 hour 5 minutes less, p < 0.001). Time between treatment and discharge (T2–T3) was shorter for both the least severe (20 minutes shorter, p < 0.001) and medium severe patients (45 minutes shorter, p < 0.001) when seen by GPs compared with ED clinicians.
Discharge destination
Across all marker conditions, for those treated by ED staff and GPs, most patients were discharged home after their ED visit, though some patients were referred to other healthcare providers (ED 3.5–9.3%; GPs 3.3–8.1%). There was a small proportion of patients who self-discharged having been seen by either ED clinician [during the treatment to discharge (T2–T3) interval; 0.7–1.8%] or GPs (0.0–0.9%), while some did not wait for treatment (ED 1.6–2.8%; GPs 0.7–3.3%).
In the case of the sensitivity analyses, across all marker conditions, for those treated by ED clinicians and GPs, most patients were discharged home after their ED visit, though some patients were referred to other healthcare providers (ED 2.0–7.0%; GPs 2.3–6.6%). There was a small proportion of patients who self-discharged having been seen by either ED clinicians (0.3–0.9%) or GPs (0.0–0.8%), and some did not wait for treatment (ED 0.3–0.9%; GPs 0.0–0.8%).
Reattendance to emergency department with the same complaint
One of the concerns when comparing GP and ED clinician management of patients overall, and specifically the marker conditions, is that suboptimal management may result in reattendance to the ED (with the same condition). A reattendance with the same presenting complaint within 7 days was considered a reasonable time period in which to attribute a relationship between the original and the reattendance. In Chapter 7, we discuss reattendance as a potential marker of patient safety. Here, we investigate it because of its cost consequences. We have investigated the reattendance rate (with the same condition) across all the patients in our marker condition cohorts in the first 7 days after discharge.
Overall, there were 24,834 initial attendances across all marker conditions; 83% (n = 20,658) of these were seen by ED staff, and 17% (n = 4176) were seen by GPs. Of these, 1586 (6%) reattended within the first 7 days after discharge. Of those seen by ED staff, 1319 (6%) reattended, while of those seen by GPs 267 (6%) reattended [χ² (1) = 0.0004, p = 0.983]. There were no significant differences in the proportion of reattendances between physician types for any individual marker condition.
Multiple regression analysis
These analyses were undertaken with several variables included to investigate their effect on patient time within the ED. Time was included as the dependent variable; categorical variables, such as condition, gender or being seen by GPs or ED clinicians, were included as fixed variables; and continuous variables, such as age, were included as covariates. Time in ED was categorised into time from arrival to treatment (T1–T2), time from treatment to discharge (T2–T3) and overall time (T1–T3).
Time from arrival to treatment (T1–T2)
The patients seen by ED clinicians spent less time waiting to be seen and treated than those by GPs (9.9 minutes, p < 0.001). This model gave a baseline intercept value of 98.8 minutes after adjusting for treating doctor (ED or GP), condition type, age, discharge status and investigations and treatment. However, this model accounted for 1.9% of the variability meaning that unknown variables accounted for a further 98.1%.
Time from initial treatment to discharge (T2–T3)
Patients seen by the GP spent 17.5 fewer minutes being treated than those seen by ED clinicians (p < 0.001) after adjusting for treating doctor (ED or GP), condition type, age, discharge status and investigations and treatment. This model accounted for 42.9% of the variability meaning that unknown variables accounted for a further 57.1%.
Overall time in emergency department (T1–T3)
Overall, after adjusting for treating doctor (ED or GP), condition type, age, discharge status and investigations and treatment, patients spent a baseline value of 247 minutes in ED between arrival and departure. Those patients seen by GPs spent 7.7 fewer minutes in ED than those seen by ED clinicians (p < 0.001). This model accounted for 33.3% of the variability meaning that unknown variables accounted for a further 66.7%.
Costs
The costs of GPs in EDs vary depending on the type of funding model adopted by individual trusts. In some cases where the service is provided through a contract placed with a private provider, there are no data available to estimate the cost per GP session or an hourly rate. This has meant that the actual cost of a GP has been difficult to ascertain. Table 13 in Chapter 5 outlines different scenarios for the cost of the GP in ED. In some scenarios, GPs cost less than ED staff, while in others they cost more.
We used HRG codes to categorise the severity of the attendance, and analyses were adjusted for severity where possible. HRG codes are derived from EDs and ignore data about the treating physician; this makes the use of HRG codes to cost the hourly rate of the respective clinicians impossible.
Discussion
Our CCA to investigate the economic impact of GPs working at study site Parallel-2 suggests that GPs can provide a time and investigation sparing service to patients with the marker conditions selected for this research, without increasing admission or reattendance rates. Our results from the analysis of the outcomes of management of all marker conditions and the related sensitivity analyses suggest that these GPs may manage the patients presenting with the marker conditions more quickly, the main driver of this difference being the time taken from treatment to discharge, rather than the time from admission to the ED to being seen for treatment. However, in this single-site observational study, caution must be exercised in overinterpreting patient conditions where the disparity in age of patients streamed to GP compared to ED clinician, for some marker conditions (chest pain, abdominal pain), suggests potential selection bias, with ED clinicians seeing older higher-risk groups.
The GPs completed patient management (i.e. T2–T3) more quickly, compared with ED clinicians, in both the base-case and sensitivity analyses. However, there may be other factors affecting these time differences. To adjust for these other factors, a regression analysis was undertaken on the overall population (all marker conditions). Adjusting for the potential influencing factors (treating doctor; GP vs. ED clinician, the marker condition, patient age, whether admitted or discharged, investigation and treatment category and triage category, patients spent 7.7 fewer minutes overall in ED but from the time when treatment is initiated, to discharge (T2–T3) patients with marker conditions had 17.5 fewer minutes being treated by GPs than ED clinicians. This is a potentially meaningful amount of time, at a stage of treatment where clinician time is a scarce resource and the time saved may be useful for deployment elsewhere if aggregated across a shift or day. However, given high unexplained variance for this analysis, caution is required in interpretation of its significance. Furthermore, it is important to consider the impact of the way of working in this site; the GPs work from a separate area and can be relatively undisturbed when they are seeing patients and the ED clinician may be managing more than one patient and/or being interrupted.
This economic analysis did not set out to examine the effectiveness of the streaming service. Our results suggest streaming at Parallel-2 effectively directs lower severity and less complex patients to the GP service, potentially enabling shorter treatment times (and improved patient experience) than if the patient with the same marker condition severity were seen by ED clinicians.
Across all marker conditions, the trend was for GPs to admit fewer patients than ED clinicians. This trend was more evident (and for some reaching statistical significance) among those requiring the lowest levels of intervention. Reassuringly, the reattendance rate for patients with the same marker condition at 7 days was the same for both GPs and ED clinicians and patients’ destination at discharge did not vary between the treating clinicians. The Parallel-2 study site which provided the data for analysis could provide costs of providing the GP service. This was because the funding for the service was provided by the local CCG as part of a wider package that supported urgent care in the region across several sites and the salary data were not available to the CD. However, across all study sites, we gained a reasonable sense of the different ways in which the GPs providing the service were paid and the pros and cons of these approaches (see Chapter 5, Table 14).150 One site (Integrated-2) provided hourly rates of £65 for GPs employed in the ED, and we used this as our base case and undertook a sensitivity analysis using other information. From the cost scenarios we put together in Table 14 it seems that the GP service, however funded, is likely to cost more per hour of provision than middle-grade ED clinicians seeing patients that GPs might see. There are trade-offs – again potentially unique to each ED – in that while there may be resource release for ED clinicians, these must be offset against potentially increased admissions, investigations and treatments for patients managed by ED clinicians. Caution is required in interpreting this as there may be selection bias for types of patients treated in the ED (even at given severity levels).
As each GP in ED service is likely to have individual characteristics and sources of funding and our research here is based on only one site – an inside–parallel model – the findings of the study, both costs and consequences should be interpreted and applied with caution as different service models may not see the same outcomes. This research should be contextualised by individual trusts or CCGs for potential application, to decide whether the time savings observed when using GPs in EDs are also likely to result in cost savings or resource release or a better way of managing flow and patient care, as results at this case site suggest. Any service model must also be viewed in the light of its local funding model and where the costs are borne.
We have therefore refined our initial theory as follows:
New theory: If a patient attends an ED with a primary care type problem and is triaged and streamed appropriately to a GP service (C), the GP can use their skills and experience to manage the patient appropriately (M). In this setting, the GP can take less time to manage the patient than an ED clinician (O). The GP is also likely to use fewer investigations and treatments and admit fewer patients (M) without a negative impact on reattendances for the same problem (O). This service may incur relatively higher salary costs (O) which may (or may not) be offset by costs saved through reductions in activity outcomes, but GPs efficiently managing primary care type problems (M) may enable ED clinicians to see more seriously ill patients (O).
Strengths and limitations
Our analysis of the management of marker conditions has strengths and weaknesses which affect interpretation.
The strength of this study is that the data were comprehensive, reasonably complete (at this site) and supported the CCA (see Chapter 5). The hospital collects high-quality ED data and was an early adopter of the ECDS and invests in data management and analysis. The service had a modern well-resourced Urgent Care service staffed at least 10 hours per day. However, this site will not function as other GP services do, so our findings may not be generalisable or replicable.
As a service that has matured, and the 12-month period selected for our data extract was viewed as the service running at ‘steady state’, we believe our findings to be valuable. However, insights from the qualitative research (see Chapter 4) suggest that the performance of the service is influenced by ‘intangible’ factors; for example, it was suggested that the type of GP is important – ‘our sort of people’ – who fit well with aims of the service and ways of working and it took time to reach this situation. The service is also committed to ‘sorting the patient out’ once they have attended rather than redirecting them to a potentially more appropriate place of care.
The findings revealed a clear pattern of GPs seeing patients in the less severe/less complex HRG categories and the ED clinicians seeing patients who have more severe and complex HRG investigation and treatment categories. However, this should be interpreted with caution: If the ED clinicians overtreat and investigate patients who are in fact less complex and severe, then we are miscategorising these patients as severe and may have underestimated differences in admission rates between ED and GP clinicians.
Although some significant differences were observed in admission rates between GPs and ED clinicians, most differences were not significant. It is possible that there are true differences between the clinician groups, but because of small sample size for admission rates within conditions and severity levels, this difference could not be observed.
Further research
The original aim of the study was to undertake the analysis presented here in all the contributing centres. We conceived that either availability or quality of the data may preclude some centres contributing data. The COVID-19 pandemic made further enquiries for data to examine the impact of GP models on ED resources impossible. As this is an analysis based on a single centre, although potentially representative of some EDs in metropolitan areas, further research is necessary in a range of EDs and typologies, as originally conceived for this research to assess generalisability. This would deliver a better assessment of whether and how a GP service supports the care of patients attending EDs with primary care problems.
The process of defining the analysis was iterative, supported by the site CD and data analyst and the ED clinician co-investigators. Feedback about the data analysis for the ED and its GP service was deemed very useful, providing new insights. This feedback suggests that undertaking similar analyses on a regular basis may enable EDs with GPs supporting the service to understand the contribution that GPs make and how patient management is impacting the service as ECDS data collection matures.