Open Access

A patient-safety and professional perspective on non-conveyance in ambulance care: a systematic review

  • Remco H.A. Ebben1Email author,
  • Lilian C.M. Vloet1, 2,
  • Renate F. Speijers1, 3,
  • Nico W. Tönjes1, 4, 5,
  • Jorik Loef1,
  • Thomas Pelgrim1,
  • Margreet Hoogeveen6 and
  • Sivera A.A. Berben1, 2, 7
Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine201725:71

https://doi.org/10.1186/s13049-017-0409-6

Received: 21 April 2017

Accepted: 22 June 2017

Published: 17 July 2017

Abstract

Background

This systematic review aimed to describe non-conveyance in ambulance care from patient-safety and ambulance professional perspectives. The review specifically focussed at describing (1) ambulance non-conveyance rates, (2) characteristics of non-conveyed patients, (3) follow-up care after non-conveyance, (4) existing guidelines or protocols, and (5) influencing factors during the non-conveyance decision making process.

Methods

We systematically searched MEDLINE, PubMed, CINAHL, EMBASE, and reference lists of included articles, in June 2016. We included all types of peer-reviewed designs on the five topics. Couples of two independent reviewers performed the selection process, the quality assessment, and data extraction.

Results

We included 67 studies with low to moderate quality. Non-conveyance rates for general patient populations ranged from 3.7%–93.7%. Non-conveyed patients have a variety of initial complaints, common initial complaints are related to trauma and neurology. Furthermore, vulnerable patients groups as children and elderly are more represented in the non-conveyance population. Within 24 h–48 h after non-conveyance, 2.5%–6.1% of the patients have EMS representations, and 4.6–19.0% present themselves at the ED. Mortality rates vary from 0.2%–3.5% after 24 h, up to 0.3%–6.1% after 72 h. Criteria to guide non-conveyance decisions are vital signs, ingestion of drugs/alcohol, and level of consciousness. A limited amount of non-conveyance guidelines or protocols is available for general and specific patient populations. Factors influencing the non-conveyance decision are related to the professional (competencies, experience, intuition), the patient (health status, refusal, wishes and best interest), the healthcare system (access to general practitioner/other healthcare facilities/patient information), and supportive tools (online medical control, high risk card).

Conclusions

Non-conveyance rates for general and specific patient populations vary. Patients in the non-conveyance population present themselves with a variety of initial complaints and conditions, common initial complaints or conditions are related to trauma and neurology. After non-conveyance, a proportion of patients re-enters the emergency healthcare system within 2 days. For ambulance professionals the non-conveyance decision-making process is complex and multifactorial. Competencies needed to perform non-conveyance are marginally described, and there is a limited amount of supportive tools is available for general and specific non-conveyance populations. This may compromise patient-safety.

Keywords

Emergency medical services [MeSH] Patient safety [MeSH] Clinical competence [MeSH] Non-conveyance

Background

The past decades, ambulance care has evolved from a health care facility that conveys patients to the hospital, into emergency medical services (EMS) that provide advanced out-of-hospital care for (non-) life-threatening conditions [1, 2]. At the same time, the utilization of ambulance care has increased throughout the developed world, with various underlying reasons such as ageing of the population, changes in social support, accessibility and costs [3]. Together, these developments put a growing demand on ambulance systems and ambulance capacity, the emergency departments (ED) and the wider healthcare system, and this may compromise patient safety, healthcare quality, and access [3]. In addition to this growing demand, frequent overcrowding of the ED occurs [4, 5].

The ambulance process is situated within this context. This process often results in patient conveyance to an ED or other healthcare facility, but ambulance care can also result in patients not being conveyed. The NHS Litigation Authority (2012) defines conveyance as “the transfer of patients, medical and clinical personnel, equipment and associated records, as appropriate including from one healthcare facility to another as well as the initial journey from the scene.” [6]. Non-conveyance is defined as “an ambulance deployment as appropriate, where the patient after examination and/or treatment on-scene does not require conveyance with medical personnel and equipment to the healthcare facility” [7]. Non-conveyed patients can be treated and ‘discharged’ on-scene, or may be referred to other (primary) healthcare facilities such as the general practitioner. According to the literature, non-conveyance can be divided in two categories: the patient-initiated refusal and the ambulance professional decision [8]. Often, non-conveyance is a combination of these two categories.

Non-conveyance rates of patients who received on-scene emergency care from an ambulance emergency crew, have been reported up to 30% [9, 10]. On the other hand, it has been estimated that 11%–61% of the conveyances is medically not necessary [11]. Factors influencing these non-conveyance rates are patients with low-acuity problems or primary care problems who call an ambulance [12, 13], accuracy of triage systems at the EMS dispatch centre [14], and professional competencies [15].

The priority to conduct research on non-conveyance is reflected on the Dutch National Pre-hospital Research Agenda for EMS 2014–2018 [16]. From patient-safety and professional perspective, little is known about non-conveyance. Insight into characteristics and outcomes of the non-conveyance patients is lacking. Furthermore, it is unknown how often non-conveyance exactly occurs, which complaints non-conveyed patients have, what care is provided after non-conveyance, and how often these patients have adverse events. Conversely from the professional perspective, little is known about the on-scene non-conveyance decision-making process. As ambulance care has become a more complex environment, ambulance professionals are faced with decision-making over multiple care options as conveyance to an emergency department, or another non-emergency service, treat-and-release or referral to another healthcare professional [17]. Literature described that this decision-making process requires adequate competencies, skills and clinical reasoning of ambulance professionals [18], although ambulance professionals curricula include a little on conveyance decision making [19]. Also, few ambulance services developed non-conveyance protocols and policies [20]. However, the question is whether the literature describes guidelines, protocols or triage criteria to support the ambulance professionals in the decision making process for non-conveyance, how competent are they to decide and apply for non-conveyance, and how are they influenced during the decision making process for non-conveyance? These aspects of patient safety and ambulance professional perspectives related to non-conveyance in ambulance EMS have not yet been synthesized in an overview.

Aim

The aim of this systematic review is twofold. The first aim is safety orientated, as we want to describe non-conveyance rates, characteristics of patients, and follow-up care after non-conveyance. The second aim is formulated from the perspective of the ambulance professional, as we want to describe available guidelines or protocols and triage criteria, competencies needed by ambulance professionals to make appropriate (non-) conveyance decisions, and also to describe which factors influence ambulance professionals during the decision-making process.

Methods

Design

A systematic review of the literature was performed according to the steps of the Cochrane Handbook for Systematic Reviews of Interventions [21]. This review is reported in concordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (Additional file 1: PRISMA) statement [22].

Search strategy

Firstly, the Cochrane database for systematic reviews and the DARE database were checked for a similar review (protocol). No review was identified, therefore systematic searches were performed in MEDLINE (EBSCO), PubMed, CINAHL (EBSCO), and EMBASE (OVID) in June 2016. Search strategies were developed to represent ‘terms for non-conveyance’ AND ‘terms for pre-hospital ambulance care’. Full search strategies per database are given in Additional file 2: Appendix 1. Searches were not restricted by year of publication. In addition to the electronic searches, after full-text inclusion we hand-searched reference lists to identify relevant studies.

Study selection procedure

We included all types of peer-reviewed systematic reviews, and quantitative or qualitative designs in real clinical practice or simulation situations, on non-conveyance. We defined non-conveyance as ‘the situation where an ambulance was dispatched and where the patient received on-scene diagnostics and/or treatment, followed by professional and/or patient initiated non-conveyance to the ED or another emergency care facility’. Studies were included when reporting on one or more of the following criteria:
  • Non-conveyance rates;

  • Characteristics of non-conveyed patients;

  • Follow-up care after non-conveyance;

  • Non-conveyance guidelines, protocols, or on-scene triage criteria;

  • Professional competencies needed to initiate non-conveyance;

  • Factors influencing the non-conveyance decision-making process.

Conference abstracts, narrative reviews, editorials, personal communications, or unpublished studies were excluded. All articles were screened on title and abstract by two independent reviewers (RE, SB, RS, NT, LV). In case of doubt, a third reviewer (SB, LV) was asked to make a final decision. The remaining articles were screened full text by two independent reviewers (RE, SB, RS, NT, JL, LV). In addition, reference lists of included articles were screened (RE, JL) and potentially relevant publications were screened in a similar way (RE, RS, NT, JL).

Quality assessment

To assess the risk of bias of (pre-, or quasi-) experimental studies we used the ‘risk of bias assessment tool’ [21]. This tool is a domain-based evaluation to assess selection bias, performance bias, attrition bias, detection bias and reporting bias. For non-randomized studies, the Cochrane collaboration recommends to add additional domains. Therefore, we added two domains to the tool: (1) randomization (yes/no), and (2) control group (yes/no). To assess the quality of systematic reviews we used AMSTAR, as recommended by Cochrane [23]. To assess the quality of observational studies (retrospective, cross-sectional, prospective) and qualitative studies we used tools developed for evaluating primary research papers in a variety of fields [24]. From the 14-criteria quantitative tool, we deleted three criteria (criteria five, six, and seven) on experimental research as we assessed quality of experimental studies with the tool described above. For qualitative studies we used the 10-criteria tool. The quality assessment was performed by couples of two independent researchers (RE, RS, NT, JL). In case of doubt, a third reviewer from these four researchers was asked to make a final decision.

Data extraction

Data were extracted by two independent researchers (RE, RS, NT, JL). Outcomes extracted were non-conveyance rates, characteristics of non-conveyed patients, existing guidelines, protocols or triage criteria for non-conveyance, follow-up care by patients after non-conveyance, ambulance professionals competencies needed to perform non-conveyance, and factors influencing ambulance professionals during the non-conveyance decision-making process.

Data synthesis and presentation

Due to heterogeneity of the studies with regard to patient populations, interventions and outcomes, a meta-analysis was not possible. Instead, we extensively analysed and synthesized the studies, by scrutinizing and categorizing data and formulating (sub)themes. To report non-conveyance rates, percentages were extracted or calculated. When patients died or left the scene before ambulance arrival, these were not taken into account for non-conveyance rates. To compare patients’ initial complaints or conditions across studies, we classified these according to the ICD-10 classification [25]. The ICD-10 classification is an international standard to classify diseases or other health problems, and is widely accepted and used. For each ICD-10 category we described the proportions of the patients who had a certain classification.

Results

Review statistics

The initial search identified 2989 unique records, after the selection procedure 67 studies were included (see Fig. 1). A list of excluded articles (n = 67) is provided in Additional file 3: Appendix 2.
Fig. 1

study selection process

Study Characteristics

The designs of the included studies concerned two systematic reviews [10, 26], four experimental designs: one cluster-randomized controlled trial [27], one quasi-experimental [28], and two pre-test post-test [29, 30], 52 observational designs: 27 retrospective [8, 9, 3155], 23 prospective [5678], and two cross-sectional [79, 80], one mixed method design [81], and eight qualitative designs [8289] (Table 1 and Table 2).
Table 1

Characteristics of quantitative and qualitative included studies (n = 65)

1st author (Year) Country [ref]

Design

Methods/Data sources

Patients (n)

Professionals (n)

Alicandro (1995) USA [29]

Pre-test post-test

Data card, Online database

Patients (n = 361) who refused conveyance

Not described

Alrazeeni (2016) Saudi Arabia [31]

Retrospective, observational

Patient care reports

Patients (n = 1791) who were not conveyed

EMTs

Anderson (2002) Denmark [32]

Retrospective, observational

Prehospital database, National Patient Register, Central Personal registry, Registry of Causes of Death

Patients (n = 1187) with hypoglycaemia

MICU physicians

Burstein (1996) USA [56]

Prospective, cohort

Identifying card, Telephone follow-up

Patients (n = 361) who refused medical assistance

Emergency physicians (n = 22), ALS and BLS providers

Burstein (1998) USA [57]

Prospective, observational

10-point assertiveness scale, ED disposition instrument

Patients (n = 130) who refused medical assistance

Paramedic medical-control console operators, EMS-crews, Emergency physicians

Burrell (2013) UK [82]

Qualitative

Topic guided in-depth interviews

No patient population included

EMT level 2 (n = 1), EMT level (n = 4), Paramedics (n = 5), Paramedic team leaders (n = 4), Emergency care practitioner (n = 1)

Cain (2003) USA [58]

Prospective, observational

Patient care report, Refusal form

Ambulance calls (n = 17,416)

Basic & advanced paramedics

Carter (2002) Canada [59]

Prospective, observational

Telephone calls, Ambulance call reports

Patients (n = 100) with hypoglycaemia receiving IV dextrose

Paramedics, Emergency medicine senior residents

Chen (1996) Taiwan [60]

Prospective, observational

Dispatch record, Ambulance run record, ED disposition form

Patients (n = 1035) who called an ambulance

EMTs

Cone (1995) USA [8]

Retrospective, observational

Emergency department records, Telephone follow-up, Ambulance call reports, Medical command control forms

Patients (n = 85) who refused conveyance

Paramedics, Volunteer municipal basic life support units

Deasy (2008) Ireland [61]

Prospective observational

Data sheets

Ambulance calls (n = 263)

Emergency Medicine Specialists, Paramedics

Ebrahimian (2014) Iran [83]

Qualitative

Semi-structured interviews

No patient population included

EMS staffs (n = 18)

Gerlacher (2001) USA [79]

Cross-sectional

Patient records

Patients (n = 15,409) ≤ 12 years

First responder firefighters, EMTs, Paramedics

Goldstein (2015) Canada [33]

Retrospective, observational

Electronic patient care records

Patients (n = 63,067) ≥ 65 years

Primary care paramedics, Intermediate care paramedics, Advanced care paramedics

Haines (2006) USA [62]

Prospective, observational

Telephone follow-up questionnaire, Ambulance records

Patients (n = 5336) <21 years

ALS-paramedics, Physicians

Halter (2011) UK [84]

Qualitative

Semi-structured interviews

No patient population included

EMTs, Paramedics (n = 12)

Hipskind (1997) USA [63]

Prospective, observational

Ambulance run reports

Patients (n = 683) who refused conveyance

Paramedics (n ≈ 350)

Højfeld (2014) Denmark [34]

Retrospective, observational

MECU database, Medical records

Mobile emergency care unit runs (n = 15,392)

Anaesthesiologists

Jensen (2013) Canada [64]

Prospective, observational

Data from emergency health services, Patient care records, Databases

Ambulance calls (n = 265) for long term care facility patient

Extended care paramedics (n = 7), Paramedics

Kahalé (2006) Canada [65]

Prospective, observational

Ambulance call reports, Hospital charts, Telephone interviews

Patients (n = 345) <16 years

EMTs, Paramedics

Kamper (2001) USA [35]

Retrospective, observational

Ambulance run records, ED records, Hospital records

Ambulance calls (n = 53,627)

Paramedics

Kannikeswaran (2007) USA [36]

Retrospective, observational

Standardized data extraction sheets

Ambulance runs (n = 5976) for children <18 years

EMT-Ps, EMT-Bs

Keene (2015) Australia [85]

Mixed-methods

Structured interviews, Patient care records

Patients (n = 33,333) where an ambulance was dispatched

Ambulance paramedics, Intensive care paramedics

Key (2003) USA [30]

Pre-test post-test

Patient/ambulance records

Ambulance calls (n = 11,488)

Paramedics, EMTs

Knight (2003) USA [37]

Retrospective, descriptive

State-wide EMS data, State-wide ED data, Death certificate data

EMS dispatches (n = 277,221)

Not described

Lerner (2003) USA [66]

Prospective, observational

Telephone interviews

Patients (n = 36) with hypoglycaemia

EMT-Ps (n = 23)

Magnusson (2016) Sweden [38]

Retrospective, observational

Patient notes

Patients (n = 529) with low priority, uncertain need for ambulance and vague symptoms

Ambulance nurses

Marks (2002) UK [9]

Retrospective, observational

Patient report forms

Patients (n = 500) not conveyed

EMTs, Paramedics

Mechem (1998) USA [67]

Prospective, observational

Telephone interviews

Ambulance calls (n = 115,135)

Nurses, Paramedics

Minhas (2015) Canada [39]

Retrospective, cohort

EMS patient records, ED patient records

Patients (n = 286) 18–65 years with supraventricular tachycardia

ALS paramedics

Moss (1998) USA [40]

Retrospective, observational

Prehospital records

EMS responses (n = 6512)

Paramedics

Murphy-Jones (2016) UK [86]

qualitative, phenomenological

Semi-structured interviews

No patient population included

Paramedics (n = 6)

Newton (2015) South-Africa [68]

Prospective, observational

Computerized dispatch logs, Patient report forms

Ambulance calls (n = 1689)

BLS emergency care providers, ILS emergency care providers, ALS emergency care providers

O’Hara (2015) UK [87]

Qualitative

Reviewing relevant national and local documents (Reports, policies, protocols), Semi-structured interviews, Observations, Digital diaries, Informal interviews, Focus groups, Written notes

No patient population included

Directors, Managers, Specialist paramedics, Paramedics, Emergency care assistants/technicians/support workers

Persse (2002) USA [69]

Prospective, observational

Patient care records, Structured telephone interviews

Patients (n = 2207) ≥ 65 years

Paramedics, EMTs

Peyravi (2013) Iran [41]

Retrospective, observational

National data registry, Ambulance station data registry

Ambulance runs (n = 84,084)

Nurses, Paramedics, GPs

Peyravi (2015) Iran [42]

Retrospective observational

Patient care records, Telephone interviews

Ambulance runs (n = 81,999)

Not described

Porter (2007) UK [88]

Qualitative

Focus groups (n = 3)

No patient population included

Paramedics (n = 25)

Pringle (2005) USA [43]

Retrospective, observational

EMS reports, Telephone interviews

EMS patient encounters (n = 1894)

EMT-Bs, Paramedics

Rudolph (2011) Denmark [44]

retrospective, observational

Medical emergency care unit database, Autopsy reports

Patients (n = 4762) with acute opioid overdose

Anaesthesiology specialists, ALS providers

Schmidt (2001) USA [70]

Prospective, observational

Patient records

Patients (n = 1433) were an ambulance was dispatched

EMT-Ps, EMT-ILSs, EMT-Bs

Schmidt (1998) USA [71]

Prospective, observational

Structured telephone interview

Patients (n = 324) who refused conveyance

Paramedics

Schmidt (2000) USA [72]

Prospective observational

Data sheets

Patients (n = 1433) where an ambulance was dispatched

EMT-Ps, EMT-ILSs, EMT-Bs

Schmidt (2006) USA [45]

retrospective, observational

EMS database

Ambulance runs (n = 1501)

Paramedics

Selden (1990) USA [46]

Retrospective, observational

Run records

Ambulance runs (n = 11,780)

Paramedics

Seltzer (2001) USA [47]

Retrospective, observational

Run records, Structured telephone interviews

Patients (n = 89) <18 years who refused conveyance against medical advice

EMT-Ds, EMT-Ps

Shaw (2006) UK [81]

Mixed methods

Patient records

Ambulance runs (n = 76,635)

Paramedics, EMTs

Simpson (2014a) Australia [74]

Prospective, cohort

Data sheets, Administrative databases

Patients (n = 1610) ≥65 years who have fallen

Paramedics

Simpson (2014b) Australia [73]

Prospective, cohort

Data collection tool, Dispatch system

Patients (n = 1610) ≥65 years who have fallen

Paramedics (n = 384)

Snooks (2005) UK [89]

Qualitative

Focus groups

No patient population included

Paramedics (n = 26)

Snooks (2014) UK [27]

CRCT

Paramedic records, ED records

Patients (n = 779) ≥65 years who have fallen

Paramedics (n = 42)

Snooks (2004a) UK [28]

Quasi-experimental

Patient report forms, ED records, GP records, Questionnaire

Patients (n = 797) were an ambulance was dispatched

Paramedics (n = 5), EMTs (n = 5)

Socransky (1998) USA [48]

Retrospective, observational

Patient records, Hospital records

Ambulance runs (n = 10,888)

Paramedics

Stark (1990) USA [49]

Retrospective, observational

EMS database

Ambulance calls (n = 1715)

Paramedics, Physicians

Staudenmayer (2012) USA [50]

Retrospective, cohort

Population-based injury database

Patients (n = 69,413) with a primary diagnosis of ‘injury’ or ‘trauma’

Not described

Strote (2008) USA [75]

Prospective, cohort

Medical incident report forms, Telephone interviews

Patients (n = 2359) with hypoglycaemia

EMTs, Paramedics

Stuhlmiller (2005) USA [51]

Retrospective, observational

On-line medical command audio tapes, Patient run sheets, Non-conveyance sheets

On-line medical control calls (n = 137) for patient-initiated refusals

Paramedics

Tiedemann (2013) Australia [76]

Prospective, cohort

Patient records, Questionnaires (e-mail)

Patients (n = 2842) ≥70 years who have fallen

Paramedics

Tohira (2016a) Australia [53]

Retrospective cohort

Patient care records, ED information system, Death registry

Patients (n = 1238) post-ictal or with hypoglycaemia

Paramedics

Tohira (2016b) Australia [52]

Retrospective, cohort

Patient care records, ED information system, Death registry

Patients (n = 127,574) were an ambulance was dispatched

Paramedics

Van der Pols (2011) Netherlands [77]

Prospective, cohort

Patient record, Hospital databases, Dispatch centre database

Patients (n = 1842) were an ambulance was dispatched

Ambulance nurses

Vilke (1999) USA [54]

Retrospective, observational

Prehospital database, Death registry

Patients (n = 94,466) were an ambulance was dispatched

Paramedics

Vilke (2002) USA [78]

Prospective, observational

Telephone interviews

Patients (n = 636) ≥ 65 years and who signed out against medical advise

EMTs, EMT-Ps, EMT-Ds

Zachariah (1992) USA [55]

Retrospective, observational

Patient records, Structured telephone interviews

Patients (n = 158) not conveyed

Paramedics

Zorab (2015) UK [80]

Cross-sectional

Questionnaires

No patient population included

Emergency Care Assistants, Ambulance Technicians, Student Paramedics, Paramedics, Emergency Care Practitioners, Critical Care Paramedics

Abbreviations: ALS Advanced life Support, BLS Basic Life Support, ED Emergency Department, EMD emergency medical department, EMS Emergency Medical Service, EMT Emergency Medical Technician, EMT-B Emergency Medical Technician Basic, EMT-D Emergency Medical Technician Defibrillation, EMT-ILS Emergency Medical Technician Intermediate Life Support, EMT-P Emergency Medical Technician Paramedics, GP general practitioner, ILS Intermediate Life Support, MECU Mobile Emergency Care Unit, MICU Mobile Intensive Care Unit

Table 2

Characteristics systematic reviews (n = 2)

1st author (year) country

Aim

Databases

Selection criteria

Included articles

Mikolaizak (2013) Australia [26]

To summarize the evidence in relation to (1) non-conveyance rates, (2) outcomes following non-conveyance, and (3) outcomes from alternative care pathways for non-conveyed older people who have fallen

1. Medline

2. Embase

3. CINAHL

4.PsycINFO

5.Cochrane Library

6. Web of Science

1. Peer-reviewed articles

2. Original data relating to non-transport rates for older people who have fallen

3. Outcomes on falls or outcomes for alternate care pathways for non-transported people who have fallen

12 articles: 2 randomized controlled trials, 5 prospective cohort studies, 4 retrospective cohort studies and 1 historical cohort trial.

Snooks (2004b) UK [10]

1. To describe outcomes of non-conveyed patients

2. To describe triage ability of crews

3. To assess effectiveness and safety of protocols that allow crews to convey patients to alternative receiving units or to self-care

1. Medline

2. BIDS

3.Healthplan

4. Helmis

Articles on paramedics trained with extra skills to perform tasks beyond their baseline competencies

31 articles: 13 retrospective observational studies, 8 prospective observational studies, 6 cross-sectional studies, 3 case studies and 1 quasi-experimental study

The two systematic review were performed in Australia and the UK. The empiric studies were conducted in North America (n = 36), Europe (n = 17), Australia (n = 6), Asia (n = 5), and Africa (n = 1), and concerned general patient populations or specific patient populations, including patients with hypoglycaemia, patients who refused conveyance, paediatric and/or older patients, patients with supraventricular tachycardia, patient with acute opioid overdose, post-ictal patients, and patients who had fallen. The ambulance professionals in these studies were ambulance nurses, basic and advanced life support paramedics, emergency medical technicians, (specialized) physicians, general practitioners, and first responder fire fighters. For this review we will use the term ‘ambulance professional’ to cover all these types of professionals.

Quality assessment (Additional file 4: Appendix 3, Additional file-5: Appendix 4, Additional file 6: Appendix 5, Additional file 7: Appendix 6)

The two included systematic reviews had moderate [26] and low quality [10] (Additional file 4: Appendix 3). The four experimental designs included one CRCT of moderate quality [27], one quasi-experimental study [28] and two pre-test post-test [29, 30] of poor quality (Additional file 5: Appendix 4). The quality of the quantitative studies (n = 53) varied from good [76] to poor [42] (Additional file 6: Appendix 5), and the quality of the qualitative studies (n = 8) varied from good [83] to poor [88] (Additional file 7: Appendix 6).

Outcomes

Non-conveyance rates (Additional file 8: Appendix 7)

Non-conveyance was initiated by the ambulance professional, the patient and/or his relatives, or a joint decision. Non-conveyance rates for general patient populations ranged from 3.7% up to 93.7% [28, 30, 31, 3335, 37, 38, 4043, 45, 46, 49, 51, 52, 57, 60, 61, 64, 68, 77, 81]. Seventeen studies reported non-conveyance rates for specific patient populations. For patients with hypoglycaemia non-conveyance rates ranged from 12.2% up to 84.3% [32, 48, 53, 58, 59, 75]. Non-conveyance rates for people who had fallen ranged from 11%–56% [26, 27, 73, 74]. For paediatric patients non-conveyance rates ranged from 13.2%–27.7% [36, 62, 79]. Two studies reported non-conveyance rates for patients with an opioid overdose, ranging from 6.0%–77.0% [44, 54]. Non-conveyance rates for other specific patient groups were 14.0% for post-ictal patients [53], 33.2% for patients with supraventricular tachycardia [39], 10.7%–11.5% for elder people [69], and 8.6% for patients with injuries [50].

Characteristics of non-conveyed patients (Additional file 8 Appendix 7)

The demographic characteristics were age, gender, ethnicity, and geographic area. For general patient populations, the age ranges from 14 up to 90 years [9, 29, 31, 33, 3840, 45, 48, 50, 52, 54, 56, 62, 63, 6567, 73, 74, 76, 78, 79, 85]. Twenty studies reported on patient gender: in ten studies the gender is predominantly male, in the other studies the population is predominantly female [9, 33, 3840, 45, 48, 50, 52, 54, 62, 63, 6567, 73, 74, 76, 79, 85]. Three studies described the geographic location of non-conveyed patients [33, 65, 74]. Two of these show that most non-conveyed people stay in a metropolitan/urban area. The third study showed that 58.6% of the patient are in their residence. Two studies described the patient’s ethnicity [45, 79], with one study reporting 90.6% of the non-conveyed patient as white, the other study reported 48.3% of the patient as African-American.

The clinical characteristics of the patient were initial complaints and conditions, vital signs, and patient history. A variety of initial complaints and conditions was described [9, 29, 34, 38, 40, 45, 52, 56, 57, 6163, 65, 74, 7779, 85]. Most often, we found initial complaints and conditions classified as VI- diseases of the nervous system (n = 16) or category XX - External causes of morbidity and mortality (n = 16). For category VI the proportion of patients with these complaints and conditions ranged from 1.0%–29.0% [9, 29, 34, 38, 40, 45, 52, 56, 57, 61, 63, 65, 7779, 85], for category XX the proportion ranged from 11.0%–68.5% [9, 29, 38, 40, 45, 52, 56, 57, 6163, 65, 7779, 85].

Three studies described the vital signs of non-conveyed patients [50, 52, 63]. One study on a general population reported that 14.9% of the non-conveyed patients had abnormal vital signs (blood pressure, O2-saturation, Glasgow Coma Scale, and body temperature) [52]. A second study in a non-conveyed general patient population reported that 70.0% had a blood pressure within normal limits, 72.2% had a heart rate within normal limits, and 63.2% had a respiratory rate within normal limits [63]. The last study on vital signs with injured people not conveyed reported a mean systolic blood pressure of 134.7 mmHg (±21.1), a mean pulse rate of 91.8 (±15.9), and a mean Glasgow Coma Scale of 15.0 (±0.3) [50].

Five studies described the patient’s history by describing the medical history and/or current medication use [48, 63, 73, 74, 76]. Two studies [63, 76] described the medical history, for general patient populations 68.7% had no medical history [63], for people aged ≥70 years who had fallen 43.8% had urinary incontinence and 39.0% had a central nervous system disorder.

Follow-up of patients after non-conveyance (Table 3)

Follow-up was reported as (a) repeated access to healthcare and (b) patient outcomes. Sixteen studies combined these outcome categories, the other studies used outcomes within one category [8, 26, 28, 32, 3740, 4345, 48, 50, 52, 5559, 62, 6467, 69, 7578, 90]. Repeated access to healthcare was specified as repeated access to (1) emergency department (2) EMS-system (call or ambulance run), (3) the general practitioner, and (4) walk-in clinic. For all outcomes, a variety of follow-up periods was used. In every study that reported on repeated access to healthcare a proportion of patients re-entered the (emergency) healthcare system.
Table 3

Follow-up care after non-conveyance

1st author (year) Country [ref]

Follow-up outcomes

Results

Anderson (2002) Denmark [32]

• Patient outcome – hospitalization

• Patient outcome – recurrent symptoms

• 76/968 (7.9%) patients have secondary blood glucose regulatory problems <72 h

 ◦ 46/76 (60.5%) have a recurrent hypoglycaemia, 33/46 (71.7%) of these cases occur <24-72 h

• 49/968 (5.1%) are hospitalized <72 h

 ◦ 21/49 (42.9%) have a recurrent hypoglycaemia of which 12/21 (57.1%) are hospitalized <24-72 h

Burstein (1996) USA [56]

• Repeat access general healthcare – GP

• Repeat access emergency healthcare – EMS (call or EMS run)

• Repeat access emergency healthcare – ED

• 199/321 (62.0%) patients who had follow-up.

 ◦ 95/199 (47.7%) patients sought additional medical care <1 week.

  ▪ 51/95 (53.7%) went to the ED: 7 through EMS, 41 referred themselves to the ED and 3 were referred by their physician.

  ▪ 44/95 (46.3%) were seen by their physician.

Burstein (1998) USA [57]

• Repeat access general healthcare – GP

• Repeat access emergency healthcare – ED

• Patient outcome – mortality

• Patient outcome – hospitalization

• 66/69 (95.7%) patients could be contacted through follow-up <2–3 days

 ◦ 33/66 (50.0%) patients saw their own physicians

 ◦ 17/66 (25.8%) went to an ED on their own

 ◦ 8/66 (12.1%) were admitted to the hospital

 ◦ 4/66 (6.1%) died

Cain (2003 USA [58]

• Repeat access emergency healthcare – EMS (call or EMS run)

40/145 (27.6%) patients had signs and symptoms compatible with low blood sugar occurring <10 months after initial event and requiring a repeat EMS call:

• 2/24 (8.3%) patients >65 years

• 38/121 (31.4%) patients <65 years

3/145 (2.1%) patients had signs and symptoms compatible with low blood sugar occurring <48 h after initial event and requiring a repeat EMS call:

• 0/24 (0.0%) patients >65 years

• 3/121 (2.5%) patients <65 years

• No significant differences in repeat (p = .43) any time during the ten-month study period, recurrences (p = .33) <48 h and interval for repeat episodes (p = .60) between conveyed and non-conveyed patient calls.

Carter (2002) Canada [59]

• Patient outcome – recurrent symptoms

Repeated access to healthcare <21 days:

• 6/41 (14.6%) patients for all complaints

• 2/41 (4.9%) patients for the same complaint

Cone (1995) USA [8]

• Repeat access general healthcare – GP

• Repeat access emergency healthcare – ED

• Patient outcome – hospitalization

54/81 (67%) had follow-up:

• 37/54 (68.5%) sought no medical care

• 10/54 (18.5%) were evaluated in the ED: 3 were discharged, 7 were admitted: 3 were admitted to monitored beds and 4 were admitted to unmonitored beds

• 7/54 (13.0%) saw their own physician <48 h after refusal

Haines (2006) USA [62]

• Repeat access general healthcare – GP

• Repeat access emergency healthcare – ED

• Patient outcome – hospitalization

527/704 (74.8%) completed phone follow-up:

• 13/527 (2.5%) non-transport group hospitalized

• 279/527 (52.9%) patients had follow-up-care <72 h (median 2.5 h, inter-quartile range 1.5–13 h)

 ◦ 203/279 (72.6%) patients had follow-up-care <12 h

 ◦ 148/279 (65.9%) patients came to ED

 ◦ 95/279 (34.1%) patients came via primary care physician

 ◦ 19/279 (6.8%) patients were evaluated by a medical provider more than once in 72 h

Højfeld (2014) Denmark [34]

• Repeat access emergency healthcare – ED

• Patient outcome – mortality

• Patient outcome – hospitalization

113/1609 (7.0%) patients had renewed treatment in hospital or ED <24 h

 ◦ 58/113 (51.3%) had to be admitted

 ◦ 51/113 (45.1%) visited the ED

 ◦ 4/113 (3.5%) died

Jensen (2013) Canada [64]

• Repeat access emergency healthcare – EMS (call or EMS run)

6/238 (2.5%) patients who received extended paramedic care but who were not transported subsequently triggered a EMS call <48 h

Kahalé (2006) Canada [65]

• Repeat access general healthcare – GP

• Repeat access general healthcare – walk-in clinic

• Repeat access emergency healthcare – ED

51/345 (14.8%) non-transported children were seen at the ED <48 h

Telephone follow-up with patients (n = 106) about additional care <48 h:

• 51/106 (48.1%) patients did not seek medical follow-up

• 28/106 (26.4%) patients went to the ED

• 22/106 (20.8%) patients visited the family physician/paediatrician office

• 4/106 (3.8%) patients visited a walk-in clinic

• 1/106 (0.9%) patients went to a hospital/outpatient clinic

Knight (2003) USA [37]

• Repeat access emergency healthcare – ED

• Repeat access emergency healthcare – EMS (call or EMS run)

• Patient outcome – mortality

• Patient outcome – hospitalization

3454/26574 (13.0%) follow-up was obtained <1 week:

• 174/3454 (5.0%) patients were admitted to the hospital

• 25/3454 (0.7%) patients died

• 465/3454 (13.5%) patient had an EMS dispatch

 ◦ < 3 years: 8/465 (1.7%)

 ◦ 3–12 years: 14/465 (3.0%)

 ◦ 13–17 years: 24/465 (5.2%)

 ◦ 18–64 years: 301/465 (64.7%)

 ◦ ≥ 65 years: 118/465 (25.4%)

• 2790/3454 (80.1%) of the patients had an ED visit

 ◦ < 3 years: 133/3454 (3.9%)

 ◦ 3–12 years: 175/3454 (5.1%)

 ◦ 13–17 years: 223/3454 (6.5%)

 ◦ 18–64 years: 2041/3454 (59.1%)

 ◦ ≥ 65 years: 218/3454 (6.3%)

• 174/3454 (5.0%) of the patients were admitted

 ◦ < 3 years: 12/174 (6.9%)

 ◦ 3–12 years: 13/174 (7.5%)

 ◦ 13–17 years: 7/174 (4.0%)

 ◦ 18–64 years: 97/174 (55.7%)

 ◦ ≥ 65 years: 45/174 (25.9%)

Lerner (2003) USA [66]

• Repeat access general healthcare – GP

• Repeat access emergency healthcare – ED

20/36 (55.6%) sought further medical assistance <48 h:

• 11/20 (55.0%) called their personal physician

• 8/20 (40.0%) visited their personal physician

• 1/20 (5.0%) went to the ED

Magnusson (2016) Sweden [38]

• Repeat access general healthcare – GP

• Repeat access emergency healthcare – ED

• Patient outcome – hospitalization

38/200 (19.0%) patients visited the ED <72 h:

• 24/38 (63.2%) self to ED

◦ 12/24 (50.0%) admitted

• 14/38 (36.8%) referred by GP

◦ 8/14 (57.1%) admitted

Mechem (1998) USA [67]

• Repeat access general healthcare – GP

• Repeat access emergency healthcare – ED

• Repeat access emergency healthcare – EMS (call or EMS run)

• Patient outcome – hospitalization

94/103 (91.3%) patients had no recurrence of symptoms in <72 h:

• 7/94 (7.4%) contacted private physician

9/103 (8.7%) recontacted the EMS < 72 h:

• 5/9 (55.6%) transported and released from ED

• 3/9 (33.3%) transported and admitted

• 1/9 (11.1%) refused transport

Mikolaizak (2013) Australia [26]

• Repeat access general healthcare – GP

• Repeat access general healthcare – walk-in clinic

• Repeat access emergency healthcare – ED

• Repeat access emergency healthcare – EMS (call or EMS run)

• Patient outcome – mortality

• Patient outcome – hospitalization

Follow-up periods varied from 1 to 12 months. Outcomes: 12%–49% readmission in ambulance or other health service facility, non-transported patients have significantly higher risk of death compared to age matched peers

Minhas (2015) Canada [39]

• Repeat access emergency healthcare – EMS (call or EMS run)

1/76 (1.3%) of the patients treated and released had 14 representations <72 h

Moss (1998) USA [40]

• Repeat access emergency healthcare – ED

• Repeat access emergency healthcare – EMS (call or EMS run)

• Patient outcome – mortality

• Patient outcome – hospitalization

431/443 (97.3%) patients a follow-up was obtained:

• 10/431 (2.3%) called EMS again <48 h

 ◦ 4/10 (40.0%) were admitted to a hospital

 ◦ 4/10 (40.0%) were discharged from the ED

 ◦ 1/10 (10.0%) died

 ◦ 1/10 (10.0%) was transferred to another facility

Persse (2002) USA [69]

• Patient outcome – hospitalization

Phase 1: 151/254 (59.5%) patients were contacted by telephone:

 • 56/151 (37.1%) sought further medical help <24 h

 • 19/151 (12.6%) were hospitalized

Phase 2: 109/198 (55.1%) patients were contacted by telephone:

 • 37/109 (33.9%) sought further medical help <24 h

 • 7/109 (6.4%) were hospitalized

Pringle (2005) USA [43]

• Patient outcome – mortality

• Patient outcome – hospitalization

310/906 (34.2%) follow-up was obtained (1 week):

 • 172/310 (55.5%) patients sought medical care:

  ◦ 106/172 (61.6%) medical care was changed

 • 25/310 (8.1%) were admitted to a hospital

 • 1/310 (0.3%) patients died

Rudolph (2011) Denmark [44]

• Patient outcome – mortality

18/2241 (0.8%) patients released on scene died <48 h

Schmidt (2006) USA [45]

• Patient outcome – mortality

2/128 (1.6%) patients not-transported died <30 days

Snooks (2004a) UK [28]

• Patient outcome – hospitalization

Intervention group: 5/93 (5.4%) patients were admitted to a hospital <14 days

Control group: 12/195 (6.2%) patients were admitted to a hospital <14 days

Socransky (1998) USA [48]

• Repeat access emergency healthcare – ED

• Patient outcome – hospitalization

• Patient outcome – recurrent symptoms

25/412 (6.1%) of the patients who refused transport had a relapse <48 h:

 • 14/25 (56.0%) refused transport again

 • 6/25 (24.0%) admitted to the ED

 • 5/25 (20.0%) were admitted to a hospital

Staudenmayer (2011) USA [50]

• Repeat access emergency healthcare – ED

• Patient outcome – hospitalization

• Patient outcome – mortality

1715/5865 (29.2%) follow-up obtained:

 • 1616/1715 (94.2%) patients were seen in the ED and discharged

 • 92/1715 (5.4%) were admitted to the hospital

 • 7/1715 (0.4%) died

Strote (2008) USA [75]

• Repeat access general healthcare – GP

• Repeat access emergency healthcare – ED

• Patient outcome – hospitalization

203/402 (49.5%) follow-up obtained:

 • 111/203 (54.7%) patients contacted their primary care physician <24 h

 • 8/203 (3.9%) patients called the EMS again <48 h

 • 16/203 (7.9%) patients went to the hospital <48 h

Tiedemann (2013) UK [76]

• Patient outcome – recurrent symptoms

62/251 (24.7%) of the non-transported patients required ≥1 fall related repeat ambulance attendance <6 months

Tohira (2016b) Australia [52]

• Repeat access emergency healthcare – ED

• Repeat access emergency healthcare – EMS (call or EMS run)

• Patient outcome – mortality

• Patient outcome – hospitalization

Subsequent events after discharge at the scene, Unadj OR (95% CI) Adj OR (95% CI)

Ambulance request

• Within 1 day 672/11096 (6.1%) 3.5 (3.1–4.0) 3.4 (3.0–3.9)

• Within 3 days 995/11096 (9.0%) 2.3 (2.1–2.5) 2.1 (1.9–2.4)

• Within 7 days 1305/11096 (11.8%) 1.9 (1.7–2.0) 1.7 (1.6–1.9)

ED attendance

• Within 1 day 514/11096 (4.6%) 3.4 (3.0–3.9) 3.3 (2.8–3.8)

• Within 3 days 710/11096 (6.4%) 2.0 (1.8–2.2) 1.9 (1.7–2.2)

• Within 7 days 898/11096 (8.1%) 1.5 (1.4–1.6) 1.4 (1.2–1.5)

Hospitalisation

• Within 1 day 361/11096 (3.3%) 4.1 (3.5–4.9) 4.2 (3.4–5.1)

• Within 3 days 500/11096 (4.5%) 2.5 (2.2–2.9) 2.3 (2.0–2.7)

• Within 7 days 634/11096 (5.7%) 2.0 (1.8–2.2) 1.8 (1.6–2.0)

Death

• Within 1 day 19/11096 (0.2%) 1.6 (0.9–2.8) 1.8 (0.99–3.2)

• Within 3 days 32/11096 (0.3%) 1.7 (1.1–2.6) 1.9 (1.2–3.0)

• Within 7 days 56/11096 (0.5%) 1.6 (1.2–2.3) 1.8 (1.3–2.5)

vs. ED-discharge

Van der Pols (2011) The Netherlands [77]

• Repeat access general healthcare – GP

Motorcycle response vehicles with one ambulance nurse with additional training (n = 468) compared to regular ambulance (n = 1196):

 • referral to GP 138/468 (29.5%) vs 167/1196 (14.0%) RR 2.11 (95%CI 1.73–2.58)

Vilke (2002) USA [78]

• Repeat access general healthcare – GP

• Repeat access general healthcare – walk-in clinic

• Repeat access emergency healthcare – ED

• Repeat access emergency healthcare – EMS (call or EMS run)

71/121 (58.7%) follow-up was obtained:

 • 27/71 (38.0%) visited family physician

 • 25/71 (35.2) visited urgent care facility

 • 9/71 (12.7%) second EMS call and transported to ED

 • 9/71 (12.7%) transport to ED by private vehicle

 • 1/71 (1.4%) second EMS call and treated at scene

Zachariah (1992) USA [55]

• Repeat access general healthcare – GP

• Patient outcome – hospitalization

93/158 (58.9%) follow-up was obtained:

 • 60/93 (64.5%) sought care from a physician:

  ◦ 15/60 (25.0%) were admitted to hospital.

Repeated access to the ED is measured in seventeen studies [8, 26, 37, 38, 40, 48, 50, 52, 56, 57, 62, 6567, 75, 78, 90]. For general patient populations, the follow-up periods ranged from <24 h up to <7 days, and repeated access percentages varied from 4.6–7.0% (<24 h), 19.0% (<48 h), 6.4–25.8% (72 h) up to 8.1–80.1% (<7 days). For specific patient populations (hypoglycaemia, people who had fallen, people aged >65 years, children and people with minor injuries), the follow-up periods ranged from <48 h up to <12 months, and repeated access percentages varied from 5.0–26.4% (<48 h), 65.9% (<72 h), up to 12.0–49.0% (12 months).

Repeated access to the EMS-system is measured in ten studies [26, 37, 39, 40, 52, 56, 58, 64, 67, 78]. For general patient populations, the follow-up periods ranged from <24 h up to <7 days, and repeated access percentages varied from 6.1% (<24 h), 2.3–2.5% (<48 h) up to 7.4–13.5% (<7 days). For specific patient populations (hypoglycaemia, people who had fallen, supraventricular tachycardia, and people aged >65 years), the follow-up periods ranged from <48 h up to <12 months, and repeated access percentages varied from 0.0–2.5% (<48 h), 1.3–8.7% (<72 h), 8.3–31.4% (10 months) up to 12.0–49.0% (12 months).

Repeated access to the GP is measured in thirteen studies [8, 26, 38, 5557, 62, 6567, 75, 77, 78]. For general patient populations, the follow-up periods ranged from <48 h up to <7 days, and repeated access percentages varied from 13.0% (<24 h), 36.8–50.0% (<72 h) up to 46.2% (<7 days). For specific patient populations (hypoglycaemia, people who had fallen, children, and people aged >65 years), the follow-up periods ranged from <24 h up to 12 months, and repeated access percentages varied from 54.7% (24 h), 7.4–40.0% (<48 h), 34.1% (72 h) up to 12.0–49.0% (12 months).

Repeated access to walk-in clinic is measured in three studies for specific patient populations (children, people who had fallen, and patients aged >65 years) [26, 65, 78]. The follow-up periods used for this outcome ranged from <48 h up to 12 months, and repeated access percentages varied from 3.8% (<48 h) up to 12.0–49.0% (12 months).

The patient outcomes measured are mortality, hospitalization and recurrence of symptoms. For general patient populations, the follow-up periods for mortality ranged from <24 h up to <30 days, and mortality rates ranged from 0.2–3.5% (<24 h), 0.3% (<48 h), 0.3–6.1% (<72 h), 0.3%–0.7% (<7 days) up to 1.6% (<30 days) [26, 34, 37, 40, 43, 45, 50, 52, 57]. The one study reporting on a specific patient population (opioid overdose) reported a 0.8% mortality rate < 48 h [44].

The hospitalization follow-up period for general patient populations ranged from <24 h up to <14 days, and hospitalization rates ranged from 3.3% (<24 h), 1.0% (<48 h), 4.5–12.1% (<72 h), 5.0–8.1% (<7 days) up to 5.4–6.2% (<14 days) [8, 28, 34, 37, 38, 40, 43, 52, 55, 57]. For specific patient populations (hypoglycaemia, people who had fallen, children, people with minor injuries, and people aged >65 years) the follow-up periods ranged from <48 h up to 12 months, and hospitalization rates ranged from 1.2–7.9% (<48 h), 2.5–5.1% (<72 h) up to 12.0–49.0% (<12 months) [26, 32, 48, 50, 62, 67, 69, 75].

Recurrence of symptoms for specific patient populations (hypoglycaemia and people who had fallen) varied from 6.1% (48 h), 7.9% (<72 h), 4.9% (<21 days) up to 24.7% (<6 months) [32, 48, 59, 76].

Existing guidelines, protocols and triage criteria for non-conveyance (Additional file 9: Appendix 8)

Criteria to guide the (non-) conveyance decision described mostly are abnormal vital functions related to ‘breathing’ (respiration rate, respiratory distress, dyspnea), abnormal vital functions related to ‘circulation’ (systolic/diastolic blood pressure, pulse), suspected or confirmed ingestion of alcohol or drugs, and an altered level of consciousness (Glasgow coma scale) [28, 29, 39, 40, 43, 46, 5154, 59, 70, 72, 73, 75, 79, 84, 88]. Ten of these studies described more specific flowcharts, tools, checklist or standard operating procedures for non-conveyance in general [43, 51, 72], patients who refuse conveyance [29, 40, 46], and patients who had fallen [84], with supraventricular tachycardia [39], with social problems [28], with hypoglycaemia [53], and post-ictal patients [53].

Professionals competencies and other factors influencing the non-conveyance decision-making process (Table 4)

Factors influencing the non-conveyance decision-making process are related to the professional, the patient and his relatives, the healthcare process/system, or supportive tools [26, 29, 49, 51, 57, 64, 65, 74, 77, 78, 80, 8389] (Table 4). These factors can be present at (a) pre-arrival, when the professional forms an early opinion based on information from the emergency call, during (b) initial patient contact where the ambulance professional gets a first impression of the patient, during (c) patient assessment of vital signs and other parameters, and (d) during the actual (non-) conveyance decision moment [84].
Table 4

Competences and influencing factors (n = 18)

Authors (publication year) country [ref]

Competences/influencing factors

Type of factor

Alicandro (1995) USA [29]

The implementation of a (1) high risk card (T1) and (2) online medical control (T2) for patients with high-risk criteria improved the transport rate: T0 2/60 (3.3%)- T1 7/70 (10.0%) - T2 12/34 (35.3%) p = .00003

1. Supportive tools

2. Healthcare process/system

Burstein (1998) USA [57]

The implementation of medical control by telephone to convince patients who attempt refusal of medical care to be transported to the ED: 61/130 (47%) of the patients was convinced

1. Healthcare process/system

Ebrahimian (2014) Iran [83]

Affecting factors of EMS staffs’ decision about transporting:

1. patient’s condition:

 a. Physical health status

 b. Socioeconomic status:

  i. Patient support system

  ii. Patient and his family’s educational status

  iii. Patient and his family’s financial status

c. Cultural background:

  i. Confidence

  ii. Believes and attitudes

2. The context of the EMS mission:

  a. Characteristics of the mission

  b. EMS staffs’ characteristics

1. Patient/relative

2. Healthcare process/system

Halter (2011) UK [84]

Influencing factors:

 1. Pre-arrival: forming an early opinion from information from the emergency call

 2. Initial contact: assessing the need for any immediate action and establishing a report

 3. Continuing assessment: gathering and assimilating medical and social information

 4. Making a conveyance decision: negotiation, referral and professional defense using professional experience, instinct

1. Healthcare process/system

Jensen (2013) Canada [64]

Extended care paramedics received additional specialized training in the following “extended care” roles:

 1. Geriatric assessments and management

 2. End-of-life care

 3. Primary wound closure techniques (suturing, tissue adhesive)

 4. Point-of-care testing.

LTC patients treated by ECPs remained at the LTC facility in 98 of 140 (70%) cases, compared to 21 of 98(21.4%) of emergency paramedic calls.

1. Professional

Kahalé (2006) Canada [65]

Reasons for non-transport as cited in parent/patient interviews (n = 106):

 1. 31/106 (29.2%) EMS-personnel stated that transport was unnecessary

 2. 25/106 (23.6%) parents thought that going to the hospital was unnecessary

 3. 22/106 (20.8%) parents wanted to use another method of transportation to seek medical care

 4. 5/106 (4.7%) parents were concerned about costs related to ambulance transports

 5. 23/106 (21.7%) other

1. Professional

2. Patient/relative

Keene (2015) Australia [85]

Reasons for not accepting transport (from fieldnotes):

 1. Just wanted reassurance, assistance, advice or support/ referral

 2. Symptoms had resolved prior to arrival or during assessment

 3. Concern over ED waiting time/ED workload

 4. Prior negative experience with a hospital

 5. Personal reasons: (e.g. ‘I just didn’t want to go’. ‘I was embarrassed by all the fuss’

1. Patient/relative

Mikolaizak (2013) Australia [26]

Factors influencing transport decision:

 1. refusal to travel

 2. patient did not sustain an injury/only minor injuries

 3. sufficient on-scene treatment

 4.referral to GP

1. Patient/relative

Murphy-Jones (2016) UK [86]

3 main themes:

1. Patient wishes (insufficient care plans, nursing care staff insufficient knowledge of patients’ wishes, patients’ inability to express their wishes)

2. patients’ best interest (when patients were not considered to have the capacity for decision making, paramedics want to act in their best interest, factors used: diagnosis, comorbidities, quality of life, wishes and current condition, risks and benefits of hospitalization, concerns about care provision in some nursing homes

3. influence of others (nursing home staff, patients’ relatives and other paramedics)

1. Patient/relative

2. Healthcare process/system

O’Hara (2015) UK [87]

7 overarching system influences on decision making:

1. Increasing demand (of non-emergent cases)

2. Performance regime and priorities

3. Access to appropriate care options in case of non-conveyance to an ED

4. Disproportionate risk aversion: non-conveyance was perceived as a risk for both patient and paramedic

5. Beneficial impact of additional training on decision making competences

6. Communication and feedback to crews

7. Ambulance service resources

1. Healthcare process/system

Porter (2007) UK [88]

Influencing factors:

1. Patient autonomy

2. Opinion family/carers

3. Clinical need as assessed by crew members

4. Protection of themselves for the risk of litigation by crew members

5. Mental capacity of the patient to make a transport decision

6. Lacking skills or status of the crew member to be judging the mental capacity of the patient

7. Back-up of other professionals

8. Fear of a possible comeback if the non-conveyance decision turned out to be wrong

1. Patient/relative

2. Professional

Simpson (2014a) Australia [74]

6-item predictive model for non-conveyance odds (goodness-of-fit test indicated good model fit (8 DF, χ2 = 7.43, p = 0.49), factors associated with increased odds of a non-conveyance outcome.

1. 65–74 year

2. Lower response priority (90 min response time)

3. The presence of personal alarm

4. The absence of new injury/pain

5. Normal physiology

6. Change in usual level of function post fall

1. Patient/relative

2. Healthcare process/system

Snooks (2005) UK [89]

Influencing factors on ED conveyance:

1. Experience and intuition of the paramedic

2. Pragmatism: conveyance – the easy option

3. Patient/carer factors

1. Professional

2. Patient/relative

Stark (1990) USA [49]

Predictors for left at Scene Against Medical Advice:

1. Family present (β = −1.87, p = .001)

2. Disorientation (β = −1.04, p = .04)

3. Abnormal speech (β = −1.92, p = .05)

4. Police hold (β = −2.04, p = .03)

5. Alcohol use (β = 1.48, p = .006)

6. Treated hypoglycemia (β = 1.63, p = .05)

1. Patient/relative

2. Healthcare process/system

Stuhlmiller (2005) USA [51]

28/137 (20.4%) patients with whom the online medical control (OLMC) physician spoke during the encounter: 9/28 (32.1%) agreed to be transported, compared with nine (8.3%) of the 109 patients who did not speak to the OLMC physician (p = .001)

1. Supportive tools

Van der Pols (2011) Netherlands [77]

Motorcycle response vehicles with one ambulance nurse with additional training (n = 468) compared to regular ambulance (n = 1196): (1) treat and release 129/468 (27.6%) vs 149/1196 (12.5%) RR 2.21 (95%CI 1.80–2.73)

1. Professional

Vilke (2002) USA [78]

Patient reasons (n = 100) for patients to refuse transport:

1. 37/100 (37.0%) did not want transport and ED care

2. 23/100 (23.0%) concerned about the cost/coverage of ED

3. 19/100 (19.0%) paramedics implied no transport was needed

4. 17/100 (17.0%) concerned about the cost of the ambulance

5. 4/100 (4.0%) language barrier

1. Patient/relative

Zorab (1999) UK [80]

274/302 (90.7%) paramedics felt that a lack of health information of the patient had led to a less appropriate carepathway being selected, information that could have helped according to paramedics:

1. Resuscitation status (n = 233, 77.2%)

2. Current medication (n = 184, 60.9%)

3. Allergy information (n = 103, 34.1%)

4. Previous medical history (n = 262, 86.8%)

5. Patient’s normal parameters (n = 235, 77.8%)

6. End of life care choices (n = 221, 73.2%)

7. Information about implanted devices, e.g. pacemakers (n = 106, 35.1%)

8.Other, e.g. ECG, mental health records, blood and other test results (n = 38, 1.3%)

1. Professional

As for professional related factors, two studies described professional competencies needed to perform non-conveyance. These studies showed that additional training for ambulance professionals led to higher non-conveyance rates compared to ambulance professionals who received regular training [64, 77]. Besides competencies, other professional related factors are weighing of patient risks and personal litigation risk in case of a wrong non-conveyance decision [87, 88], experience and intuition of the ambulance professional [89], and pragmatism as conveyance being an easy option compared to non-conveyance [89].

For patient related factors, firstly the health status of the patient influenced the non-conveyance decision of the professional [26, 49, 65, 74, 78, 83, 85, 88]. Only three studies specified these physical conditions: the sufficiency of on-scene treatment [26], if problems/injuries have resolved pre-arrival or were only minor [26, 85], patient physiology [74], the absence of new pain or injury [74], and possible changes in usual level of functioning [74]. A second patient related factor is refusal. Refusal might be related to relatives thinking conveyance is not necessary [65], but also by patients concerns about costs of conveyance or ED care [65, 78], or the refusal reasons were not further specified [26, 85]. Thirdly, patient wishes and the patients’ best interest are factors that influence a conveyance decision [86].

Influencing factors related to the healthcare system are access/referral to GP or alternative healthcare facility in case of non-conveyance [26, 87]. To make appropriate conveyance or referral decisions, access to patient information is essential. One study [80] showed that 90.7% of the ambulance professionals felt that a lack of patient information leads to less appropriate care being selected. To make appropriate decisions, ambulance professionals gave high priority to previous medical history, patient’s usual vital signs and resuscitation status as patient information.

Finally, three studies showed that implementing online medical control as supportive tool, where a physician can be contacted by the pre-hospital professional, solely or in combination with a high risk card, increased conveyance rates for patients with high risk criteria or patients who refused conveyance [29, 51, 57].

Discussion

This systematic review includes 67 articles that describe non-conveyance in ambulance care from patient safety and ambulance professional perspectives. Our results show that non-conveyance occurs in all types of EMS systems across the world, and that there is a wide variation in non-conveyance rates for general and specific patient populations. These variations might be caused by differences in patient populations (medical acuity and medical necessity to convey), and differences between EMS-systems in terms of triage systems, types of services, educational levels of ambulance professionals, and type of vehicles (conveying and non-conveying) [9193]. Although non-conveyance in itself is a valid outcome of ambulance care [17], our results do not distinct between justified or unjustified non-conveyance. This can be a focus of future research.

Our review provides a first insight in characteristics of non-conveyed patients. Our results show that patients of all ages and both men and women are represented in the non-conveyance population. Non-conveyed patients most often had a neurological or trauma related complaint or condition. Vulnerable patients as children and elderly, and specific patient groups of people who had fallen or people with hypoglycaemia are relatively high represented in the non-conveyance population. Another subpopulation is patients who refuse care and/or conveyance. From our results it remains unknown what kinds of complaints or conditions these patients have from ICD-10 perspective, and what consequences their refusal has from patient-safety perspective.

Although the assessment of vital signs is an important aspect of the primary survey in ambulance care to make appropriate treatment and triage decisions [94], we found only three studies describing vital signs of non-conveyed patients. These studies show that roughly 15% of the non-conveyed patients have vital signs that deviate from limits. We do not know whether vital signs differ between conveyed and non-conveyed patients. Therefore future research should focus on a comparison of vital signs and follow-up outcomes between conveyed and non-conveyed patient groups. Furthermore, it remains unclear if abnormal vital signs were present in the medical history due to illness or medication use. Poor access to healthcare information systems by ambulance professionals is reported [80], this underlines the possible advantage of access to healthcare information systems in the chain of emergency care, and the accessibility of the general practitioner.

Results show that a significant amount of non-conveyed patient re-enters the (emergency) healthcare system. For instance, 6.1% of the patients re-enters the EMS-system <24 h after non-conveyance, and up to 19.0% of the patient visits an ED within 48 h after non-conveyance. From the patient-safety perspective it remains unclear whether these repeated EMS calls and ED visits are based on medical necessity, as it remained unclear in the data which complaints or conditions these patients had during this repeated access to emergency healthcare, and whether it was similar to the initial EMS contact. Furthermore, the studies did not describe whether the re-entry is based on professional referral or self-referral. Clinical practice could benefit from the development of valid quality indicators for patient safety in the chain of emergency care. These could measure systematically (un)justified re-entry of the emergency healthcare system and quality of care provided.

From the professional perspective, our results indicate that the non-conveyance decision-making process is multifactorial, with influences from the professional, the patient and his relatives, the healthcare system, and supportive tools. Our results do not give clear direction which additional competencies ambulance professionals need to make safe non-conveyance decisions, as only two studies describe positive effects of additional training. Studies not included in our review suggest that pre-hospital professionals with additional training on the conveyance decision, and on management of minor illness and injuries, are less likely to convey patients compared to regular ambulance staff [15, 95]. Initiatives to implement new competencies of pre-hospital professionals in EMS or possibly new professionals with additional competencies in clinical reasoning and conveyance decision-making should be explored and tested regarding patient safety.

As for supportive tools, our results show that there is a limited number of flowcharts, checklists or protocols available to guide non-conveyance decisions for general and specific patient populations. However, it remains unclear how these tools were developed and to what degree they are evidence-based. This urges the need to develop evidence-based supportive tools to guide non-conveyance decision-making for different patient groups. In order to do so, future research should be aimed at identifying factors to guide accurate non-conveyance decision making, to predict non-conveyance in the EMS dispatch phase through tailored triage criteria, or to predict follow-up outcomes such as mortality and re-enters in the emergency healthcare system. This with the aim to support professionals in their decision making and to enhance quality and safety in pre-hospital care.

Limitations of included studies

As described in the result section, the quality of included studies varied. For the quantitative studies (Additional file 4: Appendix 3, Additional file 5: Appendix 4, Additional file 6: Appendix 5), the quality assessment criteria objective/aim, design, methods of subject/group selection, appropriateness of sample size, description analytical methods, and detailed reporting of results scored good quality. The moderate assessment criteria were description of subject characteristics, outcome definition, and the relationship between results and conclusion. The reporting of estimate of variance was poor, and due to design most studies could not be controlled for confounding. Within the qualitative studies (Additional file 7: Appendix 6) the quality assessment criteria objective/aim, design, connection to theoretical framework, data-collection and data-analysis scored good quality. The moderate assessment criteria were description of context, sampling strategy, and conclusion supported by results. Use of verification procedures and reflexivity of account were the two poor assessment criteria. Another limitation concerned the studies describing initial complaints and conditions. These studies used different types of classification systems, or systems were lacking. Therefore, we recommend to use one classification system, such as the ICD-10, in future research to enhance generizability and comparability of results.

Study strengths and limitations

Despite the fact that this systematic review is the most complete and systematic analysis to date of non-conveyance in ambulance care, there are some limitations. A possible limitation is that our review did not cover the entire ambulance care process, as we focused on the phases after ambulance dispatch. Additional research should focus on the accuracy and predictive value of current EMS dispatch systems for non-conveyance decisions. Secondly, a meta-analyses was not feasible due to heterogeneity amongst studies. Another limitation concerns the quality assessment tools for quantitative and qualitative designs. A variety of these tools exist without a clear evidence-base. Strengths of our study concern the usage of Cochrane and PRISMA methods and tools to perform and report our research.

Conclusion

This systematic review shows that non-conveyance occurs in all types of EMS systems across the world, and that a wide variation in non-conveyance rates for general and specific patient populations exists. Patients in the non-conveyance population present themselves with a variety of initial complaints and conditions, although initial complaints or conditions related to trauma and neurology, and vulnerable patients groups such as children, elderly and patients with hypoglycaemia, are well represented. Nevertheless, further insight in characteristics of the non-conveyance population is needed. From patient safety perspective it turns out that a proportion of non-conveyed patients re-enters the emergency healthcare system within one or 2 days after non-conveyance. Why these patients re-enter the emergency healthcare system, and what outcomes these patients have remains unclear. For ambulance professionals the non-conveyance decision-making process is complex and multifactorial, with influences from the professional, the patient and his relatives, the healthcare system (referral or access to general practitioner) and supportive tools. Competencies needed to perform non-conveyance are marginally described, this should be priority in future research. Despite the fact that a limited amount of supportive tools is available for general and specific non-conveyance populations, there is a need to develop evidence-based guidelines and protocols to guide non-conveyance decision-making.

Declarations

Acknowledgements

Not applicable.

Funding

The study was funded by Dutch National Sector Organization for Ambulance Care, Zwolle, The Netherlands. The funding body had a role in determining the scope and key-questions for this review. There was no role during data collection, selection, analysis and interpretation.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Authors’ contributions

Study design (RE, SB, MH, TP, LV). Data collection, selection, extraction and analysis (RE, SB, RS, NT, JL, LV). Quality assessment (RE, SB, RS, NT, JL, LV). Manuscript preparation (RE, SB, RS, NT, JL, MH, TP, LV). All authors read and approved the final manuscript

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Research Department of Emergency and Critical Care, HAN University of Applied Sciences, Faculty of Health and Social Studies
(2)
Radboud University Medical Center, Radboud Institute for Health Sciences, IQ healthcare
(3)
Ambulance Service Gelderland-Zuid
(4)
Ambulance Service IJsselland
(5)
Ambulance Academy
(6)
Dutch National Sector Organisation for Ambulance Care
(7)
Radboud University Medical Center, Eastern Regional Emergency Healthcare Network

References

  1. Shah MN. The formation of the emergency medical services system. Am J Public Health. 2006;96:414–23.View ArticlePubMedPubMed CentralGoogle Scholar
  2. Jensen JL, Bigham BL, Blanchard IE, Dainty KN, Socha D, Carter A, Brown LH, Travers AH, Craig AM, Brown R, Morrison LJ. The Canadian National EMS Research Agenda: a mixed methods consensus study. CJEM. 2013;15:73–82.View ArticlePubMedGoogle Scholar
  3. Lowthian JA, Cameron PA, Stoelwinder JU, Curtis A, Currell A, Cooke MW, McNeil JJ. Increasing utilisation of emergency ambulances. Aust Health Rev. 2011;35:63–9.View ArticlePubMedGoogle Scholar
  4. Richardson LD, Asplin BR, Lowe RA. Emergency department crowding as a health policy issue: past development, future directions. Ann Emerg Med. 2002;40:388–93.View ArticlePubMedGoogle Scholar
  5. Snooks H, Wrigley H, George S, Thomas E, Smith H, Glasper A. Appropriateness of use of emergency ambulances. J Accid Emerg Med. 1998;15:212–5.View ArticlePubMedPubMed CentralGoogle Scholar
  6. Anonymous. London ambulance service. In: Managing the conveyance of patients policy and procedures; 2017. http://www.londonambulance.nhs.uk/talking_with_us/freedom_of_information/classes_of_information/our_policies_and_procedures.aspx.Google Scholar
  7. Ambulances-in-zicht 2015. Ambulances-in-zicht 2015. 2017: http://www.vrgz.nl/nieuws/ambulances-in-zicht-2015/
  8. Cone DC, Kim DT, Davidson SJ. Patient-initiated refusals of prehospital care: ambulance call report documentation, patient outcome, and on-line medical command. Prehosp Disaster Med. 1995;10:3–9.View ArticlePubMedGoogle Scholar
  9. Marks PJ, Daniel TD, Afolabi O, Spiers G, JS NVT. Emergency (999) calls to the ambulance service that do not result in the patient being transported to hospital: An epidemiological study. Emerg Med J. 2002;19:449–52.View ArticlePubMedPubMed CentralGoogle Scholar
  10. Snooks HA, Dale J, HartleySharpe C, Halter M. On-scene alternatives for emergency ambulance crews attending patients who do not need to travel to the accident and emergency department: A review of the literature. Emerg Med J. 2004;21:212–5.View ArticlePubMedPubMed CentralGoogle Scholar
  11. Gratton MC, Ellison SR, Hunt J, Ma OJ. Prospective determination of medical necessity for ambulance transport by paramedics. Prehosp Emerg Care. 2003;7:466–9.View ArticlePubMedGoogle Scholar
  12. Booker MJ, Simmonds RL, Purdy S. Patients who call emergency ambulances for primary care problems: a qualitative study of the decision-making process. Emerg Med J. 2014;31:448–52. 5pView ArticlePubMedGoogle Scholar
  13. Booker MJ, Shaw ARG, Purdy S. Why do patients with 'primary care sensitive' problems access ambulance services? A systematic mapping review of the literature. BMJ Open. 2015;5:e007726.View ArticlePubMedPubMed CentralGoogle Scholar
  14. Verhage V, Tuinstra J, Baller R. Ambulanceritten zonder vervoer van een patiënt. Een verkennende studie naar het ontstaan van eerste hulp geen vervoer ritten. Tijdschr Soc geneeskd. 2014;92:119–24.Google Scholar
  15. Tohira H, Williams TA, Jacobs I, Bremner A, Finn J. The impact of new prehospital practitioners on ambulance transportation to the emergency department: a systematic review and meta-analysis. Emerg Med J. 2014;31:e88–94.View ArticlePubMedGoogle Scholar
  16. van de Glind I, Berben S, Zeegers F, Poppen H, Hoogeveen M, Bolt I, van Grunsven P, Vloet L: A national research agenda for pre-hospital emergency medical services in the Netherlands: a Delphi-study. Scand J Trauma Resusc Emerg Med. 2016;24. doi:https://doi.org/10.1186/s13049-015-0195-y.
  17. Johnson M, O'Hara R, Hirst E, Weyman A, Turner J, Mason S, Quinn T, Shewan J, Siriwardena AN: Multiple triangulation and collaborative research using qualitative methods to explore decision making in pre-hospital emergency care. BMC Med Res Methodol. 2017;17. doi:https://doi.org/10.1186/s12874-017-0290-z.
  18. Leikkola P, Mikkola R, Salminen-Tuomaala M, Paavilainen E. Non-conveyance of patients: challenges to decision-making in emergency are. Clin Nurs Stud. 2016;4:4. https://doi.org/10.5430/cns.v4n4p31 Google Scholar
  19. Champion HR, Sacco WJ, Gainer PS, Patow SM. The effect of medical direction on trauma triage. JTrauma. 1988;28:235–9.Google Scholar
  20. Snooks H, Kearsley N, Dale J, Halter M. New models of care for 999 callers with conditions that are neither life threatening nor serious: results of a national survey. Prehospital Immediate Care. 2000;4:180–2. 3pGoogle Scholar
  21. Higgins JPT, Green S (editors). Cochrane Handbook for Systematic Reviews of Interventions Version 5.0.1 (updated September 2008). The Cochrane Collaboration, 2008. Available from http://training.cochrane.org/handbook
  22. Moher D, Liberati A, Tetzlaff J, Altman DG, PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Int J Surg. 2010;8:336–41.View ArticlePubMedGoogle Scholar
  23. Shea BJ, Grimshaw JM, Wells GA, Boers M, Andersson N, Hamel C, Porter AC, Tugwell P, Moher D, Bouter LM. Development of AMSTAR: a measurement tool to assess the methodological quality of systematic reviews. BMC Med Res Methodol. 2007;7:10.View ArticlePubMedPubMed CentralGoogle Scholar
  24. Kmet LM, Lee RC, Cook LS. Quality assessment criteria for evaluating primary research papers from a varierty of fields. 2004.Google Scholar
  25. World Health Organization. The ICD-10 classification of mental and behavioural disorders: clinical descriptions and diagnostic guidelines. World Healht Organization, Geneva.1992, 2017: Google Scholar
  26. Mikolaizak AS, Simpson PM, Tiedemann A, Lord SR, Close JC. Systematic review of non-transportation rates and outcomes for older people who have fallen after ambulance service call-out. Australas J Ageing. 2013;32:147–57.View ArticlePubMedGoogle Scholar
  27. Snooks HA, Carter B, Dale J, Foster T, Humphreys I, Logan PA, Lyons RA, Mason SM, Phillips CJ, Sanchez A, Wani M, Watkins A, Wells BE, Whitfield R, Russell IT. Support and assessment for fall emergency referrals (SAFER 1): Cluster randomised trial of computerised clinical decision support for paramedics. PLosOne. 2014;9(9): e106436. https://doi.org/10.1371/journal.pone.0106436.
  28. Snooks H, Kearsley N, Dale J, Halter M, Redhead J, Cheung WY. Towards primary care for non-serious 999 callers: Results of a controlled study of "Treat and Refer" for ambulance crews. Qual Saf Health Care. 2004;13:435–43.View ArticlePubMedPubMed CentralGoogle Scholar
  29. Alicandro J, Hollander JE, Henry MC, Sciammarella J, Stapleton E, Gentile D. Impact of interventions for patients refusing emergency medical services transport. Acad Emerg Med. 1995;2:480–5.View ArticlePubMedGoogle Scholar
  30. Key CB, Pepe PE, Persse DE, Calderon D. Can first responders be sent to selected 9-1-1 emergency medical services calls without an ambulance? Acad Emerg Med. 2003;10:339–46.View ArticlePubMedGoogle Scholar
  31. Alrazeeni DM, Sheikh SA, Mobrad A, Al GM, Abdulqader N, Al GM, Al QM, Al Khaldi B. Epidemiology of non-transported emergency medical services calls in Saudi Arabia. Saudi Med J. 2016;37:575–8.View ArticlePubMedPubMed CentralGoogle Scholar
  32. Anderson S, Hogskilde PD, Wetterslev J, Bredgaard M, Sorensen MJT, Dahl JB, Hogskilde S. Appropriateness of leaving emergency medical service treated hypoglycemic patients at home: A retrospective study. Acta Anaesthesiol Scand. 2002;46:464–8.View ArticlePubMedGoogle Scholar
  33. Goldstein J, Jensen JL, Carter AJE, Travers AH, Rockwood K. The epidemiology of prehospital emergency responses for older adults in a provincial EMS system. Can J Emerg Med. 2015;17:491–6.Google Scholar
  34. Højfeldt SG, Sørensen LP, Mikkelsen S. Emergency patients receiving anaesthesiologist-based pre-hospital treatment and subsequently released at the scene. Acta Anaesthesiol Scand. 2014;58:1025–31. 7pView ArticlePubMedGoogle Scholar
  35. Kamper M, Mahoney BD, Nelson S, Peterson J. Feasibility of paramedic treatment and referral of minor illnesses and injuries. Prehosp Emerg Care. 2001;5:371–8. 8pView ArticlePubMedGoogle Scholar
  36. Kannikeswaran N, Mahajan PV, Dunne RB, Compton S, Knazik SR. Epidemiology of pediatric transports and non-transports in an urban emergency medical services system. Prehosp Emerg Care. 2007;11:403–7.View ArticlePubMedGoogle Scholar
  37. Knight S, Olson LM, Cook LJ, Mann NC, Corneli HM, Dean JM. Against all advice: an analysis of out-of-hospital refusals of care. Ann Emerg Med. 2003;42:689–96.View ArticlePubMedGoogle Scholar
  38. Magnusson C, Källenius C, Knutsson S, Herlitz J, Axelsson C. Pre-hospital assessment by a single responder: The Swedish ambulance nurse in a new role: A pilot study. Int Emerg Nurs. 2016;26:32.View ArticlePubMedGoogle Scholar
  39. Minhas R, Vogelaar G, Wang D, Almansoori W, Lang E, Blanchard IE, Lazarenko G, McRae A. A prehospital treat-and-release protocol for supraventricular tachycardia. Can J Emerg Med. 2015;17:395–402.Google Scholar
  40. Moss ST, Chan TC, Buchanan J, Dunford JV, Vilke GM. Outcome study of prehospital patients signed out against medical advice by field paramedics. Ann Emerg Med. 1998;31:247–50.View ArticlePubMedGoogle Scholar
  41. Peyravi M, Ortenwal P, Djalali A, KhorramManesh A. An overview of Shiraz emergency medical services, dispatch to treatment. Iran Red Crescent Med J. 2013;15:823–8.View ArticlePubMedPubMed CentralGoogle Scholar
  42. Peyravi M, Örtenwall P, Khorram-Manesh A: Can Medical Decision-making at the Scene by EMS Staff Reduce the Number of Unnecessary Ambulance Transportations, but Still Be Safe?. PLOS Currents Disasters. 2015 Jun 30 . Edition 1. doi:https://doi.org/10.1371/currents.dis.f426e7108516af698c8debf18810aa0a.
  43. Pringle RP Jr, Carden DL, Xiao F, Graham DD Jr. Outcomes of patients not transported after calling 911. J Emerg Med. 2005;28:449–54.View ArticlePubMedGoogle Scholar
  44. Rudolph SS, Jehu G, Nielsen SL, Nielsen K, Siersma V, Rasmussen LS. Prehospital treatment of opioid overdose in Copenhagen-Is it safe to discharge on-scene? Resuscitation. 2011;82:1414–8.View ArticlePubMedGoogle Scholar
  45. Schmidt M, Handel D, Lindsell C, Collett L, Gallo P, Locasto D. Evaluating an emergency medical services - Initiated nontransport system. Prehosp Emerg Care. 2006;10:390–3.View ArticlePubMedGoogle Scholar
  46. Selden BS, Schnitzer PG, Nolan FX. Medicolegal documentation of prehospital triage. Ann Emerg Med. 1990;19:547–51.View ArticlePubMedGoogle Scholar
  47. Seltzer AG, Vilke GM, Chan TC, Fisher R, Dunford JV. Outcome study of minors after parental refusal of paramedic transport. Prehosp Emerg Care. 2001;5:278–83.View ArticlePubMedGoogle Scholar
  48. Socransky SJ, Pirrallo RG, Rubin JM. Out-of-hospital treatment of hypoglycemia: refusal of transport and patient outcome. Acad Emerg Med. 1998;5:1080–5.View ArticlePubMedGoogle Scholar
  49. Stark G, Hedges JR, Neely K, Norton R. Patients who initially refuse prehospital evaluation and/or therapy. Am J Emerg Med. 1990;8:509–11.View ArticlePubMedGoogle Scholar
  50. Staudenmayer K, Hsia R, Wang E, Sporer K, Ghilarducci D, Spain D, MacKersie R, Sherck J, Kline R, Newgard C. The forgotten trauma patient: Outcomes for injured patients evaluated by emergency medical services but not transported to the hospital. J Trauma Acute Care Surg. 2012;72:594–600.View ArticlePubMedPubMed CentralGoogle Scholar
  51. Stuhlmiller DFE, Cudnik MT, Sundheim SM, Threlkeld MS Jr. CT: Adequacy of online medical command communication and emergency medical services documentation of informed refusals. Acad Emerg Med. 2005;12:970–7. 8pView ArticlePubMedGoogle Scholar
  52. Tohira H, Fatovich D, Williams TA, Bremner AP, Arendts G, Rogers IR, Celenza A, Mountain D, Cameron P, Sprivulis P, Ahern T, Finn J. Is it Appropriate for Patients to be Discharged at the Scene by Paramedics? Prehosp Emerg Care. 2016:1–11.Google Scholar
  53. Tohira H, Fatovich D, Williams TA, Bremner A, Arendts G, Rogers IR, Celenza A, Mountain D, Cameron P, Sprivulis P, Ahern T, Finn J. Paramedic Checklists do not Accurately Identify Post-ictal or Hypoglycaemic Patients Suitable for Discharge at the Scene. Prehosp Disaster Med. 2016;31:282–93.View ArticlePubMedGoogle Scholar
  54. Vilke GM, Buchanan J, Dunford JV, Chan TC. Are heroin overdose deaths related to patient release after prehospital treatment with naloxone? Prehosp Emerg Care. 1999;3:183–6. 4pView ArticlePubMedGoogle Scholar
  55. Zachariah BS, Bryan D, Pepe PE, Griffin M. Follow-up and outcome of patients who decline or are denied transport by EMS... including commentary by McSwain NE Jr. Prehosp Disaster Med. 1992;7:359–63. 5pView ArticleGoogle Scholar
  56. Burstein JL, Henry MC, Alicandro J, Gentile D, Thode HC Jr, Hollander JE. Outcome of patients who refused out-of-hospital medical assistance. Am J Emerg Med. 1996;14:23–6.View ArticlePubMedGoogle Scholar
  57. Burstein JL, Hollander JE, Delagi R, Gold M, Henry MC, Alicandro JM. Refusal of out-of-hospital medical care: Effect of medical-control physician assertiveness on transport rate. Acad Emerg Med. 1998;5:4–8.View ArticlePubMedGoogle Scholar
  58. Cain E, AckroydStolarz S, Alexiadis P, Murray D. Prehospital hypoglycemia: The safety of not transporting treated patients. Prehosp Emerg Care. 2003;7:458–65.View ArticlePubMedGoogle Scholar
  59. Carter AJ, Keane PS, Dreyer JF. Transport refusal by hypoglycemic patients after on-scene intravenous dextrose. Acad Emerg Med. 2002;9:855–7.View ArticlePubMedGoogle Scholar
  60. Chen JC, Bullard MJ, Liaw SJ. Ambulance use, misuse, and unmet needs in a developing emergency medical services system. Eur J Emerg Med. 1996;3:73–8.View ArticlePubMedGoogle Scholar
  61. Deasy C, Ryan D, O'Donnell C, Cusack S. The impact of a pre-hospital medical response unit on patient care and Emergency Department attendances. Ir Med J. 2008;101:44-6.Google Scholar
  62. Haines CJ, Lutes RE, Blaser M, Christopher NC. Paramedic initiated non-transport of pediatric patients. Prehosp Emerg Care. 2006;10:213–9.View ArticlePubMedGoogle Scholar
  63. Hipskind JE, Gren JM, Barr DJ. Patients who refuse transportation by ambulance: a case series. Prehosp disaster Med. 1997;12:278–83.View ArticlePubMedGoogle Scholar
  64. Jensen JL, Travers AH, Bardua DJ, Dobson T, Cox B, McVey J, Cain E, Merchant R, Carter AJE. Transport outcomes and dispatch determinants in a paramedic long-term care program: a pilot study. CAN J EMERG MED. 2013;15:206–13. 8pGoogle Scholar
  65. Kahale J, Osmond MH, Nesbitt L, Stiell IG. What are the characteristics and outcomes of nontransported pediatric patients? Prehosp Emerg Care. 2006;10:28–34.View ArticlePubMedGoogle Scholar
  66. Lerner EB, Billittier AJ 4th, Lance DR, Janicke DM, Teuscher JA. Can paramedics safely treat and discharge hypoglycemic patients in the field? Am J Emerg Med. 2003;21:115–20.View ArticlePubMedGoogle Scholar
  67. Mechem CC, Kreshak AA, Barger J, Shofer FS. The short-term outcome of hypoglycemic diabetic patients who refuse ambulance transport after out-of-hospital therapy. Acad Emerg Med. 1998;5:768.View ArticlePubMedGoogle Scholar
  68. Newton PR, Naidoo R, Brysiewicz P. The appropriateness of emergency medical service responses in the eThekwini district of KwaZulu-Natal, South Africa. S Afr Med J. 2015;105:844.View ArticlePubMedGoogle Scholar
  69. Persse DE, Key CB, Baldwin JB. The effect of a quality improvement feedback loop on paramedic-initiated nontransport of elderly patients. Prehosp Emerg Care. 2002;6:31–5.View ArticlePubMedGoogle Scholar
  70. Schmidt TA, Atcheson R, Federiuk C, Mann NC, Pinney T, Fuller D, Colbry K. Hospital follow-up of patients categorized as not needing an ambulance using a set of emergency medical technician protocols. Prehosp Emerg Care. 2001;5:366–70.View ArticlePubMedGoogle Scholar
  71. Schmidt TA, Mann NC, Federiuk CS, Atcheson RR, Fuller D, Christie MJ. Do patients refusing transport remember descriptions of risks after initial advanced life support assessment? Acad Emerg Med. 1998;5:796–801.View ArticlePubMedGoogle Scholar
  72. Schmidt T, Atcheson R, Federiuk C, Mann NC, Pinney T, Fuller D, Colbry K. Evaluation of protocols allowing emergency medical technicians to determine need for treatment and transport. Acad Emerg Med. 2000;7:663–9.View ArticlePubMedGoogle Scholar
  73. Simpson PM, Bendall JC, Tiedemann A, Lord SR, Close JC. Epidemiology of emergency medical service responses to older people who have fallen: a prospective cohort study. Prehosp Emerg Care. 2014;18:185–94.View ArticlePubMedGoogle Scholar
  74. Simpson PM, Bendall JC, Toson B, Tiedemann A, Lord SR, Close JC. Predictors of nontransport of older people who have fallen who receive ambulance care. Prehosp Emerg Care. 2014;18:342–9.View ArticlePubMedGoogle Scholar
  75. Strote J, Simons R, Eisenberg M. Emergency medical technician treatment of hypoglycemia without transport. Am J Emerg Med. 2008;26:291–5.View ArticlePubMedGoogle Scholar
  76. Tiedemann A, Mikolaizak AS, Sherrington C, Segin K, Lord SR, Close JC. Older people who have fallen attended to by an ambulance but not transported to hospital: a vulnerable population at high risk of future falls. Aust N Z J Public Health. 2013;37:179–85.View ArticlePubMedGoogle Scholar
  77. Van Der Pols H, Mencl F, De Vos R. The impact of an emergency motorcycle response vehicle on prehospital care in an urban area. Eur J Emerg Med. 2011;18:328–33.View ArticlePubMedGoogle Scholar
  78. Vilke GM, Sardar W, Fisher R, Dunford JD, Chan TC. Follow-up of elderly patients who refuse transport after accessing 9-1-1. PrehospEmergCare. 2002;6:391–5.Google Scholar
  79. Gerlacher GR, Sirbaugh PE. Macias CG: Prehospital evaluation of non-transported pediatric patients by a large emergency medical services system. Pediatr Emerg Care. 2001;17:421–4.View ArticlePubMedGoogle Scholar
  80. Zorab O, Robinson M, Endacott R. Are prehospital treatment or conveyance decisions affected by an ambulance crew's ability to access a patient's health information? BMC Emerg Med. 2015;15:1–7. 7pView ArticleGoogle Scholar
  81. Shaw D, Dyas JV, Middlemass J, Spaight A, Briggs M, Christopher S, Siriwardena AN. Are they really refusing to travel? A qualitative study of prehospital records. BMC Emergency Med. 2006;6. doi:https://doi.org/10.1186/1471-227X-6-8.
  82. Burrell L, Noble A, Ridsdale L. Decision-making by ambulance clinicians in London when managing patients with epilepsy: a qualitative study. Emerg Med J. 2013;30:236–40. 5pView ArticlePubMedGoogle Scholar
  83. Ebrahimian A, Seyedin H, JamshidiOrak R, Masoumi G. Exploring factors affecting emergency medical services staffs' decision about transporting medical patients to medical facilities. Emerg Med Int. 2014. doi:https://doi.org/10.1155/2014/215329.
  84. Halter M, Vernon S, Snooks H, Porter A, Close J, Moore F, Porsz S. Complexity of the decision-making process of ambulance staff for assessment and referral of older people who have fallen: a qualitative study. Emerg Med J. 2011;28:44–50. 7pView ArticlePubMedGoogle Scholar
  85. Keene T, Davis M, Brook C. Characteristics and outcomes of patients assessed by paramedics and not transported to hospital: A pilot study. Australas J Paramedicine. 2015;12:1-7.Google Scholar
  86. Murphy-Jones G, Timmons S. Paramedics' experiences of end-of-life care decision making with regard to nursing home residents: an exploration of influential issues and factors. Emerg Med J: EMJ. 2016;0:1-5. doi:https://doi.org/10.1136/emermed-2015-205405.
  87. O'Hara R, Johnson M, Siriwardena AN, Weyman A, Turner J, Shaw D, Mortimer P, Newman C, Hirst E, Storey M, Mason S, Quinn T, Shewan J. A qualitative study of systemic influences on paramedic decision making: care transitions and patient safety. J Health Serv Res Policy. 2015;20:45–53.View ArticlePubMedGoogle Scholar
  88. Porter A, Snooks H, Youren A, Gaze S, Whitfield R, Rapport F, Woollard M. 'Should I stay or should I go?' Deciding whether to go to hospital after a 999 call. J Health Serv Res Policy. 2007;12:S1:32–8.View ArticleGoogle Scholar
  89. Snooks HA, Kearsley N, Dale J, Halter M, Redhead J, Foster J. Gaps between policy, protocols and practice: A qualitative study of the views and practice of emergency ambulance staff concerning the care of patients with non-urgent needs. Qual Saf Health Care. 2005;14:251–7.View ArticlePubMedPubMed CentralGoogle Scholar
  90. Hjälte L, Suserud B, Herlitz J, Karlberg I. Why are people without medical needs transported by ambulance? A study of indications for pre-hospital care. Eur J Emerg Med. 2007;14:151.View ArticlePubMedGoogle Scholar
  91. Billittier AJ, Lerner EB, Moscati RM, Young G. Triage, transportation, and destination decisions by out-of-hospital emergency care providers. Prehosp Disaster Med. 1998;13:22–7.View ArticlePubMedGoogle Scholar
  92. Eric Carlström, Lars Fredén, The first single responders in Sweden – Evaluation of a pre-hospital single staffed unit. Int Emerg Nurs, Volume 32, May 2017, Pages 15-19, ISSN 1755-599X, https://doi.org/10.1016/j.ienj.2016.05.003. http://www.sciencedirect.com/science/article/pii/S1755599X16300490).
  93. Hoyle S, Swain AH, Fake P, Larsen PD. Introduction of an extended care paramedic model in New Zealand. Emerg Med Australas. 2012;24:652–6.View ArticlePubMedGoogle Scholar
  94. Coats TJ, Wilson AW, Cross FW. On-scene medical decision making and overtriage. Br J Surg. 1993;80:1291.View ArticlePubMedGoogle Scholar
  95. Bloemhoff A, Schoonhoven L, de Kreek AJ, van Grunsven PM, Laurant MG, Berben SA. Solo emergency care by a physician assistant versus an ambulance nurse: a cross-sectional document study. Scand J Trauma Resusc Emerg Med. 2016;24. doi:https://doi.org/10.1186/s13049-016-0279-3.

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