Table 2 Overview of included papers and quality appraisal
From: Driving the ambulance: an essential component of emergency medical services: an integrative review
Author/s | Year | Study focus | Country | Study design and method | Study population | Quality appraisal* |
|---|---|---|---|---|---|---|
Beom et al | 2018 | Driving patterns and possibilities to conduct CPR during transport | Korea | Quantitative, analytic statistical analysis | Ambulance personnel (n = 48) and simulated driving patterns (n = 10) | High |
Bui et al | 2018 | Driving pattern and behavior among ambulance drivers and impact on safety | USA | Quantitative, analytic statistical analysis | Driving data from 1.1 million km and ambulance crashes (n = 44) | High |
Péculo-Carrasco et al | 2020 | Feelings of safety within the EMS | Spain | Qualitative, content analysis | Patients and ambulance personnel (n = 65) | Acceptable |
Fleischmann | 2013 | Transportation time and the effects of navigation system support | USA | Quantitative analysis statistical analyses | Retrospective analysis of ambulance transports (n = 48,248) | High |
Hoedemaker et al | 2020 | Timely transportation of percutaneous coronary intervention patients | The Nether- lands | Quantitative, analytic statistical analysis | Calculation of driving routes based on EMS records and postal codes | Acceptable |
Jansson et al. | 2020 | Comparing transport time when using lights and sirens and no lights and sirens during interhospital transports | USA | Quantitative, analytic statistical analysis | Interhospital transports of critical patients (n = 5863) | High |
Koski et al | 2019 | Safety risks and factors when caring within the EMS | Finland | Qualitative, inductive content analysis | Written statements of ambulance drivers (n = 44) | Acceptable |
McDonald et al | 2019 | The impact of using lights and sirens during non-critical EMS transports | USA | Quantitative, analytic statistical analysis | Ambulance drivers (n = 80) | Acceptable |
Missikpode et al | 2018 | Safety risks when driving with lights and siren | USA | Quantitative, quasi-induced exposure method | Emergency vehicle crashes (n = 2903) | High |
Partridge et al | 2020 | Ambulance transport of infants with regards to the best way of driving to minimize the medical condition | UK | Quantitative, analytical statistical analysis | Mobile phone registration of EMS transports (n = 1700) | Acceptable |
Petzäll et al | 2011 | Driving speed and pattern in relation to distances, the patient’s condition, and time saved | Sweden | Quantitative, analytic statistical analysis | Emergency high speed ambulance transportation in urban and rural areas (n = 30) | Acceptable |
Suserud et al | 2013 | Caring for patients within the EMS during high speed transports | Sweden | Qualitative, content analysis | Individual interviews with ambulance personnel (n = 33) | Acceptable |
Thézard et al | 2019 | Head and neck motion when transported in ambulances | Canada | Quantitative, analytic statistical analysis | Study persons (n = 18) and ambulance drivers (n = 12) | Acceptable |
Tremblay et al | 2020 | Stress management in ambulance driving | Canada | Quantitative, analytic statistical analysis | Ambulance drivers (n = 17) | High |
Venesoja et al | 2020 | Patients’ experiences of EMS safety | Finland | Qualitative, content analysis | Individual interviews with EMS patients (n = 21) | Acceptable |
Watanabe et al | 2019 | Ambulance use of lights and sirens | USA | Quantitative, analytic statistical analysis | Emergency responses (n = 19 million) | High |
Westerlund et al | 2016 | Driving pattern and occurrence of patients’ nausea | Sweden | Qualitative, content analysis | Individual interviews with ambulance nurses (n = 16) | Acceptable |