Abstract
Objective
We aimed to determine the feasibility of quality indicators (QIs) for prehospital advanced airway management (PAAM) from a provider point of view.
Design
The study is a survey based feasibility assessment following field testing of QIs for PAAM.
Setting
The study was performed in two physician staffed emergency medical services in Switzerland.
Participants
42 of the 44 emergency physicians who completed at least one case report form (CRF) dedicated to the collection of the QIs on PAAM between 1 January 2019 and 31 December 2021 participated in the study.
Intervention
The data required to calculate the 17 QIs was systematically collected through a dedicated electronic CRF.
Primary and secondary outcome measures
Primary outcomes were provider-related feasibility criteria: relevance and acceptance of the QIs, as well as reliability of the data collection. Secondary outcomes were effort to collect specific data and to complete the CRF.
Results
Over the study period, 470 CRFs were completed, with a median of 11 per physician (IQR 4–17; range 1–48). The median time to complete the CRF was 7 min (IQR 3–16) and was considered reasonable by 95% of the physicians. Overall, 75% of the physicians assessed the set of QIs to be relevant, and 74% accepted that the set of QIs assessed the quality of PAAM. The reliability of data collection was rated as good or excellent for each of the 17 QIs, with the lowest rated for the following 3 QIs: duration of preoxygenation, duration of laryngoscopy and occurrence of desaturation during laryngoscopy.
Conclusions
Collection of QIs on PAAM appears feasible. Electronic medical records and technological solutions facilitating automatic collection of vital parameters and timing during the procedure could improve the reliability of data collection for some QIs. Studies in other services are needed to determine the external validity of our results.
Keywords: Quality in health care, ACCIDENT & EMERGENCY MEDICINE, Adult intensive & critical care
STRENGTHS AND LIMITATIONS OF THIS STUDY.
The heterogeneity of the characteristics of the physicians who participated to the study is representative of the prehospital emergency physician population practising in Switzerland.
The process of monitoring prehospital advanced airway management and its documentation in the case report forms (CRFs) on a daily basis allowed to optimise a high completeness of the data.
A small part of the physicians answered the questionnaire of the survey up to 2 years after completing their last CRF as some of them just complete a 6-month fellowship in the service.
Despite using questions used in previous feasibility studies, proposing the questionnaire in two languages and data retrieval and software having been the same for all the physicians, there was a high range in certain answers.
The study was conducted in two physician-staffed emergency medical services and external validity can be seen as limited.
Introduction
Prehospital advanced airway management (PAAM) is a critical care intervention consisting of successive complex tasks that can be delivered to a high standard in the prehospital setting.1 2 However, despite a straightforward rationale for carrying out PAAM, its benefit in improving outcomes remains disputed.3 Studies that use standard research methods have struggled to reliably evaluate this complex intervention, mainly because of not sufficiently taking into account the considerable heterogeneity in patients and clinical scenarios, as well as the diversity of providers and techniques, all of which may influence outcomes.4–6 Complex interventions like PAAM might be better evaluated by using specific quality improvement methodology that measures dedicated, well-defined indicators.6 7 The collection and monitoring of quality indicators (QIs) in prehospital critical care is rare and has not yet been described for a specific topic such as advanced airway management.8
To contribute to progress on this issue, an international group of experts in 2018 developed a set of 17 QIs divided into the 3 categories described by Donabedian (structure, process, outcome) and covering all steps of PAAM (figure 1).9 In 2019, we introduced the collection of data required to calculate these QIs in two physician-staffed emergency medical services (PEMS) based in Lausanne, Switzerland. In this study, we aimed to assess the feasibility of the 17 QIs for PAAM from a provider point of view by using a survey among the prehospital emergency physicians of these two services.
Figure 1.
Quality indicators for prehospital advanced airway management.9†Intubation attempt: an attempt is each time the laryngoscope blade passed the front teeth. Correction of the tube’s depth is not defined as a new attempt.‡Laryngoscopy duration: defined as the time between the moment the preoxygenation mask is removed from the face of the patient and the moment the tube position is confirmed in the trachea (preferably with capnography). §Intubation success: a success is defined by a tube confirmed in the trachea (preferably by at least two different techniques, one of them ideally being quantitative EtCO2 measure immediately after insertion).¶Services with blood gas analysis possibility should use PaCO2. ¥Complications contain the items of the updated Utstein-style airway template.29 Immediately recognised/corrected oesophageal intubation; not immediately recognised/corrected oesophageal intubation; endotracheal tube misplaced in left or right main stem bronchus; incorrect positioning or difficult ventilation with supraglottic airway device; dental trauma; aspiration or vomiting during airway management (and not present before); cardiac arrest during airway management; complications during surgical or percutaneous airway management (eg, bleeding or pneumothorax); new hypoxia during airway management; new bradycardia during airway management; new hypotension during airway management. The three latter ones are defined as follows: hypoxia: adults and children: SpO2 < 90%. Hypotension: infants <1 year: systolic blood pressure (SBP) <70 mm Hg (systolic, children 1–10 years: SBP <70 + (2 × age), children >10 years: SBP <90 mm Hg, adults: SBP <90 mm Hg or decrease >10% from baseline value. Bradycardia: newborn to 3 years: <100 beats per minute, 3–9 years: <80 beats per minute, 10–16 years: <60 beats per minute, adults: <50 beats per minute.29
Method
Study setting
Physicians of the prehospital sector of the Emergency Department of Lausanne University Hospital are staffing two PEMS units: the Lausanne Ground Emergency Medical Service (GEMS) and the local helicopter of the Helicopter Emergency Medical Service (HEMS) Rega-Swiss Air Ambulance. Both PEMS units are systematically staffed with a physician and a paramedic. They are available 24/7 and respond annually to about 1500 and 900 missions, respectively.10 Whereas the GEMS mainly responds to primary missions (on scene; >95%), the HEMS also performs a significant share of secondary missions (interhospital; ca. 50%).11
The level of airway management training and clinical experience of the physicians ranges from emergency medicine residents to senior attending specialists in emergency medicine and/or anaesthesiology with several years of experience. Physicians working on the HEMS have at least 1 year of clinical experience in anaesthesiology, as well as 6 months in intensive care medicine.
In both services, PAAM is performed exclusively by the physicians. Of about 150 intubations performed during primary missions annually, one-third are related to the HEMS and two-thirds to the GEMS. Standard PAAM includes rapid sequence intubation for patients with vital signs, systematic use of a C-MAC PM (KARL STORZ SE & Co. KG, Tuttlingen, Germany) videolaryngoscope for intubation and mandatory use of continuous waveform capnography after intubation. All videolaryngoscopies are recorded, stored and reviewed by a senior consultant of the ED.
Since 1 January 2019, the two PEMS have collected the data required to calculate the 17 QIs for PAAM through a dedicated case report form (CRF) by using Research Electronic Data Capture tools (REDCap Consortium, Vanderbilt University, Nashville, Tennessee, USA).12 The CRF was completed by the physician immediately after every mission in which PAAM had been attempted.
Outcomes
The main goal of the study was to assess the feasibility of each of the 17 QIs for PAAM from the provider’s point of view. Feasibility was assessed by the provider through evaluation of each of the following criteria, which represent the primary outcomes: relevance, acceptance and reliability of data collection. The definitions of the criteria and the questions used for their assessment are presented in the questionnaire in table 1. Relevance and acceptance were assessed with a ‘yes or no’ approach and the correlation between them was evaluated.13 Reliability of data collection was assessed by using a five-point Likert scale, corresponding to positive (excellent and good), fair and negative (poor and very poor) ratings. Further, participants could report promoting and hindering factors for retrieving data for each QI.14
Table 1.
Questionnaire for the assessment of the feasibility of QIs for PAAM from a provider point of view
| For each QI | |
| Relevance | |
| Do you consider this QI suitable to meaningfully describe/measure the quality of care in this specific aspect of prehospital advanced airway management? | Yes/no/I don’t know |
| Acceptance | |
| Would you accept that an aspect of the quality of prehospital advanced airway management would be measured and rated using this indicator? | Yes/no/I don’t know |
| Reliability of data collection | |
| How do you estimate the reliability of data collection for this QI? | Excellent/good/fair/poor/very poor |
| Promoting and hindering factors | |
| Are there additional promoting factors for retrieving data required for this QI? And if so, what promoting factors? | Free text |
| Are there additional hindering factors for retrieving data required for this QI? And if so, what hindering factors? | Free text |
| Only for QI 1, 2, 3, 15, 17 | |
| Effort | |
| How much time would you approximately need to obtain the required data to calculate this QI? | Time (minutes) |
| Under your given day-to-day practice routine, is this effort reasonable to you? | Yes/no/I don’t know |
| General questions about the REDCap CRF | |
| Effort | |
| How much time would you approximately need to complete a REDCap CRF airway management for a simple procedure (success at first attempt) | Time (minutes) |
| Under your given day-to-day practice routine, is this effort reasonable to you? | Yes/no/I don’t know |
CRF, case report form; PAAM, prehospital advanced airway management; QI, quality indicator.
Secondary outcomes were assessment of the effort required to collect specific data needed to calculate five QIs (QI 1, 2, 3, 15 and 17) not included in the CRF, as well as of the completion of the dedicated CRF on REDCap. To assess the effort, we asked participants to estimate the time needed to complete the task and to judge whether this time was reasonable or not.
Cross-sectional survey
A questionnaire was developed with the LimeSurvey online survey tool (LimeSurvey GmbH, Hamburg, Germany). We tested and adapted it from the feedback of three emergency physicians who did not participate in the survey later on. For better understanding, we made the questionnaire available to the participants in both French and English. The translation was validated by an English native speaker who was independent of the study group.
All physicians who worked for the two PEMS and who had completed at least one REDCap CRF between 1 January 2019 and 31 December 2021 were informed of the upcoming survey and their email addresses were checked.12 They were invited to participate in the survey by sending them a personal link. Participation was voluntary. The survey started on 11 April 2022. A weekly reminder was emailed until the survey was closed after 30 days.
Statistical analysis
Categorical variables were described as frequency and relative percentages. Continuous variables were described as mean and SD if normally distributed and as median and IQR if not normally distributed. The statistical correlation between two continuous variables was measured by Pearson’s correlation coefficient.
The statistical analyses were performed by using STATA statistics software V.14.2 (StataCorp LLC).
Results
Study sample
Forty-two (95%) of the 44 physicians who worked in the PEMS during the study period completed the questionnaire. Fifty-nine per cent (n=26) of the participants were male.
Over the study period, 470 CRFs were completed and the median number of completed CRFs per physician was 11 (IQR 4–17; range 1–48). The median time to complete the CRF was 7 min (IQR 3–16; range 1–25) and this was deemed reasonable by 95% (n=40) of the participants.
Assessment of the QIs
The relevance, acceptance and reliability of data collection of each of the 17 QIs are presented in figure 2. On average, 75% of the physicians assessed the set of QIs to be relevant and thus meaningful in describing or measuring the quality of PAAM, and 74% accepted that the set of QIs assessed the quality of PAAM. A positive correlation was found between relevance and acceptance (Pearson’s r=0.87).
Figure 2.
Provider-related feasibility criteria.
Sixty-five per cent of the physicians estimated the collection of the data required for the set of QIs to be reliable. Free-text comments on promoting and hindering factors for retrieving the data required to calculate the different QIs are summarised in online supplemental file 1.
bmjopen-2023-081951supp001.pdf (89.6KB, pdf)
The time required to collect QI 1, 2, 3, 15 and 17 is presented in table 2. Overall, the time required to collect these QIs was assessed as reasonable given the day-to-day practice routine and constraints.
Table 2.
Estimation of the time and reasonability of the effort to retrieve the data to calculate QI 1, 2, 3, 15 and 17 by the physicians (n=42) of the two PEMS
| QI no. | Estimated time to retrieve the data required to calculate each QI* | Reasonability of the effort to retrieve the data required to calculate each QI | ||||
| ≤60 min n (%) median (IQR) |
>60 min n (%) |
I don’t know n (%) |
Reasonable n (%) |
Not reasonable n (%) |
I don’t know n (%) |
|
| QI 1 | 20 (47) 10 (3–45) |
13 (31) | 9 (21) | 25 (60) | 11 (26) | 6 (14) |
| QI 2 | 28 (67) 12.5 (3–30) |
6 (14) | 8 (19) | 33 (79) | 4 (10) | 5 (12) |
| QI 3 | 23 (55) 15 (5–60) |
11 (26) | 8 (19) | 23 (55) | 11 (26) | 8 (19) |
| QI 15 | 22 (52) 5 (2–15) |
6 (14) | 14 (33) | 22 (52) | 13 (31) | 7 (17) |
| QI 17 | 27 (64) 5 (2–60) |
5 (12) | 10 (24) | 22 (52) | 13 (31) | 7 (17) |
For times ≤60 min, physicians were invited to estimate the time with a precision of 1 min. If they estimated that the time was >60 min, no further precision was required.
PEMS, physician-staffed emergency medical services; QI, quality indicator.
Discussion
The results of this study suggest that the collection of QIs to measure the quality of PAAM is feasible in PEMS. The providers found the QIs to be relevant, acceptable and the collection of data required to calculate the QIs reliable. The completion of a dedicated CRF was deemed feasible and the effort to complete it was considered acceptable within the available resource and time constraints.
Feasibility criteria
Feasibility is key in continuous quality improvement to enhance acceptance of upcoming feedback based on the measurement of the QIs.15–18 Although the meaning of feasibility seems intuitive and many criteria have been described in the past, there is no internationally validated set of criteria.17 19 20 We based our study on the feasibility criteria previously published in two studies on the feasibility of QIs in an ambulatory setting, which has many similarities to prehospital critical care.14 17 We focused on three provider-related feasibility criteria: relevance, acceptance and reliability of data collection.14 We did not assess non-provider-related feasibility criteria such as applicability, availability of data and technical feasibility of data collection. Indeed, PAAM is an important procedure performed regularly by the physicians in both PEMS and data were collected directly in a REDCap CRF specifically developed for this purpose.
Relevance and acceptance
The average relevance and acceptance of the set of QIs (75% and 74%, respectively) are comparable to the highest values described by Ewald et al (76% and 73%, respectively) for a subgroup of QIs and are higher than the values described by de Cruppé et al (61% and 58%, respectively).14 17
A high relevance might be related to the scientific evidence and strength of an indicator and reflects the quality of the QI development process, especially if assessed by a different group than the one that developed the QI.15 16 On the other hand, acceptance might be influenced both by the reliability of data collection and by the overall acceptance of healthcare being assessed through indicators. Further, acceptance is not only influenced by relevance, but it also highly correlates with it, as described in the past.14
The two QI assessed as most relevant to describe the quality of PAAM were the duration of the laryngoscopy (QI 9, 92.9%) and the overall intubation clinical practice (QI 1, 85.7%). Both describe the pure technical skill of intubation and also figure among the top three of the most accepted QIs (88.1% and 83.3%, respectively), together with the number of intubation attempts (QI 4, 83.3%). These findings support the fact that technical skill seems to be key in determining the quality of PAAM.3 21
Monitoring capnometry during transport was the QI with the highest acceptance (QI 11, 90.8%). Normoventilation is aimed for in most ventilated patients and is associated with decreased mortality when applied in the early management of traumatic brain injury.22 23
Capnometry monitoring during transport enables targeted optimisation of ventilation en route the hospital.21 24
The intubation indication threshold (QI 10, 50%), automated ventilation during transport (QI 12, 54.8%) and preoxygenation duration (QI 7, 59.5%) obtained both lowest acceptance and relevance. Unlike the best-rated QI, they describe elements of PAAM that are not directly related to the technical act of intubation and their impact on outcome QIs might seem less intuitive.
Reliability of data collection
The average reliability of data collection required for the QIs (65%) is similar to the value described by de Cruppé et al (69%) and higher than the 50% described by Ewald et al.14 17 This can be explained by the high proportion of electronic medical records (EMR) in both de Cruppé’s study and our study.14
The lowest reliability of data collection was observed for the QI in which data had to be recorded by the physician himself and required his attention during PAAM (duration of preoxygenation: QI 7, duration of laryngoscopy: QI 9, desaturation during laryngoscopy: QI 15), and for those dependent on data collected by another service/organisation (overall intubation clinical practice: QI 1, periodic overall intubation exposure: QI 3). The latter two QIs were also those requiring the longest time to retrieve the data.
Reliability of data collection is often a limiting factor in quality measurement initiatives due to the availability and retrievability of the data required to calculate the QI.14 17–19 25 Retrievability of the data is dependent on the format of the data.14 The increasing use of EMR will increase availability and retrievability of the data, and thus also improve its reliability. Further, the collection of QIs should be a prospective effort, QIs first being defined and then the required data being collected. The availability of the data should not restrict or influence the decision to collect an indicator or not.19
Beyond this, and as mentioned in the free-text comments, reliability of data collection could be further improved by the automatic export of data (eg, vital parameters) from medical devices (eg, monitor) to the EMR, video recording of the procedure, or a dedicated person present on scene and looking for specific data points.26 Moreover, most of the datapoints have been shown to be reliably collectable in specific projects in the past.2 27 However, the collection of the data must remain feasible in the long term and within the given resource and time constraints. In our study, the effort to complete a dedicated CRF for the collection of the QIs for PAAM was considered reasonable by almost all the physicians who participated to the survey (95%), a much higher result than that reported by de Cruppé et al (unacceptable for 67%) and Ewald et al (acceptable for 35%).14 17 The regular involvement of the service’s physicians in scientific projects might in part explain these outstanding results. Further, the topic addressed in our study was specific and the time to complete it was much lower. For monitoring of larger QI sets, technical solutions should be found to allow for automated data collection and/or direct collection in the EMR, the data being part of the standard data set documented for every HEMS mission.14 17
Finally, a culture of transparency and learning both from excellence and mistakes in a service is paramount for continuous quality improvement. Automated data collection is possible for certain indicators such as vital signs, but human documentation will remain necessary for other indicators such as complications and success, where a reporting bias is always possible.
Improvement of the QI set
Feasibility field testing allows improvement of a set of QI. Its content validity can be increased by improving the average relevance of the set of QIs either by removing or modifying the least relevant QIs.28 On the other hand, it enables the identification of QIs where reliability of data collection is low and in need of improvement.
AAM being a relatively rare intervention in our PEMS and in order to have a representative sample and a valuable assessment before potentially adapting the QIs and the REDCap CRFs, a 3-year field test to reach 470 CRFs seemed to be adequate and comparable to a previous study on QIs in prehospital critical care in which the data from 450 missions were collected during its pilot phase.7 20 However, the length of the study period may represent a limitation, as some physicians answered the questionnaire 2 years after completing their last CRF. Nevertheless, the study also included 30% of senior physicians who participated over the 3-year period.
Another limitation might be related to the questionnaire. Despite using existing questions from previous feasibility studies and proposing the questionnaire in two languages, there was a high range in certain answers, although data were retrieved from the EMR by using the same procedure and software (especially for QI 15 and QI 17). This might be due to ambiguities in the questions or misunderstanding of the participants.
One of the strengths of the study is the high participation rate (95% of all physicians who worked in the PEMS during the study period) and the heterogeneity of the physicians’ characteristics, which is representative of the prehospital emergency physician population practising in Switzerland. However, the study was conducted in two PEMS and external validity can be seen as limited. Nevertheless, our results show that monitoring of QI for PAAM, a specific but critical and highly relevant procedure of prehospital emergency medicine, is feasible with simple means. This should inspire other PEMS to follow the path which will contribute to increase the external validity of our results and improve quality of PAAM.
In conclusion, a set of 17 QIs on PAAM obtained high acceptance and relevance when assessed by emergency physicians of two PEMS. The collection of the data required to calculate the QIs through a dedicated CRF is reliable, and the effort to complete the CRF was considered reasonable for the size of the set. In order to maximise the reliability of data collection, data should be collected prospectively and electronically. Wherever possible, data should be collected automatically and/or directly in the EMR.
Supplementary Material
Acknowledgments
The authors sincerely thank Dr. A.S. Feiner for English proofreading of the survey questionnaire.
Footnotes
Twitter: @alexkottmann
Contributors: All authors participated substantially to the project. Conceptualisation: AKottmann, MP, P-NC, SJMS and AKrüger. Development of the CRF: AKottmann, MP, LM and J-DR. Study design: AKottmann and MP. Ethics approval coordination: AKottmann. Development of the survey: AKottmann, DC-B and MP. Data analysis: AKottmann. Writing of the manuscript: AKottmann, MP, P-NC, LM, LS and SJMS. Review of the manuscript: TR, J-DR, RA and AKrüger. Guarantor: AKottmann. All authors have read and agreed to the published version of the manuscript.
Funding: The Norwegian Air Ambulance Foundation covered the open access publication fees.
Competing interests: None declared.
Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review: Not commissioned; externally peer reviewed.
Supplemental material: This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.
Data availability statement
Data are available upon reasonable request.
Ethics statements
Patient consent for publication
Not applicable.
Ethics approval
The project was considered a quality assurance study and was therefore exempted from a formal agreement by the local ethic committee (Human Research Ethics Committee of the Canton of Vaud, Switzerland: CER-VD Req-2021-01289). Participants gave informed consent to participate in the study before taking part.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
bmjopen-2023-081951supp001.pdf (89.6KB, pdf)
Data Availability Statement
Data are available upon reasonable request.