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Abstract
Objective To develop a general and internationally applicable template of data variables for reporting interhospital neonatal intensive care transports.
Design A five-step Delphi method.
Setting A group of experts was guided through a formal consensus process using email.
Subjects 12 experts in neonatal intensive care transports from Canada, Denmark, Norway, the UK and the USA. Four women and eight men. The experts were neonatologists, anaesthesiologists, intensive care nurse, anaesthetic nurse, medical leaders, researchers and a parent representative.
Main outcome measures 37 data variables were included in the final template.
Results Consensus was achieved on a template of 37 data variables with definitions. 30 variables to be registered for each transport and 7 for annual registration of the system of the transport service. 11 data variables under the category structure, 20 under process and 6 under outcome.
Conclusions We developed a template with a set of data variables to be registered for neonatal intensive care transports. To register the same data will enable larger datasets and comparing services.
- neonatology
- data collection
- infant
Data availability statement
Data sharing not applicable as no datasets generated and/or analysed for this study.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
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WHAT IS ALREADY KNOWN ON THIS TOPIC
Reporting the same data variables enables building larger data sets and comparing services.
Benchmarking purposes help to develop high-quality care and uncover areas with room for improvement.
WHAT THIS STUDY ADDS
A set of data variables to be reported during neonatal intensive care transports.
HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY
It may enhance quality assurance and quality improvement initiatives, larger data sets and research collaborations.
Introduction
Improved treatment and centralisation of neonatal intensive care have decreased patient morbidity and mortality but also increased the number of transports of neonates between hospitals.1 2
Organisation of transport services varies within each country and between countries.1 3 4 Variations include team composition, training, skills, use of protocols, equipment, evaluation and quality measures.1 5 6 Some national and international networks capture data and report trends in treatment practices and patient outcomes, but data retrieved during the transport phase varies and remains scarce.7–9 To compare services internationally is important both to prioritise within one’s own service, to identify strength and weaknesses and aim for continuous advancements. These benchmarking purposes help to develop high-quality care and uncover areas with room for improvement.10 To merge data and compare practices in different services, it is pivotal to register the same set of data variables with one precise definition.11 Challenges with heterogeneous data have previously been reported in the prehospital setting.12 Lee reported on the varying definitions of timeline in different transport services and networks.6 A medical field which has used templates to guide research and quality improvement initiatives is cardiac arrest, with the Utstein template.13 Today there are big cardiac arrest registries around the world collecting the same set of data, making larger studies, comparing hospitals and services possible. Templates have been produced to reduce differences and agree on a set of data variables or quality indicators to be registered.14 15 These initiatives aim to enhance benchmarking, quality improvement and research initiatives across services.
There have been some regional and national initiatives to develop a set of metrics to evaluate and benchmark neonatal and paediatric intensive care transports.16 17 However, regional or national biases may limit the generalisability elsewhere. To our knowledge, there are currently no internationally established and widely adopted templates for neonatal intensive care transports.
Our aim was to develop a generic and internationally applicable template for reporting neonatal intensive care transports, using a five-step Delphi method.
Methods
A panel of experts in neonatal intensive care transports was guided through a consensus process, using a five-step Delphi method.18 We invited a group of experts in neonatal intensive care to propose, discuss and agree on relevant data variables to be registered for neonatal intensive care transports. All five steps were conducted using email. No exact criteria for selection of Delphi participants have been agreed on.18 19 The invited experts were identified using PubMed and the professional network of the study group and approached by email explaining the project background and the consensus process. Non-responders were reminded up to three times by email. The study is reported using the framework of the Revised Standards for Quality Improvement Reporting Excellence 2.0 from Equator Network.20
The project group
The project group consisted of the authors, all participants in the NeoTrans research group, at Oslo University Hospital and the Norwegian Air Ambulance Foundation. The group comprises neonatologists, anaesthesiologists, helicopter emergency medical services doctors, a professor, senior researchers and PhD candidates. Four in the project group conduct neonatal intensive care transports as a part of their daily work.
The expert group
The expert group consisted of neonatologists, anaesthesiologists, neonatal intensive care nurse, anaesthetic nurse, researchers, medical directors and a parent’s representative. The participants were made aware of the composition and professional background of the panel members, but the names of each participant were kept confidential. The group consisted of eight men and four women from different services in Canada, Denmark, Norway, the UK and the USA. Candidates for the expert panel were identified during autumn 2021 and invited by email in October 2021.
Conceptual framework
The participants of the expert panel were individually asked to propose data variables in the main categories: ‘structure, process and outcome’ as described by Donabedian in his assessment of quality of care.21 The term structure describes physical settings, human resources and organisational structure. Process relates to how systems work to deliver the expected result, and outcome evaluates results and changes in the patients’ health status.
The Delphi method
The Delphi method consists of five steps. In step 1, each expert was asked to suggest 3–10 variables in each of the main categories: structure; process and outcome, up to 30 variables in total. A fourth category, other, was provided for variables difficult to fit in the other three categories. After step 1, the project group organised the variables and removed duplicates within each category. The proposed data variables from step 1 were organised in a worksheet (Microsoft Excel for Mac V.16.77).
In the second step, the experts were asked to rate each variable from 1 to 5 according to importance, where 1 was not important and 5 was very important. Variables rated 4 or 5 by more than 70% of the experts were defined as consensus and included in the template draft.
In step 3, the experts were asked to rerate a shortlist of data variables rated 4 or 5 by 50%–70% of the experts. Variables rated 4 or 5 by more than 70% of the experts in either step 2 or step 3 were included in the template draft. The experts were also asked to group similar variables and comment on the placing of the variables. The project group organised variables, suggested report intervals and provided suggested definitions for each variable based on available literature, discussion and experience.
In step 4, the experts were asked to comment on placing, definitions, categories and report interval for the suggested variables.
In step 5, the template was sent to the experts for final approvement.
Results
The Delphi process was conducted from October 2021 to July 2022. 18 experts were invited to the process. 14 experts agreed to participate and 12 completed all 5 stages. The experts had worked within neonatology and neonatal intensive care transports between 8 and 35 years and ranged in age from 43 to 63. The expert group consisted of six neonatologists, two anaesthesiologists, one intensivist, one neonatal intensive care nurse, one anaesthetic nurse, six researchers, five medical directors and a parent’s representative. Eight had background from more than one field.
A flow chart of the Delphi process is presented in figure 1. 254 data variables were proposed in the first step. After duplicates were removed within each main category, 198 data variables entered step 2. 55 variables entered step 3 where duplicates and overlapping data variables were removed and put in the most suitable category. Some data variables were moved to be selected as categories or values under a more overriding variable. In step 4, with 39 variables, the experts commented on the placing of the variables, definitions, categories and report interval. In step 5, the template draft with 37 data variables was sent to the experts for final consensus.
Flow chart of the Delphi process.
The final template consisted of 37 data variables. 11 in the main category structure, 20 in process and 6 in outcome (see table 1). Seven variables were considered system specific/organisational and to be reported annually. 30 variables were suggested to be reported for each transfer. See online supplemental table 1 for definitions and online supplemental table 2 for categories and values of each variable.
Supplemental material
Data variables and report interval
All experts approved the final template.
Discussion
In this study, we coordinated the development of a template for reporting data variables from neonatal intensive care transports. To improve the quality of the medical transfers, comparison of services and data merging from different services using the same set of data variables is important. A panel of experts agreed on 37 data variables to be reported in neonatal intensive care transports, 7 of these to be reported only annually to provide background information on organisation of the service.
Transport services and neonatal intensive care transports are differently organised between services and countries. This makes it heterogeneous how these transports are conducted. There is insufficient knowledge regarding the best way to transport neonates. To better be able to answer these questions, it is important that we measure the same set of data variables to be able to compare services, organisational models and structure. Templates with a defined set of data variables can guide real-time quality improvement initiatives through a dashboard solution, make it easier and faster to capture changes in quality assurance and quality improvement, for example, when introducing new equipment, administrative data, baseline data for research and retrospective and prospective studies. The seven data variables in this template concerning organisation of services may help us compare services, clarify differences and enhance the development of the best organisational model.
Interventions and procedures are moved outside the hospital, and we need good baseline data to assure this is safe and will benefit the patients. The data variables in our template with a defined timeline, details about type of transport, monitoring, and treatment before and during transport will give good baseline data and may encourage future research. Reporting the variables concerning adverse events and complications will help us learn from them and monitoring changes within our own service and between services. Family-centred care is an integrated strategy of care in neonatal units and should also be implemented during transport.22 23
Strengths and limitations
We originally planned to do a modified nominal group technique (NGT) with two steps on email before a plenary meeting in Oslo. Unfortunately, due to the COVID-19 pandemic and the travel and meeting restrictions at the time, we were not able to arrange the plenary session, to let the experts meet and discuss. We decided to continue changing to a Delphi process with email only. Both the NGT and the Delphi process are formal consensus development methods concerned with obtaining a group decision from a set of expert participants. The main difference between an NGT and the Delphi method is the plenary meeting.18 In the Delphi method, the participants never meet or interact directly face-to-face. This may have influenced the process and the final set of data variables suggested. Some of the discussion and clarification are lost using email only. Some of the experts expressed their anticipation as an opportunity to convene and discuss with their colleagues in the field. We think a meeting would have enhanced the discussion and potential misunderstandings would have been easier to sort out than per email.
To develop a template feasible for different services in different countries, it was important that the participants in the panel were considered experts in the field, had credibility in their services and a broad background according to experience, competence, geographically localisation and gender. The varied background within the expert panel, according to gender, professions, countries and experience, remains a strength for this study, which we hope will also enhance the implementation of the template. Another strength is that 12 of the 14 experts who agreed to participate completed all five steps in the consensus process.
All the experts came from countries with well-established transport services, and the suggested template of data variables may, therefore, not necessarily be transferable to other services or countries with less developed systems for neonatal transports. Perhaps some parts of the template, a set of core variables, are more universally relevant and can be used by a wider range of services. This may be studied in a future project, after getting some experience using the template during real transports. Experts were recruited searching published articles in the field and using the professional network of the study group. This may represent a selection bias to who was invited to participate. The background and experience of the experts may influence implementation and which services that will use the template. Experts with position as a leader or conducting neonatal intensive care transports themselves may have easier access to implementing the template in their service. Participating in developing this template will hopefully make the experts want to try out the template in their daily work.
Another strength of this consensus process is that all variables have definitions (see online supplemental table 1). This is important to secure that everyone using the template measure the exact same data.
Barriers to implementation
For successful implementation in their service, it is important that the experts perceive a sense of ownership to both the process and the final template. We originally planned for a plenary meeting, but due to the pandemic this was cancelled and changed to an email-based Delphi process. This might have influenced the feeling of investment in the project by the experts.
To enhance compliance of reporting the data variables in the template and secure completeness of data, it is important that the set of variables to be registered for each transfer is not too large. For the template to be used during neonatal intensive care transports, it is also important that the template is easy to fill in and there is an easy access to the variables to be registered. This can be solved through developing a digital scheme or an application to be used on a tablet or phone instead of a paper journal, and the variables already registered in other systems to be automatically captured in the template to minimise the extra work needed to complete a registration. Testing the template on real transports will disclose if any of the variables are difficult to collect. Using the data collected in the template for quality improvement initiatives and research is important, so the participants filling in the template feel it useful to do the extra job.
It can be discussed whether variables should be mandatory or voluntary. The feasibility of a mandatory versus a voluntary set of variables has been investigated by Tønsager et al.24 One of the benefits with mandatory variables is that it may be easier to get a complete data set. One of the challenges is that some participants just click through the scheme to get it done. A voluntarily set of variables may give more missing data but may be the data collected are more accurate as the participants would not fill in something they do not have collected.
Future perspectives
The template now needs to be tested and evaluated according to its internal and external validity. It also needs to be tested on its reliability and feasibility. Using the same set of data variables may enable developing a database for these transports. Reporting the same data variables may encourage larger studies and collaborations in research.
Conclusions
We developed a template with 37 data variables for reporting neonatal intensive care transports by guiding a panel of experts through a consensus process using the Delphi method. Every variable comes with a definition and suggested report interval.
Data availability statement
Data sharing not applicable as no datasets generated and/or analysed for this study.
Ethics statements
Patient consent for publication
Ethics approval
This project did not involve research on biological material, humans or confidential information, and therefore, fell outside the mandate of the Health Research Act and the Regional Committee for Medical and Health Research waived the need for ethic approval (ref. 209552). Since the project did not collect sensitive or personal data, it was exempt from the Data Protection for Research restrictions (ref. 11190357).
Supplementary materials
Supplementary Data
This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.
Footnotes
Collaborators NeoTemplate Collaborating Group:Aastrøm Hege Anita. MSc. Bigham Michael T. MD. Bloch Vilni Verner Holst. MSc. Breindahl Morten. MD, PhD. Guthe Hans Jørgen. MD, PhD. Heimdal Hans Julius. MD. Hjertnes Siri. MD. Klingenberg Claus. MD, PhD. Lee Kyong-Soon. MD, MSc. Ramnarayan Padmanabhan. MD. Saunders Scott. MD, PhD. Steinnes Solfrid. MSc.
Contributors MR, FH and JH had the idea to the project. MB and MR prepared the protocol which was approved by all in the project group. MB sent information and each step of the process to the expert group. MB and MR organised the suggested variables and prepared the preliminary and final template, in collaboration with the rest of the project group. All authors from the project group contributed to and approved the final manuscript. All the experts in the NeoTemplate Collaborating Group completed all five steps in the consensus process. MB is responsible for the averall content as the guarantor.
Funding The project was funded by the Norwegian Air Ambulance Foundation, but they played no part in planning the study design, data collection, data analysis or preparing this manuscript.
Competing interests No, there are no competing interests.
Patient and public involvement Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods section for further details.
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.