Collecting core data in physician-staffed pre-hospital helicopter emergency medical services using a consensus-based template: international multicentre feasibility study in Finland and Norway

The study was an international multicentre feasibility study including two physician-staffed pre-hospital services. As the aim of the study was to examine the feasibility of collecting template data in a standard operational pre-hospital context, we designed a two-method collection protocol. We hypothesized that by using a dedicated and motivated group of physicians (focused data collection method), we would achieve a robust indication of whether the template data were possible to collect in general. By comparing data collected with the focused collection method to routinely collected data (standard data collection method) we could assess whether both methods were feasible, or if data collection was feasible for specially dedicated physicians only.

For the standard data collection method, data from the five p-EMS bases administered by FinnHEMS (the national operator of p-EMS in Finland), covering a total population of 3.7 million inhabitants, were extracted from their database for a period of 12 months (March 2013 through February 2014). The physicians were not informed that data were extracted, thus completeness rates represents routinely collected data for FinnHEMS.

For the focused data collection method, template data were collected prospectively for six weeks in Norway (January through March 2014) by 16 physicians from four p-EMS bases, covering a total population of 1.75 million inhabitants. Each participating physician was asked to collect template data as complete as possible on a predefined form and all physicians were informed that this was a study of completeness rates. Emphasis was on keeping the data collection period short to avoid study-fatigue. Data were placed in standardized categories and data sets from Finland and Norway were then merged.

Feasibility of the two data collection methods were assessed by comparing completeness rates on several variables. Variables that proved difficult to collect were identified and reasons for different completeness rates were sought by comparing completeness rates for different patient groups and operational settings. Data were stratified according to medical problem, p-EMS escort to hospital, severity of the patient’s condition, patient age, time from p-EMS arrival on scene to delivery at hospital and mode of transportation.

Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) [40] and Standards for Quality Improvement Reporting Excellence (SQUIRE) [41] guidelines were consulted when drafting the manuscript.

The template for data collection consists of five main sections [34]. The first section, “Fixed system variables” contain data about service area, organization and activation criteria and is identical to all missions for each base, hence this section was not included in the study. The second section, “Event operational descriptors”, contain time data, data on dispatch and type of transportation. The third section, “Patient descriptors”, contain patient data, data on patient physiology and medical problem. The fourth section, “Process mapping data”, contain data on medication and procedures performed during the mission and the fifth section, “Outcome measures”, contain data on mission outcome. A full description of all variables is provided in Additional file 1. Physicians in Norway were instructed to register event operational and patient descriptors, process mapping and outcome measures. In total 33 variables were registered. Information on gender was omitted to de-identify patients. Further, the outcome measure “Physiological improvement” was also omitted, as this is a proposed quality indicator yet to be validated. The corresponding variables were extracted from the FinnHEMS database. For the standard data collection method, all process mapping data and data on unit arrival at scene, type and result of dispatch, comorbidity and medical problem were mandatory to register to complete patient records. For the focused data collection method, no variable was mandatory.

The two data collection methods were compared by comparing completeness rates on several variables. Variables that proved difficult to collect were identified and reasons for different completeness rates were sought by comparing completeness rates for different patient groups and operational settings. Data were stratified according to medical problem, p-EMS escort to hospital, severity of the patient’s condition, patient age, time from p-EMS arrival on scene to delivery at hospital and mode of transportation. Categorical data are presented as counts (n) and proportions (%) while continuous data are presented as median and interquartile range (IQR). Standard Chi-Square, Fisher’s Exact Test and Mann-Whitney U Test were used for group comparison of categorical and continuous data. Kolomogorov-Smirnov test [42] was used for comparison of distributional properties. Data were analyzed using IBM SPSS statistics version 22 and R 3.1.0.

FinnHEMS submitted data from 12,486 missions. Of these, 8049 (64%) missions were excluded due to no patient encounter (supervision or advice only or due to a concurrent mission, weather or technical conditions), leaving 4437 (36%) missions eligible for further analyses. Norwegian p-EMS submitted data from 177 missions. Of these, 49 (28%) missions were excluded because of no patient encounter (due to weather or technical conditions), leaving 128 (72%) missions eligible for further analyses. The physicians in Norway registered on average 8 forms each, which is 1–2 forms per shift.

Patient and mission characteristics are summarized in Table 1. In both countries the majority of dispatches were for medical missions. Finland had more trauma dispatches than Norway but fewer inter-hospital transfers. In both countries, trauma was the single most common medical problem, followed by cardiac arrest in Finland and chest pain in Norway. In Finland, p-EMS physicians were transported to the scene by helicopter, but most patients were transported to the hospital by ground ambulances accompanied by the p-EMS physician. Most Norwegian patients were transported to the hospital by helicopter. Finland had significantly longer median on-scene time and median time from origin call to patient arriving hospital compared with Norway, but there was no difference in transport time or time from when call was received at the emergency medical communication centres to p-EMS arrival at scene. Significantly more advanced procedures were performed in Finland compared to Norway, but there was no difference in the number of patients receiving medication.

With the standard data collection method, all 13 mandatory variables were 100% complete (Table 2) while further four of the variables were > 80% complete. Ten variables had < 50% completeness. Six out of ten physiological variables (first and last value of heart rate, systolic blood pressure, heart rhythm, oxygen saturation and respiratory rate) had < 50% completeness. With the focused data collection method, seven variables were 100% complete, and overall 29 variables were > 80% complete. Two variables were < 50% complete. Except from the two variables reporting first and last systolic blood pressure, all physiological variables were > 80% complete.

Completeness rates were affected by clinical problems encountered and mission characteristics. Significantly more variables were collected with a focused data collection method than with a standard data collection method, both for different medical conditions, when patients were severely ill or injured and when patient care was less than 20 min. An additional file (Additional file 2) depicts our definition of a severely ill or injured patient. More variables were collected with focused data collection, regardless of transport mode. Completeness rate variations among different clinical problems are depicted in Figs. 1 and 2 and Table 3.

When comparing different patient groups for each data collection method, we found that for both methods, significantly less variables were collected when patient care was less than 20 min than when patient care was more than 20 min. Further, to be escorted by a physician to hospital resulted in more reported variables than when patients were treated by physicians on-scene and transported without physician. For children under 10 years of age, less variables were collected than when patients were older. Transport by helicopter resulted in significantly higher completeness rates with a standard data collection method, but there was no significant difference regarding transport mode with a focused data collection method. With standard data collection, significantly more variables were collected when patients were severely ill or injured compared to not severely ill or injured patients. There was no significant difference among these patient groups with a focused data collection. Differences in completeness rates among different patient groups with the two data collection methods are summarized in Table 4.

The present study has several limitations. We did not include a formal questionnaire to investigate reasons for missing data, although most physicians in Norway provided informal information regarding this. A questionnaire could have been useful to discover reasons for registration failure of importance to aid revision of the template. In Finland, the physicians were not informed about the study in advance, so the database reflects normal documentation rates in FinnHEMS bases. In Norway, the Hawthorne effect is an obvious and wanted effect, whereas the risk for this in Finland is lower.

The data are from 2013/2014 and this may be considered old. However, documentation method or organisation of p-EMS have not changed in either Finland or Norway since 2014, thus we believe the results still are valid and that newer data would have yielded similar results.

In Norway, 16 physicians participated, and each physician had on average 5 shifts during the data collection period. Each physician registered on average 8 cases, this is on average 1,6 cases per shift. This is a low number if each physician were to be evaluated individually. Because the aim of the study was to evaluate the documentation system, not the individual physician, we find the total number of cases registered in Norway to be acceptable.

The study was conducted in two similar p-EMS settings in two high-income countries and results may not be applicable to all other EMS settings. However, documentation for the study was paper-based, not including expensive equipment. The principles for pre-hospital emergency medical treatment are generally recognized, and international expert consensus on important data to be collected in the field should apply to both low- and high-income EMS systems. The concept of using a template by motivated personnel for data collection may therefore be applicable to other less resource-intensive settings.

Thirteen of the variables are mandatory to register in Finland and electronic patient files cannot be saved unless these variables are registered; completeness rates are therefore 100%. To compare these with Norwegian data will not give an idea of what is possible to collect in an everyday setting or if implementation challenges also apply for this type of data. Finally, the challenge with possible fabricated data to finalize registrations must be addressed.