Testing quality indicators and proposing benchmarks for physician-staffed emergency medical services: a prospective Nordic multicentre study

Abstract

ObjectivesA consensus study from 2017 developed 15 response-specific quality indicators (QIs) for physician-staffed emergency medical services (P-EMS). The aim of this study was to test these QIs for important characteristics in a real clinical setting. These characteristics were feasibility, rankability, variability, actionability and documentation. We further aimed to propose benchmarks for future quality measurements in P-EMS.DesignIn this prospective observational study, physician-staffed helicopter emergency services registered data for the 15 QIs. The feasibility of the QIs was assessed based on the comments of the recording physicians. The other four QI characteristics were assessed by the authors. Benchmarks were proposed based on the quartiles in the dataset.SettingNordic physician-staffed helicopter emergency medical services.Participants16 physician-staffed helicopter emergency services in Finland, Sweden, Denmark and Norway.ResultsThe dataset consists of 5638 requests to the participating P-EMSs. There were 2814 requests resulting in completed responses with patient contact. All QIs were feasible to obtain. The variability of 14 out of 15 QIs was adequate. Rankability was adequate for all QIs. Actionability was assessed as being adequate for 10 QIs. Documentation was adequate for 14 QIs. Benchmarks for all QIs were proposed.ConclusionsAll 15 QIs seem possible to use in everyday quality measurement and improvement. However, it seems reasonable to not analyse the QI ‘Adverse Events’ with a strictly quantitative approach because of a low rate of adverse events. Rather, this QI should be used to identify adverse events so that they can be analysed as sentinel events. The actionability of the QIs ‘Able to respond immediately when alarmed’, ‘Time to arrival of P-EMS’, ‘Time to preferred destination’, ‘Provision of advanced treatment’ and ‘Significant logistical contribution’ was assessed as being poor. Benchmarks for the QIs and a total quality score are proposed for future quality measurements.

The first seven years of nationally organized helicopter emergency medical services in Finland – the data from quality registry

“…Over the years there have been minor revisions in the datasets, presented in Additional File 3. FHDB is used for daily reporting, scientific purposes and the governing of HEMS operations as a whole [16,[18][19][20]. The database also allows the creation of specific casereport forms for research projects or to monitor effects of specific quality improvement interventions.…”

“…The database contains only a subset of all EMS patients and dispatching criteria in our system might omit patient groups prominent in other systems. Despite these limitations, FHDB stores a large amount of nationwide data that can be, and already has been, used for further research in prehospital EMS and HEMS [16,18,19]. The data is being combined with the national discharge register and mortality data, enabling studies assessing survival, factors associated with changes in mortality and length of hospitalization.…”

Developing Quality Indicators for Helicopter Emergency Medical Services Coordination in Norwegian Emergency Medical Communication Centrals: A Consensus Process

“…25 A good quality assessment system consists of multiple indicators addressing different dimensions of quality. Moreover, Haugland et al 18 recently suggested some characteristics essential for QIs in order to make them as useful in clinical practice as possible. Most of our developed indicators were process indicators.…”

“…Moreover, the indicators should be feasible, rankable, actionable, and variable. 17,18 By this, one understands that a QI, which is nonmeasurable, is of little value. The QI should also be possible to rank, from high to low or good to bad.…”

Mortality and quality of care in Nordic physician-staffed emergency medical services

“…For the purpose of describing the quality of care for patients who died within 30 days, a quality scale for the EQUIPE quality indicators was used. This quality scale presents QI performances as average (within the interquartile range (IQR); yellow zone), above average (above IQR; green zone) or below average (below IQR; red zone) [16] based on the value of all QIs. Moreover, the quality scale defines a benchmark for every QI at the transition between the yellow and green zone.…”