Minimaler Notfalldatensatz MIND3

Ambulance deployment without transport: a retrospective difference analysis for the description of emergency interventions without patient transport in Bavaria

BACKGROUND

Not all patients who call the ambulance service are subsequently transported to hospital. In 2018, a quarter of deployments of an emergency ambulance in Bavaria were not followed by patient transport. This study describes factors that influence patient transport rates.

METHOD

This is a retrospective cross-sectional study based on data from all Integrated Dispatch Centres of the Free State of Bavaria in 2018. Included were ambulance deployments without emergency physician involvement, which were subdivided into ambulance deployments without transport and ambulance deployments with transport. The proportion of transported patients were determined for the primary reasons for deployment and for the different community types. On-scene time was compared for calls with and without patient transport. Differences were tested for statistical significance using Chi2 tests and the odds ratio was calculated to determine differences between groups.

RESULTS

Of 510,145 deployments, 147,621 (28.9%) could be classified as ambulance deployments without transport and 362,524 (71.1%) as ambulance deployments with transport.The lowest proportion of patients transported was found for activations where the fire brigade was involved ("fire alarm system" 0.6%, "fire with emergency medical services" 5.4%) and "personal emergency response system active alarm" (18.6%). The highest transport rates were observed for emergencies involving "childbirth/delivery" (96.9%) and "trauma" (83.2%). A lower proportion of patients is transported in large cities as compared to smaller cities or rural communities; in large cities, the odds ratio for emergencies without transport is 2.02 [95% confidence interval 1.98-2.06] referenced to rural communites. The median on-scene time for emergencies without transport was 20.8 min (n = 141,052) as compared to 16.5 min for emergencies with transport (n = 362,524). The shortest on-scene times for emergencies without transport were identified for activations related to "fire alarm system" (9.0 min) and "personal emergency response system active alarm" (10.6 min).

CONCLUSION

This study indicates that the proportion of patients transported depends on the reason for deployment and whether the emergency location is urban or rural. Particularly low transport rates are found if an ambulance was dispatched in connection with a fire department operation or a personal emergency medical alert button was activated. The on-scene-time of the rescue vehicle is increased for deployments without transport. The study could not provide a rationale for this and further research is needed. Trial registration This paper is part of the study "Rettungswageneinsatz ohne Transport" ["Ambulance deployment without transport"] (RoT), which was registered in the German Register of Clinical Studies under the number DRKS00017758.

[Linking Health Claims Data and Records of Emergency Medical Services: Building a Bridge via Patient's Health Insurance Number?]

INTRODUCTION

In Germany, Emergency Medical Services (EMS) were involved in a total of 7.3 million emergency cases in 2016/2017. Information on prehospital care is stored in several secondary data sources, yet combined analysis of these data at the level of individual patients or EMS cases happens rarely. Research is needed on which methods and variables are suitable for the linkage of these data sources.

METHODS

We linked EMS records from five Bavarian emergency service districts to health claims data belonging to ten statutory health insurers (data from 2016). Two linkage approaches at the level of individual patient's EMS case/reimbursement case were demonstrated. First, a deterministic linkage was conducted based on the patient's unique identifying health insurance number. The second linkage was probabilistic. As linkage variables, it comprised the only partially available health insurance number plus several non-unique key variables, the latter being a patient's health insurance provider, sex, year of birth and distance travelled. In order to verify the deterministic and the probabilistic linkages' quality, rates of accordance of several variables present in both data sources were calculated.

RESULTS

The starting point for our data linkage were 106,371 EMS records (independent of certain health insurance companies) and 432,693 EMS services reimbursed by health insurers (independent of specific EMS providers). 4,327 EMS records could be linked to health claims data - out of 5,921 EMS records that coded a health insurance company contributing claims data to Inno_RD. With a probabilistic linkage, it was possible to increase this number to a total of 5,379 linked EMS records. All checks carried out indicated a high linkage quality for both the deterministic and the probabilistic approach.

CONCLUSION

A linkage of EMS records with health claims data is possible. In Inno_RD, a probabilistic approach has proven a valuable alternative to deterministic linkage via health insurance number since EMS records can be linked meaningfully even if the health insurance number is unavailable or where a minority of non-unique key variables show non-accordance or missing values.

Medizinische Ereignisse auf Windenergieanlagen offshore – retrospektive Analyse der Behandlungsdaten 2017–2020

Hintergrund

Insgesamt arbeiten täglich mehrere Tausend Menschen im Offshore-Bereich. Die Arbeit findet regelhaft unter beengten Bedingungen, in Höhen und Tiefen statt, woraus ein erhöhtes Gefahrenpotenzial mit spezifischen Verletzungen resultiert. Weiterhin müssen die Arbeiter in ihren mehrwöchigen Einsätzen allgemeinmedizinisch versorgt werden. Nach erfolgter Digitalisierung der medizinischen Einsatzdokumentation sollen nun die ersten Jahre ausgewertet und vor allem Art und Inzidenz der Notfälle analysiert werden.

Methode

4356 Datensätze aus dem Zeitraum Juni 2017 bis Dezember 2020 wurden im Rahmen der Versorgung und Einsatzdokumentation durch das eingesetzte Rettungsfachpersonal mittels digitalem Protokoll erfasst und nun anonymisiert retrospektiv ausgewertet.

Ergebnisse

Bei den definierten Diagnosegruppen waren am häufigsten die Infektionen (13,2 %) und Atemwegserkrankungen (8,4 %) sowie bei den Unfällen die Traumata der oberen (8,4 %) und unteren (4,6 %) Extremität. Entsprechend zählten 21,2 % der Einsätze zu den traumatologischen Notfällen, 71,1 % zu internistischen und 4,0 % zu sonstigen Erkrankungen. Die meisten Fälle wurden als geringfügige (61,2 %) oder ambulant behandelbare Störungen (23,4 %) eingestuft. Der nur bei vollständigen Datensätzen (n = 884) zu errechnende Schweregrad (Mainz Emergency Evaluation Score) lag im Mittel bei 24,1 ± 2,2 von 28 Punkten. Nur 1,9 % der Patienten wurden per Offshore-Rettungshubschrauber an Land verlegt, 4,0 % konnten mittels „crew transfer vessel“ transportiert werden.

Schlussfolgerung

Bei den meisten medizinischen Notfällen handelte es sich um minderschwere Ereignisse aus dem internistischen Spektrum mit geringfügiger Störung und ambulanter Behandlung. Bei den traumatologischen Notfällen sind Verletzungen an den Extremitäten führend. War eine Landverlegung erforderlich, geschah diese meist mittels „crew transfer vessel“ und nur zu einem Viertel der Fälle via Offshore-Rettungshubschrauber. Auch hier überwogen internistische Erkrankungen als Transportindikation.

[Preclinical emergency anesthesia : A current state analysis from 2015-2017]

BACKGROUND AND OBJECTIVE

Due to multiple factors the performance of preclinical emergency anesthesia is fraught with risks even for experienced emergency physicians. In order to support emergency physicians in monitoring and management of anesthesia, the German practice management guidelines for preclinical emergency anesthesia in adults were published in 2015; however, current data on adherence to the guidelines are not available.

MATERIAL AND METHODS

In a retrospective register analysis of preclinical anesthesia from 2015-2017 in Baden-Württemberg, the recorded anesthetic agents, monitoring, airway management and medical disciplines of emergency physicians were analyzed. The anesthetic agents utilized were compared to the emergency scenarios in the guidelines (e.g. cardiac patients, patients with acute respiratory insufficiency or acute neurological disorder and trauma patients).

RESULTS

Midazolam and propofol were predominantly used in the 12,605 cases of preclinical emergency anesthesia evaluated. The adherence to the guidelines was 35% for cardiac patients, 51% for patients with acute respiratory insufficiency or 52% for acute neurological disorders and 79% for trauma patients. Securing the airway was carried out in 88.5 % with endotracheal intubation (capnography 79%). Discipline-related differences occurred in airway management for the devices used, capnography, muscle relaxation and the frequency of the subjectively difficult airway. A higher adherence for trauma patients and patients with acute neurological disorders was found for emergency physicians who were anesthesiologists compared to non-anesthesiologists.

CONCLUSION

The study of the current state of preclinical emergency anesthesia in Germany showed a deficient implementation of the pharmacological recommendations for action except for trauma patients. Reasons for divergence could arise due to different availability of rescue equipment, training concepts or discipline of emergency physicians. Suitable education and training could improve the quality of prehospital anesthesia in Germany.

[Future of emergency medicine in Germany 2.0]

In 2003 an article on the future of prehospital emergency medicine in Germany was published in the journal Der Anaesthesist. Emergency medicine in Germany, which at that time was almost exclusively defined as prehospital emergency rescue, has evolved and now in-hospital domains have increasingly moved into the focus. At that time, the primary goal was to connect prehospital management with a smooth transition to hospital admission and further care in the hospital and to further optimize the rescue chain from the actual emergency through to causative treatment. Now after 15 years, the authors have critically assessed the development postulated in 2003 and reevaluated it. Which aspects could be developed further and become firmly established, what is still open and which questions in preclinical and clinical emergency treatment of the population will occupy us in the coming 15 years? With a critical eye to the past, the present contribution aims to capture the essential and new topics and open questions and provide a fresh perspective for the future of emergency medicine. Regulation at the state level or even lower levels of government often stand in contrast to more sweeping and economically effective approaches at the federal level. Prehospital emergency medicine in Germany is on the whole well-positioned with respect to facilities and personnel; however, as far as the economic situation and the utilization of available systems are concerned, there is still substantial room for improvement.

[National data set "emergency department": development, structure and approval by the Deutsche Interdisziplinäre Vereinigung für Intensivmedizin und Notfallmedizin]

BACKGROUND

The Deutsche Interdisziplinäre Vereinigung für Intensivmedizin und Notfallmedizin (DIVI) is divided into sections one of which is the "Sektion Notaufnahmeprotokoll" (emergency department protocol section) founded in 2007. The main task was to create a national data set for the documentation of patients in emergency departments (ED).

MATERIAL AND METHODS

In order to create such a data set a careful look was taken at the current state of documentation in many different hospitals throughout Germany. In addition, existing registries and international requirements were also taken into consideration. The content of the dataset "ED documentation" was developed in interdisciplinary and interprofessional expert rounds.

RESULTS

The dataset "ED documentation" forms the first basis for documentation in German EDs. The modular data set contains 676 fields and covers all relevant information of the whole clinical process in the ED. Legal issues as well as several aspects for internal and external quality management are also included. For this reason the data of several German quality registries (e.g. TraumaRegister DGU® of the German Society of Trauma Surgery) are part of the data set. Furthermore, the data set forms the basis for several financial and billing aspects. A set of six forms was created in accordance with the developed modular data set. In 2010 the data set was approved by the executive committee of the DIVI. Several German medical associations (e.g. German Association for Emergency Medicine/Deutsche Gesellschaft Interdisziplinäre Notfall- und Akutmedizin, DGINA) recommend its use. Currently 80 hospitals are using the data set.

CONCLUSION

Beside the ability to exchange information the presented data set is the basis for internal and external quality assessment in the ED even if most of the available scoring and benchmarking tools are not validated for the German medical system. Implementing an ED register in Germany which is planned in the future, could close this gap.

LOINC in prehospital emergency medicine in Germany - experience of the `DIRK´-project

BACKGROUND

Treatment of patients picked up by emergency services can be improved by data transfer ahead of arrival. Care given to emergency patients can be assessed and improved through data analysis. Both goals require electronic data transfer from the emergency medical services (EMS) to the hospital information system. Therefore a generic semantic standard is needed.

OBJECTIVES

Objective of this paper is to test the suitability of the international nomenclature Logical Observation Identifiers Names and Codes (LOINC) to encode the core data-sets for rescue service protocols (MIND 2 and MIND 3). Encoding diagnosis and medication categories using ICD-10 and ATC were also assessed.

METHODS

Protocols were broken down into concepts, assigned to categories, translated and manually mapped to LOINC codes. Each protocol was independently encoded by two healthcare professionals and in case of discrepancies a third expert was consulted to reach a consensus.

RESULTS

Currently 39% of parameters could be mapped to LOINC. Additional use of other coding systems such as International Statistical Classification of Diseases and Related Health Problems (ICD-10) for diagnoses and Anatomical Therapeutic Chemical Classification System (ATC) for medications increases the rate of 'mappable' parameters to 56%.

CONCLUSIONS

Although the coverage is low, mapping has shown that LOINC is suitable to encode concepts of the rescue services. In order to create a generic semantic model to be applied in the field our next step is to request new LOINC codes for the missing concepts.

[Standardized documentation in emergency departments with the core dataset of the DIVI]

In Germany the documentation of every prehospital emergency medical treatment has been standardized since 1997 based on the core data-set MIND (minimal emergency physician data-set). Against this background it is very surprising that there is still no standardized data-set implemented for the documentation of early inhospital emergency care. In order to create such a data-set the current state of documentation in many different hospitals all over the country was scrutinized. In addition existing registries and international requirements were taken into consideration. Finally, a modular data-set was created using a Delphi process. This data-set was tested, clinically validated and finally ratified by the executive committee of the DIVI (German Interdisciplinary Association of Critical Care Medicine). The modular data-set was designed in such a way that a basic module forms the foundation for every patient. Process-oriented modules (e.g. surveillance) and symptom-oriented modules (e.g. trauma, neurology) were added if necessary. Along with this data-set a set of six modules was created for graphical representation when required. This high level of standardization not only allows an internal and external quality assessment but also provides a sophisticated documentation system especially to the trauma team in the emergency department. In terms of content major parameters of interhospital quality management are recorded and important factors of process management, such as MTS (Manchester triage system), ATLS (advanced trauma life support) and EWS (early warning score) have been implemented. The data-set includes all necessary information for transfers between physicians and non-academic staff as well as between physicians and could also be used as a fundamental discharge letter. Moreover, this new core data-set is the implementation of items required by existing registries into the daily routine documentation in order to reduce unnecessarily time-consuming and error-prone secondary data acquisition. For example, all items of the preclinical and emergency room documentation for the TraumaRegister DGU® (documentation phase S, A and B of the standard and QM form) have been included. This is sufficient for participation as a TraumaNetzwerk DGU® member as far as the early clinical treatment of multiple injured patients is concerned.