German emergency department measures in 2018: a status quo based on the Utstein reporting standard.

BACKGROUND: Compelling data on clinical emergency medicine is required for healthcare system management. The aim of this survey was to describe the nationwide status quo of emergency care in Germany at the healthcare system level using the Utstein reporting template as the guideline to measure the data collected. METHODS: This cross-sectional survey collected standardized data from German EDs in 2018. All 759 of the EDs listed in a previously collected ED Directory were contacted in November 2019 using the online-survey tool SoSci Survey. Exclusively descriptive statistical analyses were performed. Absolute as well as relative frequencies, medians, means, ranges, standard deviations (SD) and interquartile ranges (IQR) were reported depending on distribution. MAIN RESULTS: A total of 150 questionnaires of contacted EDs were evaluated (response rate: 19.8%). Hospitals had a median of 403 inpatient beds (n=147). The EDs recorded a median of 30,000 patient contacts (n=136). Eighty-three EDs (55%) had observation units with a median of six beds. The special patient groups were pediatric patients (< 5 years) and older patients (> 75 years) with a median of 1.7% and 25%, respectively. Outpatients accounted for 55%, while 45% were admitted (intensive care unit 5.0%, standard care unit 32.3%, observation unit 6.3%) and 1.2% transferred to another hospital. CONCLUSIONS: The use of the Utstein reporting template enabled the collection of ED descriptive parameters in Germany. The data can provide a baseline for upcoming reforms on German emergency medicine, and for international comparisons on admission rates, initial triage categories, and patient populations.

[The way to routine data from 16 emergency departments for cross-sectoral health services research : Experiences, challenges and solution approaches from the extraction of pseudonymous data for the INDEED project]. / Der Weg zu Routinedaten aus 16 Notaufnahmen für die sektorenübergreifende Versorgungsforschung : Erfahrungen, Herausforderungen und Lösungsansätze aus der Extraktion pseudonymer Daten für das Projekt INDEED.

BACKGROUND: In Germany there is currently no health reporting on cross-sectoral care patterns in the context of an emergency department care treatment. The INDEED project (Utilization and trans-sectoral patterns of care for patients admitted to emergency departments in Germany) collects routine data from 16 emergency departments, which are later merged with outpatient billing data from 2014 to 2017 on an individual level. AIM: The methodological challenges in planning of the internal merging of routine clinical and administrative data from emergency departments in Germany up to the final data extraction are presented together with possible solution approaches. METHODS: Data were selected in an iterative process according to the research questions, medical relevance, and assumed data availability. After a preparatory phase to clarify formalities (including data protection, ethics), review test data and correct if necessary, the encrypted and pseudonymous data extraction was performed. RESULTS: Data from the 16 cooperating emergency departments came mostly from the emergency department and hospital information systems. There was considerable heterogeneity in the data. Not all variables were available in every emergency department because, for example, they were not standardized and digitally available or the extraction effort was judged to be too high. CONCLUSION: Relevant data from emergency departments are stored in different structures and in several IT systems. Thus, the creation of a harmonized data set requires considerable resources on the part of the hospital as well as the data processing unit. This needs to be generously calculated for future projects.

[Routine Data from Emergency Departments: Varying Documentation Standards, Billing Modalities and Data Custodians at an Identical Unit of Care]. / Routinedaten aus Notaufnahmen: Unterschiedliche Dokumentationsanforderungen, Abrechnungsmodalitäten und Datenhalter bei identischem Ort der Leistungserbringung.

BACKGROUND: Currently, there is a big need for data on emergency department (ED) utilization in Germany. One reason is the ongoing reorganisation of emergency care. Possible sources are routine data that are being collected based on legal regulations. Different payers and compensation systems have their own requirements for data collection. METHODOLOGICAL CHALLENGES: Due to the sectoral separation of health care services, there is no dataset or data holder to provide information on all ED treatments in Germany. From an administrative point of view, emergency care in Germany is considered ambulatory outpatient or inpatient care from the time point of admission to the ED. In contrast, clinical decision about inpatient admission can sometimes only be made towards the end of emergency care. EDs themselves cannot be identified in claims data; only the medical discipline (e. g. surgery) is classified. In the case of outpatient treatment, reimbursed by the Association of Statutory Health Insurance Physicians, at least one coded diagnosis (ICD) has to be recorded, accompanied by an additional code for the likelihood of this diagnosis. In case of multiple ICDs, a primary diagnosis cannot be specified. In the case of in-hospital treatment, an admission diagnosis must be recorded. After completion of hospital treatment, the main diagnosis and possibly secondary diagnoses are transferred to the respective health insurance fund. The statutory occupational accident insurance has its own requirements. SOLUTIONS: Depending on the research question and study design, different approaches are required. If data are queried directly in emergency departments or hospitals, additional information on the designated data holder and billing mode is crucial. When using health insurance data from inpatient care, the identification of emergency departments can be estimated on the basis of the reason for hospital admission and defined "unique" emergency ICDs. The case-related hospital statistics has its own limitations, but includes inpatients of all payers. DISCUSSION: Differing requirements for the administrative documentation cause a high workload in emergency departments. A standardised data collection system for all payers for inpatient and outpatient emergency care is recommended. This would contribute to the creation of valid and comparable datasets. The introduction of a particular identifier for EDs in claims data would enhance health services research.

Implementation of Emergency Department Performance Benchmarking Using R and LaTeX.

The German Emergency Department Data Registry (GEDD-registry, AKTIN) provides an infrastructure for collecting and querying up-to-date medical records in a distributed manner. Within this framework, a benchmark report on cross-institutional comparison using the program R is prepared using routine data of participating hospitals. Currently, 16 emergency departments (EDs) routinely transfer data of 1,200 to approximately 5,000 patients per month to a federated GEDD-registry datawarehouse. Using various packages in the R environment, hospitals receive a monthly visual report on their data among all participating hospitals. Graphical representations are implemented using column diagrams and box plots. Reports currently contain 25 tables and 40 graphs. Benchmark reports are created in R-Studio and exported using Portable Document Format, PDF. Quarterly expert meetings with the heads of participating EDs are currently performed for further improvements. Preparation of external benchmarking reports with R enables a detailed data presentation for participating hospitals and ED managers.

Scientific Challenge in eHealth: MAPPATHON, a Metadata Mapping Challenge.

Scientific challenges based on benchmark data enable the comparison and evaluation of different algorithms and take place regularly in scientific disciplines like medical image processing, text mining or genetics. The idea of a challenge is rarely applied within the eHealth community. Mappathon is a metadata mapping challenge that asks for methods to find corresponding data elements within similar datasets and to correlate data elements among each other.

The way from pen and paper to electronic documentation in a German emergency department.

BACKGROUND: Some of the advantages of implementing electronic emergency department information systems (EDIS) are improvements in data availability and simplification of statistical evaluations of emergency department (ED) treatments. However, for multi-center evaluations, standardized documentation is necessary. The AKTIN project ("National Emergency Department Register: Improvement of Health Services Research in Acute Medicine in Germany") has used the "German Emergency Department Medical Record" (GEDMR) published by the German Interdisciplinary Association of Intensive and Emergency Care as the documentation standard for its national data registry. METHODS: Until March 2016 the documentation standard in ED was the pen-and-paper version of the GEDMR. In April 2016 we implemented the GEDMR in a timeline-based EDIS. Related to this, we compared the availability of structured treatment information of traumatological patients between pen-and-paper-based and electronic documentation, with special focus on the treatment time. RESULTS: All 796 data fields of the 6 modules (basic data, severe trauma, patient surveillance, anesthesia, council, neurology) were adapted for use with the existing EDIS configuration by a physician working regularly in the ED. Electronic implementation increased availability of structured anamnesis and treatment information. However, treatment time was increased in electronic documentation both immediately (2:12 ± 0:04 h; n = 2907) and 6 months after implementation (2:18 ± 0:03 h; n = 4778) compared to the pen-and-paper group (1:43 ± 0:02 h; n = 2523; p < 0.001). CONCLUSIONS: We successfully implemented standardized documentation in an EDIS. The availability of structured treatment information was improved, but treatment time was also increased. Thus, further work is necessary to improve input time.

[Requirements for a sustainable standardization and digitalization in clinical emergency and acute medicine]. / Anforderungen an eine nachhaltige Standardisierung und Digitalisierung in der klinischen Notfall- und Akutmedizin.

Digitalization and standardization of documentation in medicine are increasingly progressing. In the decision of the Federal Joint Committee (G-BA) for a staged system of emergency structures in hospitals and in the report of the expert committee for development in the healthcare system on needs-oriented guidance of healthcare, the actuality of the topic is underlined with concrete naming of future tasks. The section on emergency admission protocols of the German Interdisciplinary Association of Intensive and Emergency Care Medicine (DIVI) has been working for years on this topic and has repeatedly reported on the progress of the topic in clinical emergency care. Standardization and digitalization represent the foundation for health services research spread across locations as well as the possibility for benchmarking. Digitalization makes the secondary use of primary clinical routine data possible. Digitalization decreases redundancies of data transmission by avoiding manual data input in, for example registers.

Comparing the German Emergency Department Medical Record with the US HL7 Data Elements for Emergency Department Systems.

Interoperability between emergency department (ED) information systems requires a shared data specification. In 2013 Health Level Seven International, an international standards body, approved a specification for Data Elements for Emergency Department Systems (DEEDS) for use in the United States. A similar specification was created in Germany for national employment, defining data elements and forms. This study presents the first step in the efforts to harmonize the two data definitions for International approval by comparing the meaning of the German Emergency Department Medical Record (GEDMR) data element definitions with the US DEEDS using a methodology for terminology mapping from ISO/TR 12300. The comparison between GEDMR and DEEDS did show significant differences in certain domains. The results support development of an international standard for ED data elements.

Lessons learned in applying the International Society for Pharmacoeconomics and Outcomes Research methodology to translating Canadian Emergency Department Information System Presenting Complaints List into German.

OBJECTIVES: The patient's presenting complaint guides diagnosis and treatment in the emergency department, but there is no classification system available in German. The Canadian Emergency Department Information System (CEDIS) Presenting Complaint List (PCL) is available only in English and French. As translation risks the altering of meaning, the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) has set guidelines to ensure translational accuracy. The aim of this paper is to describe our experiences of using the ISPOR guidelines to translate the CEDIS PCL into German. MATERIALS AND METHODS: The CEDIS PCL (version 3.0) was forward-translated and back-translated in accordance with the ISPOR guidelines using bilingual clinicians/translators and an occupationally mixed evaluation group that completed a self-developed questionnaire. RESULTS: The CEDIS PCL was forward-translated (four emergency physicians) and back-translated (three mixed translators). Back-translation uncovered eight PCL items requiring amendment. In total, 156 comments were received from 32 evaluators, six of which resulted in amendments. CONCLUSION: The ISPOR guidelines facilitated adaptation of a PCL into German, but the process required time, language skills and clinical knowledge. The current methodology may be applicable to translating the CEDIS PCL into other languages, with the aim of developing a harmonized, multilingual PCL.

Disseminating a Standard for Medical Records in Emergency Departments Among Different Software Vendors Using HL7 CDA.

A standardized medical record for the emergency department (GEDMR) was released in Germany, but only sparsely and randomly implemented by emergency department (ED) electronic health record (EHR) vendors. A reason for this may be a lacking common language between the medical and the Health Information Technology (HIT) domain. HL7 clinical document architecture (CDA) may leverage this communication gap. This paper reports on the effects of a professional medical association record standard on EHR vendors and the German ED-EHR market. Standard records and data standards are developed and published by different institutions either on governmental, healthcare agency or medical association level. There are some standard records, especially by US cardiology associations, transformed into HL7 C-CDA. GEDMR was modeled as HL7 CDA with the use of interoperable terminologies like LOINC and SNOMED CT. Being part of an emergency department data registry development project, local deployment at 15 project hospitals receiving sufficient funding was performed. Two major ED-EHR vendors adapted GEDMR within their product including CDA export. 106,868 CDAs were produced in six hospitals until now. Four local implementations with four different ED-EHRs were developed, producing 42,256 CDAs. Five additional vendors are adapting or developing an ED-EHR. The GEDMR-CDA implementation guide with funding for implementation in project hospitals had a significant impact on the German ED-EHR market. Within two years after release, a broadening and increasingly self-enforcing support by German ED-EHR vendors is notable.

Mapping Equivalence of German Emergency Department Medical Record Concepts with SNOMED CT After Implementation with HL7 CDA.

INTRODUCTION: The German Emergency Department Medical Record (GEDMR) was created by medical domain experts and healthcare providers providing a dataset as well as a form. The trauma module of GEDMR was syntactically standardized using HL7 CDA and semantically standardized using different terminologies including SNOMED CT, LOINC and proprietary coding systems. This study depicts the mapping accuracy with aforementioned syntactical and semantical standards in general and especially the content coverage of SNOMED CT. METHODS: The specification of GEDMR (V2015.1) concepts with eHealth-standards HL7-CDA, LOINC, SNOMED CT was analyzed. A content coverage assessment was made using the ISO TR 12300 rating scheme, following descriptive analysis. RESULTS: The trauma module of GEDMR contains 489 concepts, with 202 concepts expressed via HL7 CDA structure. It is possible to code 89 % of the remaining concepts via SNOMED CT. 79 % provide an advanced level of semantic interoperability, as they represent the source information either lexically or as an approved synonym. DISCUSSION: The terminology binding problem is relevant when combining different standards for syntactic and semantic interoperability with best practice documents and reference specifications providing guidance. A national license and extension for SNOMED CT in Germany as well as an ongoing effort in contributing to the International Version of SNOMED CT would be necessary to gain full coverage for concepts in German Emergency Medicine and to leverage the associated standardization process.

Balancing the need for big data and patient data privacy--an IT infrastructure for a decentralized emergency care research database.

Emergency rooms of hospitals provide care to a lot of patients and have great impact on their outcome, so researching the quality of care seems important. Research using registries has yielded impressive results in other areas of medicine. However centralized data-storage has its pitfalls, especially regarding data privacy. We therefore drafted an IT infrastructure that uses decentralized storage to ensure data privacy, but still enables data transfer between participating hospitals. It implements an independent information broker to ensure anonymity of patients. Still it provides a way for researchers to request data and hospitals to contribute data on an opt-in basis. Although not an entirely new approach, the emphasis on data privacy throughout the design is a novel aspect providing a better balance between the need for big sample sizes and patient privacy.

Corrected incidences of co-morbidities - a statistical approach for risk-assessment in anesthesia using an AIMS.

OBJECTIVE: In anesthesia and intensive care logistic regression analysis are often used to generate predictive models for risk assessment. Strictly seen only independent variables should be represented in such prognostic models. Using anesthesia-information-management-systems a lot of (depending) information is stored in a database during the preoperative ward round. The objective of this study was to evaluate a statistical algorithm to process the different dependent variables without losing the information of each variable on patient's conditions. METHOD: Based on data about prognostic models in anesthesia an iterative statistical algorithm was initiated to summarize dependent variables to subscores. Seven subscores out of several preoperative variables were calculated corresponding to the proper incidence and the correlation to the occurrence of intraoperative cardiovascular events was evaluated. After that first step logistic regression was used to build a predictive model out of the seven subscores, 10 patient-related, and two surgery-related variables. Performance of the prognostic model was assessed using analysis of discrimination and calibration. RESULT: Four out of seven subscores together with age, type and urgency of surgery are represented in the prognostic model to predict the occurrence of intraoperative cardiovascular events. The prognostic model demonstrated good discriminative power with an area under the ROC curve (AUC) of 0.734. CONCLUSION: Due to reduced calibration, the clinical use of the prediction model is limited.

An integrated data-warehouse-concept for clinical and biological information.

The development of medical research networks within the framework of translational research has fostered interest in the integration of clinical and biological research data in a common database. The building of one single database integrating clinical data and biological research data requires a concept which enables scientists to retrieve information and to connect known facts to new findings. Clinical parameters are collected by a Patient Data Management System and viewed in a database which also includes genomic data. This database is designed as an Entity Attribute Value model, which implicates the development of a data warehouse concept. For the realization of this project, various requirements have to be taken into account which has to be fulfilled sufficiently in order to align with international standards. Data security and protection of data privacy are most important parts of the data warehouse concept. It has to be clear how patient pseudonymization has to be carried out in order to be within the scope of data security law. To be able to evaluate the data stored in a database consisting of clinical data collected by a Patient Data Management System and genomic research data easily, a data warehouse concept based on an Entity Attribute Value datamodel has been developed.

Impact of inadequate surgical antibiotic prophylaxis on perioperative outcome and length of stay on ICU in general and trauma surgery. Analysis using automated data collection.

Within surgical departments, a large amount of antibiotics is used for perioperative prophylaxis. Despite the existence of several guidelines and recommendations for administering antibiotic prophylaxis, mistakes still do occur and have an unknown impact on outcome severity. Based on the electronic anaesthesia records of 4304 patients undergoing defined surgical procedures requiring perioperative antibiotic prophylaxis, a matched pairs approach was used to evaluate the impact of inadequate antibiotic prophylaxis on hospital mortality and prolonged length of stay on intensive care. Stepwise regression models were developed to predict the impact of inadequate antibiotic prophylaxis on outcome measures. An inadequate antibiotic prophylaxis was found for a total of 877 cases. 77.9% of cases were successfully matched, leading to 683 cases and controls each. The crude mortality ratio of cases to controls was 1.5 (cases = 21 versus controls = 14; P = 0.19). The case group had a significantly (P < 0.01) prolonged stay on ICU when analysed as a metric variable. Using logistic regression analysis, we could determine that inadequate antibiotic prophylaxis had no impact on either hospital mortality or prolonged length of stay on ICU (>1 day; yes or no).

Review of antibiotic drug use in a surgical ICU: management with a patient data management system for additional outcome analysis in patients staying more than 24 hours.

BACKGROUND: A number of developments have been made in computerized patient data management systems (PDMSs), making them of interest to medical and nursing staff as a means of improving patient care. OBJECTIVES: The aim of this study was to assess the capability of a PDMS to record and provide drug-administration data and to investigate whether the PDMS may be used as a means of support for clinical audits and quality control. Furthermore, we assessed whether antibiotic therapy as a surrogate for infections correlates with hospital mortality in patients staying >24 hours in a surgical intensive care unit (SICU). METHODS: Because of its medical and economic importance in ICU treatment, we chose to use the field of antibiotic therapy as an example. A PDMS was used in a 14-bed SICU (Department of Anesthesiology, Intensive Care Medicine, and Pain Therapy, University Hospital Giessen, Giessen, Germany) to record relevant patient data, including therapeutic, diagnostic, and nursing actions. During a 15-month period (April 1, 2000 to June 30, 2001), antibiotic drug therapy was electronically analyzed and presented using the anatomic therapeutic chemical (ATC) category for antibacterials (ATC group, J01) with daily defined doses. Furthermore, the correlation of antibiotic therapy with patient outcome (hospital mortality) was tested using logistic regression analysis. RESULTS: A total of 2053 patients were treated in the SICU. Of these, 58.0% (1190 patients) received antibiotics (4479 treatment days; 13,145 single doses). Cephalosporins (ATC category, J01DA) were used most frequently (1785 treatment days [39.9% of treatment days]), followed by combinations of penicillins with beta-lactam inhibitors (ATC category, J01CR; 1478 treatment days [33.0%]) and imidazole derivatives (ATC category, J01XD; 667 treatment days [14.9%]). The antibiotic therapy lasted <3 days in 65.6% of cases. In 13.8% of cases, the treatment lasted >1 week. A total of 36.7% of cases were treated with only 1 antibiotic agent, 14.1% were given a combination of 2, and 7.2% were given a combination of > or =3 antibiotic agents. Seven hundred twenty-six patients remained in the SICU for >24 hours; 143 (19.7%) died during their hospital stay; 110 (15.2%) in the SICU. The duration of antibiotic therapy (odds ratio [OR], 1.46) and number of different antibiotic drugs used (OR, 2.15) significantly correlated with hospital mortality. CONCLUSIONS: Antibiotic therapy in a SICU can be assessed and analyzed in detail using a PDMS. Furthermore, in this study, the duration of antibiotic therapy and the number of antibiotic agents used correlated with hospital mortality. In further developing PDMSs, it is important for quality-assurance purposes to document the reasons for giving antibiotics and for changing prescriptions. It would also be helpful to integrate certain therapy standards and reminder functions for the duration of therapy in the PDMS.

A data model for managing drug therapy within a patient data management system for intensive care units.

The major intent of this article was to describe the design principles of the drug-therapy documentation module of the Patient Data Management System (PDMS) ICUData, in routine use at the intensive care unit (ICU) of the Department of Anesthesiology and Intensive Care Medicine at the University Hospital of Giessen, Germany, since February 1999. The new drug management system has been in routine use since March 2000. Until 8 January 2001, 1140 patients have been documented using this approach. It could be demonstrated that it was possible to transform the formerly unstructured text-based documentation into a detailed and structured model. The mediated benefit resulted in the automatic calculation of fluid balance. Further, detailed statistical analyses of therapeutic behavior in drug administration are now possible.