Dominik Brammen

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.

Minimaler Notfalldatensatz MIND3

ZusammenfassungDer fortgeschriebene Minimale Notfalldatensatz MIND3 ist ein Kerndatensatz, der eine definierte und von der DIVI autorisierte Menge an Merkmalen und Merkmalsbeschreibungen enthält, die zur Dokumentation der prähospitalen Notfallrettung durch Rettungs- und Notarztdienst erforderlich sind. Der modulare Aufbau ermöglicht eine situations- und einsatzgerechte Dokumentation auf einem Basismodul-DIVI-Notfalleinsatzprotokoll und entsprechenden Zusatzmodulen. Mit einer IT-gestützten Datenerfassung werden die Grundlagen für ein medizinisches Qualitätsmanagement gelegt.AbstractThe updated minimum emergency data set MIND3 is a core data set which contains a defined amount of criteria and descriptions of criteria authorized by the German Interdisciplinary Association for Intensive Care and Emergency Medicine (DIVI) which are necessary for documentation of prehospital emergency missions by rescue and emergency medical services. The modular construction allows documentation compatible with the situation and mission on a basic module DIVI emergency mission protocol and appropriate additional modules. The foundations for medical quality management are laid with information technology support for data collation.

Kerndatensatz „Notaufnahme“ der DIVI

ZusammenfassungHintergrundFür die Dokumentation der Notfallversorgung in deutschen Notaufnahmen existierte bislang kein einheitlicher Standard. Sowohl einrichtungsübergreifende Analysen der behandelten Patientenkollektive im Rahmen der Versorgungsforschung als auch krankenhausinterne Analysen des Qualitätsmanagements waren somit nur schwer möglich. Ziel der Sektion Notaufnahmeprotokoll der Deutschen Interdisziplinären Vereinigung für Intensivmedizin und Notfallmedizin (DIVI) war es, den 2010 konsentierten modularen Kerndatensatz „Notaufnahme“ für eine standardisierte Dokumentation der frühen innerklinischen Notfallversorgung zu entwickeln.MethodenRecherche und Auswertung aktueller Literatur, Expertentreffen, Delphiprozess.ErgebnisseIn interdisziplinären Expertenrunden wurden zunächst die Anforderungen an die Dokumentation in einer Notaufnahme analysiert, bereits existierende Dokumentationssysteme ausgewertet und ein Kerndatensatz erarbeitet. Der so entwickelte Kerndatensatz ermöglicht die interdisziplinäre und interprofessionelle Dokumentation der Notfallpatientenbehandlung in deutschsprachigen zentralen Notaufnahmen (ZNA) unter Berücksichtigung der Punkte Informationsweitergabe, Qualitätsmanagement, Benchmarking, medikolegaler Aspekte und Ökonomie. Durch einheitliche Verwendung dieses Dokumentationsstandards kann die Vergleichbarkeit der Prozess- und Ergebnisqualität in Notaufnahmen gesteigert werden. Mit der geplanten Integration des Datensatzes in EDV-gestützte Dokumentationssysteme wird neben der Verbesserung der Dokumentationsqualität auch die automatisierte Bedienung von bundesweiten Registern und Vermeidung von redundanter Dokumentation erreicht.ZielDas vorliegende Update stellt den zurückliegenden und zukünftigen Entwicklungsprozess des Kerndatensatz „Notaufnahme“ dar und erläutert die Möglichkeiten der Nutzung dieser Daten für Zwecke des Qualitätsmanagements, eines nationalen Notaufnahmeregisters sowie der Versorgungsforschung anhand von 11 Aspekten der Kennzahlenanalyse. Erkannte Limitationen werden beschrieben und Wege, diese in zukünftigen Entwicklungsstufen zu verbessern, beleuchtet.AbstractBackgroundUntil recently no standards for the documentation of emergency patients in Germany existed, impairing the analysis of this group of patients as well as distribution of resources according to requirements. The section on emergency admission protocol (Sektion Notaufnahmeprotokoll) within the German Interdisciplinary Association of Critical Care and Emergency Medicine (DIVI), in close cooperation with several German medical associations, established the modular core dataset “emergency department” (ED) designed to define a standard for the documentation of early in-hospital emergency care.MethodsResearch and analysis oft he current literature, expert rounds, modified delphiprocess.ResultsThis core dataset will make it possible to document the treatment of all ED patients in Germany, across professions and disciplines, in one standardized form while giving due consideration to the most important aspects: distribution of information, quality management, benchmarking, legal and economic aspects. Consistent definition standards within the dataset make it easier to compare procedural quality as well as the outcome of treatment within emergency departments nationwide. The intended integration of the dataset into computer-based documentation systems will achieve improvement in the quality of documentation, create data for commonly used nationwide registers and also decrease redundant documentation.ObjektiveThe goal of this article is to describe how the core dataset “emergency department” was developed and to illustrate how to apply these data for benchmarking, quality management and the implementation of a nationwide emergency department register. Limitations are addressed, as well as measures to improve the core dataset in the future.

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

ObjectiveIn 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.MethodBased 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.ResultFour 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.ConclusionDue to reduced calibration, the clinical use of the prediction model is limited.

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.