[AKTIN - The German Emergency Department Data Registry - real-time data from emergency medicine : Implementation and first results from 15 emergency departments with focus on Federal Joint Committee's guidelines on acuity assessment]. / Das AKTIN-Notaufnahmeregister ­ kontinuierlich aktuelle Daten aus der Akutmedizin : Ergebnisse des Registeraufbaus und erste Datenauswertungen aus 15 Notaufnahmen unter besonderer Berücksichtigung der Vorgaben des Gemeinsamen Bundesausschusses zur Ersteinschätzung.

BACKGROUND: Emergency care in Germany is in transition. Emergency departments (EDs) treat their patients based on symptoms and acuity. However, this perspective is not reflected in claims data. The aim of the AKTIN project was to establish an Emergency Department Data Registry as a data privacy-compliant infrastructure for the use of routine medical data. METHODS: Data from the respective documentation systems are continuously transmitted to local data warehouses using a standardized interface. They are available for several applications such as internal reports but also multicentre studies, in compliance with data privacy regulations. Based on a 12-months period we evaluate the population with focus on acuity assessment (triage) and vital parameters in combination with presenting complaints. RESULTS: For the period April 2018 to March 2019, 436,149 cases from 15 EDs were available. A triage level is documented in 86.0% of cases, and 70.5% were triaged within 10 min of arrival. Ten EDs collected a presenting complaint regularly (82.3%). The respective documentation of vital signs shows plausible patterns. CONCLUSIONS: The AKTIN registry provides an almost real-time insight into German EDs, regardless of the primary documentation system and health insurance claims data. The Federal Joint Committee's requirements are largely met. Standardized presenting complaints allow for symptom-based analyses as well as health surveillance.

Predictors of hospitalizations for diabetes in Germany: an ecological study on a small-area scale.

OBJECTIVES: Our objective was to evaluate the role of potential predictors in explaining spatial variation among diabetes hospitalization rates in Germany. STUDY DESIGN: This was an ecological analysis using hospital routine data. METHODS: County-level hospitalization rates (n = 402) in 2015 were calculated based on the German Diagnosis Related Groups database. We used a funnel plot to identify counties with high hospitalization rates. To examine the impact of predictors such as socio-economic status or structure of primary care, we performed linear and logistic regression analyses. RESULTS: The crude hospitalization rate was 262 admissions per 100,000 population. In multivariable logistic models, we found the percentage of employees with academic degree (odds ratio [OR]: 0.72, 95% confidence interval [CI]: 0.56-0.91), high hospital bed rate (4th quartile vs 1st quartile; OR: 2.73, CI: 1.03-7.24), and diabetes prevalence (OR: 1.49, CI: 1.17-1.90) to be significant predictors for high hospitalization rates. In multivariable linear models, the percentage of unemployed (regression coefficient b: 4.79, CI: 0.81-8.78) and rurality (b: 0.52, CI: 0.19-0.85) explained the variation in addition to predictors from logistic regression. Primary care structure was not a significant predictor in multivariable models. CONCLUSIONS: The non-significant impact of primary care in adjusted models casts the use of diabetes hospitalizations as indicators for access and quality of primary care into doubt. Diabetes hospitalizations may rather reflect demand for care.

Capturing diagnosis-timing in ICD-coded hospital data: recommendations from the WHO ICD-11 topic advisory group on quality and safety.

PURPOSE: To develop a consensus opinion regarding capturing diagnosis-timing in coded hospital data. METHODS: As part of the World Health Organization International Classification of Diseases-11th Revision initiative, the Quality and Safety Topic Advisory Group is charged with enhancing the capture of quality and patient safety information in morbidity data sets. One such feature is a diagnosis-timing flag. The Group has undertaken a narrative literature review, scanned national experiences focusing on countries currently using timing flags, and held a series of meetings to derive formal recommendations regarding diagnosis-timing reporting. RESULTS: The completeness of diagnosis-timing reporting continues to improve with experience and use; studies indicate that it enhances risk-adjustment and may have a substantial impact on hospital performance estimates, especially for conditions/procedures that involve acutely ill patients. However, studies suggest that its reliability varies, is better for surgical than medical patients (kappa in hip fracture patients of 0.7-1.0 versus kappa in pneumonia of 0.2-0.6) and is dependent on coder training and setting. It may allow simpler and more precise specification of quality indicators. CONCLUSIONS: As the evidence indicates that a diagnosis-timing flag improves the ability of routinely collected, coded hospital data to support outcomes research and the development of quality and safety indicators, the Group recommends that a classification of 'arising after admission' (yes/no), with permitted designations of 'unknown or clinically undetermined', will facilitate coding while providing flexibility when there is uncertainty. Clear coding standards and guidelines with ongoing coder education will be necessary to ensure reliability of the diagnosis-timing flag.

[ICD-10 adaptation of 15 Agency for Healthcare Research and Quality patient safety indicators]. / Adaptation au codage CIM-10 de 15 indicateurs de la sécurité des patients proposés par l'Agence étasunienne pour la recherche et la qualité des soins de santé (AHRQ).

BACKGROUND: In the United States, the Agency for Healthcare Research and Quality (AHRQ) has developed 20 Patient Safety Indicators (PSIs) to measure the occurrence of hospital adverse events from medico-administrative data coded according to the ninth revision of the international classification of disease (ICD-9-CM). The adaptation of these PSIs to the WHO version of ICD-10 was carried out by an international consortium. METHODS: Two independent teams transcoded ICD-9-CM diagnosis codes proposed by the AHRQ into ICD-10-WHO. Using a Delphi process, experts from six countries evaluated each code independently, stating whether it was "included", "excluded" or "uncertain". During a two-day meeting, the experts then discussed the codes that had not obtained a consensus, and the additional codes proposed. RESULTS: Fifteen PSIs were adapted. Among the 2569 proposed diagnosis codes, 1775 were unanimously adopted straightaway. The 794 remaining codes and 2541 additional codes were discussed. Three documents were prepared: (1) a list of ICD-10-WHO codes for the 15 adapted PSIs; (2) recommendations to the AHRQ for the improvement of the nosological frame and the coding of PSI with ICD-9-CM; (3) recommendations to the WHO to improve ICD-10. CONCLUSIONS: This work allows international comparisons of PSIs among the countries using ICD-10. Nevertheless, these PSIs must still be evaluated further before being broadly used.

[Are hospital administrative data suitable for external quality assurance? Comparison of quality indicators based on separate statutory data collections (BQS) and hospital administrative data]. / Krankenhaus-Routinedaten zur externen Qualitätssicherung? Vergleich von Qualitätsindikatoren anhand der Daten der gesetzlichen externen Qualitätssicherung (BQS) und Routinedaten.

BACKGROUND: German hospitals are obliged legally to provide clinical data for external comparative quality assurance. Data rely on administrative data and just as on additional data collections for this purpose only. They are used to identify defined quality indicators (so-called BQS data). The Agency for Healthcare Research and Quality (AHRQ) also developed quality indicators that rely on hospital administrative data to evaluate the quality of inpatient care. METHODS: Six selected quality indicators were computed by both methods. 2007 data from the nationwide external quality assurance program were analyzed and compared to quality information derived from a 2007 10 % nationwide sample of administrative hospital data. RESULTS: Regarding the indicators "Obstetric trauma", "Mortality of community acquired pneumonia", "Postoperative deep vein thrombosis" and "Postoperative pulmonary embolism" rates are significantly higher in hospital administrative data than in BQS data (p < 0.01). Inversely, rates of the indicator "Decubitus ulcer" are significantly lower (p < 0.001). CONCLUSION: Possible causes for the results might be divergent motivations for data collection or restrictions in data collection. It remains unclear which method properly reflects the true status. Selected indicators (e. g. obstetric trauma), however, are suitable to be substituted by hospital administrative data.

A methodological framework for the conversion of procedure classifications.

OBJECTIVES: During the adaptation of the Australian Refined Diagnosis Related Groups for Germany mapping tables between procedure classifications were needed. The mapping between the German OPS-301 2.0 and the Australian MBS-Extended should transfer the Australian expertise by keeping a well-established terminology system. METHODS: A methodological framework for the development of mapping tables had been developed based on the model for representation of semantics provided by the European Committee of Standardization. Two approaches were used; the concept-based approach from OPS-301 2.0 to MBS-Extended and the class-based approach the other way round. A conversion had to be identified between 23,160 classes of the OPS-301 2.0 and 6,328 classes of the MBS-Extended in two asymmetrical mapping tables. RESULTS: The class-based approach leads to a low number of 6,980 conversions but misses 82.6% of the classes of the OPS-301. Because of domain incongruencies and missing domain completeness of the OPS-301 2.0 for non-operative procedures 15.7% of the MBS-Extended-classes remain without conversion. The concept-based approach leads to a slightly higher mean number of conversions per class of 1.35 in comparison to 1.31 with the class-based approach. But it was possible to find conversions for 99.5% of the OPS-301 2.0-classes. 16.3% of the DRG-relevant classes of the MBS-Extended were missed. CONCLUSIONS: The class-based approach was not useful, because the MBS-Extended is significantly broader than the OPS-301 2.0. An external validation study for the direction OPS-301 2.0 to MBS-Extended revealed a satisfactory quality. The empirical and the reference-based approach are important alternatives to the ones used in this project. There are clear criteria about the appropriate application area for the methodological approaches presented here.

[Clinical potency of nitrous oxide--is MAC the gold standard?]. / Die klinische Potenz von Stickoxidul--Ist MAC der Goldstandard?

Nitrous oxide is delivered during most cases of general anaesthesia. Though it has a history of approx. 150 years there is no univocal understanding about its clinical potency. Research studies during the last 10 years support, however, the view that 1. the potency of nitrous oxide in the clinical settings is only 1/3 of the potency as estimated from the MAC value; 2. the potency of combinations of nitrous oxide and volatile anaesthetics is represented more appropriately by quantities which are derived from the EEG than by the addition of MAC fractions. The findings of the last 10 years do not support the hypothesis, that the addition of nitrous oxide to the breathing gas is more beneficial than waiving the use of nitrous oxide.