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Benchmarking, sprich die Vergleichsanalyse von Prozessen mit festgelegtem Bezugswert, findet zunehmend Einzug in die Welt der Gesundheits-IT. Dabei spielen jedoch viele Faktoren zusammen, die einen einfachen Vergleich von IT-Kosten bei Weitem übersteigen. Eine Forschungsgruppe der Hochschule Osnabrück hat mit dem IT-Benchmark Gesundheitswesen ein Analysetool vorgelegt, das auch einen Länder- vergleich ermöglicht.
Für die Versorgungsforschung ist wichtig, dass verteilte und heterogene Daten so integriert werden, dass sie offen für neue Analyse-Anforderungen und leicht um neue Datenquellen erweiterbar sind. Für die Integration von Versorgungsdaten werden bislang hauptsächlich Data-Warehouses eingesetzt, die Daten dimensional oder als Entity-Attribute-Value-Struktur (EAV) modellieren. Diese Datenmodelle sind jedoch entweder unflexibel oder weisen ein zu geringes Maß an Datenorganisation auf, was longitudinale Analysen erschwert. Wir haben den EAV-Ansatz um die Data-Vault-Modellierung ergänzt und damit die Datenstrukturen der Krankenhaus-Qualitätsberichte des Gemeinsamen Bundesausschusses (G-BA) modelliert sowie die Daten der Jahre 2011 bis 2015 integriert. Dies ermöglicht eine Historisierung der Metadaten für Merkmale, insbesondere der Qualitätsindikatoren, sowie ein hohes Maß an Erweiterbarkeit gegenüber neuen heterogenen Datenquellen. Der vorgeschlagene Ansatz erlaubt es, den Abstraktionsgrad für die zu modellierenden Entitäten frei zu wählen, so dass auch ein vollständig generisches EAV-Modell mit historisierten Metadaten erstellt werden kann.
Health IT adoption research is rooted in Rogers' Diffusion of Innovation theory, which is based on longitudinal analyses. However, many studies in this field use cross-sectional designs. The aim of this study therefore was to design and implement a system to (i) consolidate survey data sets originating from different years (ii) integrate additional secondary data and (iii) query and statistically analyse these longitudinal data. Our system design comprises a 5-tier-architecture that embraces tiers for data capture, data representation, logics, presentation and integration. In order to historicize data properly and to separate data storage from data analytics a data vault schema was implemented. This approach allows the flexible integration of heterogeneous data sets and the selection of comparable items. Data analysis is prepared by compiling data in data marts and performed by R and related tools. IT Report Healthcare data from 2011, 2013 and 2017 could be loaded, analysed and combined with secondary longitudinal data.
Frequent users of emergency departments (ED) pose a significant challenge to hospital emergency services. Despite a wealth of studies in this field, it is hardly understood, what medical conditions lead to frequent attendance. We examine (1) what ambulatory care sensitive conditions (ACSC) are linked to frequent use, (2) how frequent users can be clustered into subgroups with respect to their diagnoses, acuity and admittance, and (3) whether frequent use is related to higher acuity or admission rate. We identified several ACSC that highly increase the risk for heavy ED use, extracted four major diagnose subgroups and found no significant effect neither for acuity nor admission rate. Our study indicates that especially patients in need of (nursing) care form subgroups of frequent users, which implies that quality of care services might be crucial for tackling frequent use. Hospitals are advised to regularly analyze their ED data in the EHR to better align resources.
Die Verbreitung von Informationstechnologien (IT) im Gesundheitswesen sowie deren Einflussgrößen sind Betrachtungsobjekt der Adoptions- und Diffusionsforschung. Neues Wissen aus diesen Studien wird dabei häufig als summative Umfrageergebnisse disseminiert. Mit dem in diesem Beitrag vorgestellten Web-Portal werden die individuellen Umfrageergebnisse im Vergleich zu einer Referenzgruppe präsentiert. Das erfolgt in flexibler Form unter Verwendung von reliablen und validen Kennzahlen der IT-Prozessunterstützung, die in einer hierarchischen Struktur angeordnet sind. Es werden die Entwicklung des Web-Portals als Benchmarking Instrument, seine Anwendung und eine initiale Evaluation vorgestellt. Es zeigte sich, dass das Web-Portal anhand aktueller Benchmarking-Ergebnisse von 197 Krankenhäusern einsetzbar ist, seine Anwendung als nützlich und die Indikatoren als verständlich eingeschätzt werden.
Background: Crowding in emergency departments (ED) has a negative impact on quality of care and can be averted by allocating additional resources based on predictive crowding models. However, there is a lack in effective external overall predictors, particularly those representing public activity.
Objectives: This study, therefore, examines public activity measured by regional road traffic flow as an external predictor of ED crowding in an urban hospital.
Methods: Seasonal autoregressive cross-validated models (SARIMA) were compared with respect to their forecasting error on ED crowding data.
Results: It could be shown that inclusion of inflowing road traffic into a SARIMA model effectively improved prediction errors.
Conclusion: The results provide evidence that circadian patterns of medical emergencies are connected to human activity levels in the region and could be captured by public monitoring of traffic flow. In order to corroborate this model, data from further years and additional regions need to be considered. It would also be interesting to study public activity by additional variables.
Although user participation may facilitate the realisation of IT innovations, various literature analyses show only minimal to moderate evidence for such effects possibly due to disregard of mediating factors. Against this background, this study examines the extent to which joint intrapreneurship of clinical leaders and IT leaders as well as a distinct innovation culture mediate the effect of user participation on hospitals’ IT innovativeness. IT innovativeness was measured by the availability and usability of IT functions and by the perceived ‘innovative power’ of a hospital. An empirical model was developed and tested with data from 168 clinical leaders and IT leaders who participated pairwise in a survey representing 84 German hospitals. Three parallel mediation analyses indicated that the participation of users could only lead to IT innovativeness if they were accompanied by intrapreneurial leadership on the part of clinical directors and IT leaders and if a pronounced innovation culture prevailed.
Das Ausmaß der Digitalisierung im Gesundheitswesen bemisst sich daran, wie gut die vorhandene IT Informationslogistik bedienen kann. Der IT-Report Gesundheitswesen ist eine Umfragereihe, die seit 16 Jahren den Digitalisierungsgrad in Krankenhäusern untersucht und eine Familie von Composite Scores bereitstellt, insbesondere den Workflow Composite Score (WCS) zur Messung der klinischen Informationslogistik. Dieser lag mit durchschnittlich 56 von 100 Punkten im Jahr 2017 nur knapp über der Marke von 50 Punkten. Weitere Sub-Scores wie z. B. der für den Aufnahmeprozess lagen mit 44 Punkten sogar darunter. Dieses Ergebnis zeigt, dass es ein großes Potenzial zur Verbesserung gibt, das ausgeschöpft werden muss, soll Digitalisierung ihren Effekt der Vernetzung, Transparenz, Datenanalytik und Wissensgenerierung entfalten.
Use of Emergency Departments by Frail Elderly Patients : Temporal Patterns and Case Complexity
(2019)
Emergency department (ED) care for frail elderly patients is associated with an increased use of resources due to their complex medical needs and frequently difficult psycho-social situation. To better target their needs with specially trained staff, it is vital to determine the times during which these particular patients present to the ED. Recent research was inconclusive regarding this question and the applied methods were limited to coarse time windows. Moreover, there is little research on time variation of frail ED patients’ case complexity. This study examines differences in arrival rates for frail vs. non-frail patients in detail and compares case complexity in frail patients within vs. outside of regular GP working hours. Arrival times and case variables (admission rate, ED length of stay [LOS], triage level and comorbidities) were extracted from the EHR of an ED in an urban German teaching hospital. We employed Poisson time series regression to determine patterns in hourly arrival rates over the week. Frail elderly patients presented more likely to the ED during already high frequented hours, especially at midday and in the afternoon. Case complexity for frail patients was significantly higher compared to non-frail patients, but varied marginally in time only with respect to triage level and ED LOS. The results suggest that frailty-attuned emergency care should be available in EDs during the busiest hours. Based on EHR data, hospitals thus can tailor their staff needs.