Vortragssitzung

Krankenhausmanagement

Talks

Was können Krankenhäuser von der Luftfahrtindustrie lernen?
Malte Raetzell, Crework

Abstract

Die moderne Medizin ist komplex, personelle und materielle Ressourcen sind limitiert, ein hoher Sicherheitsstandard wird erwartet. Zugleich müssen Erwartungen und die Versorgung des Patienten im Mittelpunkt stehen - eine Herausforderung, der das Gesundheitswesen bislang nicht in Gänze zu genügen vermag. Zahlreiche menschl. und techn. Schnittstellen, die in der gegenwärtigen Situation von keinem QM-System in der Medizin umfänglich adressiert, trainiert und überwacht werden, beeinträchtigen Patientensicherheit und ökon. Effizienz zugleich. Die inhaltl. Orientierung an der Luftfahrt - einem der Medizin bzgl. der Bedeutung von Verfahrenssicherheit und Prozesseffizienz ähnl. Arbeitssystem - birgt das Potenzial umfassender Verbesserungen in beiden Dimensionen.

Method

Grundlegend ist zunächst der Abgleich medizinischer Verfahren mit jenen der Luftfahrt zur Identifikation des Transferpotentials. Dies erfolgt durch die Gegenüberstellung idealtypischer Prozeduren und die komparative Analyse von Fallstudien. So wird ersichtlich, dass in der Luftfahrt etablierte Methoden wie Crew Ressource Management oder einheitl. Entscheidungsstrukturen Optimierungspotenziale des Gesundheitswesens bedienen. Die Autoren haben auf dieser Grundlage ein Schulungskonzept entwickelt, welches aus den Elementen Problembewusstsein, Problembewältigung und Nachhaltigkeit durch Training in einem Flugsimulator besteht. Wesentlicher Vorteil ist hierbei das Zusammenwirken der drei Professionen BWL, Pilot und Arzt.

Results

Es ist ersichtlich, dass die Luftfahrt die Notwendigkeit zu max. Verfahrenssicherheit bei zugleich bestmöglicher Wirtschaftlichkeit im Zuge kontinuierlicher Prozessoptimierung über Jahrzehnte zur Entwicklung eines Arbeitssystems nutzte, welches bzgl. Robustheit und Effizienz Maßstäbe setzt. Zugleich erlaubt die strukturelle Ähnlichkeit den Transfer von Best Practices in die Medizin. Dies gelingt durch hybride Fortbildungskonzepte, welche sowohl die Informationsvermittlung durch Seminare als auch das praktische Erfahren (Flugsimulator-Training als didaktisch erfolgversprechender Ansatz) beinhalten. Die Einbettung des Erlernten in das Gesundheitswesen hat das Potenzial, Sicherheit und Effizienz nachhaltig zu verbessern. Ggü. experimenteller “Trial & Error”-Ansätze umfasst die Anlehnung an etablierte Best Practices auch Vorzüge hinsichtlich Zeit/Kosten.

Conclusion

Qualitätsanspruch, Komplexität und der zeitkritische Charakter von Entscheidungen, die essentielle Notwendigkeit der Fehlervermeidung unter wirt. Effizienzdruck stehen beispielhaft für die strukturelle Nähe von Medizin und Luftfahrt. Inhaltl. und didaktisch überzeugend konzipierte Schulungskonzepte sind in der Lage, das resultierende Transferpotenzial zu heben und den Grundstein zur nachhaltigen Implementierung erfolgreicher Verfahren zur Stärkung des Gesundheitswesens zu legen.


Authors
Malte Raetzell, Facharzt für Anästhesie, Notfallmedizin
Daniel Diekmann, Betriebswirt
Gregor Diekmann, Berufspilot Langstrecke
Comparing cost accounting systems at patient-level in healthcare facilities: A systematic literature review and conceptual framework
Caroline Schatz, Ludwig-Maximilians-Universität München, Institute of Health Economics and Health Care Management, Germany - Helmholtz Zentrum München, Institute of Health Economics and Health Care Management, Germany

Abstract

The trend to more efficient healthcare has sparked several cost accounting systems, each promising a specific measurement of costs. One of these systems is traditional cost accounting (TA) where costs are allocated mainly volume based. Newer systems are mostly bottom-up approaches, with the focus on measuring processes and resources used for treating a patient. An adequate cost accounting system is key to effective management and the basis for decisions made by managers and clinicians. Researchers use such cost accounting data in cost analysis and economic evaluations. However, how can we measure these costs at patient-level in healthcare facilities detailed and achievable in practice? And which cost components are the main driver for estimation differences?

Method

A systematic search strategy was developed covering the following databases: Web of Science, Embase, Medline, Academic Search Complete, Business Source Complete and EconLit. The review was conducted based on the PRISMA statement with thematic analysis to investigate quantitative and qualitative data. Only studies with a detailed explanation of the applied cost accounting system are included. All selected articles compare at least two approaches with another and investigate differences. They are categorized into TA and other top-down systems as well as bottom-up systems like activity-based costing (ABC), time-driven-activity-based costing (TDABC), resource consumption accounting (RCA) and other bottom-up approaches. The main target criteria are the investigated cost accounting system, cost components and differences in estimations.

Results

Currently, 15 articles are included in the study. The vast majority of studies reveal variations in the calculated amount of costs, ranging from minor differences up to more than 100%. From 14 studies comparing a kind of bottom-up system with a top-down system, 13 agree that the first one results mainly in lower values than the latter one. The granularity of the investigated cost components varies from distinguishing only indirect- from direct cost to detailed analyses of several material- and personnel costs. There appears to be a consensus, that overhead- and indirect cost are the main driver for estimation differences in cost accounting systems.

Conclusion

Cost accounting systems at patient-level may serve different purposes. Based on the underlying technical calculations, bottom-up systems seem to be more suitable for gaining detailed information about individual and special treatments of patients, but with increased efforts. Further research is needed to develop strategies to overcome challenges of measuring costs for complex treatments detailed and practicable.


Authors
Caroline Schatz, Ludwig-Maximilians-Universität München, Institute of Health Economics and Health Care Management, Germany - Helmholtz Zentrum München, Institute of Health Economics and Health Care Management, Germany
What factors drive differences in quality management systems in hospitals?
Fenja Hoogestraat, Hamburg Center for Health Economics

Abstract

The provision of high-quality patient care is of utmost importance in the competitive hospital market. Against this background, implementing quality management systems has evolved into an important management task for hospitals. The central importance of quality in hospital care is also recognized by legislators through numerous regulations regarding structural and process quality. Despite this high degree of regulation, however, hospitals differ in their quality management systems (QMS). In this study, we aim to advance our understanding on factors explaining these differences in QMS. In doing so, we investigate various organizational and environmental factors explaining the inter-organizational and temporal variations in hospitals’ QMS.

Method

As a research setting, we focus on German acute care hospitals for the years 2014 to 2018. Data on hospitals’ QMS is taken from the structured quality reports. QMS is measured using an additive index comprising 29 quality management practices related to the dimensions of risk management, critical incident reporting systems and hygiene management. A higher QMS index indicates a more comprehensive use of quality management practices. In terms of organizational factors, hospitals’ size, teaching status, ownership, degree of specialization, and hospitals’ medical urgency score were considered. As for the environmental factors, we included hospital competition and hospital location. To investigate organizational and environmental factors explaining the inter-organizational and temporal QMS variations, we estimated fixed effects panel regression models.

Results

Descriptive statistics show that there is a temporal QMS index variation (σ=6.59) and an inter-organizational QMS index variation (σ=6.21). Preliminary regression results indicate that organizational factors such as hospital teaching status (p < 0.001) and size (p < 0.01) are positively associated with hospitals’ QMS, while the hospitals’ medical urgency score (p < 0.01) and hospital specialization (p < 0.001) are negatively associated with hospitals’ QMS. As for the environmental factors, hospital competition is negatively associated with hospitals’ QMS (p < 0.01). Hospital location and ownership are not significantly associated with hospitals’ QMS.

Conclusion

The study results increase our understanding of variations in hospitals’ QMS. Our results inform both hospital managers and policy makers about possible approaches to improve QMS in hospitals. Further, profound knowledge about factors associated with QMS will help to enhance our understanding of anticipating changes in hospitals’ QMS through organizational and environmental oriented interventions.


Authors
Fenja Hoogestraat, Hamburg Center for Health Economics
Eva-Maria Wild, Hamburg Center for Health Economics