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Hospital data analytics in clinical applications

Analytics tools can leverage the power of data in clinical applications to increase efficiency and drive health outcomes in hospitals. Data analytics provides valuable insights for adjusting processes and improving clinical results.

Data-Analytics

Utilizing Analytics to reduce the overwhelming amount of alarms at the point-of-care

"Alarm Fatigue", the decreasing perception of alarms due to their enormous number, is one of the biggest threats in the hospital for patient safety. Research has shown that on average, up to 350 alarms a day can occur at an intensive care bed. Of these alarms, up to 95% are clinically irrelevant and the remaining clinical alarms are only noticed properly by a rate of 50%.1 Missing alarms of medical devices is listed in the Top 10 Health Technology Hazards of 2019.

The stress for patients and caregivers is negatively affecting therapy outcomes, important clinical work-flows are unnecessarily interrupted, and an alarm desensitization of the nursing staff can be observed. 

Data can create transparency by providing an analysis of all the alarms that have occurred in a hospital. On this basis, systematic process flows, alarm settings and personnel planning can be optimized to increase the alarm management efficiency and ultimately reduce the stress for clinical staff and patients.

Identify measures to reduce alarms in Acute Care!

The Alarm History Analytics dashboard provides insights on alarms that have occurred in an acute care environment from supported Infinity patient monitors. Analyse alarms in the unit to optimize systematic process flows and staff planning. Increase alarm management efficiency and aim to enable reduction of alarms.

  • Optimization of the departmental staff allocation for managing alarms
  • Review the impact of measures on reduction of alarm fatigue
  • Ensuring SOP compliance with regards to the alarm reaction times


Alarm History Analytics: Enabling to reduce alarms at the Point-of-Care

How Alarm History Analytics can support your workflows

Watch the video to discover why Alarm History Analytics is an important tool to optimize your hospital alarm management.  

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Alarm History Analytics Dashboard in Dräger Connect

Click on the link below to view the Alarm History Analytics dashboard in full screen size. Discover which widgets are available to analyze the alarms from Infinity patient monitors in your department.

View dashboard

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​Alarm History Analytics

The Alarm History Analytics application provides insights on alarms from medical devices that have occurred in an acute care environment. The application enables both the analysis of alarms in a care unit to optimize systematic process flows and staff planning as well as improving alarm management efficiency. By identifying the sources of recurring alarms, the application can help to take measures to reduce these alarms and show the results over a period of time.

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Infinity® Gateway Suite

Get the most out of your clinical information systems by integrating data from Dräger monitoring and therapy devices with lab results, entries in electronic medical records and clinical information systems across hospital departments.

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Infinity® Acute Care System

Transform your clinical workflow with Infinity® Acute Care System. Its multiparameter monitor integrates with its networked medical-grade workstation, giving you real-time vital signs, access to clinical hospital systems and data management applications for a comprehensive range of patient information and powerful analysis tools at the point-of-care.

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Infinity® M300+

The Infinity® M300+ provides continuous surveillance of telemetry patients using the hospital’s WiFi network. Receive visible and audible alarms to alert you to changes in your patient’s condition while supporting patient mobility.

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Case Study Avera Heart Hospital, USA

With a data-driven approach, Dräger helped the Avera Heart Hospital to reduce alarm rates by more than 30% while continuing to keep patients safe.

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About the physical, economical and ecological effects of volatile anaesthetics

Anaesthetic gases are required to support improving surgery outcomes in the operating room. However, the quantity of these gases that is being used should be kept at a low level. Low- and minimal-flow techniques offer an effective yet easy way to humidify respiratory gas and reduce the amount of anaesthetic gases used.3,4,5,6 Due to the limited inflow of cold and dry gas, low-flow applications are suitable for maintaining the optimal breathing gas temperature.3 Protective ventilation strategies like low- and minimal-flow techniques allow the reduction in incidence of post-operative pulmonary complications (PPC).7,8 In addition, anaesthetic gases have a considerable impact on the costs of an intervention. Simultaneously, a negative impact on the environment can be observed. Halogenated chlorofluorocarbons and fluorinated hydrocarbons are harmful to the earth’s ozone layer and may contribute to global warming.9

Utilizing Analytics to optimize the consumption of anaesthetic gases

The Gas Consumption Analytics dashboard allows to derive clinical and economical insights from the agent consumption of supported Dräger anaesthesia devices. Create transparency on consumption uptake, efficiency, cost and applied fresh gas flows as a foundation to reduce costs while simultaneously improving patient outcomes. This provides a foundation to implement patient protecting low- and minimal-flow practices.

Gas Consumption Analytics: Providing insights into anaesthetic agent usage

Gas Consumption Analytics: Providing insights into anaesthetic agent usage

Watch the video to discover why Gas Consumption Analytics is an important tool to improve efficiency and drive health outcomes in your operating rooms.

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Gas Consumption Analytics Dashboard in Dräger Connect

Click on the link below to view the Gas Consumption Analytics dashboard in full screen size. Discover which widgets are available to analyze the use of volatile anaesthetic gases in your department.

View dashboard

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Gas Consumption Analytics

Reduce the consumption of volatile anaesthetics with Gas Consumption Analytics. The application helps you to derive clinical and economical insights from the agent consumption of your anaesthesia devices and creates transparency on consumption uptake, efficiency, cost and applied fresh gas flows.

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Dräger Perseus® A500

Outstanding ventilator technology meets the latest approaches to ergonomics and system integration in one innovative anaesthesia machine, developed together with experts from all over the world to streamline your anaesthesia workflow.

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Dräger Atlan® A300/A300 XL

Imagine the flexibility to have one anaesthesia device platform with high-class safety in every OR. The comprehensive set of clinical features and proven ventilation quality make Atlan the ideal anaesthesia workstation for all patients and surgical procedures.

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Dräger Atlan® A350/A350 XL

Imagine the flexibility to have one anaesthesia device platform with high-class safety in every OR. The comprehensive set of clinical features and proven ventilation quality make Atlan the ideal anaesthesia workstation for all patients and surgical procedures.

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Sustainable Development in the OR

With an analytic approach, the Paris Saint-Joseph Hospital Group was able to minimize the consumption of Halogens, reducing their impact on the environment.

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Data security and privacy

Over 75% of clinicians expect that securely transmitted health information and data can improve the quality of care that is being delivered.10

Our Data Analytics solutions are designed with security and data privacy in mind. Find more detailed information on the security concept in the following infographic. 

Security and Data Privacy Concept

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Types of Data Analytics applications

“Data Analytics is the aggregation, analysis, and use of clinical, financial, operational, and nontraditional data captured inside and out of the healthcare setting to directly inform decision-making.”11

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Descriptive Analytics is the examination of data or content, usually manually performed, to answer the question "What happened?", characterized by traditional business intelligence (BI) and visualizations such as pie charts, bar charts, line graphs, tables or generated narrative.

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Diagnostic Analytics is a form of advanced analytics to answer the question "Why did it happen?", and is characterized by techniques such as drill-down, data discovery, data mining and correlations.

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Predictive Analytics is a form of advanced analytics to answer the question "What is likely to happen?", and is characterized by techniques such as regression analysis, forecasting, multivariate statistics, pattern matching, predictive modeling, and forecasting.

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Prescriptive Analytics is a form of advanced analytics to answer the question "What should be done?", and is characterized by techniques such as graph analysis, simulation, complex event processing, neural networks, recommendation engines, heuristics, and machine learning.

Get in touch with Dräger

Contact Us Hospital

Draeger Australia Pty. Ltd.

8 Acacia Place
Notting Hill
Victoria 3168

1800 372 437

Draeger New Zealand Ltd.

Unit 4
24 Bishop Dunn Place
East Tamaki
Auckland 2013

0800 372 437

References

1. Jones, K. (2014). Alarm fatigue a top patient safety hazard. Canadian Medical Association Journal, 186(3), 178

2. ECRI Institute (2018). 2019 Top 10 Health Technology Hazards: Executive Brief

3. Canet et al. (2010). Prediction of postoperative pulmonary complications in a population-based surgical cohort. Anesthesiology, 113(6), 1338-1350

4. Branson et al. (1999). Humidification for Patients with Artificial Airways. Respiratory Care, 44(6), 630-642

5. Bilgi et al. (2011). Comparison of the effects of low-flow and high-flow inhalational anaesthesia with nitrous oxide and desflurane on mucociliary activity and pulmonary function tests. Eur. J. Anesthesiol., 28(4), 279-283.

6. Branson et al. (1998). Anaesthesia circuits, humidity output, and mucociliary structure and function. Anesthesia Intensive Care, 26(2), 178-183.

7. Kilgour et al. (2004). Mucociliary function deteriorates in the clinical range of inspired air temperature and humidity. Intensive Care Med., 30(7), 1491-1494

8. Hönemann C. & Mierke B. (2015). Low-Flow, Minimal-Flow und Metabolic-Flow Anaesthesia. Lübeck: Drägerwerk AG & Co. KGaA.

9. Yasny, J. S., & White, J. (2012). Environmental implications of anesthetic gases. Anesthesia progress, 59(4), 154–158.

10. Bain & Company (2018). Front line of healthcare report 2018.

11. HiMSS (2019). HiMSS20 Conference Education Topics.