Optimizing Clinical Outcomes: Hospitals' Secret to Enhanced Care and Cost Savings

A blog by Job Kamphuis, Managing Director International Markets

November 16, 2023

A perfect storm

The healthcare industry faces significant challenges, including the increasing demand for specialized care due to an aging population, a shortage of healthcare staff straining resources, and continuous pressure to control costs without compromising quality. These complex issues call for innovative solutions, such as integrating technology, expanding medical education, investing in research, and designing sustainable policies. Healthcare facilities worldwide are seeking ways to become more efficient and smarter. However, their digital transformation is not an easy endeavor. It is a journey that spans many years and impacts all aspects of the organization.

The foundation for Smart Hospitals

The integration of systems plays a pivotal role in transforming a hospital into a smarter and more efficient healthcare facility – a smart hospital of the future. Traditional hospitals often have many isolated systems with little or no data sharing between them. Connecting various digital systems, such as electronic health records (EHRs), medical devices, patient monitoring platforms, and administrative databases, allows these systems to work together and optimize workflow support. In particular, when medical devices are integrated, and the aggregated data is used to complement the more static EHR data, a hospital can achieve a unified and comprehensive view of patient data. Typically, this is accomplished within a central monitoring station.

Improving efficiency and safety by centrally monitoring data

A central station empowers healthcare providers to monitor multiple patients from a single location, offering a comprehensive real-time view of patients' vital signs and clinical data. Continuous monitoring through a central station supports patient safety by enabling timely interventions and reducing the risk of adverse events. It ensures that healthcare providers have immediate access to vital patient information, facilitating informed decision-making and safer patient care.

Central monitoring stations provide numerous advantages, including:

  • Reducing Alarm Fatigue: Alarms are prioritized and directed to the appropriate staff, reducing unnecessary distractions, and enabling staff to respond promptly to critical alerts.
  • Standardization of Care: Centralized monitoring promotes consistency in patient care, as all patients are monitored using the same system and protocols. This standardization supports patients with receiving high-quality and consistent care, regardless of the care unit they are in.
  • Data Analysis and Trend Monitoring: A central care station collects and stores patient data, allowing for retrospective analysis and trend monitoring. This data can be valuable for quality improvement initiatives, research, and identifying areas for process optimization.
  • Support for Telemedicine: In recent times, telemedicine has gained popularity, enabling medical experts to provide care remotely. A central monitoring station can integrate with telemedicine platforms, facilitating virtual consultations and enabling experts to monitor patients from a distance.
  • Continuous Patient Monitoring: Central monitoring stations allow healthcare providers to continuously monitor multiple patients' vital signs, including heart rate, blood pressure, oxygen saturation and respiratory rate. This constant surveillance helps promptly detect any changes or abnormalities, enabling timely interventions and reducing the risk of medical complications.

So, central monitoring stations lead to more streamlined and optimized workflows, improving efficiency and safety. Continuous patient monitoring serves as a compelling example of the positive impact of central monitoring stations.

Clinical Surveillance: Turning Data into Action
When data is aggregated, it can be continuously analyzed to detect patient complications in the early stages. Some examples of these complications include: 

  • Septic Shock
  • Respiratory Distress
  • Acute Decompensated Heart Failure (ADHF)
  • Acute Kidney Injury (AKI)
  • Sudden Bleeding
  • Neurological Changes
  • Diabetic Emergencies
  • Dehydration or Fluid Overload
  • Electrolyte Imbalances
  • Venous Thromboembolism

For each of the above there is a significant potential for cost savings. For instance, the Healthcare Financial Management Association (HFMA) estimates that the average full marginal loss for a U.S. hospital's treatment of sepsis amounts to as much as $34 million annually, making it one of the most challenging cost-containment issues (1). Sepsis can be challenging to diagnose, and a patient's condition can deteriorate suddenly. Therefore, continuous monitoring and having near real-time data available are key to identifying patients developing sepsis.

A study by Luo J, Yu H, Hu YH, Liu D, Wang YW, Wang MY, Liang BM, and Liang ZA (3) delves into the identification of patients at risk for acute respiratory distress syndrome (ARDS) among severe pneumonia cases. This research, published in the Journal of Thoracic Disease in October 2017, employed a retrospective cohort study design. By analyzing a significant number of cases, the researchers aimed to establish early signs or risk factors that could indicate the development of ARDS in patients with severe pneumonia. The article proposes one method that relies solely on ventilator parameters and lab results to identify respiratory distress, without requiring user interaction. Another method discussed is the Lung Injury Score (LIS), which necessitates one human input and three ventilator parameters.

Another example is found in an article by Lopes JA and Jorge S, published in the Clinical Kidney Journal in February 2013 (4). This article offers a critical and comprehensive evaluation of the RIFLE (Risk, Injury, Failure, Loss, and End-stage kidney disease) and AKIN (Acute Kidney Injury Network) classifications for acute kidney injury (AKI). The review discusses how RIFLE and AKIN can be employed to classify the level of kidney failure and identify patients at risk of transitioning from one threshold to another using automated calculations.

The implementation of automatic alarming and the notification of staff regarding the deterioration of a patient's condition can yield substantial cost savings and, more importantly, make the difference between life and death. Algorithms for detecting complications will continue to evolve, underscoring the importance of having an open platform as the foundation for a central monitoring system. An open platform enables hospitals to develop their own algorithms or utilize third-party algorithms without the constraints of vendor lock-in.

How to Ensure Actions Are Taken?

To ensure that the analyzed data translates into actionable steps on the work floor, it is essential to establish effective interoperable communication systems between a central monitoring station and clinical staff. The key is to deliver the pertinent data to the appropriate individuals at the precise moment, irrespective of their location or communication device. This ensures efficient care coordination and collaboration among healthcare professionals. This holistic approach, encompassing the collection, analysis, and timely communication of data to the right person, is what makes the difference between data having a meaningful impact and remaining underutilized.

Pioneering hospitals in healthcare digitization face integration challenges, hindering interoperability vital for goals like clinical surveillance. Ascom, a digitalization leader, offers guidance and solutions for institutions to achieve effective digital transformation.
Chandana Samaranayake, Head of Clinical Solutions and Consulting, Ascom

Taking the Next Step

In the examples above, data is aggregated from various systems to support clinical outcomes and enhance cost cutting. Once aggregated, this data can serve diverse strategic objectives, including diminishing medical errors, curbing aggression towards staff, controlling infections, enhancing patients’ experience, staff productivity and patient flow. In the future, liberating data from isolated systems and consolidating it into a unified data lake will empower hospitals to attain their strategic goals more rapidly, optimizing their workflows in ways that were once deemed impossible.

The digital transformation of hospitals is undeniably challenging, involving complex integration of various technologies, processes, and systems. There is no one-size-fits-all solution or silver bullet that can instantly make a hospital smart and efficient. Instead, it is a journey that necessitates collaboration and partnership rather than solely relying on vendors.

Ascom recognizes this critical aspect and has emerged as a reliable digital transformation partner for numerous hospitals worldwide.By tailoring solutions to meet specific needs, Ascom assists hospitals in optimizing their workflows, streamlining communication and enhancing patient care. Through this collaborative approach, Ascom empowers healthcare institutions to navigate the intricacies of digital transformation and unlock the full potential of innovative technologies within their unique healthcare environments.

If you would like to find out more about Ascom solutions and references, please visit www.ascom.com.

About the author

Job Kamphuis is a seasoned expert with a background in Electrical Engineering, holding a master's degree in the field. With over a decade of experience, he has dedicated the first part of his career to workflow automation within high-security environments, particularly in airports and ports. For the past eight years, Job has shifted his focus to the healthcare industry, specializing in workflow optimization. Currently serving as the Managing Director for International Markets at Ascom, Job is passionate about driving innovation and efficiency in patient care and communication solutions worldwide.

(1)    Sepsis poses a cost-containment challenge in the face of the COVID-19 pandemic (hfma.org)
(2)    Septic shock - Misra D, Avula V, Wolk DM, Farag HA, Li J, Mehta YB, Sandhu R, Karunakaran B, Kethireddy S, Zand R, Abedi V. Early Detection of Septic Shock Onset Using Interpretable Machine Learners. J Clin Med. 2021 Jan 15;10(2):301. doi: 10.3390/jcm10020301. PMID: 33467539; PMCID: PMC7830968.
(3)    Respiratory distress - Luo J, Yu H, Hu YH, Liu D, Wang YW, Wang MY, Liang BM, Liang ZA. Early identification of patients at risk for acute respiratory distress syndrome among severe pneumonia: a retrospective cohort study. J Thorac Dis. 2017 Oct;9(10):3979-3995. doi: 10.21037/jtd.2017.09.20. PMID: 29268409; PMCID: PMC5723858.
(4)    Acute kidney injury - Lopes JA, Jorge S. The RIFLE and AKIN classifications for acute kidney injury: a critical and comprehensive review. Clin Kidney J. 2013 Feb;6(1):8-14. doi: 10.1093/ckj/sfs160. Epub 2012 Jan 1. PMID: 27818745; PMCID: PMC5094385.

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