Siemens Healthineers- Optimizing Operations In Laboratories
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Siemens Healthineers- Optimizing Operations In Laboratories

Julia Abrams, Senior Director Global Solutions Marketing
Julia Abrams, Senior Director Global Solutions Marketing

Julia Abrams, Senior Director Global Solutions Marketing

Evolution of Workflow with Regard to Current Technological Trends

The workflow landscape has evolved immensely over the years, particularly in the last decade. The major part of this involves recent healthcare trends like consolidation of hospitals through mergers and the formation of hospital systems. This is considered as one of the most profound organizational changes in the recent past and is trending particularly in the United States and Western Europe regions. Another trend is the moving towards larger networks of hospitals, which is certainly driven by the chief requirement to grow and flourish, apart from cutting down on costs. Additionally, investing in scientific breakthroughs definitely has a massive influence on the way workflow is being improved in our laboratory. Yet another trend observed is the budding need to make healthcare more accountable through value-based healthcare; the requirement to prove that lab services effectively adds value to patient outcomes.

How Advances in Workflow Have Helped Solve Complexities

Taking into consideration the space of clinical diagnostics laboratories, there is a dire need to run workforces more efficiently by rendering higher throughput of lab tests and specimen samples. This is because as the number and types of tests increase, a menu of tests a lab would need to run; but at the same time, the throughput of specimen needs to be maximized. The specimen in this scenario can be blood, urine, etc. The main goal is attaining all of this at lower investments. But how would one accomplish that, considering that the biggest cost driver at clinical diagnostics laboratories is human capital? This is where automation comes into picture to reduce costs, which has had a huge impact on improving workflow efficiency and reducing human errors through process improvements to ultimately deliver more precise results. Reducing the human factor not only equates to lower investments but also to precise results, as it essentially limits the possibility of human error. Automation also is the suitable answer for laboratories that are understaffed and must keep up with the rising demand in workflow.

How Technology aids the Working Environment

Siemens Healthineers pioneered the development of laboratory automation almost 20 years ago, and its impact has been groundbreaking ever since. Automation is no stranger to our customers who have enlisted the help of our consulting services to guide them through the implementation process. As a result, many of our customers are currently on their second or third generation. Automation technology has become much faster and efficient, especially after its integration with IT — which is otherwise known as the brain of automation. Examples include intelligent routing of samples and sample management. Automation optimizes laboratory operations and improves the overall efficiency of workflow. For instance, sample handling; wherein quality checks are incorporated to test analytics and optimize the turnaround time. A fact worth noting is that this incorporation also impacts the comprehensive patient experience, such as determining more rapidly the diagnosis and appropriate treatment of a condition.

Common Issues that Organizations Face

Some of the more obvious challenges from the past include driving down costs and focusing on value-based healthcare. Turnaround time, which in clinical diagnostics means the time between taking specimen samples from patients to returning lab results to the allocated physician, is an increasing area of interest. Speed and efficiency are both factors to be considered in any laboratory as results dictate next steps in patient care. Reducing turnaround time is of particular significance when considering samples from emergency rooms; for example samples specific to cardiac regions as they are most time-sensitive. Sample handling is a tedious task to begin with. Most emergency room samples used to be treated individually by front-loading them onto specific analyzers. Our new solution will ensure that intelligent sample management, i.e. automated prioritization of emergency samples is incorporated along every step of the way, into the very depths of our workflow.

  Automation is the suitable answer for laboratories that are understaffed and must keep up with the rising demand in workflow  

Your Advice to Fellow CIOs/CXOs

The integration of automation into an organization must be seen as an opportunity to re-engineer and optimize your processes. One thing CIOs/CXOs must focus on is ensuring that key stakeholders are involved during decision-making procedures, which in our work culture is handled by the workflow consultants. This can be challenging for organizations that have the silo mentality, but can be combated with the right administration. Even though people are usually resistant to change, these workflow enhancements can benefit the organization and even the patients tremendously.

Digitalization Changes the Face of Workflow

The changes digitalization brought about with its inclusion are massive. Considering a single apparatus in the lab that goes from manual to automated and digitalized processes will suffice to prove this. This means free time for the employees, which can then be redirected towards critical samples or useful research. Apart from the major physical change evidenced towards the complete redesign of workflow, there is a technological change experienced as well. Luckily, at Siemens Healthineers, our consultants do a great job at guiding our customers through the process of change management.

Future Trends

As the IT industry continues to intertwine with healthcare, future trends would lean towards making workflows more intelligent. Siemens Healthineers is currently benefitting from this trend; the emergency sample handling solution as mentioned earlier, is mostly driven by intelligent IT. Additional trends would include making data available for larger ecosystems and lacing them with artificial intelligence to open more possibilities of innovation.

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