Emergency Medical Services Analytics to Improve ED Throughput

Emergency Medical Services Analytics and its tools for injury case analysis are indispensable to large health systems. They operate hundreds of licensed beds in their many acute care hospitals. These health systems also provide around-the-clock emergency care to thousands of patients annually in specialized trauma centers. They report saving tens of thousands of dollars per year by reducing the length of stay (LOS) for target population groups in the emergency departments (EDs). What makes their strategy so successful?

Health systems strive to attain the best outcomes via evidence-based practice, while ensuring quality care for every patient. To guarantee that the patient's outcome is great, they have to comprehend each patient's condition and identify critical improvement areas, such as trauma team arrival time.

It’s not enough to have access to a trauma registry database, because the data available may be retrospective. They need real-time analytics on meaningful data regarding the trauma patient's info.

Here data analytics software from healthtech providers, such as Emergency Medical Services Analytics for getting more patients through the emergency room, could be useful. Belitsoft brings a full set of medical solution development services for healthcare SaaS startups that provide their clients with advanced analytics tools: from MVP and PoC development to continuous support and consulting.

What Challenges May Be on the Way to Improving ED Throughput?

Health systems that serve high-density areas see a lot of people in their emergency departments. When there are insufficient staff and resources, ED throughput issues can arise. Patients have to wait in line for long periods, and become frustrated. Some may even leave without being seen (LWBS). For those who do get seen, physicians may inadvertently spend less time than industry standards because of the influx of patients.

Seriously injured patients who don't receive timely trauma team care may become ill and die more often than the patients who get urgent treatment.

The same trauma in young and old patients has different results, different rates of decompensation, and is not in favor of the older patient. If medical personnel don’t accurately assess the severity of their injury and don’t assign activations to them per the level of injury sustained, such patients don’t receive a full trauma team and resources on time. Their condition can rapidly deteriorate without early aggressive treatment, and it negatively influences a certain population's outcomes.

Historically, physicians have collected patient and injury data from electronic medical records, reviewing them manually or through an IT report request. This is a reactive approach with retrospective data, as it takes several weeks to review the data and write a report. It’s hard for physicians to drive change in real time or make a difference in real time while patients are still in the hospital.

To get better results for patients who need activations based on the level of injury sustained and to reduce their length of stay (LOS) in the ED, healthcare systems try to be proactive, not reactive, and demand an approach driven by analytics.

Emergency Medical Services Analytics with a range of apps for data visualization helps stakeholders see better how they are doing and keep improving the way things work.

What Are the Features of Emergency Medical Services Analytics Software to Decrease Patients' LOS in ED?

With analytics software and improved access to detailed, reliable data stores, healthcare companies are able to improve the efficiency of EDs. Emergency Medical Services Analytics and its tools for injury care analysis help:

Identify the time when most patients arrive in an ED.
Alert staff about the hospital's workload level and handle their activities by the prioritization functionality in the application.
Evaluating the response time by age groups and trauma type, the arrival time to elderly patients and the alert activation processes for a certain severity level injury.
Analyze the trend in patient numbers and their ED utilization patterns for the periods of interest.
Compare activations for trauma cases based on a certain level of seriousness to determine the age group of patients most susceptible to this particular injury; e.g., a hip fracture is a geriatric injury, typical for older people.
Access to standard protocols to order diagnostic imaging and lab tests even if there is no available bed in the ED for the patient.
Examine key performance indicators that affect the capacity of emergency departments (patient transportation time, LOS metrics, hospital occupancy rates, time needed to clean a room, etc.)
Pinpoint opportunities for ensuring timely treatment of elderly patients.

What Are the Organizational Actions to Get the Benefits from the Analytics?

Analytical apps cannot, on their own, deliver immediate performance improvements even as they are advanced and finely tuned. The responsible team must change its processes and expected response time to elderly patients with trauma to improve the timeliness of care.

It should evaluate and improve its alert activation processes for certain severity-level injuries. To do this, the team reaffirms the expected response time and working processes with the trauma team.

The team should change the workflow of the emergency department. Usually, care begins when a medical staff admit a patient to the hospital. It’s better if the patient receives care as soon as they arrive in the emergency department. With data from the analytics app, the responsible team should track trauma level activations and the time the trauma teams visit the patient. Then it could give performance feedback to them.

If the trauma team does not meet the expected time to arrive, the responsible team must find out why, eliminate obstacles, and ensure that the trauma team arrives on time.

What Benefits Do Practices Get from Emergency Medical Services Analytics Tools?

The analytics approach enables practices to reduce the average LOS in the ED for patients with injuries of a certain severity level. Healthcare companies report that after about a year of using the tools, they got tens of thousands of dollars in cost avoidance by reducing ED LOS. Other sustainable outcomes are the following:

A roughly one-third relative decrease in the time it takes for the trauma team to arrive for patients of all ages — from infants to the elderly.
A roughly five times relative decrease in ED length of stay for kids, teens, and middle-aged patients, and a major drop for older patients.
Notably decreased level of readmissions.

How Do the Custom Medical Software Development Firms Support?

Data analytics companies in the USA can work together with healthcare software development organizations like Belitsoft which bring deep experience to build and customize data analytics platforms and apps. These platforms help users track key metrics, allow them to pinpoint gaps, and improve workflow coordination.

Integrated analytics platforms and data operating systems collect, keep, process and analyze big datasets from lab systems, electronic medical records, billing systems, clinic management systems and other sources. These solutions help in:

Automating the workflows, i.e., cleansing, standardizing, and normalizing.
Customizing scalable data stores.
Carrying out analytical software to design monitoring panels, reports and visualizations of data.
Keeping robust data security and compliance with HIPAA and other regulations.
Integrating ML and AI into analytics.

Healthcare software development organizations create robust solutions like Emergency Medical Services Analytics and a range of tools for:

Accessing real-time data and data not captured earlier (type of injury, arrival place, time the trauma team arrives, result measures by trauma type, patient level details, and so on).
Filtering for selecting data of interest (e.g., time of day, period).
Monitoring performance metrics that are related to LOS, laboratory tests, care unit utilization and so on.
Showing facility performance indicators — arrival trends, LWBS rates, and so on.
Visualizing the number of patients and throughput reports in graphs with LWBS rates, hospital door-bed periods, ED discharge-leave periods, and other parameters.
Unifying thorough reports for managing clinical practice.
Showing visually how the arrival time impacts patient results (for example ED length of stay).
Visualizing the statuses of hospital occupancy via dashboards with color indicators.

Companies that are searching for top-notch assistance in building HL7 interfaces, hybrid or on-premises environments, data analytics, data platforms, data infrastructure, in workflow engineering, and in cloud development (Google Cloud, AWS, Azure) can turn to Belitsoft.