Sustainable Outcomes
Proven Results

Key Features Use Cases

Get More Out of Your Data and Empower Your People

Predicts the unpredictable

analyticsMD pulls in massive amounts of data from many systems, such as EMRs, and external data sources, like weather. The system constantly monitors that data and knows what’s happening in real-time. It uses machine learning and artificial intelligence to predict potential problems ahead of time, like a surge in the emergency department.

Prescribes the best solutions

We know you’re too busy to stand around and stare at dashboards so we’ll automatically let you know when you need to take an action. Even better, we’ll use your data to recommend the best way to solve the problem at hand.

Persuades teams to act

analyticsMD closes the gap between intelligence and action. Using built-in communication channels, we send recommendations directly to the right team members. Teams work together in a virtual, interdisciplinary huddle - course correcting in the moment. So, patients get a better experience and so do your providers.

How it Works: Surge in the ER

Debbie, the ED's charge nurse, was constantly looking at data to figure out whether they were going to run out of capacity.

With analyticsMD, that monitoring is done for her. The system knows it’s a week before Thanksgiving, it’s cold outside and Dr. Smith just came on board; he’s slower and orders more labs. Capacity will run out in the next two hours. Debbie's relevant ancillaries get a nudge in the form of a text: Congestion Likely. Prioritize Discharges. This allows them to refocus resources and coordinate a response. Not only does analyticsMD allow Debbie to solve problems immediately, it also helps create a powerful culture of teamwork and empowerment.

We Deploy Anywhere

Emergency Room

Anticipate patient surges and handle them more efficiently. Many Emergency Departments operate reactively: overflow beds are opened once patients are already waiting outside, staff is called in once the existing team is already overloaded, and clinicians scramble to discharge patients when beds are full. analyticsMD anticipates these scenarios and delivers recommendations to nurses, charge nurses, physicians and admitting units so they can get ahead of the issues.

Operating Room

OR teams struggle to improve utilization, reduce case delays, shorten turnarounds, and cut down on unnecessary overtime. Often, these issues arise because cases run long, white space appears suddenly on the schedule, and staff are reacting to the day as it unfolds. analyticsMD predicts these events and recommend which turnarounds to prioritize, when to have more or less staff, and how to improve block utilization.

In-patient Wards

On the floors, unit managers contend with last minute admissions from the ED and unanticipated surgical admissions. analyticsMD helps unit managers forecast how their census will change throughout the week and then recommends changes to staffing and bed allocation to meet that demand. This means less last-minute struggling to meet ratios, less agency and overtime spend, and smoother patient flow.

Patient Experience

Patient experience is more important than ever and metrics are reported publicly. Rather than reacting to complaints or HCAHPS scores months after the fact, wouldn’t it be better to know where and when to intervene in a patient’s visit? analyticsMD uses data to detect which patients are most likely to be dissatisfied with their encounters. We notify unit managers and patient experience teams in real time so that they can visit the patient and recover the experience.

And More

These are just a few examples of how analyticsMD can help improve hospital operations. Contact us to learn how we can help you in your facility.

Customer Stories

Natividad Medical Center

Natividad Medical Center is a 172-bed acute care hospital located in Salinas. Safety net hospitals like Natividad make up only 15 of California’s more than 450 hospitals and health care systems yet provide 50% of all hospital care for California’s 6.6 million uninsured. Natividad had recently seen rising patient volumes. Improvements in patient flow and throughput were needed to meet increased demand. Natividad began a strategic initiative in its ED to improve patient flow and productivity with strong engagement from its frontline providers and nurses. With analyticsMD, Natividad saw a 42% decrease in LWBS rate, a 20% reduction in door to doc time and a 30 minute (8%) reduction in a patient’s total length of stay. These improvements will provide an estimated 850 additional visits yearly, and a projected $425,000 in additional revenue.

Mercy Hospital Fort Smith

Mercy Hospital Fort Smith, a 336-bed acute care hospital, engaged analyticsMD to improve emergency department flow. The ED receives around 50,000 visits per year and analyticsMD helped to achieve a 30 percent decrease in "left without being seen" rate. The hospital also saw a 24 minute reduction in length of stay and a 20 percent reduction in door-to-door time. The ED was able to accommodate 3,000 additional visits per year after the workflow update and is projected to report $1.3 million in additional annual revenue and savings through the increased capacity and reduced length of stay. Additionally their patient satisfaction scores increased substantially, allowing them to move from 29th among the Mercy systems thirty-one Emergency Departments to top three in the system. As a result of this success, we have expanded efforts to more broadly support the Mercy network.

El Camino Hospital

El Camino Hospital engaged analyticsMD to help enhance their performance improvement efforts in areas such as patient safety and patient experience. With the help of analyticsMD’s Patient Falls Prevention platform, the clinical teams at El Camino Hospital introduced a new proactive method for fall prevention. El Camino Hospital’s Performance Improvement teams worked with analyticsMD to evaluate data inputs from multiple sources (for example, call button and bed movement data) in real time, and then could apply advanced algorithms to predict exactly which patients were at risk for an imminent fall. Care teams were alerted of at-risk patients in real-time through wireless communication devices such as Vocera, and could then take immediate action prior to the potential injury or fall. The result: since the inception of the entire fall prevention program in December of last year, El Camino Hospital experienced a 39% reduction in falls within a six month period.

Learn more about analyticsMD

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