These 3 Clinics Cut Patient Wait Times, Improved Patient Flow and Saved Money Using Data

Big data is profoundly impacting the healthcare sector at many levels. With the right predictive analytics software, a clinic can quickly turn abstract figures into insights and direction.

Some healthcare organizations are getting ahead of the curve by building tools or partnering with solutions providers that translate the organizations’ data into improved systems and services. As a result, these organizations are seeing better patient outcomes and better operational efficiencies.

How so? According to Mandi Clossey, a principal with Somerset CPAs and Advisors, data analytics is “shifting away from just an accounting and payroll function to becoming more of a strategic thought partner at the practice, providing real insight to support organizational decisions.”

The bottom line? A better bottom line. Jeff Lagasse, editor at Healthcare Finance, reports that a majority of healthcare executives expect a 15 percent savings over the next five years by implementing predictive analytics.

With the right data analytics software in place, medical clinics can take a step-by-step approach to improving the efficiency of their processes by:


  1. Utilizing past data to highlight inefficiencies in the current system.

  2. Finding the most affordable way to fix these inefficiencies, or using the data to find which change in the existing process will result in the best ROI.

  3. Using predictive analytics to optimize systems for time, cost or patient flow moving forward.

Below are three innovative clinics that have found operational efficiencies through their own data.


Carilion Clinic Anticipates Patient Health Risks

Data analytics can help clinicians make better decisions regarding patient risk and care, which in turn translates into more efficient patient flow.

In 2016, Virginia-based Carilion Clinic implemented an analytics solution that integrated with the clinic’s existing EHR system. That solution featured a proprietary index that tracked and visualized patients’ health over time. It automated the process of pulling vital signs, lab information and nursing assessments to create a composite and visual score of a patient’s condition.

Clinicians at Carilion are able to use that software to make key decisions along a patient’s path within the clinic. More than a few of these decisions had direct impacts on both patient risk and patient flow, including:

  • Determining when to discharge patients.

  • Prioritizing bedside visits and nursing assignments for clinicians.

  • Improving (and sometimes automating) the documentation process.

  • Maximizing capacity management.

In short, data-driven decision-making helped clinicians determine which patients need to go to the ICU and which are ready to go home. The payoff was better patient outcomes and a better bottom line for the clinic.

Erin Wolfe, a local reporter at The Roanoker, writes that Carilion has avoided overpaying in one of the most expensive areas of healthcare, hospital stays, by making a smart investment in data analytics.

CHRISTUS Health Gets ‘360-Degree’ View of Patients to Prioritize Care

Rich Krueger, CEO of Hospital IQ, says that instead of spending money on consultants or trial-and-error experimentation, embracing analytics can translate into better insight for clinics of all sizes. This is just one example of how.

In 2018, the CHRISTUS Trinity Mother Frances Health System (CTMFHS) in Texas received the Acclaim Award from the American Medical Group Association for its “ideal delivery model - one that is safe, effective, patient-centered, timely, efficient and equitable.”

CTMFHS did this by leveraging granular data it had about patients, including socio-economic information. The data “helps us better manage costs and avoid hospitalizations because we can connect with the patient and take that opportunity to educate them," says Andrea Anderson, CHRISTUS’s administrative director of population health and primary care, in the press release.

"That 360° view really has been invaluable in how the navigators educate and inform patients and helped in their approaches when coordinating care for their patients."

CTMFHS is now better able to identify and target its most risky patients, those at higher risk of poor outcomes over the next 12 months. The result has been a 32-percent reduction in ER visits.


AP-HP in Paris Predicts Patient Flows With Amazing Precision

At an advanced level, predictive analytics can be used to prepare a clinic’s staff for an inflow of patients. Bernard Marr at Forbes reports on four Paris hospitals that use data analytics to predict patient admissions down to the hour.

The Assistance Publique-Hôpitaux de Paris (AP-HP) group has taken internal and external data sources (such as a decade of hospital admissions records) to predict the number of patients coming through the door. The team at Springwise reports that AP-HP cast a wide net in its data analysis. This included everything from flu-infection patterns to weather forecasts to public holidays. The goal was to “better manage high demand of health resources.”

The result is an interface that allows administrators and clinicians alike to forecast admissions up to 15 days in advance. “Extra staff can be drafted in when high numbers of visitors are expected, leading to reduced waiting times for patients and better quality of care,” Marr says.

The AP-HP example highlights how data analytics can also improve patient satisfaction and care along the way of improving functionality and efficiency. As Dr. Benson S. Hsu and Emily Griese write at Harvard Business Review, data clearly “represents a rich resource with the potential to improve care.”

For example, software development company Diceus reports that hospitals (like the AP-HP network) use data analytics to predict patient flow month to month, with some using machine learning to make these admissions trend predictions automatic.

Being prepared for changes in patient flow translates into a more efficient use of clinic resources. Further, it improves patient care and patient satisfaction because it cuts down on wait times and ensures staff are able to give the attention each patient requires.

The Importance of Data Analytics in Practice

These clinics didn’t build these systems from scratch. Instead, they partnered with software providers who specialize in analytics. These are knowledgeable partners who understand how to work within legacy systems and datasets. “If an organization doesn’t have in-house analytics resources or the money to build a team, a contract with a data analytics company could help,” Gienna Shaw writes at Health Data Management.

When it comes to rolling out an analytics capability, the key is to start small. Simply auditing your current processes and systems can get you well on your way to realizing the benefits of data analytics in cutting patient wait times, improving patient flow and saving your clinic money.


Images by: rawpixel, Martha Dominguez de Gouveia

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