Big and Buzzworthy: How Data Analytics Is Driving Improvements in Healthcare

Many healthcare organizations find themselves at the intersection of data rich and information poor. With an overabundance of data readily available, health systems have struggled with how to harness that data and unleash actionable insights.

Advancements in technology and the leap into the digital age have catapulted big data into hyper drive, and it seems everyone is giving it a spin. Data analytics have been widely used in other industries for decades, but has only recently picked up speed among healthcare organizations.

With continuous changes in the industry, hospitals and health systems have felt the pressure to find efficient and cost-effective methods for delivering high-quality care — or risk falling behind. This is where big data can add value. That is, if you know how to use it.

The first step is to understand what the term “big data” actually means. Traditionally, big data referred to the massive amounts of complex data that couldn’t be processed by traditional software. More recently, it has been used to refer to predictive analytics or other advanced analytics methods that extract value from data. The keyword here is extract.

Because big data is so immense, it takes specific technology and analytics methods to make sense of the information and transform it into something valuable. Left alone, big data is simply an immense amount of numbers and code. It is only when it is able to be analyzed that it becomes relevant and useful.

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Used successfully in various industries such as retail and manufacturing for over a decade, predictive analytics is building a growing fan base in healthcare. One method called time series analysis can be used to analyze past data and look for trends and patterns and make a forecast of events that recur over time. Time series techniques are particularly relevant to forecasting patient census in a hospital.

Able to predict supply needs and patient re-admissions, predictive analytics’ impact on patient care is far-reaching. One area in which advanced analytics can add tremendous value is in the scheduling of care staff. Predictive analytics can help improve staffing problems by accurately forecasting workforce needs weeks in advance of a shift. This ensures the right type of provider is in the right place at the right time to provide patient care.

But data isn’t perfect, and algorithms are not magic. Predictive analytics is a tool to be used in combination with extensive knowledge of staffing strategies. Data experts are needed to routinely monitor the predictive model, and functional leaders within the healthcare organization help make sure the model is being applied as intended.

To help ensure an organization is set on a path to success, information should be made readily available to the analytics team. This means enabling access to data streams, which ideally include a few years of patient census data and other workload indicators, depending on the area or service line involved. The more years of data provided the more accurate the predictions will be from the start.

While big data has become buzz-worthy in the healthcare industry, it is solidifying its presence by offering valuable insights to organizations that know how to leverage it. Provider organizations that have leveraged predictive analytics for scheduling and staffing have achieved outcomes that include increased staff satisfaction scores, improved nurse retention, reductions in their annual labor spending, and decreased the amount of time managers spend on schedule creation and staffing tasks — delivering valuable time back to managers to focus on staff development and patient care.

With continued pressure on provider organizations to improve the patient experience while driving down costs, predictive analytics offers a strategic solution to leverage data to help organizations meet demand.

 

Jackie Larson

Jackie Larson
Jackie Larson is president of Avantas, a provider of workforce management technology, services, and strategies for the healthcare industry.

Jackie Larson

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