Driving Advanced Analytics in Healthcare

 

Advanced Analytics

Advanced analytics in healthcare is the process of carrying out a broad category inquiry that can be used to help drive changes and improvements in business practices. Predictive analysis, data mining, big data analytics and location intelligence are all analytical categories that fall under advanced analytics. This is one of the important reasons why driving advanced analytics is important. These technologies are widely used and hugely important in the healthcare industry as well as other industries. Normal traditional analytical tools are comprised of basic business intelligence but advanced analytics focuses in forecasting future events and behaviors and this enables healthcare organizations to conduct possible scenarios and A/B testing which enables the predictions of potential changes in business strategies. As quoted below

“Because of the growing complexity and demands of the healthcare environment (e.g., clinical care, operations, regulatory environment, declining reimbursement, and the need to control costs), every healthcare organization needs access to good data. With the implementation of our EDW, we now have a truly integrated, single source of truth to support the best practices, care process models, and population health management that healthcare will only require even more in the future.”

– Jill Hoggard Green, Ph.D., RN Chief Operating Officer

Advanced AnalyticsThe operating room provides a good opportunity for quality improvement using advanced analytics. Operating rooms are the biggest sources of revenue for healthcare organizations. In most hospitals, the efficient use of operating rooms (ORs) played a big role in the entire organization’s financial sustainability. Thus, improving surgery through that improved access to data-driven insight into baseline measurement and opportunities for clinical and operational improvements could affect real change for the organization. Having an automated daily surgical workflow will be a good place to start. Numerous other processes in the health system have been automated over the years but the surgical flow has not been one of them. The health system and healthcare organizations rely on manual data preparation processes from multiple disparate systems. These systems have in inefficient timing perspective and carry the risk of potential data quality issues. The process of pulling data from different systems and generating operational reports for Mission’s system of ORs consumes nearly half of a full-time employee’s time.

Despite all of this dedicated time and effort, many data gap continue to exist. It’s difficult, if not impossible, to make quality, financial, and operational improvement decisions—especially with limited ability to quickly make changes to queries, such as drilling down into the data.

New Tools

An emerging best practice among leading hospitals is making use of an Advanced Analyticsoperating room dashboard, a data-rich tool that helps clinicians and administrators make the right call on allocating valuable resources.

It also helps identify areas for efficiency improvements—and, not surprisingly, one of the most profitable areas to start improving is with first case on-time starts. As most who have worked in the OR know, when the first surgical case of the day is delayed, the rest of the day is typically impacted by a series of late starts, as well. Among the chief reasons for the first (and subsequent) delays is a lack of timely and comprehensive data about each of the surgeries scheduled. An automated workflow dashboard could improve visibility to this information in and out of Mission’s operating rooms.

Of course, technology alone would not fully drive improvement to meet quality goals. In the typical hospital environment, many different employees and departments have a stake in the OR’s limited resources, and to embrace the use of an analytical OR dashboard, all must be committed to data-driven decision-making. For that to happen, Mission needed to drive a paradigm shift throughout the organization to embrace an evidence-based culture. The health system would need to educate and encourage people, at all levels, on the use and value of data automation and actionable information to make better care and operational decisions.