How big data helps lower hospital readmission rates

How big data helps lower hospital readmission rates

Mistakes sometimes happen in the medical world, leading to missed diagnoses, improper self-medication, and, inevitably, hospital readmissions. But business intelligence (BI) is changing that by equipping healthcare professionals with powerful real-time information.

At its core, BI software is all about data analytics. BI software is capable of accepting overwhelming amounts of data in short periods of time. It also uses advanced analysis algorithms to search for trends in the data that even the most experienced statistician cannot find. Because it can provide deep insights on such tight schedules, businesses across industries have utilized different BI software to gain competitive advantages and streamline their workflows. For instance, businesses in the healthcare industry use BI to manage their readmission rates.

Readmission refers to when a patient returns for more care within 30 days of their original hospital stay. Cases like these usually stem from conditions immediately following the initial visit, such as mismanagement of the original condition, improper self-medication, and not enough access to proper medical services and medications in their community.

BI can help reduce readmission rates in several ways. For instance, by using patient fields such as income level, English proficiency, housing conditions, and community resources instead of finance-specific variables like previous number of purchases, order size, and order frequency, hospital administrators will have greater insight into the welfare of their patients. This knowledge will enable them to provide extra care to people who need it most and help them prevent expensive readmissions.

Furthermore, by combining socioeconomic data with electronic medical records (EMR) in a BI software environment, medical professionals can easily create individual profiles that will predict how likely a patient is going to require readmission, even before care is provided. For practices looking for methods to reduce readmissions by 3% or greater, predictive analytics allow doctors to ensure that certain types of patients can totally avoid readmissions with proper initial care.

Effective implementation of these solutions can definitely save hospitals a lot of money. In fact, one particular practice was able to save $72 million on medical services after reducing the incidence of readmissions by 6,000 patients annually while avoiding $4 million in Medicare penalties and boosting its reputation by leaps and bounds.

Big data isn’t only for big businesses. BI software can provide your practice with unprecedented levels of care and efficiency. Whether you want to lower readmission rates or ensure EMR compliance, we have the knowledge and experience to get it done for you. Call us today to partner with a proven IT expert.

Published with permission from TechAdvisory.org. Source.


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