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How big data helps lower hospital readmission ratesIn the healthcare industry, mistakes lead to misdiagnoses, improper medical treatment, 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 staggering amounts of data in short periods of time. […]

The post How big data helps lower hospital readmission rates appeared first on Complete Technology Resources, Inc..

How big data helps lower hospital readmission rates

In the healthcare industry, mistakes lead to misdiagnoses, improper medical treatment, 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 staggering amounts of data in short periods of time. It uses advanced analysis algorithms to search for trends in the data that even the most experienced statistician cannot find. Because BI can quickly provide deep insights, businesses across industries have utilized different BI software to gain competitive advantages and streamline their workflows. For instance, healthcare organizations use BI to manage their readmission rates.

What is readmission?

Readmission refers to the instance a healthcare institution admits a patient within 30 days of that patient’s previous hospital stay. Readmissions usually occur because of:

  • Complications arising from the preceding treatment
  • Errors committed by hospital staff (e.g., leaving a sponge in the patient’s body after surgery)
  • Patients not following their doctors’ recommendations
  • Insufficient access to proper medical services and medications in the patient’s community

Why should hospitals want to reduce their readmission rate?

There are three main reasons why hospitals must strive to keep patients from returning for additional treatments:

  1. Readmissions are financially crippling and more medically risky for patients
    Medical care in America is one of the most expensive in the world. While the degree of how much medical expenses affect people’s decisions to file for bankruptcy is up for debate, such expenses are nevertheless a contributing factor. Having to be treated more than once is therefore backbreaking for Americans, especially for those who are living paycheck to paycheck. Not only that, but the likelihood of getting hospital-acquired infection also increases the more one visits and/or the longer one stays in a healthcare facility. This results in a costly downward spiral no one wants to be in.
  2. Medicare and Medicaid won’t pay for complete coverage
    Readmissions also take a toll on Medicare and Medicaid. This is why the Centers for Medicare and Medicaid Services (CMS) impose a payment reduction penalty of up to 3% upon hospitals that exceed certain thresholds for readmission rates. That is, CMS only pays 97% of covered medical costs instead of the entire 100%. The penalty is arguably also a tool to keep hospitals from profiteering.
  3. Having a high readmission rate can reduce a hospital’s reputation
    Once people find out that your hospital has a high readmission rate, they may begin to avoid your institution, thinking it provides poor-quality care.

How can business intelligence help hospitals with readmission rate reduction?

BI can help reduce readmission rates in several ways. For instance, by using patient-centric data points such as income level, English proficiency, housing conditions, and community resources, hospital administrators will have greater insight into the welfare of their patients. This knowledge will enable healthcare professionals to factor in their patients’ circumstances, create special care plans to increase the likelihood that their patients will abide by their medical recommendations, and help them prevent expensive readmissions.

Furthermore, by using BI software to merge socioeconomic data with electronic medical records, medical professionals can easily create individual profiles that will predict how likely a patient is going to require readmission, even before care is provided. Predictive analytics allows doctors to adjust the initial care they provide certain types of patients so that the likelihood of readmitting such patients is dramatically reduced.

In addition to helping you lower readmission rates, BI software can also provide your practice with unprecedented levels of care and efficiency. Call us today to get started with proven IT experts.

Published with permission from TechAdvisory.org. Source.

The post How big data helps lower hospital readmission rates appeared first on Complete Technology Resources, Inc..

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