Business intelligence (BI) refers to the process of gathering data and turning it into useful insights. This data can be used to make better decisions about all aspects of a business, including operations, marketing, and sales. And in today's world, big data is crucial in enhancing processes in major industries like healthcare.
BI software, which is primarily all about data analytics, is capable of accepting massive amounts of data in short periods of time. It uses advanced analysis algorithms to search for trends in the data that may be difficult for even the most skilled statistician to find. As 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.
Readmission: What it is and why it occurs
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 previous treatment
- Errors committed by hospital staff (e.g., leaving a sponge in the patient’s body following a surgery)
- Patients not following their physicians’ recommendations
- Insufficient or a lack of access to proper medical services and medications in the patient’s community
Reasons hospitals want to lower their readmission rate
There are three main reasons why hospitals must strive to keep patients from returning for additional treatments:
- Medicare and Medicaid won’t pay for full coverage. Readmissions also affect 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%. Imposing a penalty is arguably a way to prevent hospitals from profiteering.
- Readmissions are financially crippling and more medically risky for patients. America has one of the most expensive healthcare systems worldwide. 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 backbreaking for many Americans, especially for those who are living paycheck to paycheck. Also, frequent visits to and/or longer stays in a healthcare facility increases the likelihood of getting hospital-acquired infection. This results in a costly downward spiral no one wants to be in.
- Having a high readmission rate can diminish a hospital’s reputation. People tend to avoid hospitals that are known to have a high readmission rate because they may think that it provides low-quality care.
How business intelligence helps hospitals reduce readmission rates
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, healthcare 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, dramatically reducing the likelihood of readmitting such patients.
Besides helping lower readmission rates, BI software can also provide your practice with unprecedented levels of care and efficiency. Consult our IT experts to learn how your healthcare facility can leverage BI — call us today.
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