Healthcare institutions are expected to have efficiency and organization in all of their workflows to guarantee consistent patient satisfaction and more importantly, maintain the trust of the patient. For patients with health insurance, if their health information is incorrect or missing, it can potentially lead to more spent being spent on claim rejection and the sending and receiving of documents and less time on actually providing medical care and treatments. This can result in loss of revenue and productivity for the medical institution as well as a decreased patient satisfaction level.
How a Healthcare Company Uses Data
Some healthcare institutions are currently offering advanced data analytics to their medical professionals to allow them to know the condition of their patients better using wearable medical and fitness devices. As their client base continues to expand, they require additional support in processing and analyzing the data collected by these devices.
Due to the highly specialized tasks performed by healthcare professionals, they need proper data mining tools in order to get relevant information from these devices to start treatment that would suit the patient’s lifestyle and health condition. This has led to a more personalized and customizable form of treatment that has significantly raised patient satisfaction levels/
Let’s look at 3 key ways in which data analytics is improving healthcare:
Improve Efficiency and Accuracy
A good sign that healthcare institutions need data analytics is when they start experiencing a slowdown in their healthcare processes. Additionally, they tend to be quite cost-effective when compared to hiring an in-house staff that would require training, a salary and various other benefits.
Most analytics software tends to have an annual subscription and improve workflows by providing increased accuracy in examining patient history as well as analyzing staff efficiency. Such types of software automate reports and are capable of detecting fraudulent invoices that can potentially lead to legal issues and as a result, more unwanted expenses.
Reduce Human Error
If a medical institution is regularly encountering claims processing errors as a result of human oversight, then they need to use data analytics to help them organize all their information pathways and ensure that the information within them is correct. It is estimated that around 80% of medical bills tend to have errors and might lead to more rejections as well as lowering the overall level of patient satisfaction.
Such oversights and human errors are preventable. Data analytics can be leveraged for denial mapping review and categorization, allowing healthcare institutions to effectively analyze patient data, provide the correct information and decrease or (in some workflows) eliminate error that can potentially lead to disastrous effects for both, the patient and the healthcare institution
Provide Better Patient Care
The ultimate goal of any medical institution is to provide patient care and satisfaction. When the processes within a healthcare institution are improved using data analytics software, it reduces human error and waits times for the patients while simplifying appointments, the processing of insurance claims and the issuing of medical bills. The accurate transmission of patient information and history also leads to more personalized treatment programs for patients which further leads to reduced readmissions as a result of medical errors or misdiagnosis.