Technology has allowed for new and innovative ways to capture a more conclusive look at member health data. Data can be powerful when handled properly; however, many healthcare organizations — and most other businesses for that matter — don’t know how to effectively take advantage of all the information this new data can provide. The full power of patient data is unlocked when you learn to optimize the data and maximize your efficiency using a data analytics platform and Natural Language Processing (NLP).
A large amount of patient data is found within unstructured text in clinical charts, and accessing that data can be challenging. New patient data technologies are able to mine the structured and unstructured chart data, then analyze it to identify documentation gaps or miscoded data. The features ensure that coding is accurate and no charts have to be repeated.
Data mining allows organizations to keep up with all incoming data and organize it into concise charts. Analytics platforms transform complex data into actionable intelligence so that organizations can improve efficiency and accuracy while reducing costs. A wealth of data awaits you.
Generate Real-Time Reports
Data analytics platforms can create reports with real-time details with little need to wait to gain insights into coding. The technology has the power to analyze data immediately across a wide range of customized data sets and provide you with critical information. The database, which is continuously updated with the latest medical codes, provides coders and stakeholders with the most up-to-date reference information.
The right technology can identify coding errors at the point of care to promote more accurate coding in real-time. These real-time reports can easily be adopted by healthcare organizations moving toward value-based initiatives.
The real-time reports give you on-demand visibility into the medical coders. These insights into coder performance make it possible to manage the financial impact from risk adjustment and increase compliance confidence by increased quality outcompes with fine tuned accuracy of code capture. The technology can collect information, such as:
- Start and end-times for coding charts
- Chart types that take more than the typical time allotted
- Number of charts coded per hour by coder
- Which cases coders are processing
Create Provider Education Initiatives
Medical coders spend a lot of time identifying documentation gaps and errors so they can fill in missing information. When you have ownership of the technology, you are able to access the raw data and look out for the original gaps in documentation. You can then identify patterns in missed and inaccurately coded conditions by providers.
With that relevant data, you can find ways to educate providers about the missing or erroneous codes. Education will hopefully prevent future mistakes, ultimately improving coding accuracy and reduce the time coders spend completing a chart. By educating providers, the technology can impact patient care for the better.
Real-time reports can also identify patterns and trends in miscoding from the coders. If multiple coders are struggling with a specific type of code, the technology can track patterns. Data can then be used to create educational materials for the coders and improve accuracy and efficiency.
Collaborate Between Payers & Providers
In order for value-based initiatives to work, providers and payers need to have the ability to exchange patient data in real-time. Patient data analytics platforms allow data and technology to be synchronized across the provider/payer ecosystem. The two-way movement of data allows for perfect collaboration between both parties.
Shift From Retrospective to Prospective Risk Adjustment
Retrospective risk adjustment is the expected mode of operation for healthcare organizations, but that does not mean that it is the most effective strategy. Risk adjustment takes place months after the patient visits a doctor, which means that vendors have to chase down charts and go through several rounds of chart reviews. This process is time-intensive and prone to human error.
Data analytics platforms allow organizations to take a prospective approach to risk adjustment. Providers and payers have access to important data in the moment. Their documentation and coding practices, therefore, have much higher accuracy rates. A prospective risk adjustment system reduces the need for back-and-forth collecting and checking of patient data.
Intelligent patient data technologies can help organizations detect fraud, waste, and abuse. The platform can reference the database to find patterns of fraud schemes or unusual practices. Discover outstanding anomalies or outliers to avoid deceit or inappropriate utilization of services. A trusted technology works as a partner to identify the fraudulent use of risk adjustment data.
The additional insights that healthcare organizations can extract from patient data make data analytics platforms extremely useful because you can optimize your data usage for the greatest strategic value while conserving resources.
Talix offers a full suite of data analytics tools for healthcare organizations of all sizes. Elevate your efficiency and generate further value today by partnering with Talix.