The healthcare sector has changed in high magnitude. The abundant healthcare data generated today, especially from Electronic Health Records (EHRs), pharmaceutical research, genomic sequencing, medical imaging, etc. have aided to improve healthcare. However, even while there is so much recorded Big Data, the healthcare industry doesn’t use it to the maximum. On an average, there are more than 1.2 billion clinical documents generated every year. But, there’s a deficiency in utilizing it to improve care.
Apixio is here to enhance the use of Big Data in healthcare by providing data insights for a healthier world. With its machine learning technology, Apixio creates a better decision-making scenario for improved quality in healthcare. Also, the company imbibes Artificial Intelligence on its platform to transform disparate data into actionable knowledge.
“Our technology analyzes unstructured and structured datasets to model patient care,” says Darren Schulte, the CEO of Apixio. “We help providers and payers better perform critical activities such as risk adjustment and quality reporting to achieve optimal outcomes.” For an improved speed and scale, the Apixio data processing pipeline operates in a parallel computing environment. “We can process hundreds of millions of clinical notes in just hours!” he adds.
“Data Insights for a Healthier World”
Unless you have the right tools at hand, accessing healthcare data is quite difficult. The AI platform from Apixio is your go-to tool. “Our AI platform uses a secure and straightforward extraction process to pull and encrypt documents, images, billing claims, and other data types from our customer source systems,” says Darren. For further analysis and processing, the data is then sent to the Data Loader and then to Apixio’s cloud-based platform.
Next, the data is sorted out using a proprietary data specification on the Apixio platform. “We execute hundreds of separate data validation checks against imported datasets to ensure that we have the minimum elements required for customer projects,” he notes. Next, the Apixio Data Coordinator shuttles files, based upon their properties to different processing routines. For instance, medical images undergo processing with the optical character reader (OCR) pipeline.
Once through, the files are tracked all the way from data import to insight generation on the Customer Data Inventory system. The imported data is then saved in the Apixio Patient Object Model (APOM). The APOM is like a phenotype, where each APOM has information about a person’s healthcare, diseases, procedures undergone, biometric, etc. Using ensembles, predictive models, and classifiers, the APOMs can be analyzed. When a person needs to make a decision, all of these events are put together to support his/her decision.
Healthcare data put to good use!
It all comes to machine learning with an integration of AI. “Our platform extracts a variety of signals from our data using various machine learning techniques,” Darren explains. “We combine signals using ensembles to create insights, which are then bundled into configurable application workflows to support user decision making.”
Moreover, the feedback gathered from the users are further again stored in the APOMs, wherein the future it is used to re-train and improve the algorithms and enhance machine learning. “User annotation and data labeling (via automated and manual methods) are used to continuously update our models,” marks the CEO.
For this purpose, supervised and unsupervised techniques are deployed for further training models. “There are mechanisms built into our proprietary science infrastructure to deal with noisy annotations and labeling errors,” he says. This is especially done to configure the workflow applications to bring down errors and enhance accuracy. Apixio believes that this is very essential for developing and maintaining high performing algorithms, and they promise to uphold it in the future as well.
Meet the Pioneer
Darren Schulte, CEO
Darren has more than fourteen years of industry experience in healthcare analytics and technology. Darren served as the Chief Medical Officer and President of Apixio prior to being appointed CEO in 2014. Before joining Apixio, Darren served in executive leadership roles at Alere Health, Anvita Health, and Resolution Health. Darren co-developed twenty-five clinical measures endorsed by the National Quality Forum to measure ambulatory care quality using electronic data. He is a nationally recognized speaker on the topics of healthcare analytics and quality improvement.
Darren received his B.S. degree from U.C. Berkeley, his M.P.P. degree from Harvard, his M.D. from Stanford, and trained in Internal Medicine at University of California, San Francisco. Darren serves as a Board of Trustee at the Chinese American International School in San Francisco. He is the co-author of two US patents.
“Our AI platform converts unstructured patient information into actionable data, so you can get a complete picture of healthcare.”
“Our solutions support better decisions to deliver quality and affordable care.”
“We execute hundreds of separate data validation checks against imported datasets to ensure that we have the minimum elements required for customer projects.”
“We specially configure our workflow applications to reduce errors and improve the accuracy of expert annotation, which is essential for crafting and maintaining high performing algorithms.”