By: Natalie Cheng
July 6th 2021
Data is king and an integral part of the next generation of technology. With data, organizations are more informed and can make better decisions. However, just having data isn’t going to solve all your problems. How do you proceed if the data you have is incomplete, fragmented, or unactionable? Organizations must shift their thinking to value where value is over volume, investigate integrating systems, utilize machine learning and AI technologies, and ultimately get to better data.
Shifting to Value
According to Modern Healthcare, “Within five years, value-based care could be the norm for most patient populations. Value-based care organizations recognize that a significant key to success is getting the treatment plans right the first time for the right individuals.”
Instead of focusing on the number of patients in a hospital, value-based care shifts healthcare from volume to value. Value-based care provides incentives for improvements in quality, lower costs, and higher patient satisfaction. In terms of healthcare data, having a lot of information isn’t going to be helpful especially if it is irrelevant. Organizations must be able to get contextually and situationally relevant information to provide value. Instead of having to sift through a deluge of data, having the right information when you need it will provide value to your hospital and to the patient.
In addition, healthcare providers need insight into both individuals and larger groups of patients in order to deliver value-based care. Population health management addresses this with a tailored, cost-effective approach based on patients’ risk levels. According to the University of Illinois Chicago, population health management helps health care providers:
- Manage higher patient volumes due to increased access to care, leading to less out-of-network services.
- Care for population that has higher number of chronic diseases that must be treated.
- Increase market share now that patients have more options in choosing where to receive care.
To achieve value-based care, physicians need more comprehensive patient data including social determinants of health. Having to find information by switching from system to system eats up valuable time and frustrates many clinicians. Looking for interoperable solutions will alleviate problems of systems not talking to each other and having to look for data in multiple systems. “When healthcare systems become truly interoperable, they provide a multi-layered understanding of patients which enables clinicians to care for the whole person” (Modern Healthcare).
Using Machine Learning and AI
As mentioned earlier, having a lot of data doesn’t necessarily mean it’s valuable. Big data can become valuable by using machine learning and AI technologies. According to Nature.com, “ML and AI only now make it possible to unravel the patterns, associations, correlations and causations in complex, unstructured, nonnormalized, and unscaled datasets that the Big Data era brings. This allows it to provide actionable analysis on datasets as varied as sequences of images or narratives using Natural Language Processing and bringing all these datasets together to generate prediction models, such as response of a patient to a treatment regimen.” For organizations looking to tackle big data, machine learning and AI technologies can help.
Getting to Better Data
Getting to better more valuable data is possible with the right tools and practices in place. Is your organization focused on getting more comprehensive patient data in order to improve care? If you’re looking for interoperable solutions, we can help. Contact us for more information.