Articles
Real-world Improvements with Artificial intelligence and Machine Learning
by Shaswata Ghosh DM ExecutiveThe widespread adoption of data science has ensured the healthcare industry is towards progressive ends. COVID-19 driven data and analytics demands have further motivated organizations to advance their artificial intelligence (AI) and machine learning (ML) capabilities. Data science has a journey that previously lacked an actionable framework from implementation and adoption.
But hospital revenue cycle management helps organizations leverage AI and ML to support their strategic goals. As a result, data science has a significant impact on leadership decision-making, information security, revenue, operational outcomes, patient experience, and more.
Improving AI and ML for healthcare outcomes
Healthcare firms increasingly adopt advanced data science capabilities, i.e., AI and ML. Here are some easy to improve outcomes across the continuum of care.
Augment healthcare leadership
A significant number of healthcare organizations have implemented AI and ML tools at the point of care. However, few organizations have successfully applied them to high-level decision-making. With AI capabilities, it helps expand to augmented intelligence. Therefore, it's more about becoming instrumental in enhancing decision-making skills.
With augmented intelligence, healthcare debt recovery experts can help identify urgent issues, make future-oriented decisions and navigate some of healthcare's complex problems, such as solving healthcare inequality.
Overcoming data security challenges
In today's time, healthcare organizations face more security threats. For example, some security experts claim that medical records can be sold ten times what their credit card goes for. Unfortunately, this is a common practice amongst hackers.
When you can combine AI with human judgment, it's an effective way to strategize healthcare data security. Both resources power a highly accurate privacy analytics model that allows organizations to review access points to patient data and detect when a system's EHR is potentially exposed to a privacy violation, attack, or breach.
With specific techniques with supervised and unsupervised ML and transparent AI methods, health systems can advance toward a predictive, analytics-based, collaborative privacy analytics infrastructure that safeguards patient privacy.
Uncompensated care
A health system improves collecting unpaid balances from patients for healthcare services. Uncompensated care costs large health systems billions of dollars annually, making outstanding balances one of their highest costs. A payment that helps target unpaid accounts by using AI to leverage external and internal financial and socioeconomic data and identify the likelihood that patients in a population will pay their balances.
Financial teams can focus their efforts on the patients most likely to pay and connect patients with AI-powered insight. As a result, hospital revenue cycle management helps avoid bad debt. Moreover, your organization now receives compensation for the care they've delivered.
Enhanced patient flow
Many health systems struggle to effectively manage hospital flow- the movement of patients through the hospital from entry to discharge. ML-powered tools and predictive models help organizations improve patient flow for departments throughout the system.
Now, organizations can reduce patient wait times and staff overtime, improve patient outcomes, clinician satisfaction, avoiding common challenges, including surgery delays or cancellations, clinician overload and burnout, emergency department overcrowding, etc.
AI and ML are new normal decision making
Healthcare firms rely on advanced data science to understand better diseases, health conditions, patient populations, operational and financial challenges, and more. As a result, AI and ML will continue to play essential roles in new everyday decision-making.
Conclusion
The recent pandemic has provided a significant opportunity to prove its value. Healthcare firms can now leverage data to drive critical decisions from short-term emergency response to long-term recovery planning. Get assistance from the experts and make the process smooth. Remember, things are pretty competitive, and you need to take the right approach.
Sponsor Ads
About Shaswata Ghosh 
DM Executive
14 connections, 0 recommendations, 56 honor points.Joined APSense since, March 3rd, 2021, From New Delhi, India.
Created on Apr 6th 2022 08:42. Viewed 230 times.
Comments
No comment, be the first to comment.
