AI Articles and Analysis in Healthcare

Health insurance fraud may prove especially pressing due to the opioid epidemic, and thus routing out fraud could be of greater importance in the coming years.

There are many Indian startups claiming to develop artificial intelligence software to help the healthcare industry. However, their websites are filled with marketing terms and hype that could lead one to believe a company leverages AI when it does not. In sectors with a booming landscape of startups, we caution readers to take a closer look at each company before considering any of their solutions.

The Patient Protection and Affordable Care Act (ACA) has significantly changed the landscape for how healthcare providers can be reimbursed by insurers. They are now reimbursed based on the guidelines set by Value-based Purchasing (VBP) models. This type of payment model reimburses the healthcare provider based on the quality of their work with the insured patient.

The healthcare industry is perhaps second only to finance when it comes to the sheer amount of historical data available for use with artificial intelligence. Data from EMRs, insurance claims, clinical trials, and drug research and development can all be pulled into a machine learning algorithm to generate insights on patient behavior, patient risk, and effective treatments for a variety of conditions, among a variety of others.

Business leaders in pharma and life sciences have more specific business intelligence needs than peers in other industries. In addition to common business drivers like marketing, profit and loss, and customer churn, pharmaceutical companies need information regarding patients and clinical trial results.

McKinsey estimated that embarking on digital transformation to restructure value chains and drive R&D innovation across the pharmaceutical industry could be worth $50–150 billion of earnings before interest, taxes, depreciation, and amortization. In particular, machine learning is likely to continue finding a place in the pharmaceutical industry. Pharmaceutical companies have found applications for machine learning ranging from drug discovery to clinical trial retention.
The State of AI in the Asian Pharmaceutical Industry
AI seems to be making its way into the pharmaceutical space in Asia over the last two or three years, particularly in China and Japan. For the most part, the companies offering or using AI for drug discovery are just starting to acquire funding and talent. XtalPi seems to have the highest density of talent with a decent likelihood of being able to work with machine learning.

Episode Summary: Recently, we were called upon by the World Bank to do a good deal of research on the potential of applying artificial intelligence to health data in the developing world. Diagnostics was a very big focus of the information that we presented. It appears as though diagnostics is an area of great promise with regards to AI, and that's what we're focusing on in this episode the podcast.

There are few companies claiming to offer artificial intelligence solutions to orthopedics companies. We found that these solutions are intended to help orthopedics companies with at least one of the following business problems: