How Has AI Revolutionized The Healthcare Industry During COVID?

The COVID-19 public health crisis has brought transformational change to the healthcare sector as the challenges of combating a pandemic have forced providers, payers, and administrators to embrace new technologies and new methods of meeting the needs of patients. Artificial intelligence was already making inroads in the healthcare sector, although at a slower pace than in other industries. The challenges of the COVID-19 crisis forced organizations to adapt quickly to continue serving their members and patients, and AI was a big part of that.

How has AI revolutionized the healthcare industry during this public health crisis? Let’s take a look.

Healthcare Leaders See Intensified AI Adoption During Pandemic 

56% of leaders in the healthcare sector state that the COVID-19 crisis has accelerated the adoption of AI. 88% of pharmaceutical and life sciences executives and 78% of health services executives believe AI will be seen as a mainstream technology in the sector within the next year. And 93% of leaders believe AI will create more opportunities than challenges in the healthcare field. 

The primary goals of AI implementation vary across subfields; health plans and healthcare providers expect AI to be most useful in increasing efficiency and productivity, while pharmaceutical providers look to AI to create innovative products and services and grow revenue. 

Risks and Challenges of AI

Healthcare leaders do see challenges and risks concurrent with the more widespread adoption of AI. Cybersecurity and privacy threats are both concerning to healthcare leaders, and they worry about whether consumer distrust of AI technologies could affect their standing in the marketplace. Governance and effectively measuring ROI are both noted as being key to successful AI adoption and deployment. 

5 Ways Healthcare Industry Will Leverage AI In The Post-Pandemic World

1: Automated Processes and Efficiencies

With restrictions on face-to-face contact during COVID-19, technologies like remote patient monitoring (RPM) came into their own by necessity, but shows great promise even in the post-pandemic world. This technology produces better clinical outcomes and lower costs for healthcare providers. Monitoring patients from afar can improve access to care for rural patients and reduce demand on hospital capacity. AI technologies such as machine learning allow for RPM initiatives to autonomously monitor patients and notify healthcare staff when human intervention is needed. 

2: Risk Management and Intervention

Machine learning is also key to predicting and managing risks and suggesting needed interventions. For example, syndromic surveillance technology uses machine learning to scan a health system’s electronic health record (EHR) for key symptoms (such as those of infectious disease) and use that data to predict which patients may have the disease and how to deploy resources to help those in need. In the future, AI will likely allow this kind of capability to be deployed to social determinants of health as well. 

3: Payment Integrity 

With healthcare costs rising and margins shrinking, healthcare payers are under more pressure than ever before to reduce fraud, waste, and abuse costs. However, it’s estimated that 80% of healthcare claims contain overbilling and the sheer quantity of documentation is a challenge for payment integrity analysts to sort through. Artificial intelligence has the capability to sift and process vast quantities of data, helping payment integrity analysts and medical billing and coding specialists to focus their efforts on the claims most likely to contain F,W&A charges.

4: Diagnosis and Pattern Recognition

Natural language processing is an AI technology that allows computers to understand, interpret, and manipulate human language. This allows AI technology to access unstructured EHR data, such as clinician notes and reports, and mine that data for insights and analytics. This can not only lead to improved patient outcomes, but improved data in clinical trials and scientific studies.

5: Personal Health Management

Wearable healthcare technology such as fitness trackers and smartwatches collect enormous amounts of personal health data such as blood glucose, blood pressure, ECGs, and movement and activity. AI is crucial to converting this data into clinically useful information, empowering both patients and clinicians to understand daily habits and provide personalized care. 

Alaffia Health: Leveraging AI To Reduce Overpayments

Alaffia Health is one healthcare AI company that has leveraged artificial intelligence for extraordinary results. Our platform uses AI to identify high-cost, error-filled claims for further review by expert analysts. We find the overpayments and negotiate the correct amount with healthcare providers, helping healthcare payers control their costs and margins. 

Best of all for our partners, Alaffia’s turnkey solution generates results quickly and with no upfront cost. For healthcare leaders who want to see immediate results in AI investments, Alaffia Health is a proven leader in healthcare AI. Learn more now!