Public healthcare is being discussed today, more than ever. And while the quality of public healthcare is heavily dependent on the complex, geography-specific, system-driven processes, and the motivation and urge of the public health caregivers, the expectations from tech are high. As technology has successfully transformed various walks of human life, it is anticipated that it is a change-maker in the field of healthcare as well.

And it is! Technology has driven healthcare transformation across the globe. But it is often expensive, inaccessible, and complex to apply to a large public health care system. And hence, there’s no doubt about the importance of modern technologies such as Artificial intelligence in healthcare.

According to a report by Healthcare IT News, 63% of the research subjects suggest that Artificial Intelligence and Machine learning (AI/ML) are already providing excellent value in specialty care departments like radiology, generic pharmacy, and pathology.

Further reading: Some Mind-blowing Stats About AI and IoT in Healthcare

Along with private healthcare, AI is now rapidly replacing conventional public health care systems to make improved healthcare accessible to all.

In this article, let us discuss how AI can be monumental in transforming public health.

Accessing patient data across various health centers

One of the biggest hurdles in providing patient care via public health care systems, especially in countries and communities where the population is dense or displaced, is furnishing appropriate medical history and health records. The conventional public health care systems are burdened with maintaining large paperwork manually, and this is where AI-powered data management and storage can come to the rescue.

The data storage challenges of public hospitals and healthcare centers can be effectively mitigated by AI-powered cloud computing that can make the availability of patient data seamless across multiple healthcare centers and hospitals.

Improving diagnostics and screening

The AI market for healthcare applications is predicted to grow from 663.8 million in the year 2014 to 6,662 million in the year 2021. One of the key drivers of healthcare transformation by Artificial Intelligence is improved diagnostics. AI-powered tools help health caregivers to study patterns in patients and provide accurate diagnostics faster. AI tools are now used to identify patterns that can easily be missed by human eyes as well as traditional systems. AI-powered screening tests are helping caregivers offer quick diagnosis, helping the patients to access treatment rapidly.

AI-based tools that do not rely on traditional methods, for instance, can help in the diagnosis of cancer where biopsy is not possible or can give false-negatives, such as prostate. Further, AI is said to outperform human diagnostics and is said to replace doctors in the future. What this means today is that the use of AI can help in reducing the costs of diagnostics, a key plus point for public healthcare systems.

Risk prediction and intervention

Along with improved diagnostics and screening, how AI can significantly bring about a change is by helping risk prediction. The same AI-driven pattern for screening is used to identify potential risks and susceptibility to diseases and illnesses. Many patients across the globe do not have access to multiple screenings. The public healthcare systems, on the other hand, do not have bandwidth and resources for repeated screenings. This is where AI can help since it eliminates the need for actual experts for screenings with futuristic tools that also have a proven accuracy rate better than humans.

Identifying risks for large groups of people, especially during epidemics, can further help to successfully intervene in the situation and break the chain of disease contraction.

Further reading: How Artificial Intelligence is Transforming Healthcare

Tracking health worker productivity

In a public healthcare system that operates in geographies with dense populations and unmonitored operations, tracking the health worker productivity and accuracy is often ignored. But AI can help in the same by actively correlating the patient data collected on the field and cross-verifying whether or not appropriate healthcare efforts are channelized towards the same.

AI-powered apps can help public healthcare systems have better visibility in the day-to-day operations of remote healthcare workers and subsequently improve the quality of care.

Suggested reading: 10 Most Common Use Cases of AI in Healthcare

Increasing client adherence and access to treatment

One of the biggest challenges in driving successful public healthcare campaigns is patient participation and awareness. In the areas where medical care and importance of health are ignored, especially in the overlooked population clusters such as women, people below the poverty line or infants, ensuring that patients regularly attend healthcare checkups and diligently continue treatments is tough. Artificial Intelligence can help improve the same by predictive analysis.

AI-powered tools can help in detecting gaps by behavioral analysis, history of treatment to identify populations that might drop out of treatments for various reasons. This can further help the healthcare givers in extending additional counseling through awareness camps to ensure patients turn up for treatment/ health programs as expected.

Also read: How Technology can Drive Population Health Management

What does this mean for public healthcare…

From drug discovery to diagnostics, chronic disease management to healthcare worker productivity, Artificial Intelligence is set to revolutionize the public healthcare system.

With a bunch of medical imaging equipment as well as patient-facing apps, it is paving the way for improved healthcare at large. And hence, for public healthcare systems, embracing AI is now more of a ‘when’ rather than a ‘why.