Advanced technologies are changing the way we live. It’s clear today that AI has played a big role in increasing the impact of these technologies in every aspect of our lives. Public health is one of the major fields where AI is leaving its mark.
With AI’s ability to process and analyze huge amounts of data in a matter of seconds, it truly has the power to transform healthcare on a community level.
In this article, we’ll uncover the truth behind AI in public health, including its definition, role in the context of healthcare, and its revolution in the domain of population health management.
As a bonus, we’ll also discuss the major players in the industry, such as Docus.ai, and its role in transforming public health. Let’s dive right in.
What is Public Health and Why is It Important
In simple terms, public health is about safeguarding and improving the health of communities through things like preventing diseases, educating people about health, and implementing policies for the betterment of health in general.
Public health is sometimes referred to as the guardian of the community’s well-being. The main mission of public health is to improve people’s quality of life through better health.
For example, actions like promoting healthy behaviors, and running initiatives for sanitation and immunization are all part of public health.
The difference between public health and healthcare in general is the focus on the community. So, instead of treating individuals, public health operates with the philosophy that the health of 1 person impacts the health of many others.
Who is responsible for public health?
At its core, public health is a collective effort. From government agencies and NGOs to communities themselves and private sector companies, everyone has a role to play in improving the population’s health.
Why is public health important?
You might not think that public health has direct benefits, but the importance of public health shows itself at a time of crisis. Be it pandemics or natural disasters, having the right infrastructure in place can save countless lives.
Public health on its own has been around for a very long time. So, what changes when we introduce the computing power of AI to this sphere?
The Role of AI in Public Health
Let’s talk about AI in public health. What impact and applications does it have? Will AI be useful in public health at all?
When it comes to public health, one of the most important factors to consider is the AI’s ability to predict potential disease outbreaks.
Since we are already producing vast amounts of health data, all that’s left for AI systems is to analyze it and identify trends, and potential risks. Needless to say, AI algorithms can do this faster and with better accuracy than humans can.
This introduction of artificial intelligence in public health simply makes healthcare more efficient for communities, namely through timely interventions, better resource allocation, strategic planning, and much more. This is just one of the ways AI will help public health workers in the future.
AI and data-driven decision-making in public health
To completely understand the role of AI in public health, let’s compare the power of AI with traditional methods in health data analysis.
It’s no secret that healthcare produces tons of data and requires a lot of decision support. This is what makes AI the perfect match for the sphere of healthcare in general.
AI systems can analyze datasets in real-time and give healthcare professionals the upper hand. In other words, if AI algorithms can predict disease outbreaks, this gives doctors time to plan strategies to prevent them.
The bottom line is that we are all simply better off with the introduction of artificial intelligence in public health and epidemiology.
Data Analytics and Population Health Management
One of the best examples to show how AI is revolutionizing public health is the convergence between data analytics and population health management. In a way, it is because they complete each other.
AI’s best asset is its data-processing abilities. Population health management requires tons of data processing. You see where this is going, right?
Imagine your clinic gathering the demographic, socioeconomic, and environmental data of your community. AI models can use this data to anticipate the health needs of that community.
This would mean that with every other disease outbreak, the healthcare system can allocate its resources in a proactive way and ensure that everyone has equal access to care during times of need.
Another example would be the AI processing terabytes of genomic data to identify biomarkers associated with a certain disease. This, in turn, would give researchers everything they need to develop targeted therapies for communities.
Applications of Data Analytics in Public Health
AI and public health mesh in many areas, so let’s talk about a couple of other applications that AI systems have for the health of communities.
The data-driven decision-making process starts at the point of data collection. Then, it moves to analyzing and uncovering insights. A process that would’ve taken humans hours now takes AI systems mere seconds.
AI algorithms are able to detect the slightest of patterns. For example, they can make connections between lifestyle choices and environmental factors, suggest updated treatment plans, and improve overall health outcomes.
Looking at the big picture, the insights uncovered by AI models will pave the way to equipping healthcare providers with better tools to deal with health crises.
After analyzing population and community-level health data and drawing insights, the next course of action is to build predictive models. AI-powered predictive modeling allows us to build a formula for the future and put a number on risk factors that are likely to affect it.
These models can help public health officials formulate targeted interventions and be proactive rather than reactive during outbreaks.
For example, AI can predict the demand for flu vaccines in a specific community based on past data. This will give healthcare professionals all the information they need to get enough vaccines for the future.
Healthcare resource allocation
If predictive modeling can help us determine when and how many flu vaccines we will need in the future, it can also indirectly help us manage our resources better.
In other words, not only will we know how many vaccines to make, but we will also have the time to plan and make them efficiently and in a timely manner for whenever they are needed
As for times of crisis, AI can give us information about specific areas of concern. To ensure that there is equality between and among communities, AI and public health can come together to make the most impact on the population.
Real-time health surveillance
Yet another amazing application of data analytics in population health management is health monitoring. This is one of the technology advancements that takes healthcare from reactive to proactive.
AI systems are constantly looking for signs of outbreaks and patterns of concern. They do it in real time, and they do it accurately.
And if an outbreak does flare up despite vaccinations, AI algorithms can save the day with decision support - telling doctors how to change their course of action.
Modern public health is growing day by day, and it is significantly due to the introduction of AI systems. The floodgates to better resource allocation and informed policy-making have been opened.
The Role of Docus.ai in Public Health
Public health is a communal effort - this is something we already know. What we haven’t yet told you is the impact that healthcare chatbots are going to have on the betterment of public health.
With Docus.ai, the overall health metrics of the community will go up. Here are a couple of reasons why:
- Increased access to healthcare. This is true both in terms of time (it is available 24/7) and in terms of location (it is available from anywhere in the world).
- More reliable information resources. While Google might spread misinformation, our virtual healthcare chatbots are optimized for accuracy and verified by real doctors after initial assessments.
- Initial symptom assessment and diagnosis. Before reaching out to a doctor, answer a series of questions regarding your symptoms to determine whether or not you need immediate medical attention.
This is just the tip of the iceberg when it comes to the benefits of AI-powered health assistants for public health.
If we all decide to redistribute our concerns to systems that have almost infinite energy during the day instead of going straight to the doctor, the health of our communities might just improve.
So, there you go folks - the A to Z of AI in public health. In our mission to healthier communities and better healthcare systems, AI has a big role to play.
As technology continues to become better, faster, and smarter, we will continue to see improvements to our health on a communal level and how we approach public health altogether.
AI is here to help humans, not replace them. By predicting disease outbreaks, helping in better resource allocation, and managing population health data, AI systems won’t be going anywhere anytime soon.
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