The Impact of Artificial Intelligence on Health Behaviour Management by@Cryptonite

The Impact of Artificial Intelligence on Health Behaviour Management

image
Cryptonite HackerNoon profile picture

Cryptonite

Cryptocurrency & Tech Writer.

Artificial intelligence (AI) is a collection of technologies that work alongside each other to allow robots to detect, interpret, act, and learn with human-like intelligence. One area that can see major benefits from artificial intelligence is Healthcare Behavioural Management (HBM).

AI helps healthcare providers to understand the regular routines and needs of the people under their care. This enables them to provide better feedback, guidance and support for their patients, helping them to maintain good health.

In this post we’ll look at how AI is changing the healthcare industry as well as Healthcare Behavioural Management (HBM).

How is Artificial Intelligence (AI) being used in the healthcare industry?

Artificial intelligence is already being used to diagnose diseases more precisely and early on, such as cancer. 

According to the American Cancer Society, a significant number of mammograms provide false findings, resulting in one out of every two healthy women being diagnosed with cancer.

AI is allowing mammograms to be reviewed and translated 30 times faster with 99% accuracy, decreasing the need for unneeded biopsies.

Wearable technology and other medical equipment are being utilised in conjunction with AI to monitor and diagnose potentially fatal events in early-stage heart disease.

This allows doctors and other caregivers to better monitor and detect potentially life-threatening episodes at an earlier, more treatable stage.

Predictive analytics are also being used to help clinical decision-making and actions, as well as prioritize administrative activities. This is done to improve treatment by aligning massive health data with suitable and timely judgments.

The use of pattern recognition to identify patients who are at risk of getting an illness – or seeing one get worse – as a consequence of lifestyle, environmental, genetic, or other variables is another area where artificial intelligence is beginning to take root in the healthcare industry.

AI is being used to help clinicians take a more comprehensive approach to disease management, better coordinate care plans, and help patients better manage and comply with their long-term treatment programmes.

In addition to the above, artificial intelligence is being used to scan health data to assist caregivers in identifying seriously unwell patients who may be at risk of an adverse episode.

Artificial Intelligence In Health Behaviour Management

Health plans spend a lot of money maintaining their members' health in order to enhance their outcomes. 

Suboptimal health behaviour, in addition to higher operating costs, raises the probability of poor health outcomes among members dramatically.

The factors influencing people's health decisions are more complicated than ever before, thanks to technology advancements and increased access to healthcare information and services.

Existing engagement solutions are limited in their ability to recognise people's concerns at a large scale. Furthermore, their techniques are primarily focused on communications, which can be unpleasant and negatively impact the member experience.

MedOrion is one software company that has been working on AI-based solutions for Health Behaviour Management.

Their Health Behaviour Management (HBM) solution enables health plans to transition away from outsourced member-engagement services and toward an end-to-end self-service software solution that focuses on long-term behavioural change.

This gives health plans more control over their processes, priorities, and full visibility into their members' experiences. This also makes it possible for them to immediately change course when necessary to ensure positive changes in their members' health and relationships.

The system examines each member's claims, clinical, and demographic data, combining social determinants of health (SDoH) to uncover members' worries about a number of measures, such as drugs, immunizations, and cancer screening.

The platform also won the Vaccines Global Innovation Challenge, setup by Pfizer which sought creative ways to both patient education and vaccination access.

The most relevant barriers to action are then identified using behavioural science and AI. Once determined, HBM creates a persuasive communication approach that is regarded best appropriate for each individual member.

Member level health behaviour insights collect and grow more accurately over time as more member data and response patterns are analyzed by HBM monitoring technologies.

Leading tactics and products may then be better tailored to the preferences of members.

This enables health plans to build deeper member relationships, be more helpful in real time, and stay on top of the ever-changing healthcare landscape.

As trust and involvement with members improve, so does adherence to prescribed courses of action.

As a result, health plans operate more effectively, increasing overall revenues and outperforming rival health plans in terms of quality.

Final Thoughts

Due to its crucial role in a productive, healthy society, healthcare is one of the most important areas in the larger landscape of big data. 

AI in healthcare may improve patient outcomes through improving preventative care and quality of life, as well as producing more accurate diagnosis and treatment regimens. By analyzing data from the government, healthcare, and other sources, AI can help anticipate and track the spread of contagious illnesses. 

Due to the above, artificial intelligence has the potential to be a crucial tool in the global public health fight against diseases and pandemics.

Disclaimer: The content is this story is provided by an independent contributor and does not represent the views of Hacker Noon.


Welcome to the Decentralized Internet Contest!

Comments

Signup or Login to Join the Discussion

Tags

Related Stories