How AI Is Reshaping Healthcare Administration And Operations

Overview

Artificial Intelligence (AI) is revolutionising the modern world, and the healthcare sector has been significantly impacted. The introduction of AI into medical care systems makes complex tasks easier and more organised. In this article, we will discuss how AI is creating a transformative impact on healthcare administration and operations.

What is AI in healthcare?

Artificial intelligence is a rapidly evolving branch of information technology that aims to complete tasks that require human intelligence with the help of machines. It includes techniques like:¹

• Machine learning (ML)
• Deep learning (DL) 
• Natural language processing (NLP)

Around the world, the healthcare system is on the path of evolution. Technology plays a crucial role in this as AI assists in:

• Diagnosis
• Treatment plans
• Predicting clinical patient outcomes

AI tools can be used to help in areas, such as radiology, telemedicine, virtual assistance, and remote monitoring. AI also plays a crucial role in hospital management, such as streamlining administrative tasks, improving operational efficiency, and managing patient flow and scheduling.²

One such example of an AI tool widely used is powered chatbots. Chatbots are equipped with algorithms that can be integrated into electronic health record systems to streamline administrative tasks and professional efficiency.³ They are often integrated into healthcare websites and mobile apps to provide real-time access to medical information. Chatbots are therefore effective for improving overall patient health education.⁴

AI making healthcare administration easier

Simplifying appointments

The success of a healthcare practice depends on efficient management and productivity. Unsuccessful appointments such as cancellations, no-shows or missed appointments may negatively impact the patient-provider relationship. Some reasons for missed or no-show appointments include delays in appointment availability, lack of telephone access, perceived disrespect, lack of understanding of the appointment scheduling system, and patient’s socioeconomic status.⁵

The application of AI tools in scheduling patient appointments minimises the scheduling challenges by reducing the workload, delayed appointments, and patient dissatisfaction. AI can be used to create personalised appointment schedules for each patient according to their needs.

Streamlining paperwork

Detailed documentation is necessary for effective communication between the healthcare provider and the patient. Maintaining proper medical records ensures that the patient’s needs are comprehensively met. AI can reduce the burden of data entry, provide clinical decision support, integrate patient data from multiple sources, and improve the quality and value of health care.⁶

Billing and insurance made simple

NLP is a branch of AI which uses algorithms to interpret, understand, and generate human language. It helps analyse the provider’s medical prescription and makes the billing and documentation easier. AI can analyse medical data, identify patterns of fraudulent or inappropriate claims, and automate and streamline claim reviews. Predictive analysis can analyse the claim data and patient information to identify the trends and predict the likelihood of valid claims.⁷

Improving healthcare operations with AI

Better resource management

AI-powered predictive maintenance helps to enhance operational efficiency by using data, sensors and analytic algorithms to predict when the machines need maintenance. The maintenance is based on real-time data rather than predetermined schedules making them timely and cost-effective.⁸

AI also helps to manage staff scheduling efficiently. AI-driven staff management tools can optimise schedules and reduce understaffing.

Smart supply chains

AI provides a smart supply chain in hospitals and clinics by analysing trends and automating order processes. It can manage the logistics and resources, anticipate supply chain disruptions, and suggest alternate solutions.²

Enhancing patient experience 

Personalised care

AI aids in personalising treatment and meeting patient requirements comprehensively. It helps tailor communication and follow-ups effectively. This can be done by integrating AI-driven self-service patient portals. These patient portals can help manage:

• Appointment schedules
• Appointment alerts
• Doctor recommendations
• Cost estimation
• Insurance claims

Helping doctors with decisions

AI techniques like machine learning and deep learning assist in diagnosing diseases, discovering medications, and identifying patient risk factors. AI has proved to be accurate in image-based disease detection as well as prediction of treatment outcomes.⁹

Managing patient data

Bringing data together

AI has the potential to integrate patient data from different sources and can learn and recognise patterns and relationships from this combined dataset. It proposes more precise recommendations based on the integrated data and helps in a more accurate clinical care process.¹⁰

Challenges and considerations

Privacy and ethics

It is undeniable that commercial healthcare AI faces some privacy challenges. Personal medical information is one of the most private legally protected data and cybersecurity is a major concern worldwide. Technologically facilitated informed consent and clear communication of the right to withdraw the data could address some of the ethical challenges and respect patient privacy. Still, innovations and regulatory components are required to ensure the privacy of patient data.¹¹

In the European Union, the General Data Protection Regulation (GDPR) guidance came into effect in May 2018 and it influences AI implementation. GDPR guidance states that “patients own and control their own data and must give explicit consent for its use or when it is shared”.¹²

Adapting to change

Education and training of the staff is a significant challenge in implementing AI in the healthcare industry. Knowledge regarding the potential and working of AI is limited in the medical community and requires training programmes.¹²

The future of AI in healthcare

What’s next?

Today AI is widely used in healthcare to automate time-consuming and repetitive tasks. Shortly, there may be a significant improvement in the algorithms and large-scale adoption of AI in healthcare including customisation of healthcare and robotic-assisted therapies.¹³

Long-term impact

In the long term, we can expect virtual health assistants to deliver predictive and anticipatory care, AI-driven drug discovery, new curative treatments, and AI-empowered healthcare professionals.¹³

Summary

AI reshapes every aspect of healthcare administration and operations by automating tasks, optimising resources, and enhancing patient care. Here is a recap of how AI makes a difference in administration and operations.

Advances in AI may enable a future that is more precise, personalised, and predictive. In the last decade, the integration of AI into administrative tasks and operations was primarily to reduce workload. The next decade will have a greater focus on using this valuable data for better clinical outcomes and AI assistance.