How to Use and Leverage Artificial Intelligence (AI): A Guide for Healthcare Administrators

Raychel Ria

Raychel Ria

Agramon-Gacayan, BSN, RN, MPM

Updated & Fact Checked: 04.22.2024

AI has been on the news lately. Some fear that machines and programs may replace them, while some say that it will make processes easier and faster.

In the world of healthcare administrators, the latter holds true. In fact, managers can use AI to streamline hospital processes and improve the overall patient experience, among many other things.

Common AI Types in Healthcare

AI refers to technology that allows machines and computers to replicate human intelligence and problem-solving capacities. It can perform activities that usually require human intervention.

AI can be combined with other types of technology, such as robots and sensors.

In the field of healthcare,  the following AI programs are commonly used:

Machine Learning

According to IBM, machine learning (ML) involves the usage of data and algorithms to imitate how humans learn, thus making it more ‘accurate.’

Natural Language Processing

Natural Language Processing or NLP is a type of AI that uses computers to decipher and interpret human language.

Rule-Based Expert Systems

First used in the 1980s, rule-based expert systems follow if-then rules. They are largely used in electronic health records and clinical decision support. While useful, they have slowly been replaced by ML since they can only perform well up to a certain point. For example, they can cease to function should the rules reach the thousands.

Where and How to Use AI in Healthcare Administration

Healthcare administrators can leverage AI in a variety of processes and applications, such as:

Process Automation

ML can help healthcare administrators by automating processes such as appointment scheduling,  data entry, and claims processing. ML, after all, can analyze clinical documents quickly and accurately.

In the case of claims processing, for example, errors, often made by humans, can lead to reimbursement delays and denials, among many other things. With AI automating processes that reduce errors along the way, healthcare administrators can easily work through insurance bottlenecks that affect institutional finance and performance.

Monitoring and Analysis

ML also comes in handy for monitoring and analyzing indicators and outcomes, as it can easily identify patterns in hospital records.

AI can help with diagnostic analytics, which can tell the healthcare administrator why or how a certain event happened. It can also assist with predictive analytics, which can provide healthcare administrators, particularly those working in public health, with a model of predictive behavior.

There’s also prescriptive analytics, where AI can help healthcare administrators identify the proper course of action.

Diagnosis and Treatment

ML can also help in making more accurate diagnosis and treatment plans. The same can be said with NLP, which can make use of health information to identify a more precise diagnosis and personalized treatments.

For one, AI provides healthcare providers with an easier way to view the patient’s history, lab results, imaging studies, etc. It can also analyze results faster than the healthcare providers themselves.

More importantly, AI frees healthcare providers from the need to perform tedious tasks that take a lot of time, thus allowing them to focus on patient care more.

Staff Management

AI, which can be used for predictive analytics, can lead to better staff management as well. It can help administrators determine when to ramp up staffing based on patient census, bed capacity, and provider-patient ratios. This can save the hospital from the headaches associated with short staffing, such as incorrect assessments and medication errors due to patient volume.

Patient Engagement

Popular AI examples such as chatbots and virtual assistants can promote patient engagement, which is the process of involving the client in their healthcare decisions.

Chatbots can also lead to treatment adherence through reminders and alerts and as such can lead to better health outcomes. They can also be used to handle basic inquiries, which can free up a lot of the healthcare provider’s time.

For example, a patient who just wants to reschedule their appointment may choose not to go to their doctor because they’re having a hard time doing so. This can be detrimental to the patient’s health, especially if it’s for a pressing health matter.  With chatbots, patients don’t have to skip their doctor’s appointments because they can easily change their schedule as needed.

Supply Chain Management

AI can analyze historical and present data regarding inventory levels, patient census, even weather and geopolitical events. Such can help healthcare administrators plan their supply orders better, lest they want to endure another critical equipment shortage, similar to the one brought about by the Covid-19 pandemic.

Drug Development

AI also proves beneficial for administrators who are in the fields of research and pharma development. For one, AI can hasten drug development by analyzing all pertinent info and predicting how it affects the body.

AI in Healthcare Administration: The Key to BetterFinancial Management

Unsurprisingly, the above-mentioned processes performed by AI can help healthcare administrators manage the institution’s finances better. Let’s take a look at the numbers: 

Process Automation

According to a Citigroup report, about ¼ of healthcare spending is relegated to administrative tasks. Automating such processes, however, can reduce 25-30% of the said costs.

Moreover, process automation can lead to more accurate claims and reduced denial rates.

As per Medical Economics, these greatly affect hospital finances (together with the rising costs of service delivery) The report shows that these issues have led to a  23% decrease in the cash reserves of most hospitals. In the long run, these can affect the institutions’ abilities to provide quality care.

Monitoring and Analysis

In terms of monitoring and analysis, AI can help enhance financial management through:

  • Diagnostic Analytics. AI can show why the hospital had a lower fourth-quarter revenue, allowing administrators to come up with solutions that will prevent it from happening again.
  • Predictive Analytics. AI can help Identify the disease risk of patients from a certain location. This, in turn, can help administrators create better health programs and treatment sequences for the said population.
  • Prescriptive Analytics. Data from last year’s claims can help managers defend the changes in premium cost, or why they’re placing extra incentives on preventative care.

Diagnosis and Treatment

AI can greatly improve diagnosis and treatment, which makes it beneficial for any institution—both legally and financially.

While healthcare workers are educated to make accurate diagnoses and treatments, they are only human. Unfortunately, some patients who are misdiagnosed or wrongly treated will end up staying longer in the hospital, which is sure to cost the institution more money.

A study has shown that a patient who has been ‘harmed’ during their hospital stay brings about a reduced contribution margin of $1,112.

Then there are the legal fees. According to the American Medical Association, the average expense for medical liability claims (as of 2015) is $54,165. Even if the case is withdrawn, dropped, or dismissed, the hospital will have to pay approximately $30,475 in related fees.

Staff Management

Understaffing can lead to burnout. According to the Journal of the American Medical Association, the latter costs healthcare systems about $4.6 billion annually.

Reducing the burden of clerical tasks, which AI can easily do, can help healthcare administrators mitigate the costs associated with provider burnout. For example, it can take on administrative processes such as pre-authorizations and prescription checks.

Patient Engagement

Patient engagement, especially in clients with chronic diseases, can lead to financial benefits as well. That’s because based on a study, this population accounts for 86% of healthcare costs.

Patient engagement, which helps promote drug/treatment adherence, is not only good for the client; it’s beneficial to healthcare administrators as well. After all, such can lead to lower operational costs and higher satisfaction rates.

Supply Chain Management

More than just alerting healthcare administrators about when to order or how many supplies to procure, AI can provide insights that help with financial management. For example, AI can perform value analysis, which helps determine the supplies or equipment that yield better healthcare outcomes. While they may cost more than other products, they may help reduce overhead costs due to faster recovery and shorter hospital stays.

AI can also help with sourcing. Not only does it allow healthcare administrators to find suppliers that offer the best mix of quality and cost, but it can also help them determine which ones to order to prevent wastage.

For example, physicians may prefer a certain brand of gloves and ignore the other ones. Such data, which AI can pull up easily, can help administrators save money as it prevents them from ordering the brand that rarely gets used.

Drug Development

AI can minimize the time and expenses that go with routine clinical trials. According to a Citigroup report, AI could actually reduce drug discovery time by as much as 70%. Such may lead to lower drug costs, which is great for patients and healthcare administrators who have to deal with high medication costs.

The Takeaway

AI is the future of healthcare administration. It can help automate processes, monitor and analyze data, and promote accurate diagnosis and more effective treatments.

AI can also boost staff management, supply chain management, and patient engagement. As for the world of research and pharma, AI can hasten the drug development process.

Moreover, AI can help healthcare administrators manage their finances better due to the reduction of clerical tasks, improved accuracy, and data-powered decision-making, among many other benefits.

AI in Healthcare Administration Resources

Citigroup, “Smart Thinking on AI in Health

  • Discusses what’s happened in healthcare AI and its implications in the future.

Foresee Medical, “AI in Healthcare

  • Discusses the different types of AI and their role in healthcare.

Tulane University, “Data Driven Decision-Making for Health Administrators

  • Features the different types of data analytics and how they could help healthcare administrators make better decisions.