Overcoming Implementation Challenges: Best Practices for Integrating AI in Healthcare Organizations

AI in healthcare has many potential uses, from diagnosing cancerous tumors to streamlining claims processes. The benefits range from better patient outcomes to budgets that stretch further, so why isn’t AI being taken up across every aspect of business by more healthcare organizations? Examining barriers to the adoption of AI in healthcare can help organizations understand what needs to change to overcome AI implementation challenges. This includes what best practices leaders can employ to motivate their teams to be open to integrating AI-powered technology in healthcare organizations.

AI in Healthcare: Primary Barriers to Overcoming Implementation Challenges

Let’s start by looking at why some healthcare facilities are still resistant to onboarding AI-powered tools. These challenges also indicate why AI adoption may be prevalent in some areas but lagging behind in others. Cost, data quality, and meaningful comparison between tools are some of the burning issues.

Cost

As expected, cost implication is one of the primary barriers to accessing any new or advancing technology. But AI could represent a long-term return on investment (ROI). One study showed that by implementing AI into resource allocation and patient data management, clinics could reduce wait times by 10%. Shorter wait times can improve patient outcomes and less money spent on prescriptions and medical procedures. 

Yet there are potentially significant costs associated with integrating these AI-powered processes:

• Upgrading legacy systems

• Compliance, security, and data privacy updates

• Fees to vendors or third-party experts

• Employee training

Organizations may find these short-term costs too prohibitive, even with long-term savings on the horizon. 

Data Quality

Cost is just one consideration. Effective AI solutions also rely on high-quality data. Where healthcare systems are disparate, with data spread out across multiple systems — or even split between physical and digital storage — AI tools may be unable to access the data required to provide meaningful insights.

Ethical Concerns

AI is only as objective as the data on which it is trained. Concerns around bias persist, with healthcare experts discussing the ramifications of inadvertently discriminating by race or income. There are also concerns over where data for training comes from and the consent surrounding these processes. Google’s DeepMind used data from 1.6 million kidney patients without consent, and the firm is now being sued. While the data may be used to improve an app for kidney injury diagnoses, the ends can’t justify the means when people have their data stolen to fuel technology.

Context for Comparison

Where these other challenges have been considered and overcome, there’s still the question of how effective these potentially costly tools are. Although there are increasing numbers of studies into AI-powered healthcare technologies, there still isn’t enough data to determine whether a particular piece of AI healthcare tech is successful compared to competitors. Currently, most research assesses how AI compares to humans. For example, on average, AI-powered diagnosis tools are as good as or better than human clinicians when including data related to clinicians with low experience levels. 

However, when healthcare leaders invest in tech, they want to know they’re getting a good ROI. That means understanding how it performs against similar pieces of software or hardware. While AI is still in its emergent phase, this means that in certain situations, there aren’t enough available applications to fully evaluate each tool’s efficacy. 

Best Practices for Integrating AI in Healthcare

These AI implementation barriers may present challenges, but they aren’t insurmountable. By focusing on these best practices for integrating AI in healthcare, you could support incorporating AI across your organization by overcoming implementation challenges using best practices for integrating AI in healthcare.

1. Align Needs with the Available Tools

Onboarding AI for its own sake could be a costly mistake. Take the time to understand the features and benefits of the tools available to your facility. For example, AI algorithms in revenue cycle management (RCM) can help improve accuracy in payment estimates, helping healthcare organizations better manage their budgets. Weigh what’s available and what could benefit your teams and overall efficiency as an organization. 

2. Assign an AI Integration Change Specialist

Change of any type is easier with a centralized point of contact and source of information. Many healthcare facilities work with specialist consultants when they update any systems. NextGen electronic healthcare record (EHR) consultants work with all types of healthcare businesses to ensure they get the most out of their systems. These partnerships offer the twofold benefit of providing a consistent source of support while ensuring new systems are optimized to provide the best benefits.

3. Assess Vendors Carefully

Review recent literature on AI in healthcare and reviews from other healthcare facilities before choosing AI vendors. Careful research is essential whether you’re sourcing diagnostic equipment or electronic practice management (EPM) systems. Consider how vendors handle data privacy, training transparency, their ethical stance, along with performance and efficiency stats. 

How TempDev Can Help Overcome Barriers to Implementing AI in Healthcare Facilities

With AI rapidly becoming an increasingly essential aspect of healthcare, organizations must be careful so they are not left behind. TempDev’s expert consultants can help your facility onboard and integrate the latest NextGen EHR and EPM systems, working with your teams to understand the benefits of AI-powered features by overcoming implementation challenges with best practices for integrating AI in healthcare. Discover more about improved workflows, productivity, and revenue via the right systems for your facility. Contact TempDev online or call 888.TEMP.DEV.