The Healthcare Executive's Playbook for AI Adoption

 

The era of AI being a novelty in healthcare has ended. AI is now a reality and an essential component of a healthcare organization's strategy. Innovations in AI have the potential to change the way healthcare organizations provide care. AI can enhance outcomes, reduce costs, and improve the overall operational and financial efficiency of the organization.

For healthcare executives, the pertinent issue is no longer the relevance of AI. The pertinent issue is how to adopt AI in a way that drives competitive advantage in the face of almost certain overwhelming competitive pressures. The organizations that gain a first-mover advantage with AI will achieve a sustainable competitive advantage. The longer other organizations wait to adopt AI, the greater that competitive advantage will be.

This playbook describes practical frameworks for enterprise AI adoption that can be used by healthcare executives.

Why Competitive Pressure Is Accelerating AI Adoption

Perhaps the simplest way to articulate the multitude of challenges faced in the healthcare industry is that they are coming from all directions.

First, consider the pressures related to the patients and the providers. Patients now expect more customized healthcare and are receiving it faster than ever before. This places a strain on healthcare providers to control costs and improve the quality of care. The constantly changing regulations, coupled with the explosive growth of healthcare data, create an additional burden on the providers.

The healthcare systems and companies creating healthcare technologies are investing heavily in AI. These systems and technologies provide solutions to the growing challenges faced by the healthcare industry.

Those executives who do not invest run the risk of:

• Losing patients to healthcare providers with superior digital care

• Higher costs to operate

• Slower clinical and administrative cycles

• Less productive employees

• An inability to attract the best talent in healthcare

 

Enterprise AI gives the opportunity to organizations to innovate, operate, and respond faster.

Start with Business Objectives, Not Technology

The most common blunder companies make is deciding to utilize AI for the sake of trends.

The most effective healthcare executives first devise the business problems they would like to tackle. These might be:

• Making patient wait times shorter

• Increasing active care collaboration

• Cutting down costs on administrative tasks

• Improving the efficiency of the hospital

• Establishing early predictive methods for patient risk

• Improving revenue cycle management

• Better workforce schedule optimization

To yield a greater result and a noticeable return on investment, align AI projects to business strategies. 

Build an Enterprise AI Strategy

Instead of applying siloed AI technologies in each separate department, healthcare leaders need to formulate a company-wide AI policy.

An Enterprise AI Strategy links business needs with tech spending while building scalability, oversight, and a frame for sustained success.

Successful strategies offer the following:

• Backed by leadership

• Policies for governance of data

• Security and compliance are prioritized

• Ethics and transparency of AI

• Works with current healthcare tech

• Performance is monitored on an ongoing basis

 

The aim of this method is to eliminate scattered activities within the organization and drive sustainable value to the business.

Focus on Use Cases that Deliver the Most Value

Not all AI projects need to be elaborated.

The best value use cases of enterprise AI being implemented in most of the healthcare industry are: 

Intelligent Clinical Decision Support

AI aids the assessment of risk in patient data and the documentation of supportive patient cases in a more efficient manner by physicians.

Predictive Patient Care

Patient data risk models of more telling views can be created prior to the point of critical care.

Administrative Automation

AI simplifies the completion of repetitive administrative tasks like scheduling appointments, verifying insurance, processing claims, and documentation.

Revenue Cycle Optimization

Timeliness of receivables improves as AI spots discrepancies in billing and claim submissions.

Resource Optimization

Forecasting patient volumes, staffing optimization, and bed management optimization are all aided by AI in hospitals.

 Enhance Your Investment in Data Readiness

Invest in Data Readiness

Recordings through EHRs and patient engagement tools and data from medical equipment and imaging devices and clinical labs generate massive amounts of data in healthcare.

Leadership must focus on the:

• Improvement of data quality

• Integration of systems

• Management of uniform data

• Sharing of secure data

• Capacity for analytics in real time

Organizations with a solid data foundation will have AI that produces results in a timely manner with greater trust.

Empower Employees Through Change Management

Change is more than just the use of new technology.

Health care workers need to see that the new technology will support their work.

Leaders need to put their resources into:

•  AI awareness programs

• Employee training

• Cross-functional collaboration

• Transparent communication

• Continuous feedback

When workers at all levels see how AI helps with the work they do every day, it is easier to implement the new system.

Balance Innovation with Trust

Trust is the foundation of the health care system.

With the introduction of new technology, the company needs to keep the highest level of ethics and protection of the client when making decisions.

Leaders need to put systems in place that ensure the new technology is:

•  Fair

• Explainable

• Secure

• Compliant

• Regularly monitored

Using AI in this manner will strengthen the trust of the patients and lower the risks for the company. 

Measure Business Outcomes

AI initiatives should be evaluated based on their effect on business objectives. Simply counting how many AI models an organization has developed is not an effective way to determine how successful the organization has been with AI.

Healthcare executives should concern themselves with the following KPIs:

• Reduced operational costs

• Faster patient service delivery

• Improved patient satisfaction

• Lower readmission rates

• Increased workforce productivity

• Revenue improvements

• Better clinical outcomes

Having KPIs assists executives with their decision-making and helps determine the direction and amount of funding to allocate to developing AI initiatives.

Prepare for Continuous AI Evolution

Getting AI to work in your organization is not a destination, it is a journey, and your organization must be ready for the ongoing changes.

The organizations that are continuously using AI to maintain their services and operations, and to stay ahead of their competitors, are the ones that will be winning the most in the digitally focused future of healthcare.

AI systems will be changing the way services in healthcare are being provided to patients and the way staff interact with patients and staff. Organizations that have already changed to a way of working that is focused on innovation will be the ones that win in the most competitive future of healthcare.

Partner with the Right AI Transformation Expert

Purchasing enterprise AI is a component of the journey. Effective planning and strategic positioning as well as the safe and controlled rollout of AI systems are critical and will continue to be demanded.

USM Business Systems designs and delivers enterprise AI systems tailored to specific business needs, enabling healthcare organizations to rapidly adopt AI. UsM's solutions include intelligent automation, AI strategy, predictive analytics and digital transformation. Leverage AI to transform healthcare and win competitive advantages.

Book an executive AI briefing to explore AI use cases for your business.