AI Clinical Workflow Automation for Healthcare Organizations: A Vendor Example

When Admin Work Impedes Patient Care

Improving patient outcomes while remaining compliant and managing costs are constant pressures for healthcare organizations. Providing patients with better experiences is an additional pressure. Many healthcare providers continue to struggle with operational inefficiencies, slowing clinical teams, and creating unnecessary admin work.

Patient care is impacted by the workloads created from patient intake and scheduling, documentation, referrals, and care coordination. These challenges increase and become more difficult to manage as the organization grows.

For healthcare SMEs, hospitals, clinics, and healthcare IT vendors, the need for automation is obvious. The distinction is in how healthcare organizations can adopt automation with intelligence, and for the right use cases, to improve operational efficiency without disrupting current business activities.

This case study reviews the operational transformation experienced by this healthcare client as a result of the implementation of Healthcare Workflow Automation, and the role of Hyena.ai in the improvement of workflow automation and visibility with the intent of delivering measurable outcomes.

The Problem

Healthcare clients with multiple outpatient locations were experiencing growing admin burdens as their patient volumes increased, and as healthcare systems became more fragmented.

Clinical teams had to spend more time dealing with operational burdens than having direct patient contact, interaction, and care.

Some of the Key Challenges

Increased Admin Burden

Physicians, as well as nurses, spent many hours documenting patient visits, updating, and coordinating information across healthcare silos.

This created a productivity gap and contributed to employee burnout.

Disconnected Systems

Different software systems were used across the organization for scheduling, managing patient records, billing, communication, and reporting.

Staff had to repeatedly enter the same information across several systems, leading to inefficiencies and an increasing likelihood for errors.

Limited Operational Visibility

Staff at different levels within the organization were unable to see workflow performance and the demand for patients, and the resources in the organization were not able to be effectively utilized.

The ability to view demand and workflow performance was restricted, and the forecasts for demand were incorrect and mostly reactive.

Rising Operational Costs

The organization was under pressure to add additional resources to maintain the same level of service. The added pressure was due to an increased workload from administration.

Adding more personnel was not a viable solution. Leadership understood operations.

The Goal

Three short-term objectives were developed:

- Decrease the amount of time spent on administration

- Increase the productivity of clinical operations

- Build a foundation that could support future growth

Hyena.ai was contracted to provide support on goal and target setting.

The Solution

Creating a connected operational ecosystem (not implementing siloed automation) was the goal of the organization.

The solution was focused on clinical and administrative performance through the combination of optimization of workflows and rationalized, integrated decision support and next-generation analytics.

Automating Clinical Workflows

The organization focused on several workflows that were highly time consuming.

These workflows were:

- Intake and registration of patients

- Scheduling appointments

- Managing referrals

- Coordination of care

- Clinical documentation

Staff were able to focus on clinical responsibilities and patient interactions.

Bringing Together the Operations

One of the major problems in the organization was the communication gap between the main systems.

We were able to use Intelligent Automation to enhance the workflows to transport the information between the different sections and applications seamlessly.

This brought about the elimination of redundant tasks and put the information within reach to make quick decisions throughout the organization.

Processing Quick Decisions

All the data pertaining to different operations was present in the various sections of the organization. However, it was seldom put to good use.

The application of Predictive Analytics gave the leadership the data they needed to make decisions before any problems could arise.

Thus, the management was in a position to make decisions about staff, schedules, as well as resources.

The Implementation Process

The entire transformation process was conducted in a way that day-to-day operations were not disturbed.

Step 1: Workflow Study

The first step of the project was to review the workflows as they existed.

Members of the project were provided the clinical as well as administrative workflows to identify hurdles and inefficiencies, and to establish possible automation.

Step 2: Integration & Smooth Implementation

Major systems in healthcare were connected to enhance data transfer and remove the need for manual tasks.

This resulted in creating a seamless integration of the individual sections.

Step 3: Implementation of AI

The automation features were used in a phased approach for the major workflows.

The goal was to enhance the task consistency and remove the repetitive tasks.

Step 4: Improvement

Once the system started functioning, checking the system to identify possible process improvements was a routine activity.

This created a system to maintain the growing efficiency of the organization.

Results

The healthcare provider began seeing measurable improvements across various business segments within a few months of implementation.

Improved Clinical Productivity

Clinical staff were able to spend a greater amount of time delivering care to patients rather than being burdened by administrative activities.

The time taken to complete the documentation reduced workflow bottlenecks and improved the overall efficiency of the workflow.

Better Coordination Across Departments

When systems are connected, information flows unimpeded throughout the organization.

This improved inter-departmental coordination and reduced communication gaps.

More Accurate Planning

With the implementation of Machine Learning Solutions, the organization was able to gain further insights into the structure of operational activity and the demands of patients.

This helped the leadership teams to make better-informed decisions as opposed to working based on guesses.

Reduced Administrative Burden

With the implementation of automation, a significant amount of manual work was eliminated.

This allowed the staff to work on activities that were of greater value and that would help improve the outcomes for patients.

Enhanced Patient Experience

The focus on automation and workflow improvements resulted in better care coordination, communication, and faster scheduling.

This made the care process more efficient and resulted in higher levels of satisfaction for the patients.

Business Impact

The project illustrated that the successful digital transformation of a business relies on more than merely automation of business processes.

Using modern AI in Healthcare, the organization was able to lay the groundwork for sustainable excellence in operations.

The most important business outcomes were:

- Improved productivity

- Better efficiency

- Lower administrative costs

- Improved resource utilization

- Better, more informed decisions

- Improved patient experience

- Improved scalability for future business expansion

The most important outcome was that the organization was able to simplify its operations while improving business performance.

Why It Should Concern Healthcare Vendors and SMEs

Healthcare investors need partners that provide measurable outcomes, not separate technological solutions.

Healthcare SMEs want outcomes to help with their:

- Operational problems

- Limited resources

- Increased costs due to administration

- Bottlenecks in workflow

- Fragmented data

This provides a good opportunity for SMEs and vendors.

Technology partners that assist the healthcare SMEs in achieving streamlined operations and better outcomes will have a greater chance of building stronger partnerships with their clients and achieving sustainable growth.

The software component of the deal is no longer the main focus.

Summary

- The administration demands greater focus to help healthcare organizations alleviate the symptoms.

- Operational workflows that have greater constituent involvement and physical throughput help the clinical team to spend more time with their patients and less time with the administration on process control.

- Efficiency and collaboration drive out inefficiencies, especially when achieved through integrated systems.

- The greater the data integrity the greater the forecast quality, thus easier and more efficient allocation of resources.

- The benefits from the automation of operational processes in the healthcare industry will have a measurable effect on operations even in the area of finance, without impacting patient services.

- The healthcare industry is more focused on partnering with technology vendors for frameworks of art and part solutions that meet their needs.

Common Queries

What methods do healthcare organizations implement to reduce the burden on administration without employing more staff?

Many of them use automation to help manage documentation, scheduling, patient intakes, and care coordination to help their teams be more productive to meet growing demands.

What are the most common operational problems faced by healthcare organizations?

Inefficient workflows, fragmented systems and a lack of visibility into performance all have a huge impact on administrative workload.

How can Predictive Insights Improve Healthcare Operations?

Predictive models make it possible to anticipate patient demand and to calculate optimal staffing. They can also help identify potential problems and improve planning for interdepartmental activities.

Can Automation Work to the Benefit of the Patient?

Absolutely. Patients appreciate rapid scheduling, efficient communication, shorter waiting, and better coordination.

What Do Healthcare Leaders Need to Evaluate in Automation Solutions?

Healthcare organizations need to evaluate systems for healthcare process automation that will provide a return on investment, enhance operational transparency, and be flexible enough to support the organization’s approach to regulatory compliance.

What Reason Do Healthcare Vendors Have to Pursue AI Solutions?

Healthcare vendors are focusing on improving AI offerings because healthcare organizations insist that technology solutions create meaningful improvements to healthcare operations. AI solutions provide the healthcare operational scalability and decision-making throughput necessary to improve healthcare operations without sacrificing care.

Conclusion

As healthcare demand grows, organizations can no longer rely on disconnected systems and manual processes. The rapid diversification of patient needs and the growing complexity of healthcare operations require operational resource management and decision support systems that are highly automated and intelligent.

This clinical workflow automation case study illustrates the improvement of operational efficiency and the cultivation of patient and employee satisfaction for healthcare organizations.

The companies that will thrive in the connected healthcare systems of tomorrow are those that will automate the mundane and transform the actionable operational data of today.