For financial executives and revenue cycle leaders, few things are more challenging than trying to discern whether well thought-out processes and workflows are breaking down—and who or what is the cause. Pre-pandemic, if performance was lagging, a revenue cycle leader may have walked the floor, sat elbow-to-elbow with staff, or simply added resources to bring performance levels back in line. But with historic labor shortages and a transformational move to a remote revenue cycle workforce, the old ways no longer work. Today’s revenue cycle operating model requires more transparency and insights beyond what productivity monitoring and statistically insignificant quality audits can offer.
Fortunately, there is a recent capability these leaders can leverage to more efficiently and more accurately pinpoint where and how improvements need to be made: process intelligence.
Effective Adoption of Process Intelligence Depends on 4 Tactics
Process intelligence is a newer capability that leverages data mining and data visualizations to delineate operational and technical workflow deviations and gaps against leading-practice workflows. This provides valuable process insights that can expedite performance improvement opportunities and help shape artificial intelligence (AI) and robotic process automation (RPA) opportunities.
Revenue cycle leaders who are equipped with process intelligence tools are propelling continuous process improvement with data-driven approaches that identify technical and operational workflow gaps. Using such tools is the equivalent of auditing 100% of account activities while also providing visualizations of key process breakdowns.
Combining process mining with analytics and a full understanding of leading-practice workflows enables leaders to optimize their most vulnerable processes. This real-time insight helps highlight what’s working, what’s not, and why. Process owners can then easily identify and implement improvement opportunities, regardless of where or when the workforce is working.
Until recently, these types of real-time insights into process breakdowns were difficult to achieve technically and were not viable economically. However, process intelligence tools are becoming more available and easier to use. Leaders who are ready to embrace process intelligence for continuous optimization should consider 4 tactics to enable effective adoption.
4 Tactics for Effective Adoption of Process Intelligence
1. Establish a Revenue Cycle Process Intelligence Strategy
Organizations can deploy process intelligence tools to examine their revenue cycle, which will enable process improvements and automation implementation within their electronic health record (EHR) system. Process intelligence also can help organizations identify the need to leverage additional technology. However, organizations that seek to advance their revenue cycle infrastructure can work process intelligence into their broader strategic plan to drive better efficiency in revenue-to-cash conversion. Revenue cycle processes span an entire organization and are impacted by clinical operations and workflow. In order to effectively understand where key breakdowns occur, it is important to look at broader data sets that can be analyzed through process intelligence. The analyzed data can benefit revenue performance, of course, but insights such as scheduling delays, patient experience impact, and many other process insights can benefit the organization as a whole.
A robust revenue cycle process intelligence program is most successful in organizations with effective governance structures and mature technology platforms that help feed the necessary data into a selected tool. Organizations that have fragmented governance, disparate technologies, and unorganized data may find deploying this type of program challenging to start. In these cases, establishing tightly controlled governance is pivotal to the overall success of process intelligence implementation. This type of governance should consist of a multi-disciplined team with strong representation from Information Technology (IT), Business Analytics, and Business Operations leaders whose expertise span pre-service, time-of-service, and post-service areas of revenue cycle. The team’s main role is to ensure process intelligence tools are applied, evaluated, and responded to effectively and efficiently.
2. Develop Process Analytics Capabilities
Organizations have different options for deploying revenue cycle process intelligence and integrating those capabilities into their existing analytics strategy and ecosystem. Depending on their capacity, organizations with an existing intelligent automation program may be able to build their own process analytics capabilities. Other organizations will find it more advantageous to acquire these capabilities from the market. Building a native process analytics tool requires significant time and capital. However, the institutional knowledge developed in the organization will serve as an ongoing asset that will help maintain and mature the tool. This capability is especially useful to address organization-specific issues, such as changes to local payer requirements that impact a core revenue cycle workflow.
On the other hand, purchasing a process analytics platform could be a quicker, more efficient avenue. Leveraging a vendor’s experience could expediate implementation while serving as a guide to avoid potential landmines. Vendors could assist in partnering with an organization to examine the broader organizational strategy with these tools. The organization will need to evaluate how its process analytics incorporates broadly with its technology and analytics ecosystem. These tools are only as successful as the data that feeds the platform and reducing any redundancies in the ecosystem that may conflict with the process analytic tools will be vital to the overall success.
3. Prioritize the Critically Vulnerable Revenue Cycle Processes
Knowing where to start can be challenging. Prioritizing less transparent, more critically vulnerable revenue cycle processes is a great place to begin the process intelligence journey. The criticality of revenue cycle processes differs based upon individual impact on revenue and the cash each process drives for the organization. For example, revenue cycle processes that require involvement from multiple departments to efficiently get a claim paid are great candidates, particularly because these processes are typically plagued by “finger-pointing” when the overall process fails.
Many of the most vital processes are also highly vulnerable to inconsistent and/or inadequate execution. For example, the below workflow depicts a new patient scheduling workflow for a leading cancer program. It can require up to 4 different departments all doing their part to accurately, timely, and financially secure a new patient appointment.
Sample Workflow for Scheduling a New Patient Oncology Visit
Example Process Intelligence Insights for the Sample Scheduling Workflow
If any of these departments delay, skip, or perform steps out of order for the scheduling journey, it could lead to delays, patient experience impact, and (of course) financial risk. By applying process intelligence capabilities to revenue cycle workflows like this one, leaders can more easily see insights like skipped steps (e.g., Finding 1), deficient execution (e.g., Finding 2), bottlenecks (e.g., Finding 3 and 4), potential system routing issues (e.g., Finding 5a), and even which individuals are associated with skipped steps (e.g., Finding 5b). Full transparency into workflows like the one above allows leaders to course correct before the issue materially impacts revenue or patient experience.
Other critical revenue cycle processes will be closely tied to key metrics that can have various root causes, such as higher-than-normal pre-claim and post-claim errors, initial denial increases, repeated write-off issues, bad debt increases, or areas that require ample amounts of human resources to perform adequately. These types of processes help to drive immediate value and to win over key leaders within the enterprise, thus leading to wider and fuller adoption of process intelligence across all key workflows.
4. Translate Findings into Actionable Solutions
As is evident in the example workflow, process intelligence shows leaders where and how impactful the variations in the process are, potentially leading to financial risk and risk to the patient experience.
Once organizations are equipped with these findings, they need to be prepared to intervene with a multi-level approach. Some corrective actions will be minimally invasive, while others will call for more transformative methods. For example, if only looking at Findings 5a and 5b in the above example, the leader may determine that a simple re-training of the 3 users causing most of the process variation is needed, and the issue will likely be resolved. However, if the leader looks collectively at all findings, they may determine that the process is only operating as designed a fraction of the time and therefore determine that a complete overhaul of that process, both operationally and technically, is needed to gain more control over potential variations.
In these more transformative cases, the process issues are often complex and span multiple departments and business units, including administrative and clinical operations. Of paramount importance is the organization’s ability to connect process intelligence findings to sustainable solutions that allow for proper process controls that minimize variations and financial risk. These solutions include enhanced technical workflows, process redesign, stakeholder training, quality assurance monitoring tools, and installment of IA solutions. This type of intervention is not minimally invasive and will require a multi-disciplinary team to achieve success.
Combining the organization’s analytics strategy and ecosystem, operations from the business and clinical groups, and technical resources will enable a more efficient journey from findings to corrective actions when applying process intelligence to the organization’s key workflows.
Prepare for Success
Process intelligence provides a window to holistically see how individual processes are performing—a longitudinal view by service area, department, and even by individual stakeholder. When augmented with data visualizations, it can provide leaders with specific, discrete, and continuous insights as to who and/or what is causing revenue cycle breakdowns.
To get started on this journey, revenue cycle leaders should develop and incorporate their process intelligence analytic strategy, prioritize the most vulnerable revenue cycle processes, and resource the initiative with key stakeholders who can best effect improvement changes.
Once properly and fully stood up, process intelligence can unlock efficiencies within the revenue cycle environment that will better fuel the organization to operate more efficiently and effectively. This will lead to greater staff, clinician, and patient satisfaction—in addition to driving continuous financial improvement.