Abstract
This paper introduces the concept of Automation Gain, a novel term to define the framework for measuring the true value of automation initiatives in healthcare revenue cycle management (RCM). While recent technology advances offer promising tools for reducing administrative burdens and streamlining operations, their impact can be miscalculated without accounting for labor that remains unautomated and unforeseen process inefficiencies. Automation Gain provides a methodology to accurately evaluate the return on investment (ROI) of automation projects, incorporating both realized labor savings and the residual manual effort required. This paper defines Automation Gain, presents detailed formulas for its calculation, and offers actionable steps to empower healthcare leaders to implement this framework in their organizations.
Key Takeaways
By the end of this paper, readers will gain the following insights:
What Automation Gain Is: A definition of Automation Gain and its role in accurately measuring the success of automation initiatives.
Formulas for Success: Specific, actionable calculations for evaluating Automation Gain, including time savings, new work done, and secondary effects.
Residual Labor Considerations: The critical importance of accounting for leftover tasks that remain unautomated within re-engineered processes.
Steps for Implementation: A practical framework for identifying, evaluating, and prioritizing automation opportunities in the healthcare revenue cycle.
Real-World Use Cases: Examples of how Automation Gain can be applied to optimize workflows and deliver significant ROI in healthcare organizations.
Introduction
The healthcare revenue cycle is increasingly under pressure to reduce costs, improve efficiency, and adapt to evolving regulatory requirements. The use of Robotic Process Automation (RPA), machine learning, and artificial intelligence have emerged as a key solution for addressing these challenges by automating repetitive, rules-based administrative tasks. Yet, while capabilities promise transformative benefits, organizations often struggle to quantify its true impact and maximize its potential.
Automation initiatives frequently fail to account for the complexities of healthcare workflows, particularly the residual labor that remains unautomated and the unforeseen inefficiencies uncovered during implementation. To bridge this gap, this paper introduces Automation Gain, a new framework for measuring and optimizing the value of automation investments in healthcare RCM.
Automation Gain is defined as the realized cost savings and efficiency improvements from automation, adjusted for residual manual effort and incomplete processes. By adopting this framework, healthcare leaders can make data-driven decisions about where to invest in automation, calculate the ROI of specific use cases, and identify opportunities for continuous improvement.
Defining Automation Gain
Automation Gain is a metric designed to quantify the net impact of RPA initiatives, considering both direct labor savings and the broader operational context. Unlike traditional automation metrics that focus solely on the volume of work automated, Automation Gain provides a holistic view by addressing:
Work Automated: Tasks fully completed by bots, resulting in direct time and cost savings.
Residual Labor: Tasks that remain unautomated or require human intervention within an automated workflow.
New Work Done: Additional tasks that bots can perform, which were previously deprioritized or infeasible due to cost or resource constraints.
Secondary Effects: Process improvements, error reduction, and insights into workflow inefficiencies that enhance overall organizational performance.
By integrating these elements, Automation Gain serves as a comprehensive framework for evaluating the effectiveness of automation projects and prioritizing future investments.
The Automation Gain Framework
The Automation Gain framework consists of three interconnected components: process mapping, task evaluation, and quantitative analysis. These steps guide leaders through the evaluation and implementation of automation initiatives.
Step 1: Mapping the Process
A thorough understanding of the target process is critical to calculating Automation Gain. Leaders should:
Document Each Step: Map out the workflow in detail, including all tasks, decision points, and hand-offs.
Classify Task Types:
Unattended Tasks: Fully automated processes that operate without human involvement.
Attended Tasks: Processes where bots assist humans in completing specific tasks.
Identify Residual Labor: Highlight areas where human intervention is required or where automation may fail to deliver consistent results.
It is important to map the entire process from beginning to end. To often leaders focus on the sub-set of tasks they intend to automate or only the most complex tasks. Evaluation from end-to-end ensures the steps preceeding and following the target area for automation remain unaffected.
Step 2: Evaluating Task Complexity
Tasks within the workflow should be evaluated based on their complexity to determine their automation feasibility. A tiered framework can be used:
Simple Sequences: Basic, rule-based tasks (e.g., data entry, status checks).
Business Rules: Conditional tasks that require decision-making based on predefined criteria (e.g., claim edits).
Multi-Path Workflows: Processes with multiple decision points and complex logic (e.g., authorization retrieval).
Cognitive Tasks: High-complexity tasks requiring nuanced judgment or advanced reasoning (e.g., clinical appeals).
By categorizing tasks, organizations can prioritize high-value automation opportunities while acknowledging tasks that may require hybrid approaches.
In general, simpler tasks are easier to create and maintain automations for. More complex processes do not necessarily mean they are harder to automate, but they do mean that more effort is needed to build and quality control them.
Step 3: Automation Gain
3a. Time Savings
This formula calculates the direct labor savings from automating repetitive tasks. It considers how often the task is performed, the time required per task[JM2] , and the success rate of automation.
Automation Gain (Time Savings) = (Frequency of Task × Time per Task) × Automation Success Rate
Key Components:
Frequency of Task: Number of times the task is performed in a specific period (e.g., daily, weekly, monthly).
Time per Task: Average duration (in hours) required to complete the task manually.
Automation Success Rate: The proportion of tasks that can be fully automated without manual intervention (expressed as a decimal, e.g., 90% = 0.9).
Example: Suppose:
The task occurs 1,000 times per month.
Each task takes 0.25 hours to complete.
The hourly staff rate is $40/hour.
The automation success rate is 80% (0.8).
The calculation is:
Automation Gain (Time Savings) = (1,000 × 0.25) × 40 × 0.8 = 8,000
This means the automation results in $8,000 in time savings per month.
3b. New Work
This formula calculates the net gain from automation enabling new revenue-generating activities. It subtracts the costs associated with the automation process from the additional revenue collected.
Automation Gain (New Work) = Additional Revenue Collected − Associated Costs
Key Components:
Additional Revenue Collected: New income generated due to automation (e.g., faster claim processing, improved billing accuracy).
Associated Costs: Costs incurred for implementing and maintaining the automation (e.g., software licenses, IT support).
Example: Suppose:
Automation enables $50,000 in new revenue each month.
Associated costs, including system maintenance and support, total $10,000.
The calculation is:
Automation Gain (New Work) = 50,000 − 10,000 = 40,000
This means automation generates a net gain of $40,000 per month from new work.
3c. Secondary Effects
While harder to quantify, secondary effects should be documented and tracked, as they contribute significantly to the overall value of automation. These include:
Error Reduction: Fewer errors lead to lower costs associated with rework and corrections.
Improved Throughput: Automation enables higher processing volumes within the same timeframe.
Enhanced Staff Satisfaction: Relieving employees from repetitive tasks allows them to focus on more strategic and fulfilling work.
Example (Qualitative Tracking): If automation reduces errors by 20%, improves throughput by 15%, and increases employee engagement scores by 10%, these improvements should be recorded and factored into the overall return on investment (ROI) analysis.
Consistent Application of the Framework
By using these formulas in conjunction, organizations can:
Quantify the direct labor savings from time saved through automation.
Identify the financial impact of new opportunities enabled by automation.
Track and measure the secondary benefits that enhance overall efficiency and satisfaction.
Conclusion
The Automation Gain framework is a transformative approach to understanding and maximizing the impact of Robotic Process Automation (RPA) in healthcare revenue cycle management (RCM). By moving beyond traditional automation metrics and incorporating a holistic evaluation of labor savings, residual tasks, new work opportunities, and secondary effects, Automation Gain provides healthcare organizations with a clear and actionable roadmap for modernizing workflows.
Overview of the Framework's Value
Automation Gain bridges the gap between the promise of RPA and the realities of healthcare workflows. It:
Enables Precise Measurement: Through detailed formulas for time savings, new work gains, and qualitative secondary effects, the framework quantifies the value of automation initiatives in real-world terms.
Accounts for Residual Tasks: It recognizes that not all processes can be fully automated and incorporates manual interventions into the ROI calculation for a more accurate picture.
Prioritizes Strategic Initiatives: By categorizing tasks based on complexity and automation feasibility, organizations can focus resources on high-impact areas.
Drives Continuous Improvement: Secondary effects such as error reduction, throughput improvements, and enhanced employee satisfaction encourage a culture of ongoing optimization.
Applying the Framework in Your Organization
Healthcare leaders can leverage this framework to transform their RCM processes in the following ways:
Process Mapping: Begin by documenting and analyzing key workflows to identify bottlenecks, inefficiencies, and opportunities for automation.
Task Complexity Evaluation: Categorize tasks based on their complexity—simple sequences, business rules, multi-path workflows, or cognitive tasks—to prioritize where automation can deliver the highest value.
Quantifying Automation Gain:
Use the Time Savings Formula to estimate direct cost reductions from automating repetitive tasks.
Apply the New Work Formula to calculate the net financial impact of enabling new, revenue-generating activities.
Document and track Secondary Effects such as improved accuracy, throughput, and employee satisfaction to build a comprehensive ROI case.
Pilot and Scale: Start with a high-value, low-complexity process to test the framework. Use the insights gained to scale automation efforts across other workflows.
Continuous Monitoring: Regularly measure and evaluate the outcomes of automation initiatives to refine strategies and ensure sustained improvements.
Call to Action
The time to act is now. As healthcare organizations face increasing pressures to reduce costs, streamline operations, and improve patient outcomes, automation offers a powerful solution. By adopting the Automation Gain framework, leaders can:
Quantify the True Impact of Automation: Use clear, consistent methodologies to measure and communicate ROI to stakeholders.
Optimize Resource Allocation: Focus efforts on workflows where automation delivers the greatest financial and operational benefits.
Drive Meaningful Change: Empower staff by eliminating mundane tasks, enabling them to focus on patient care and strategic initiatives.
Take the first step toward a modernized healthcare revenue cycle today. Begin by applying the framework to a single workflow, measure the results, and expand from there. Automation Gain is not just a theoretical concept—it is a practical tool to help healthcare systems unlock the full potential of RPA, reduce administrative burden, and improve financial performance.
The future of healthcare RCM is automated. Let the Automation Gain framework be your guide to measurable success.