Patient Level Costing And Profitability: Making It Work

Patient Level Costing And Profitability Making It Workhfmaorgconte

Increasing changes in how insurers pay for health care in the United States and public pressure to reduce the overall cost of care are forcing healthcare organizations to move away from revenue-centric approaches to maintain their financial stability. This move requires placing a greater emphasis on measuring, managing, and monitoring the cost of providing care and the resulting profit margins—a change that is necessary even for not-for-profit healthcare organizations. To reduce costs, provider organizations must take a substantially different approach to managing costs.

Measuring costs must involve a consumption view of how resource expenditures (e.g., employee salaries, materials, supplies, power) are used for procedures, treatments, surgeries, and the like by individual patients. Traditional costing approaches in health care, such as those based on ratio of costs to charges (RCCs) or relative-value units (RVUs), are inadequate. RCCs and RVUs use broad averages that do not reflect cost accounting’s causality principle: Costing should reflect the cause-and-effect relationship between costs and the consumption of resources by cost objects (e.g., patients, procedures) that cause costs to be incurred. The Data-Driven, Consumptive Approach emphasizes adopting a comprehensive patient-level cost management analytics approach using existing data within clinical and financial systems.

The IT used in healthcare generates substantial transactional data that can be converted into cost data for each patient in real time, as costs are incurred. This wealth of data remains underutilized despite its potential to improve analysis and decision making. Industries such as manufacturing and transportation spend billions on equipping their operations to generate detailed cost data—healthcare organizations can do the same with existing information systems, transforming raw data into meaningful cost insights. However, a significant gap remains between the potential of these data sources and their actual use in healthcare settings, hampering the ability to accurately measure costs and profitability at the patient level.

To comply with the causality principle, healthcare data—residing in electronic health records (EHRs), pharmacy systems, laboratory systems, imaging, and other digital sources—must be systematically gathered, stored, and analyzed. These data streams contain valuable information that can be transformed into precise cost metrics, enabling healthcare organizations to generate detailed, real-time cost reports. Comparing these costs against patient billing and revenue collections allows organizations to identify where they are making or losing money and to understand the underlying reasons. This approach marks a paradigm shift from traditional cost allocation methods, which rely on broad averages and often misrepresent individual patient costs.

Traditional costing methods, such as those based on general ledger cost pools and allocations via RVUs or RCCs, do not adhere to the causality principle, resulting in inaccurate perceptions of individual patient costs. These methods tend to over-cost some items while under-costing others, leading to misleading data that impacts decision-making. Although performing well for external reporting and compliance purposes, they lack the granularity necessary for internal management decisions aimed at reducing costs and improving quality. This gap highlights the necessity of adopting patient-level costing based on cause-and-effect relationships.

The business case for patient-level costing centers on its ability to instantly recognize cost variances among treatments for similar conditions. Visualizing the distribution and skewness of costs across patients allows healthcare managers to scrutinize reasons behind disparities and to formulate strategies to curb unnecessary expenses. Despite each patient's unique circumstances, analytics facilitate the separation of significant cost drivers from noise—helping managers target specific areas for improvement.

Key variables influencing patient costs include timing of service, inpatient versus outpatient status, referral source, care provider, specific facilities, and resource consumption such as labor, supplies, and medications. Understanding how these variables relate to cost enables healthcare organizations to standardize procedures, implement best practices, and steer clinicians toward cost-effective treatment protocols. Data-driven insights can improve clinical decision-making while maintaining or enhancing care quality, directly reducing wasteful spending.

The methodology of patient-level costing is event-driven and real-time, contrasting with traditional period-based systems like monthly or quarterly reporting. Costs are accumulated at the point of service, providing a granular and dynamic view of expenses associated with each patient interaction. This bottoms-up approach breaks down costs into activities—such as procedures, staff time, and resource usage—and directly allocates expenses, ensuring adherence to the causality principle. By tracking expenses at this level, healthcare organizations can perform detailed comparisons across patient groups, identify anomalies, and implement targeted cost reductions.

Applying activity-based costing (ABC) to indirect expenses complements patient-level costing. ABC assigns indirect costs based on actual resource usage, refining the accuracy of overall cost analyses. Collectively, these techniques foster a culture of transparency, accountability, and continuous improvement in healthcare finance management.

Despite its advantages, patient-level cost analytics remain underutilized in the United States, impeded by organizational and cultural barriers. Resistance from staff, physicians’ reluctance to alter treatment protocols, fears of financial transparency, and leadership inertia hinder widespread adoption. Nevertheless, success stories from early adopters demonstrate the feasibility and benefits of this approach, with initial pilot projects—such as total joint replacement programs—that can achieve significant savings within weeks.

Effective implementation strategies include starting with a specific department or diagnosis-related group (DRG), demonstrating quick wins, and gradually expanding the system across the organization. High-level prototyping and iterative refinement allow for manageable deployment, minimizing disruption and fostering staff buy-in. Leadership plays a critical role in cultivating a culture that values accurate cost information, viewing it as a tool to enhance care quality, reduce costs, and sustain competitiveness.

In conclusion, shifting towards patient-level costing based on detailed, causality-driven analytics offers a powerful lever for healthcare organizations seeking cost control and improved clinical outcomes. Overcoming barriers requires leadership vision, strategic planning, and a commitment to data-driven decision-making. As healthcare continues to evolve amidst economic and regulatory pressures, organizations that embrace these innovative cost accounting methodologies will be better positioned for future sustainability and success.

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