As health systems continue to navigate several interrelated challenges — from rising costs to shifting reimbursement models — many are leveraging innovative strategies that positively impact clinical practice variation and their bottom line.
Practitioners and health system administrators have long endured the complex and perplexing issue of unwarranted clinical variation, defined as over or under-utilization of care due to deviations from evidenced-based care standards. It remains a crucial area of healthcare system improvement, with the latest research suggesting that most provider organizations have actionable savings opportunities amounting to $20M-$30M per $1B in revenue.
Meanwhile, the factors contributing to clinical care variation may include individual physician beliefs, patient preferences, and the absence of clear, measurable criteria to guide treatment options. The complexity and diversity of care variation can lead to disparities in patient outcomes and a health system’s financial burdens. Many health systems leaders grappling with this issue have realized the need for implementing a well-rounded, systematic strategy that utilizes valuable data and analytics to identify areas of improvement.
Executives also require data warehouses that are scalable and sustainable to deliver the necessary value-based care analytics for supporting population health and payer strategies. By analyzing data on patient outcomes, cost of care, and the differences in care provided, organizations can pinpoint specific areas to intervene. This data-driven approach allows for targeted improvement efforts that have the potential to yield significant cost savings without compromising the quality of care. Indeed, with high-value data and analytics capabilities and a standard approach to quality improvement, organizations can transcend mere pockets of excellence and achieve widespread transformation.
One cause for care variation is the lack of standardized clinical guidelines or protocols across healthcare providers. Hospitals or clinics may have different approaches to treating the same condition, resulting in varying levels of care quality.
Another factor contributing to care variation is the influence of financial incentives on treatment decisions. In fee-for-service payment models, where doctors are reimbursed based on the number of services they provide, there is a potential for over-utilization of tests and procedures. On the other hand, in capitated payment models where providers receive a fixed amount per patient regardless of service volume, there may be underutilization of necessary treatments due to cost-saving measures.
Compounding these issues is the scarcity of meaningful data and a robust data platform that serves as a single source of truth. Stakeholders need access to a breadth of data and detailed insights, including:
Data transparency in healthcare enables informed decision-making based on actual healthcare delivery models, provider performance, and patient outcomes, which promotes more consistency in medical practices.
The availability of these data and analytics to the entire care team is crucial for maximum impact. As such, leaders can identify variations by analyzing patient location and risk cohort or by provider. What’s more, reliable data access enables practitioners to proactively adjust the clinical course of treatment for individual patients.
These issues underscore the need for standardization in healthcare. There are five critical elements of care standardization, which include:
Organizations should dedicate time and resources to addressing each aspect of standardization to achieve lasting change. It is recommended that organizations approach these tasks methodically, giving priority to issues impacting high-value outcomes, such as improvements in clinical, financial, or operational functions.
However, each health system’s focus on near-term improvements to reduce unwarranted care variation should be based on their specific circumstances. For example, certain healthcare systems may deal with reimbursement penalties and high costs related to in-patient length of stay, readmissions, and mortality rates. In these situations, clinical and executive leaders must prioritize improving acute decompensation management and care transition processes. Conversely, some organizations have committed to value-based care agreements and would benefit from focusing on initiatives to reduce risk factors and effectively identify and manage patients.
Standardized processes for implementing evidence-based practices and prioritizing opportunities for change may include creating a governance structure and change management system. Researchers posit that collaboration and joint decision-making among physicians, along with implementing feedback loops in clinical care, can enhance mutual learning and minimize unwarranted variations in care.
This calls for strong clinical and executive leadership, direct physician involvement, and continuous program oversight and monitoring. To that end, oversight committees, comprised of frontline providers, administrators, and data analysts at the helm of strategic and operational changes, can ensure that improvement efforts are coordinated across departments and are consistently applied throughout the organization. This systematic approach also promotes team alignment and engages providers as champions in improving care delivery.
When frontline clinicians are actively involved in quality improvement projects to reduce care variation, they can provide input on improving workflows, streamlining processes, and enhancing communication. They can also help bridge the gap between theory and practice, ensuring that interventions are feasible and practical for implementation.
Indeed, clinical leaders can monitor high-level outcome goals, such as readmission rates, length of stay, costs, and patient satisfaction. They can also monitor process metrics, such as wait times, infection rates, and bundle compliance, to identify areas for improvement and implement strategies to optimize performance.
For instance, if the data shows high readmission rates for specific conditions or procedures, hospitals can develop intervention programs to provide better post-discharge support for those patients. Additionally, by analyzing staffing patterns and resource utilization data, health systems can make informed decisions about allocating resources to ensure efficient operations while providing timely care.
To standardize healthcare and address the five pillars adequately, organizations must move away from relying on disparate data systems and limited interoperability, which stores data in separate and often incompatible formats, making it difficult for healthcare professionals to retrieve data and obtain a comprehensive view of a patient’s medical status or history. Disjointed data systems also hamper continuous monitoring and improvement efforts, preventing leaders from identifying bottlenecks or inefficiencies in their current processes.
Health systems must adopt an analytical framework that uses high-quality data to drive decision-making for outcome improvements. Since most health systems have limited resources and can’t address all areas needing enhancement at once, organizations can use a Key Process Analysis (KPA) application. This allows them to focus scarce resources where they will have the greatest impact.
A KPA tool identifies clinical processes with significant variation and resource consumption by analyzing comprehensive datasets that include clinical practices, billing procedures, and cost evaluations. The solution can also establish connections between ICD-10 codes, patient-refined diagnosis-related groups, and other risk models. Using KPA for clinical quality improvement, health systems can shift towards value-based care, emphasizing advanced clinical outcomes and cost-effectiveness.
Implementing strategies to reduce care variation is crucial for improving patient care, overall population health, and controlling healthcare costs while achieving a positive and sustainable work environment for providers. By standardizing processes and protocols, practitioners can consistently deliver care across settings and patient populations, enhancing patient safety, improving resource allocation, and alleviating financial burdens.
Reducing unwanted care variation while providing value-based care is a complex but essential goal that requires a multi-pronged approach involving clinical leadership, data-driven decision-making, and a commitment to continuous improvement.
Would you like to learn more about this topic? Here are three articles we suggest:
Reducing Variation and Costs by $7M with a Scalable Improvement Framework and Analytics Platform
 High-quality hospitals deliver lower cost care 82% of the time. Advisory Board (2018). Business Wire. Retrieved from: https://www.businesswire.com/news/home/20181003005296/en/High-Quality-Hospitals-Deliver-Cost-Care-82-Time