In a groundbreaking move set to shake up the healthcare industry, the Centers for Medicare & Medicaid Services (CMS) unveiled proposed changes to hospital pricing transparency regulations earlier this year that will take effect in 2024. With approximately 7,000 hospitals across the United States set to be affected by these changes, the impact on price transparency is poised to reverberate throughout the entire healthcare landscape.
This development not only promises greater accountability and clarity in healthcare costs but also raises important questions about its potential influence on care quality improvement that hospitals and health systems provide.
The federal government sees price transparency as crucial for promoting competition and reducing healthcare costs. The proposed rule aims to simplify regulations, make it easier for hospitals to comply, and strengthen enforcement of violations. It has three main objectives:
CMS has issued civil monetary penalty notices to seven hospitals since 2021, totaling over $2 million for price transparency violations.
Meanwhile, healthcare provider organizations are grappling with various operational challenges related to quality, cost, and revenue management. Labor shortages and budget constraints disrupt operations and could hinder hospitals’ ability to provide essential care and meet compliance requirements, potentially resulting in significant fines.
As this pivotal shift towards increased pricing transparency takes center stage, it prompts a crucial examination of how it will intersect with ongoing quality improvement initiatives within hospitals and health systems.
The push for greater price visibility may very well catalyze significant changes in how healthcare organizations approach their delivery of services as they grapple with the implications of making financial information more accessible to patients and stakeholders alike.
In light of these developments, an exploration of how this newfound transparency stands to shape and potentially revolutionize quality improvement endeavors within hospital settings becomes both timely and essential.
Meanwhile, regional and local health system leaders are actively harnessing data and analytics to drive healthcare quality improvement initiatives. The advancement of data analytics platforms has provided healthcare organizations with abundant, valuable data. However, effectively leveraging this insight to drive meaningful change presents a significant challenge.
A previously published article showcases the experiences of a panel of Clinical Quality and Operations experts, who shared how they navigated these obstacles and highlighted innovative approaches that have proven successful for their organizations, giving healthcare executives a sustainable starting point for meeting their community’s data analytics and reporting needs.
While the vast amount of available data may suggest that metrics alone should dictate areas requiring improvement, healthcare leaders with experience in data analytics platforms argue the opposite. Neal Chawla, MD, FACEP, Chief Medical Information Officer at WakeMed, succinctly emphasized that the purpose of data is to move beyond it. Instead, operational initiatives should guide an organization’s progress without being distracted by irrelevant data volumes.
As Julie Watson, MD, MPH, Senior Vice President and Chief Medical Officer of INTEGRIS Health, pointed out, hospital and organization leaders are already aware of areas needing improvement. They are familiar with industry-wide issues such as mortality rates, readmissions, patient access, and length of stay.
The effectiveness of metrics lies in aligning them with an organization’s established operational initiatives. Data analytics platforms can enhance understanding of operational deficiencies by providing a nuanced context and deeper insight into quality improvement strategies.
Healthcare leaders stress that successful change begins by identifying small actionable areas that can yield significant impact. Focusing on specific areas where many people can benefit lays a strong foundation for growth using the data analytics platform effectively. This approach promotes new protocol adoption across the organization while safeguarding clinicians and care teams from burnout.
Additionally, focused analytics help identify critical behaviors that impede outcomes. For instance, Stephanie Jackson, MD, FHM, Senior Vice President and Chief Clinical Officer for HonorHealth, highlighted the importance of analyzing hand hygiene as a crucial factor in measuring surgical site infections as an example of capturing specific data. Developing targeted analytics dashboards within a data analytics platform could also reveal prioritized areas for improvement — an approach aligned with leadership initiatives to encourage buy-in for new protocols and foster ownership across the organization.
Stephanie Jackson, MD, FHM at HonorHealth, also emphasized the importance of acknowledging the human aspect behind data analytics, cautioning leaders to remember that each number represents a real person. Patient stories have the potential to inspire an entire organization, from top-level executives to those directly involved in implementing change.
William Holland, MD, MHA, Senior Vice President of Care Management and Chief Medical Informatics Officer of Banner Health, highlighted the need to create relevant and meaningful metrics for different members of an organization, tailoring data to their unique perspectives. He also noted that collaboration between data analytics and process improvement teams is crucial for health organizations leveraging analytics for quality improvement.
Creating specific analytics dashboards within a data analytics platform also demonstrates focused areas for enhancement, in line with leadership efforts to promote acceptance of new protocols and cultivate accountability throughout the organization. These guidelines contribute to a broader endeavor to minimize variations in healthcare delivery at hospitals and health facilities, a concern shared by providers and executives.
Standardizing care and improving clinical quality data in health systems can reduce unnecessary variations in care, leading to better patient experiences, provider satisfaction, and potential cost savings. As health systems face rising costs and changing reimbursement models, many are adopting innovative strategies to positively impact clinical practice variation and financial performance.
Unwarranted clinical variation, characterized by deviations from evidence-based care standards, has long been a complex issue for practitioners and health system administrators.
Factors contributing to clinical care variation include physician beliefs, patient preferences, and the lack of clear treatment criteria. Financial incentives also influence treatment decisions; fee-for-service models may result in over-utilization of services, while capitated payment models could lead to underutilization due to cost-saving measures. Experts agree that addressing these complex matters requires a systematic strategy utilizing data analytics to identify areas for improvement.
Amidst the ever-evolving healthcare landscape, organizations are under constant pressure to bolster quality improvement while reducing costs despite the increasing complexity within health systems. Unjustified clinical variation continues to present itself as a primary area for improvement.
Research indicates that health systems have significant opportunities for cost savings by reducing care variation. Indeed, most provider organizations have the potential to realize $20M- $30M in actionable savings opportunities per $1B in revenue.
New Hanover illustrates this point after successfully establishing numerous highly effective clinical programs; however, it needed more valuable data, analytics, and a systematic approach to identify opportunities and drive outcomes. The absence of valuable data and analytics and standard procedures for implementing evidence-based practices, opportunity prioritization, governance, and change management led to pockets of excellence and fragmented resources that had originally intended to align teams and engage providers.
The organization analyzed care variation, which took several months to extract encounter data from the EHR to identify improvement opportunities. Although it acknowledged the potential for improvement, the organization did not possess the high-value data and analytics required to prioritize and drive enhancement efforts.
Simultaneously, its internally developed data warehouse was not scalable or sustainable. It could not be further designed to provide value-based care analytics essential for supporting population health and payer strategies.
Eventually, the organization sought a new solution that would enable it to become an informed, data-driven entity supporting efforts to identify and reduce care variation while improving patient outcomes and enhancing success in value-based care.
New Hanover decided to implement the Health Catalyst data platform and a comprehensive set of healthcare analytics applications. This move allowed the organization to establish a flexible data ecosystem that can adjust to evolving organizational requirements.
As part of this initiative, the organization formulated a new analytics strategy, which involved enhancing data governance and improving analytics to achieve several key objectives:
The analytics strategy was closely aligned with the organization’s clinical, operational, and service-line strategies. The analytics team gained the ability to utilize the platform to deliver valuable data and insights to clinical and operational leaders to enhance performance.
Additionally, New Hanover set up a governance structure focused on achieving performance excellence. Teams dedicated to performance excellence, led by a physician and program director, collaborated with a council comprising clinical, operational, and physician leaders and senior executives.
The goal was to minimize clinical variation and enhance outcomes by leveraging high-value data and analytics from the new data platform. The council was responsible for identifying improvement opportunities across the system, prioritizing initiatives systemwide, endorsing improvement efforts, ensuring accountability for achieving outcomes, evaluating the costs and benefits of improvement efforts, and the analytics platform itself.
Furthermore, they aimed to spread their mission across the organization by improving the value of patient care. Clinical and operational teams were empowered to accelerate improvements in clinical outcomes while sustaining these enhancements over time.
Based on their available data, New Hanover’s improvement method led to desired outcomes. Within 2.5 years, the organization decreased costs by $7 million. By reducing unwarranted clinical variation — standardizing spine care, blood utilization, high-cost medication use, and treating sepsis in the emergency department — the system saved some $5.4 million.
Additionally, the organization optimized maintenance for patients with COVID-19 and enhanced transitions of care. Furthermore, there was a $1.4 million reduction in costs due to improved efficiency in analytics. By implementing the Health Catalyst data analytics platform, New Hanover was able to reduce labor costs associated with reporting and analyses.
Moving forward, New Hanover intends to prioritize its patients in its efforts for improvement and will expand the adoption of its improvement framework and analytics platform to enhance organizational performance and quality further while decreasing expenses.
While not immediately apparent, it is easy to see how the implementation of federal price transparency rules for hospitals presents a unique opportunity to align with local efforts to improve the quality of care through the utilization of healthcare data and analytics.
By requiring hospitals to disclose their prices, patients and local stakeholders can make more informed decisions about healthcare options, fostering a culture of accountability and competition that could potentially drive improvements in care quality.
The ability to provide detailed pricing information could also enable local organizations to identify disparities in access and outcomes, allowing for targeted interventions that address community-specific needs. Embracing these regulations as a catalyst for leveraging data and analytics will be crucial in advancing the collective goal of enhancing healthcare quality improvement at both national and local levels.
Would you like to learn more about this topic? Here are some articles we suggest:
Hospital Price Transparency: Five Changes You Should Know
Healthcare Leaders Share Three Best Practices to Improve the Quality of Care When Implementing a Data Analytics Platform
Standardizing Excellence: 5 Pillars for Reducing Unwarranted Care Variation
Reducing Variation and Costs by $7M with a Scalable Improvement Framework and Analytics Platform