Does vertical integration improve or imperil US healthcare?
November 19, 2021
Business Affairs
From the November 2021 issue of HealthCare Business News magazine
By M. Susan Ridgely
Healthcare consolidation is endemic across the U.S. With consolidation — both horizontal (hospitals acquiring other hospitals) and vertical (for example, hospitals and health systems acquiring physician practices) — has come public attention and regulatory scrutiny.
Proponents of consolidation argue that size generates efficiencies and offers opportunities to improve care coordination and quality. Critics point to concentrated markets and price demands that exceed the costs of delivering care. Some organizations acquire or are acquired because their executives believe that size will bring leverage in highly concentrated markets. Others just fear being left behind when the dust settles.
Assessing the benefits and risks of consolidation should not be a political or philosophical debate. These are empirical questions — and a growing body of research sheds light on whether vertical integration represents a value-add to U.S. health care.
Our team at the nonprofit, nonpartisan RAND Corporation has been studying the issue for the past six years and we’ve found that there is little data on which to make judgments about consolidation. We’ve also found that consolidation is taking on new forms, and our effort has failed to find evidence that consolidation lowers costs or improves quality.
In 2015, the Agency for Healthcare Research and Quality provided core funding to RAND — in collaboration with researchers from UCLA, Penn State, Stanford, and Harvard — to identify health systems, document how they vary from one another, and learn what characterizes systems that perform well from those that do not. We enlisted the help of four partners representing coalitions in four states that collect and publish healthcare performance data; we also engaged health systems and their executives, who generously shared their insights and experience. We supplemented these on-the-ground perspectives with an extensive compilation of federal and state-level data.
Our research unearthed some of the challenges inherent in studying health systems. While health systems and their physician providers are being held accountable for performance in value-based payment programs — both public and private — we discovered that there is no national consensus on what high-performing means or how it is measured. We used both qualitative and quantitative methods to address this gap in knowledge. For example, tapping health system executives to help us determine priorities for study and collecting data from “deep dive” interviews in 24 systems. We also used performance data to develop a new composite measure of quality performance that can be used by health system executives as well as researchers.
We also discovered how difficult it is to use administrative data to answer important policy questions about health care markets. We do not know as much as we should about health systems, and current efforts to document the relationships among health care providers are hampered by significant limitations in existing data sources. No unique system identifier exists to readily link information across administrative data files, and matching by name is fraught with error, given that there is no standardization in naming conventions. This is a problem complicated enough to require the attention of the federal agencies that collect these data.
There is one area of commonality across data sources — both public and proprietary — that also proves problematic: the way “health system” is defined in almost all administrative and survey data limits the inquiry to “owner/management” relationships. However, we know that many variations of affiliation are common. Put another way, we cannot map the health care marketplace as it actually exists with the data we have.
Despite these limitations, we are able to share a number of findings that answer some questions, while raising others.
“When you’ve seen one health system… you’ve seen one health system.” Across the 24 health systems we studied in depth, there was tremendous variability in the dimensions that previous analysts have used to explain performance, including: size; capitalization; integration at the structural, financial, and clinical levels; and implementation of interoperable health IT. Our “deep dive” into health systems suggests that other factors are more informative: for example, the operational and governance relationships among entities. These relationships reveal how and the extent to which health systems can exert leverage over the clinical performance of affiliated hospitals and physician organizations, and explain more than whether the health system “owns” an affiliated entity. Granular qualitative data offer a way to describe multilayered health systems, grasp the context in which they operate, and identify the real drivers of performance, which executives believe include organizational culture, leadership, and staff engagement, among other attributes that are not easy to measure.
We also discovered — through our focus on understanding how health systems are built and how they function — that vertical integration isn’t the only way that health systems are building out to meet the challenges of today’s market. Health systems are creating clinically integrated networks (CINs), bringing private practice physicians into contracts to provide care jointly and share profits. This phenomenon is almost completely invisible to both researchers and regulators. Because of this, the debate about the effects of health care consolidation should include a focus on CINs, which represent both an opportunity to improve care standardization across a community and a potential threat to increase prices without a proportionate impact on quality of care.
By M. Susan Ridgely
Healthcare consolidation is endemic across the U.S. With consolidation — both horizontal (hospitals acquiring other hospitals) and vertical (for example, hospitals and health systems acquiring physician practices) — has come public attention and regulatory scrutiny.
Proponents of consolidation argue that size generates efficiencies and offers opportunities to improve care coordination and quality. Critics point to concentrated markets and price demands that exceed the costs of delivering care. Some organizations acquire or are acquired because their executives believe that size will bring leverage in highly concentrated markets. Others just fear being left behind when the dust settles.
Assessing the benefits and risks of consolidation should not be a political or philosophical debate. These are empirical questions — and a growing body of research sheds light on whether vertical integration represents a value-add to U.S. health care.
Our team at the nonprofit, nonpartisan RAND Corporation has been studying the issue for the past six years and we’ve found that there is little data on which to make judgments about consolidation. We’ve also found that consolidation is taking on new forms, and our effort has failed to find evidence that consolidation lowers costs or improves quality.
In 2015, the Agency for Healthcare Research and Quality provided core funding to RAND — in collaboration with researchers from UCLA, Penn State, Stanford, and Harvard — to identify health systems, document how they vary from one another, and learn what characterizes systems that perform well from those that do not. We enlisted the help of four partners representing coalitions in four states that collect and publish healthcare performance data; we also engaged health systems and their executives, who generously shared their insights and experience. We supplemented these on-the-ground perspectives with an extensive compilation of federal and state-level data.
Our research unearthed some of the challenges inherent in studying health systems. While health systems and their physician providers are being held accountable for performance in value-based payment programs — both public and private — we discovered that there is no national consensus on what high-performing means or how it is measured. We used both qualitative and quantitative methods to address this gap in knowledge. For example, tapping health system executives to help us determine priorities for study and collecting data from “deep dive” interviews in 24 systems. We also used performance data to develop a new composite measure of quality performance that can be used by health system executives as well as researchers.
We also discovered how difficult it is to use administrative data to answer important policy questions about health care markets. We do not know as much as we should about health systems, and current efforts to document the relationships among health care providers are hampered by significant limitations in existing data sources. No unique system identifier exists to readily link information across administrative data files, and matching by name is fraught with error, given that there is no standardization in naming conventions. This is a problem complicated enough to require the attention of the federal agencies that collect these data.
There is one area of commonality across data sources — both public and proprietary — that also proves problematic: the way “health system” is defined in almost all administrative and survey data limits the inquiry to “owner/management” relationships. However, we know that many variations of affiliation are common. Put another way, we cannot map the health care marketplace as it actually exists with the data we have.
Despite these limitations, we are able to share a number of findings that answer some questions, while raising others.
“When you’ve seen one health system… you’ve seen one health system.” Across the 24 health systems we studied in depth, there was tremendous variability in the dimensions that previous analysts have used to explain performance, including: size; capitalization; integration at the structural, financial, and clinical levels; and implementation of interoperable health IT. Our “deep dive” into health systems suggests that other factors are more informative: for example, the operational and governance relationships among entities. These relationships reveal how and the extent to which health systems can exert leverage over the clinical performance of affiliated hospitals and physician organizations, and explain more than whether the health system “owns” an affiliated entity. Granular qualitative data offer a way to describe multilayered health systems, grasp the context in which they operate, and identify the real drivers of performance, which executives believe include organizational culture, leadership, and staff engagement, among other attributes that are not easy to measure.
We also discovered — through our focus on understanding how health systems are built and how they function — that vertical integration isn’t the only way that health systems are building out to meet the challenges of today’s market. Health systems are creating clinically integrated networks (CINs), bringing private practice physicians into contracts to provide care jointly and share profits. This phenomenon is almost completely invisible to both researchers and regulators. Because of this, the debate about the effects of health care consolidation should include a focus on CINs, which represent both an opportunity to improve care standardization across a community and a potential threat to increase prices without a proportionate impact on quality of care.
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