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Understanding the Hospital Consolidation Numbers: The Centrality of Data Quality

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Is hospital consolidation creating new efficiencies or does it give health care providers clout over health care insurers?  A well-publicized study published in Health Affairs last year by Robert Berenson, Paul Ginsburg, et. al said the latter:  hospital consolidation has resulted in “growing provider market clout.”

The Berenson study’s key conclusion is that growing hospital clout has resulted in insurers not aggressively containing their claims payments, a view that will stun every patient who has had a health insurance company deny coverage for a procedure, prescription or preferred health care provider.

Because the Berenson study’s finding are counterintuitive to consumer experience, and because they have been widely discussed in publications ranging from Forbes to National Journal, the Center for Regulatory Effectiveness, a regulatory watchdog with extensive experience in analyzing federal health policies, undertook an analysis to see if the study complied with the Data Quality Act (DQA).

The DQA, administered by the White House Office of Management and Budget (OMB), sets standards for virtually all data disseminated by the agencies.  Under the DQA, agencies may not use or rely on data in federal work products (reports, regulations) which don’t comply OMB’s government-wide Data Quality standards. Thus, unless the Health Affairs study complies with federal Data Quality standards, it is useless to Executive Branch policy officials.

The primary data source cited by the Berenson study as the basis for their conclusions regarding trends in relative clout between hospitals and health insurers is a well-respected, longitudinal tracking study which included interviews with heath care leaders from insurance companies, hospitals, and academia.   The health care interviews, however, were only conducted in a single year following a change in longitudinal study’s methodology.

In short, the Berenson study did not use longitudinal data; it used data from a single set of observations that was mixed with other interviews conducted outside the longitudinal study.  Interviews at a single point in time with stakeholders representing various vested interests cannot be the basis of conclusions regarding trends in anything – the Berenson study design was not capable of detecting trends.

It is also important to note that CRE found the study’s methodology to be opaque; there was no indication of the process by the study’s conclusions were derived from their dataset.  Moreover, the study included no tables, charts or specific citations to the referenced longitudinal study nor any output/results from the analysis software that the authors state they used.

Even aside from the Berenson study’s lack of analytic transparency, its basic conclusion regarding relative clout between insurers and hospitals is undermined by the Medical Loss Ratio (MLR) data obtained by CRE from publicly available Congressional sources.

The MLR data indicates that most of the major insurers reporting the data enjoyed declining MLRs from 2000-2008, meaning that the insurers were paying out a decreasing share of their premiums in claims.  It was insurers keeping a greater share of consumer premium dollars that led to the MLR regulatory requirements in the Affordable Care Act.  The data showing that insurers overall have been keeping a greater share of consumer health care premiums is at stark odds with Berenson’s conclusions regarding declining insurer clout.

CRE’s analysis “A Signature Study on Hospital Consolidation Violates the Data Quality Act,” is a detailed analysis documenting the specific ways in which Berenson 2012 violate DQA requirements.  The CRE study is available for public comment on our Hospital Consolidation website, http://thecre.com/hcf/.

Bruce Levinson is the Senior Vice President for Regulatory Intervention at The Center for Regulatory Effectiveness (CRE).


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