John Wennberg, MD and his colleagues continue to set the pace in an entire sector of health services research. A whole new generation of medical service researchers is extending Wennberg's work on variation, particularly including Elliott Fisher, MD, MPH, Therese Stukel, Wennberg's son, David Wennberg, MD and others. Their early work led to their establishing Dartmouth's Center for Clinical Evaluative Sciences, where they publish the Dartmouth Atlas of Health Care. They have made huge contributions to our understanding of medical service use. Most importantly:
The provision of health services is far from standardized. There are dramatic variations in care, sometimes many-fold, even after taking into account such factors as differences in age, gender, illness, and coverage.
Higher service levels do not equate with improved access, do not necessarily generate improved clinical outcomes, and do not lead to higher patient satisfaction, but of course they do lead to high expenditures.
About 15 years ago, I did several years worth of work on variation in hospital use in New York, primarily focused on Medicaid clients. Care of Medicaid clients was and remains highly variable. (If you'd like to see some of that work, send me an e-mail.) The original work was inspired by and based on the same methods as Wennberg. I asked at the time, "what differences do these differences make?" Since then Fisher and some of the others have written that the differences don't lead to improved outcomes or patient satisfaction. Wennberg, Fisher and their colleagues have shown that the differences in service use do yield big differences in spending. For another example, check here.
The latest work of this group, just been published in Health Affairs, is here. Particularly for those of us in New York, which is dominated by Academic Medical Centers, this one is a big deal. For example, New York's Mt Sinai has a length-of-stay double that of the Mayo Clinic. Wennberg and his colleagues looked at Medicare beneficiaries who were cared for in the last six months of life at brand-name hospitals. Highlights include:
Striking variations across hospitals in resource inputs and use of services. This includes variation in frequency of hospitalization, use of intensive care units, physician services
High correlations between patterns of care in the last six months of life with patterns of care in prior periods for the same patients with chronic illnesses.
High correlations between service use patterns for different chronic illnesses, i.e., hospitals that have high use rates for one condition tend to have high rates for other conditions. For example, they show a strong correlation between service use patterns for cancer and CHF.
Consistency of hospital-specific use rates over time.
Differences in mix of primary care physicians and specialists.
In terms of policy and operations, what does this mean?
The availability of provider-specific information should open up new opportunities for the active management of FFS health care.
Provider-specific information that profiles performance in managing chronic illness may be useful in implmenting provisions of the Medicare, Prescription Drug, Improvement and Modernization Act (MMA) of 2003.
Ultimately, success in the "longitudinal" management of populations with chronic illness will depend on the integration of care across various sectors: acute care hospitals, primary care, nursing home care, home health care, and hospice care. (I would particularly emphasize this for Medicaid clients as well as Medicare.)
Why this type of thinking is not at the center of health policy generally, Medicare policy, and Medicaid policy in New York, and every other state for that matter, is beyond me.
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