Office of Health Care Practice and Policy

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The Office of Health Care Practice and Policy conducts research relating to value and quality measurement, risk adjustment, economic analyses, processes of care, and alternative payment models. It provides consultative support to Mayo Clinic's practice, identifying quality, safety and other performance benchmarks and gathering evidence to help continually improve clinical practice.

Results of projects carried out in the Office of Health Care Practice and Policy benefit patients by advancing high-quality, affordable and patient-centric health care and by aligning optimal care delivery models with the changing reimbursement environment.

Health care policy expertise and research informs leadership with respect to national and international issues affecting health and health care delivery. This enables Mayo Clinic to maintain its position at the forefront of the national health policy discussion.

Areas of focus

  • Health policy. Provide national health policy expertise as a resource to the institution.
  • Impact assessment. Assess how health care policies and care processes affect health care quality, utilization, patient satisfaction and clinical outcomes.
  • Payment reform. Analyze health insurance reform and impact on access and quality for primary and specialty care.
  • Benchmarking. Compare outcomes of Mayo Clinic care with other institutions to identify areas of strength and opportunities to improve processes of care.
  • Comparative effectiveness. Identify and evaluate novel care delivery models.
  • Big data management. Advance techniques for data linkage and data mining.
  • Consultative services. Offer clinicians and investigators specialized services to conduct analyses on economic costs and health care resource utilization using a variety of health economic methodologies in a variety of disease areas.


Health care reimbursement and payment reform initiatives

Initiatives support the development, testing and impact of innovative health care payment models shifting from a reimbursement system based on the volume of services provided to a system based on the value of care.

Researchers in the Office of Health Care Practice and Policy assess quality and cost metrics with complex care data to identify the types of payment reform that lead to better value. This research informs and positions Mayo Clinic to engage in critical internal and external collaborative payment reform dialogues.

Find related publications.

Collaboration to improve care

Through OptumLabs, Mayo Clinic researchers are analyzing data from more than 150 million patients to find optimal treatments for conditions in a given setting, to understand variations in care and to examine the effectiveness of processes of care. OptumLabs provides a research environment and a translation network to assist in translating knowledge to changes in practice and policy.

Another major initiative is the High Value Healthcare Collaborative (HVHC). Within the HVHC, researchers work together to identify ways to improve quality of care and health outcomes. Their goal is to reduce cost by identifying best-practice care models and by facilitating adoption of those models nationwide. Further, researchers in the HVHC collaboration investigate and support development of new value-based payment models.

Quality and safety: Always a focus

As Mayo Clinic researchers seek to understand the richness of the data resources available in the 21st century, they also find new challenges. Changing policies and systems add to the complexity of the science of health care delivery. Too often, news reports of data compromise create unease and uncertainty. Part of the work in the Office of Health Care Practice and Policy centers on ensuring data quality and patient safety is ever-present in the designs of new and evolving systems.

One project showed that adding the last four digits of people's social security numbers to administrative medical data can enable trusted repositories to link data with nearly perfect accuracy without compromising patient confidentiality.

Data linkage is a fundamental building block for health information exchange. When patient-level data can be linked within and across health care-related data sources, investigators can address important health care policy issues, including tracking patients across sites, relating interventions at one site to outcomes recorded at another, identifying posthospital outcomes, and distinguishing repeat procedures on a single patient from multiple procedures that are each performed on a different patient.

Read the study abstract.

Value: More than just a good health outcome

In the current health care fiscal environment, measurement of health outcomes alone is no longer sufficient for advancing an institution's ability to demonstrate value. Researchers must also demonstrate that the expected benefits of a new agent, technology or intervention are worth the costs. To do so, they need formal economic evaluations, a group of analytic methods to quantify and compare the benefits — prevented disability, improved quality of life, and so on — and the costs of medical interventions.

One project with potential applicability across all industries looked at the impact of Mayo Clinic's worksite wellness center in Rochester, Minnesota. It showed that members of the Dan Abraham Healthy Living Center (DAHLC) who regularly participated in wellness activities experienced significant weight loss and health care costs savings.

Important results from the study include:

  • Compared with members who visited the DAHLC one to 60 times in the three-year period, members with 181 to 360 visits were 46 percent more likely to have weight loss, while the individuals with the most visits (more than 360) were 72 percent more likely to have weight loss.
  • Compared with the mean annual health care cost of $13,267 for people with one to 60 visits in the three-year period, the mean for members with 61 to 180 visits, 181 to 360 visits, and more than 360 visits had significantly lower costs, at $9,538, $9,332 and $8,293, respectively.

Read the study abstract.


Jon O. Ebbert, M.D.

Kristy L. Vierling, M.A.