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Measuring health and health care performance

Research project Administrative health and health care registers, including national quality registers, are commonly used to measure health and quality of care/health care performance.

Open comparisons of hospitals and regions (benchmarking) provide information used in treatment priorities, patients’ choice of health care provider, and financial funding. Most commonly, only very basic statistical methods are presently used by the national quality registers. Clearly, more advanced statistical methods would help to exploit register data to provide better support to quality improvement in health care. The present project is based on data from Riks-Stroke, one of the most extensive health care quality register in Sweden, and Northern Sweden MONICA Project, a longitudinal register on cardiovascular disease and diabetes. These databases will be used to apply and develop advanced statistical methods to help to interpret differences in performance used in benchmarking between hospitals and regions.

Head of project

Project overview

Project period

2012-11-01 2016-12-31

Funding

The Swedish Research Council, 2013-2016: SEK 4,800,000

Research subject

Statistics

Project description

Administrative health and health care registers, including national quality registers, are commonly used to measure health and quality of care/health care performance. Open comparisons of hospitals and regions (benchmarking) provide information used in treatment priorities, patients’ choice of health care provider, and financial funding.
Most commonly, only very basic statistical methods are presently used by the national quality registers. Clearly, more advanced statistical methods would help to exploit register data to provide better support to quality improvement in health care.

The present project is based on data from Riks-Stroke, one of the most extensive health care quality register in Sweden, and Northern Sweden MONICA Project, a longitudinal register on cardiovascular disease and diabetes. These databases will be used to

• apply advanced statistical methods to help to interpret differences in performance used in benchmarking between hospitals and regions
• develop more in-depth and cost-effective procedures for case-mix adjustment to evaluate and explain cross sectional differences between hospitals and regions and differences in secular trends
• adopt and refine advanced statistical methods for early detection of deviances from good clinical practice