Thursday, August 26, 2010

Lessons Learned from 9 States on Building Successful HAI Reporting Programs

According to the Centers for Disease Control and Prevention, healthcare-associated infections (HAIs) account for 99,000 deaths per year. In an effort to curb the spread of HAIs, 27 states now require health care facilities to publicly report infection rates.

As state and federal policy-makers consider the merits and feasibility of this reporting, a new report from the National Conference of State Legislatures offers an in-depth look at the challenges of setting up meaningful reporting systems as well as successes and lessons learned from implementation.  The report, which was sponsored by Extending the Cure, a project of the Robert Wood Johnson Foundation’s Pioneer Portfolio, includes insights gained from interviews with state legislators, health care providers and other stakeholders in nine states: Alabama, Colorado, Delaware, Illinois, Massachusetts, New Hampshire, Oregon, Pennsylvania and Washington.

Learn more.
The INQRI program is deeply committed to this type of work.  A team of INQRI researchers at Johns Hopkins University has conducted the first randomized-control trial to reduce central line associated blood stream infections among ICU patients. There are some 80,000 catheter-induced bloodstream infections each year, causing up to 28,000 deaths. This study, conducted in ICUs in 12 states, has shown in preliminary analysis that substantial reductions in infections can be widely achieved and this project did so with nurses leading the infection control efforts. Their study builds on the well-known work of Dr. Peter Pronovost, creator of the line insertion “checklist.” Hospitals that followed the components of their ICU safety program, as well as adopted a safety improvement environment that fostered nurse involvement in quality improvement efforts, reduced, and in some cases completely eliminated, bloodstream infections for several months at a time. Their research is also showing that higher nurse turnover is related to higher infection rates.

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