Leapfrog Group

<h3>Key Messages</h3> “People-centered” HIV services recognize individuals’ holistic selves—as people with unique and dynamic needs, preferences, and rights who deserve an individualized service experience tailored to their life journey. A validated, streamlined set of metrics can help the HIV community drive toward such a “people-centered” orientation and advance the Joint United Nations Programms on HIV/AIDS’ 2025 target of linking at least 90% of people living with HIV and people at risk to people-centered and context-specific integrated services. A framework of people-centered outcomes and 6 corresponding metrics were developed with and for the people they serve to elevate monitoring the degree to which an individual is healthy, comfortable, and able to participate and enjoy life events. Successfully integrating these person-centered outcome metrics in an existing HIV program can improve quality of life and health outcomes by encouraging providers and program staff to use the indicator data to improve care provision. The HIV community is invited to collaboratively refine and validate these people-centered outcome metrics using the Putting People-Centered Metrics for HIV into Practice toolkit.

To evaluate the safety of computerized physician order entry (CPOE) and associated clinical decision support (CDS) systems in electronic health record (EHR) systems at pediatric inpatient facilities in the US using the Leapfrog Group's pediatric CPOE evaluation tool. The Leapfrog pediatric CPOE evaluation tool, a previously validated tool to assess the ability of a CPOE system to identify orders that could potentially lead to patient harm, was used to evaluate 41 pediatric hospitals over a 2-year period. Evaluation of the last available test for each institution was performed, assessing performance overall as well as by decision support category (eg, drug-drug, dosing limits). Longitudinal analysis of test performance was also carried out to assess the impact of testing and the overall trend of CPOE performance in pediatric hospitals. Pediatric CPOE systems were able to identify 62% of potential medication errors in the test scenarios, but ranged widely from 23-91% in the institutions tested. The highest scoring categories included drug-allergy interactions, dosing limits (both daily and cumulative), and inappropriate routes of administration. We found that hospitals with longer periods since their CPOE implementation did not have better scores upon initial testing, but after initial testing there was a consistent improvement in testing scores of 4 percentage points per year. Pediatric computerized physician order entry (CPOE) systems on average are able to intercept a majority of potential medication errors, but vary widely among implementations. Prospective and repeated testing using the Leapfrog Group's evaluation tool is associated with improved ability to intercept potential medication errors.

BackgroundAmerican public policy makers recently established the goal of providing the majority of Americans with electronic health records by 2014. This will require a National Health Information Infrastructure (NHII) that is far more complete than the one that is currently in its formative stage of development. We describe a conceptual framework to help measure progress toward that goal.DiscussionThe NHII comprises a set of clusters, such as Regional Health Information Organizations (RHIOs), which, in turn, are composed of smaller clusters and nodes such as private physician practices, individual hospitals, and large academic medical centers. We assess progress in terms of the availability and use of information and communications technology and the resulting effectiveness of these implementations. These three attributes can be studied in a phased approach because the system must be available before it can be used, and it must be used to have an effect. As the NHII expands, it can become a tool for evaluating itself.SummaryThe NHII has the potential to transform health care in America – improving health care quality, reducing health care costs, preventing medical errors, improving administrative efficiencies, reducing paperwork, and increasing access to affordable health care. While the President has set an ambitious goal of assuring that most Americans have electronic health records within the next 10 years, a significant question remains "How will we know if we are making progress toward that goal?" Using the definitions for "nodes" and "clusters" developed in this article along with the resulting measurement framework, we believe that we can begin a discussion that will enable us to define and then begin making the kinds of measurements necessary to answer this important question.