SINI2010 – final morning sessions July 24, 2010Posted by peterjmurray in conference, education, nursing informatics, SINI2010, USA.
Tags: Baltimore, conference, informatics, nursing, SINI
The first distinguished lecture this morning is from Marilyn Chow, Vice President, Patient Care Services at Kaiser Permanente, and Murielle S. Beene, Chief Nursing Informatics Officer at Department of Veterans Affairs, and titled “Where’s the Quality in EHRs? A Collaborative Model to Promote Data Sharing and Quality Reporting”. Their talk will aim to describe how nursing leaders can have a transformative role in influencing EHR-related decisions that improve clinical effectiveness, efficiency, patient safety, and the delivery of quality-based patient care; define an emerging information model related to pressure ulcer risk that standardizes and informs nursing practice and reflects real-time clinical decision-making; and demonstrate the usefulness of common information models and reference terminologies to achieve semantic interoperability across different technology platforms.
Marilyn began by talking about her vision of being able to exchange information between the Kaiser Permanente (KP) and VA systems. KP is the US’s largest no-profit health plan, with 8.7 million members and over 40,000 nurses, while VA covers 7.8 million enrollees and 70,000 nurses. VistA, the VA system has been recognised as a world-leader for over 20 years.
The speakers summarise ‘meaningful use’ as being about financial incentives and penalties designed to support the adoption of EHRs, with the goal of linking healthcare resource use to patient outcomes. The vision is to derive quality measures directly from EHRs, improve care coordination with electronic exchange of health information, share baseline patient data across settings, and enhance clinical decision making. They went on to explore the implications of meaningful use for nurses, which include:
- identify structures and content that would meet U. S. meaningful use criteria for a quality measure;
- facilitate data portability between software applications and between organizations;
- improve the ability to aggregate outcome data for research, comparison, quality and process improvement; and
- promote nursing participation in standards development.
Currently, they say, valuable patient information is “locked” within an organization’s EHR, and data is often tightly bound to proprietary data models, which causes current and future potential problems.
The collaborative goals of work between KP and VA include defining a common Information Model driven by nursing practice that enables data capture, data re-use, and data sharing within and outside organizations. Also, they aim to facilitate the measurement and extraction of data for meaningful EHR use specific to the delivery of nursing care to support quality, safety, efficiency and clinical decision support. Nursing documentation represents a large part of the content of EHRs and therefore there is a need for nurse-lead initiatives.
They described a ‘replicable process’ for the development of the information model and data sets, and the use case scenarios, and determining the meaningful data capture, though:
1. Evaluate the Evidence
2. Leverage Clinical Expertise
3. Develop Optimum Data Sets
4. Information Harmonization – Identify the Gaps
5. Map to Reference Terminologies
6. Develop Practice-driven Information Models
7. Validate the Models
The presentation concluded by reporting that, although the work was just beginning, already made some significant progress had been made through a collaboration between the largest public and the largest private healthcare organizations on developing a nursing information model. They hope that the work promises to have an direct impact on both patient care activities and the future direction of nursing informatics within KP and the VA. They closed with a ‘call for action’ to demand the inclusion of nurse sensitive measures in the 2013 Meaningful Use criteria, and claim that the project demonstrates that the data for nursing sensitive measures can be “unlocked” from the EHR and used directly for quality reporting.