PS1-46: HMORNnet: Shared Infrastructure for Distributed Querying by HMORN Collaboratives

Abstract

Abstracts have an enormous impact on the people, processes, and technology throughout KP and other Health Care Organizations. ICD-9 is running out f codes. Hundreds of new diagnosis codes are submitted annually. ICD-10 will allow not only for more codes, but also for greater specificity and thus better epidemiological tracking. How will this change impact data? Where do analysts find the new codes and what process should they follow to get ready for this conversion. What Clarity tables and columns will carry the new codes and how should the mapping be done? This presentation will provide tools for the programmers and guide them to make this conversion less painful. Keywords: High-Level Overview of ICD-10; Difference between ICD-9-CM and ICD-10-CM; Health Methods: A prototype patient SDM tool developed for point of care use is presented to the patient as a companion piece that is congruent with a physician clinical decision support tool called CV Wizard. The patient tool was designed to convey clear, succinct and personalized information about blood pressure, lipids, blood sugar, weight, smoking, and aspirin use. Reversible CV risk associated with each of these risk factors is conveyed using a combination of symbols and text accommodating a range of patient educational and literacy levels. The patient tool was presented to the HealthPartners Patient Council (HPC), the patient education specialist and a number of physician and leadership groups for feedback on content and design. Results: The HPC found the initial version confusing. They wanted more specific information on the values of their current CV risk factors and preferred the more complex tool like the CV Wizard physician tool because of its quantitative detail on reversible CV risk and pharmacologic recommendations. However, they did acknowledge that not every patient would understand that level of detail. They noted that dialogue between the patient and the physician in conjunction with the tool was more important than the tool itself. Others thought the tool was a good start with minor modifications suggested. Conclusion: The HPC preferred more specific CV risk factor values and recommendations than were included on the low literacy, or simple tool we presented. Tools that are tailored or able to accommodate a wide range of educational and literacy levels may be desirable to facilitate provider-patient shared decision making discussions. The version of the patient tool discussed here will be implemented in summer of 2012.

Understanding the roles of three academic communities in a prospective learning health ecosystem for diagnostic excellence

“…A complete sociotechnical infrastructure—to be built of policies, processes, and technologies, carried out by people—is the enabling force behind an ecosystem's ability to grow in scope and scale. Existing example infrastructure components include D2K‐enabling platforms that manage and share clinical data, such as PopMedNet, and “big data” platforms and algorithmic toolkits that are routinely used by the ML/AI community . There are also many emerging components that support K2P, such as the Knowledge Grid (KGrid)—which stores health knowledge and generates tailored advice to drive practice change—and standards that support interoperability of such services .…”

Traits and types of health data repositories

“…A sub-network of the HMORN is the Kaiser Permanente consortium, which is reported to have over 9 M patients [ 35 ]. The HMORN shares [ 36 ] with Mini-Sentinel a technology base, PopMedNet [ 37 ] that allows data holders to independently decide whether to respond to particular queries from the network. HMORN exemplifies how research networks grow and intersect.…”